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Are NFTs Dead? Check Out What the Future Has in Store for Digital Collectibles
NFTS (non-fungible tokens) took the world by storm in 2021. Since then, there have been many predictions on what to expect from the market. The future of digital collectibles looked bright as everyone from financial consultants to pop stars partook in this exciting new trend. Digital collectibles even reached sales in the billions of dollars.
However, many people are still skeptical, and with good reason. The market reached a $38.2 billion value in the same year, but interest in digital tokens suddenly plummeted. After all the hype, you’re left with the question – “Are NFTS dead?” While it’s always difficult to precisely predict social and economic trends, there are still fair assumptions we can make.
Here’s what the future of NFTS might look like.
NFT Basics – Why They Matter
Before we delve into some future predictions for NFTS, we must first define what they are, how they function, and from where they derive their worth.
By name, NFTs are non-fungible. That means you can’t replace them. Any object that derives its worth from being one-of-a-kind falls into this category, whether it’s Vincent Van Gogh’s Starry Night (sold for $100 million) or a digital meme.
Regarding sales, NFTs mainly refer to digital tokens that feature illustrations, memes, and videos. This allows creators to claim digital ownership over things considered sharable for everyone.
While this trend took off in 2021, since 2022 NFT sales have dropped by a whopping 90%. The enthusiasm for digital tokens has waned off, and we’re left unsure of their future.
How It All Began
It was in 2017 when NFTs were first created. The company Ethereum (cryptocurrency industry) introduced a token as a standard for developers and artists. These tokens were a prominent feature of smart contracts, allowing developers to link art to their works. It’s also worth mentioning that Ethereum only started the first standard approach to NFTS, connecting them to Crypto. Certain video game platforms began using digital collectibles like skins even earlier.
After 2017, NFTs continued gathering steam until finally peaking in 2021. Celebrities made millions of dollars for their digital illustrations, and video games introduced these tokens in their gameplay.
But this isn’t a purely digital playing field, either. Leading art auction houses Christie’s and Sotheby’s also turned to this trend, pocketing $69 million through digital auctions. The backing of prominent celebrities, brands, and authorities fueled the intense but short-lived NFT craze.
What’s Going On With NFTs Now?
Once a promising market, the NFT industry and general interest in digital tokens have massively dropped in just one year.
With a loss of over 90% in overall sales, some believe it’s due to the market’s speculative nature. Currently, many NFTs on the market are trading for much less than their original sales price. At the same time, it’s hard to deduce why; it’s safe to assume that there are multiple reasons.
Decreased trading volume and shifting market circumstances have significantly reduced and even eliminated royalties. Many NFT projects base most of their worth on these royalties and are unsustainable without them. NFT prices are also closely connected to cryptocurrency prices, which have diminished in recent years, too.
Others still blame a lack of regulations on the downfall of the NFT market. For example, many participated in the activity of “wash trading.” This procedure involves re-selling an NFT to yourself, artificially inflating its value and market price. For traditional market assets, wash trading is illegal. However, the NFT market is unregulated. It’s thought that up to 80% of NFT trading volume came from wash trading. The result was an overhyped and artificially overvalued market without stability, real worth, or backing.
What Does the Future Hold for NFTs?
Since NFTS have plummeted significantly, does that mean they’re dead? The answer is both yes and no. While the original NFT market won’t ever be the same, non-fungible tokens have taken different forms for different uses.
Many are optimistic about the future of NFTs and their potential. While they may not be worth as much as they once were, they can still be used to help businesses and individuals in various ways.
Going Beyond Digital Art
Most people associate NFTs with digital art and collectibles. But they can also be used to claim ownership over digital property. Tokenization makes it easier to protect digital assets from fraud or misuse. Personal data, domain names, and social media handles can all be verified through an original NFT identity.
There can also be a crossover of digital NFTs and assets in the real world. Many might use an NFT to signify they own a certain luxury good, vehicle, or piece of real estate. Given the nature of digital tokens, this can even extend to intellectual property. There are virtually no limits to what digital tokens can represent and do for everyday transactions.
Potential NFT Application
While NFTs were formally created in 2017, they’ve been used in the gaming industry long before that. Gamers could buy skins, props, and in-game items. It’s expected that this trend will develop even further. This might result in a more interactive and lifelike game economy, where players can purchase items and freely trade amongst themselves.
Artists can also leverage tokenization to ensure better rates and compensation. If an artwork requires a digital token to prove purchase, it gives artists better control over how their work is distributed.
Other NFT Applications
Besides art, gaming, and real-world items, there are other ways that tokenization might be used in the future. Below are a few ways non-fungible tokens can change the business landscape.
Entrance Tickets for In-Person Events
Instead of using real tickets, some event planners might offer an NFT token for conferences, sporting events, and concerts. This digital invitation might be a more convenient way to access important functions permanently. Many businesses might introduce tokenization alongside an app that makes the experience more pleasurable.
Private Groups and Community Entrances
Some communities might wish to keep their membership exclusive. So in the same way passwords protect entry, entrance might require an NFT. They can even symbolize a hierarchical level in private clubs or communities.
Coupons, Discounts, and Promotions
NFTs are also finding their way into customer retention and marketing landscapes. An NFT can easily work as a coupon, membership card, or discount for your favorite service. Companies might slowly begin to replace traditional coupon methods entirely.
Additional Product Information
As mentioned, using an NFT can help others identify who owns an item. When stored, it can also give new buyers relevant information. For example, users can buy a car that comes with an NFT that gives information on mileage, past owners, and official registration.
Brands Already Embracing NFTS
To better predict the NFT trends of the future, it helps to look at certain contemporary applications. This will give us a clearer picture and help us anticipate how digital tokenization might change everyday life for businesses and individuals. Certain companies have already embraced the power of tokenization for more efficient and smoother brand experiences.
Starbucks Special Loyalty Programs
At the end of 2022 (when NFT interest was dropping), Starbucks launched a special loyalty program with an interesting twist. Those admitted would collect points in the form of digital tokens. Once they collected enough, they could exchange them for rewards, merchandise, or discounts.
Luxury Giants Gucci, Luis Vuitton, and Dior Using NFTS
One of the biggest issues in the luxury industry revolves around counterfeit items. While the quality is hard to match, certain items can come remarkably close to the real thing. By selling luxury clothing with an NFT, consumers can receive confirmation that the product is indeed genuine.
This is highly beneficial for luxury companies as it can help maintain brand reputation, customer trust, and loyalty.
Adobe and Microsoft Beta Version Testing
When a tech company does beta testing, it will make its platform available to a small amount of users. Companies like Adobe and even Microsoft have used special NFTs and tokenization to make this process as smooth as possible.
Users then give feedback regarding the platform and are rewarded with other tokens that can be exchanged for special perks, discounts, or even more platform access.
Digital Souvenirs at the Australia Open
The Australia Open has recently started using NFTs, too. These collectible tokens can represent match statistics, moments, and highlights that give viewers more information. Once the tournament is complete, they can buy these tokens as souvenirs or discounts for attendance to later tournaments.
The Final Verdict on NFTs
So, are NFTs dead? In one way, yes. The unregulated and artificially blown-up NFT market is probably a thing of the past. After reaching its peak in 2021, it dropped almost as suddenly as it rose to fame and promise. But while it might be practically impossible to trade NFTs for millions of dollars now, they still function as tokenization in other markets.
Both artists and gamers will most likely increasingly use NFTs in the future. Ownership of intellectual and digital property through tokenization is another route many businesses and individuals might choose to take. NFTs essentially allow you to prove that a certain item is both yours and authentic. As their uses diversify, the market might be worth less overall than in 2021, but it will likely be much more stable.
How Much Does It Cost to Build and Operate a Video Streaming Platform?
Now, more than ever, consumers are turning away from cable TV and using streaming services like Netflix, Amazon Prime, and Hulu. By 2027, the video streaming industry is expected to be worth more than $842.93 billion. Unsurprisingly, even more entrepreneurs are becoming increasingly interested in joining this growing market. After all, it’s ripe for new ideas, growth, and innovation. But just how much does building a streaming service cost?
Here, we’ll cover the considerations and costs of building and operating a video streaming platform.
Starting Your Streaming Platform –The Initial Costs
To tap into the billion-dollar video streaming market, you’ll first need to build your platform from scratch. While doing so will undoubtedly be a serious investment, the exact costs will fall into a wide range between hundreds of thousands and millions of dollars.
Storage costs, infrastructure, content licensing, and app design are all essential aspects that make a streaming service successful. Entrepreneurs should begin with a niche idea and detailed business plan before working out general price ranges for each step.
Consider consulting with experts or professionals who have experience in related industries. For example, a software engineer might be able to give you a price estimate for backend development.
Of course, the price will also depend on just how complex your service is. You might focus more on UX/UI design, while others might allocate more funds towards data hosting.
Let’s examine some of the main costs of creating and running a streaming platform.
Storage and Hosting Costs for Your Streaming Content
Storage and hosting costs are the main expenses for starting a streaming service.
If you stream a substantial amount of content, you’ll need enormous digital space for storage. Your storage and hosting space allows large numbers of users to access content through the platform.
To accommodate smooth hosting, you’ll also need a fully developed infrastructure, including cloud-based storage, servers, and content delivery networks.
For a modest streaming service with a smaller content library, storage and hosting alone could cost you a few hundred to a few thousand dollars every month. As your user base rises, you can expect to pay $10,000 or more for storing and hosting your content.
Buying the Content and Licensing for Your Streaming Service
This is probably the most complicated yet important step for your streaming service. You’ll need access to high-quality content to keep people subscribing and viewing your streams. Users will also need to get rights to distribute their content.
Typically, this is bought through content creators (broadcasting agencies), tech vendors, or even consulting agencies who can guide you through the process.
There are countless factors at play here. The process might also require legal professionals, business strategists, and a content acquisition team to cover every aspect of the project. Typically, this will add an additional cost of tens of thousands of dollars to even millions, depending on the content type, its creator, and the overall amount of content.
Creating the Platform’s Infrastructure With a Developer Team
Once you have storage and content ready, you’ll also need to build a solid infrastructure for your streaming. This is the platform; you’ll need a backend developer to complete the task.
The result should be a platform that can handle heavy user traffic, integrates well with devices, and provides excellent viewing experiences for subscribers. This step is crucial. You can host all the best content, but it won’t amount to much revenue if users don’t have a pleasurable experience.
For this step, you’ll need to invest either in one backend developer or a whole team. Backend developers are typically paid $51k to $133k a year, depending on the complexity of the project and their relevant experience.
Creating a Pleasurable User Experience
Once the platform is created, the service still needs more work before entering the market. Entrepreneurs will need the expertise of UI/UX designers to ensure the platform and web page have custom designs that make subscribing an easy experience for users. This won’t be a one-time price and will most likely take lots of feedback and testing before an adequate solution is reached.
These custom designs aren’t extras; they’re key for providing the audience with the right viewer experience. Since there are so many streaming platforms in today’s market, a good UI/UX design makes your service stand out.
As with other professionals, the exact price of hiring a UI/UX designer will depend on the complexity of your project and the designer’s qualifications. In the United States, the average annual salary of a UX designer is $95,000.
Adding Specialized Features to Your Streaming Service
Design shouldn’t be the only way your streaming service differs from other streaming platforms. This is a highly competitive market, so entrepreneurs will need specialized features from a developer team.
Some examples of these features may include downloading content for offline watching, maintaining customer profiles, sharing, and personalized content feeds. You’ll most likely need to test this and acquire customer feedback after the initial launch.
This expense can typically cost between tens of thousands and millions of dollars.
Maintaining and Running a Streaming Service
As we mentioned, the initial investment in creating a streaming service can be in the millions of dollars. More modest services with less content and simpler platforms might be able to get by for less. Once you get revenue, these expenses will be easier to cover overtime.
However, it’s not just starting a streaming service that requires substantial investment. Entrepreneurs must also make regular monthly payments for maintaining and running the service properly.
General Staffing
Once the platform is ready, you’ll need a well-trained team to ensure everything goes smoothly. Some of them will be tasked with developing the product, while others will hire whole departments just before the launch.
Some important teams include:
- Your technical team – This will most likely be the same team that worked on creating the app in the first place. It includes your developer team, UI and UX designers, database architects, and system administrators.
- Content acquisition team – You’ll have to negotiate to obtain audio and/or visual content through a content acquisition team consisting of legal professionals and business strategists.
- Marketing and PR team – To ensure your platform is portrayed to the public correctly, you’ll need a team of marketing and PR experts to introduce and promote your brand among media channels.
- Customer care team – If anything goes wrong with your platform, customers want to contact a customer care specialist to solve the problem.
- Security team – In today’s age, cyber security threats are becoming more advanced. Entrepreneurs will need a team focusing on protecting the platform.
While these are the main departments, other teams within your streaming service might include Q&A (quality and assurance) testers and data analysts. Entrepreneurs looking to cut costs will benefit from creating a list of team priorities and then allocating funds respectively.
Finance, Maintenance, and Subscription Service Management
Most successful platform services today are subscription-based. Customers pay a monthly fee and in turn get access to all the latest television shows, movies, and podcasts. Once you establish a payment process, you’ll also have to maintain the system so it’s available.
This will usually require the help of a third-party company, which might take a small percentage of monthly earnings. Typically, you’ll also have to pay content providers a certain regular fee to keep your licensing active. However, this will depend on your region.
Marketing and PR for User Acquisition
Even if you have the best product in the world, it won’t reach many people if it isn’t marketed properly. Streaming services like Netflix and Hulu heavily depend on campaigns and ensuring their brand is present across various media channels. In this way, they establish brand authority over time. For instance, Netflix has become almost synonymous with streaming blockbuster movies.
Marketers working for your platform will need significant funding to create ad campaigns, promotions, free trials, and discounts to attract new users. They’ll also need to constantly promote the service across multiple social media channels to build and maintain the brand’s authority.
Updating and Maintaining Infrastructure
Without a solid infrastructure, you won’t be able to host content for your viewers. So you’ll have to pay for content delivery networks based on your data transfer. To ensure everything runs smoothly, frequent backups might also add to the costs.
Servers are another part of your infrastructure that might need consistent updates, security patches, and maintenance, and which will also add to the overall cost.
Starting and Running a Streaming Service - What to Expect
By now, you’ve seen that there’s a broad range of skills, teams, and costs needed to start and run a video streaming platform. Entrepreneurs can expect to pay anywhere between hundreds of thousands to millions of dollars. This includes acquiring the content, storage, hosting, creating the platform, marketing it to your target audience, and maintaining it over time. The exact price range will depend on how complex you want the project to be.
While some might invest heavily in marketing and providing a specific niche service, others might spend more perfecting the product.
Many might think creating a service or product is done once it’s launched. However, that’s just the beginning. As time passes, entrepreneurs will likely need to manage and reallocate funds depending on the product’s strengths and weaknesses. By listening to the target audience, you can create strategies with your staff for more effective service and, in turn, better revenue.
The Ultimate Guide to Video Streaming Protocols
We’ve all come to rely on video streaming for entertainment, connection, and productivity. But have you ever wondered what makes it possible? The answer is the complex world of video streaming protocols - a combination of technology and innovation that delivers your favorite shows and virtual meetings to your screen.
Let’s take an in-depth look at how these protocols work and what they mean for the future of video streaming.
What Are Video Streaming Protocols?
Nowadays, it’s hard to go a day without streaming video. Many people predominantly watch movies, TV series, live sports, news, and more through on-demand streaming services.
While many take this technology for granted today, it wasn’t always available. Traditional film takes up a great deal of space when converted into digital format. Meanwhile, uncompressed audio and video also take up a huge amount of storage space, and their size makes smoothly streaming them nearly unfeasible. Thus, the rise in popularity of streaming can be attributed to the availability of newer protocols used to break down video files into chunks and deliver them to viewers.
These protocols use compression codecs like H264 to shrink the file size of the videos and store them in a container format (like .mkv or .avi) before they are transferred over the web. Depending on whether you are watching a live stream or VoD (video-on-demand), the source of your video will differ, and the speed and compression requirements will also vary.
The Rise of Video Streaming
Thanks to streaming platforms, entertainment is now available on demand, often in different regions at the same time. Binge-watching has become so popular that it has become part of the popular culture.
Instead of being restricted by a network’s programming schedule, people can now watch whenever they want, whenever they want. More significantly, streaming platforms have made entertainment much more accessible, regardless of income or location, through subscription plans and other options.
Television networks and cable companies have had to find new ways to keep up with the ever-evolving digital space. Some have started their own streaming services, while others have formed collaborative relationships with those that already exist. All this competition has led to an improved level of content available as companies try to hold onto and attract more viewers.
But it’s this rapidly growing demand that has presented challenges for the existing video streaming technology. With increasingly higher definition and the sheer volume of content streamed, the demand for improved streaming protocols is seemingly never-ending.
The Traditional Titans - RTMP and RTSP
Many viewers have probably experienced RTMP (real-time messaging protocol)_and RTSP (real-time streaming protocols) when watching video content online. These traditional streaming protocols are widely accepted due to their reliable performance. They are usually compatible with players that have been around for decades, such as (the recently deprecated but once-ubiquitous) Adobe Flash or Apple QuickTime Player. That said, there are still some drawbacks when using these protocols. For example, RTMP is not the best choice for mobile device streaming, and RTSP often requires additional setup on your firewall. Let’s go deeper into both.
Real-Time Messaging Protocol (RTMP)
Real-Time Messaging Protocol (RTMP) is one of the oldest protocols for live video streaming over the network. It keeps a persistent connection between servers and end destinations, producing solid performance with reduced latency.
Although many browsers and devices no longer accept RTMP, it remains popular for sending video data online due to its reasonably low latency for an old protocol and support for legacy software. Combining RTMP with other streaming protocols may allow for video streaming across various devices from different eras.
Real-Time Streaming Protocol (RTSP)
RTSP is a protocol that lets you control streaming media servers, like turning the TV on or off. To use RTSP, a user sends an RTSP request to the streaming server. This starts the setup process for video and audio streaming. After that, the actual data is sent using RTP. You can think of RTSP as a remote control for streaming media - it helps you turn streams on and off without having to send the data. The RTP protocol does that job instead.
The Up-And-Coming Video Streaming Protocols
As technology evolves, so too does video streaming – meaning more secure and efficient ways to distribute content. Next time you fire up your favorite show or movie, take a moment to appreciate the intricate network of protocols making it all possible.
HTTP Live Streaming (HLS)
HLS stands for HTTP Live Streaming, which is an effort by Apple to make watching video content online much easier. Before HLS, most smartphones used QuickTime Streaming Server as their media streaming standard. Unfortunately, QuickTime depended on non-standard ports for data transfer, and this caused firewalls to block real-time streaming protocol (RTSP).
Apple fixed this by introducing HLS, which uses the web’s native protocol. This means that you can now deploy content using regular web servers and content delivery networks. It works well in wired and wireless connections, automatically optimizing playback speed even when conditions vary.
Faster-Than-Light (FTL)
FTL stands for Faster Than Light—the speed of light, that is. FTL is a live streaming protocol that delivers low-latency streams to devices and platforms like XSplit, OBS Studio, Windows, and Xbox One. It uses two powerful modern video and audio codecs – Opus and H.264 – to provide streams that look and sound crisp, but the tradeoff is lower bitrate than RTMP’s, about 7 Mbps.
Unfortunately, since FTL is still relatively new, it can sometimes be a bit unpredictable. But it’s already been integrated into the Restream ecosystem, so you can count on quality streaming experiences with Mixer and Restream.
Secure Reliable Transport (SRT)
SRT is an open-source streaming protocol developed by Haivision and Wowza, which will likely replace RTMP soon. It offers similar advantages, such as high stability and low latency, making it possible to stream over unreliable networks. A downside is that the playback option isn’t available yet.
The developers claim SRT helps protect live videos from stutters, bandwidth fluctuations, and packet loss. Additionally, it supports real-time communication since its latency is close to FTL and WebRTC. It’s also codec-agnostic, meaning any modern video or audio codec can be used with it. However, note that since this technology is still relatively new, not all platforms have support for SRT yet.
Web Real-Time Communications (WebRTC)
WebRTC stands for Web Real-Time Communications. It works over the web and inside browsers. Every modern browser supports it, so even if you’re using a native application, you can still use WebRTC. This makes communication across different applications and websites much easier.
In the past, if you wanted to build anything with voice or video calling capabilities, you’d have to develop it in C, C++, or similar, which had long development cycles and was expensive. WebRTC changes all that by providing a JavaScript API layer, so developers don’t have to use complex code to build their applications. Although WebRTC is primarily written in C++ internally, many developers won’t need to touch it.
Dynamic Adaptive Streaming over HTTP (DASH) - MPEG-DASH
MPEG DASH uses a single XML-based file, usually with the .mpd extension, and can be used to send protected content through its compatibility with DRM and CENC encryption.
It’s well-supported across many major platforms like YouTube, Netflix, Roku, Chromecast, and Android/Apple ecosystems. Popular media players that support MPEG DASH include VLC Media Player.
Adobe HTTP Dynamic Streaming (HDS)
Adobe HDS is a streaming service that breaks up live videos into smaller chunks and sends them to the player in real time over the internet.
With adaptive bitrate streaming, the video quality will automatically change so viewers have the best possible experience, even with large audiences. Adobe HDS can also be used for DRM protection and to stream videos to places where a Flash Player isn’t available.
The Rise of FAST Channels
Ad-supported streaming television is gaining momentum as subscription plans become more expensive in the era of streaming services. People are actively seeking alternative ways to consume content without incurring additional expenses. This opens up new possibilities for creating protocols that can satisfy both viewers’ needs and maximize monetization opportunities. In other words, it’s no longer just about the technology but also about how videos are delivered.
This has led to the development of FAST (free ad-supported streaming TV) services. These channels allow you to watch traditional TV on your web-connected devices like CTV.
Choosing the Right Protocol
Finding the right streaming protocol to use can be tricky. Each one offers different advantages and drawbacks; which you choose depends on the situation. For example, for broadcasting a live event, SRT or WebRTC might work best as they reduce lag time. On the other hand, if you’re sharing pre-recorded videos, HLS or MPEG-DASH is probably the better choice.
Some of the most popular protocols for streaming video include RTMP (Real Time Messaging Protocol), RTSP (Real Time Streaming Protocol), Apple HLS, Low Latency HLS, MPEG DASH, Low Latency CMAF for DASH, Microsoft Smooth Streaming, Adobe HDS, SRT (Secure Reliable Transport), and WebRTC (Web Real-Time Communication).
Some of these protocols are considered obsolete but still have a purpose in varying scenarios. There are several competing modern standards, so at this point, there is no definitive “ideal” protocol. Factors such as latency, scalability, cost of delivery, consumer device requirements, support for DRM protection, and more affect the protocol of choice for each platform and provider.
Prime Protocol
Video streaming protocols are the foundation of how digital video works, whether you’re an enthusiast or content creator. So, there’s no harm in taking some time to become familiar with them and exploring the vast diversity of protocols.
11 Trends in Video Streaming Technology to Look Out for in 2024
Digital streaming technology is advancing at a breakneck speed, and not showing any signs of slowing down. So, as 2024 approaches, video streaming marches on with newly emerging protocols, a reworking of advertisement and subscription plans, and a retro revival.
It can be overwhelming to keep up with, but let’s take a closer look at the trends that will affect video streaming technology in 2024. Popcorn (or any other snack) is optional.
1. Optimized Video Delivery
Video streaming can serve many purposes. Entertainment is an obvious one, but it can also provide public safety information, ensure business continuity, and facilitate day-to-day activities for different business and social situations. This means that reducing lag is the prime concern for streaming technologies.
In the coming years, content distributors state that they strive to achieve sub-second latency for hybrid environments and interactivity. That said, the speed of your connection is ultimately dependent on the streaming protocol as well as the network used to broadcast your live stream.
Real-time streaming is difficult to execute as the interactive environment can be prone to lagging, errors, and pauses. For a seamless delivery of video streams with ultra-low latency capabilities, the provider needs a strong digital infrastructure. Google’s WebRTC technology is one such solution that has been emerging in many video conferencing applications for smoother streaming.
2. Capitalizing on Nostalgia
As millennials settle into adulthood, many businesses are tapping into their nostalgia for the ’80s and ’90s. For instance, streaming services like YouTube Red, Hulu, and Netflix have found success with reboots of fan favorites. “Cobra Kai” (a “Karate Kid” revival) was at first a YouTube Red exclusive, while “Veronica Mars” has been a hit on Hulu.
Netflix seems to be leading the pack by reviving iconic series like “The Baby-Sitters Club,” “Chilling Adventures of Sabrina,” and “Carmen Sandiego” to target younger generations, as well as sequels to once-popular shows such as “Fuller House,” “One Day at a Time,” and “Gilmore Girls: A Year in the Life.” “Stranger Things” is set in the ‘80s and frequently references pop culture from that era.
Looking at 2024 and beyond, it’s safe to assume that this trend will continue and likely accelerate. As the early 2000s become increasingly distant, the nostalgia for this decade will reflect that, and the 2020s are the perfect time for the revival of the 2000s media.
3. Ad-Supported Tiers
Recently, both Disney+ and Netflix have introduced lower-priced tiers with ads included. Amazon is also now including advertisements with Thursday Night Football.
Depending on how people react to this, other platforms may follow suit. Although some criticism has been leveled at Netflix for adding advertisements, CFRA increased its stock price target this week because of the prospects of its ad-supported platform.
Having multiple monthly subscriptions for various streaming services has been one of the major drawbacks of the format. As more providers are experimenting with streaming platforms while users simultaneously become more discerning about what services they subscribe to, varying ad-supported tiers may be the solution.
4. International Content
More and more streaming services are opening their doors far beyond Hollywood. Dubbed shows from all over the world are reaching broader audiences with fewer regional restrictions.
International hits such as “La Casa Del Papel” and “Parasite” have proven that content in other languages, watched with subtitles, is a viable new way to engage in entertainment. The rise of South Korean dramas is another example of this trend.
Over the years, standard Hollywood fare has lost some charm as audiences demand more diversity in content and streaming services become available in more regions. This means it’s safe to expect to see even more local language series in 2024 being brought into the international spotlight.
5. Rethinking Advertisement
The way TV and video ads are presented to viewers is changing. Growing evidence shows that traditional advertisements aren’t particularly effective because they rely on tropes and cannot provide niche experiences to diverse users.
Therefore, companies want to know more about their users – like their shopping habits, interests, and where they live – to show ads that are more likely to interest individual users. This is supposed to be better for the company and the customer because it means you’re only seeing ads that might genuinely benefit you.
But whether or not people will feel comfortable sharing their personal data is still up in the air. Some new rules are coming down the pipeline that may change how things work in the media industry, especially online and on mobile devices. These changes could mean less regulation for everyone involved, including traditional media companies. However, network neutrality is still important.
6. Ultra-High Definition Streaming
As video quality and available bandwidth increase, streaming services are looking into means to tap into the potential. Ultra-high definition (UHD, or 4K as it’s often known) is the assumed future because it offers a resolution four times higher than 1080p.
With WebRTC and SRT enabling fast streaming without losing any bit of detail from UHD content, it’s safe to expect this new technology to become even more prominent in 2024. This means exceptional clarity even on large displays, such as living room televisions.
Whether diminishing returns in video quality are fast approaching is up to each user and their setup and preferences. However, with the popularity of larger TV screens, higher resolutions are a given. Plus, more choices regarding streaming quality give more freedom to streaming services to customize their subscription tiers.
7. Personalization and AI
The streaming landscape has drastically changed over the past 10 years, offering viewers a myriad of entertainment and educational content. Unfortunately, navigating the abundance of content can feel like an overwhelming chore in some instances. Additionally, streaming can be expensive and oftentimes doesn’t feel very personal.
Personalization is the future of streaming. And as 2023, in particular, has seen an explosion of interest in artificial intelligence (AI), it’s easy to assume that streaming services will tap into the potential of AI and machine learning. This way, platforms could tailor recommendations to individual viewers more efficiently and provide more options to make finding content easier. As the industry matures, quantity will take a back seat to quality as personalized experiences become more commonplace.
8. The Proliferation of 5G
The arrival of 5G and the Internet of Things (IoT) technology has offered a possible boost to digital infrastructure. While 4G was a major step up from 3G in speed and support, 5G carries over the legacy and improves upon it. It has the potential to be considerably faster, with virtually no latency for video streaming.
That means that whatever you’re streaming, whether it’s a movie or a video game, will have minimal or no lag or stuttering. Additionally, video streaming on mobile devices will get a noticeable boost.
9. Streaming in New Industries – Fitness
The fitness industry is huge – more than $96 billion worldwide. And the digital fitness market is a considerable subset of that. It’s not hard to see why: when lockdowns happened, gyms had to adapt and figure out how to stay connected with their customers. Video streaming allowed this connection to remain strong and for people to work out from home.
As a result, a blended model emerged: on-demand and live-streamed workouts paired with in-person services. This made it possible to have the experience of being at the gym without having to leave your house. While gyms are open again around the world, these trends will remain and grow, likely extending into other activities. In fact, Global Market Insights estimates that livestream fitness will jump 35% by 2026.
10. Compression Technology
Compression technology is the backbone of streaming. It compresses and packages data, making it quicker and easier to transport over any connection type and to any capable device. As the industry grows, expect to see new compression methods that will make accessing video and audio from all around the world faster and more efficient. This possible trend calls back to the aforementioned increasing demand for higher-definition video streaming.
11. Cloud-Based OTT Video Software
Cloud technology is emerging as a cornerstone for delivering content, with the streaming industry becoming more ubiquitous. The cloud’s inherent scalability and flexibility make it an ideal backbone for OTT (over-the-top) platforms, allowing it to adapt to fluctuating viewer demands.
But the cloud’s role isn’t just about storage and scalability; it’s expected to offer more sophisticated features. By 2024, we can anticipate a surge in cloud-enabled capabilities, such as real-time analytics that provide insights into viewer behavior, AI-powered algorithms for personalized content recommendations, and robust security measures to protect against seemingly surging data breaches.
These advancements can enhance the user experience and provide streaming services with valuable data to fine-tune their offerings and analyze user engagement.
Stream Into the Future
You can expect some amazing things from the video streaming industry in 2024. Plenty of interesting and curious developments are taking place, with new technologies being unveiled and fresh ideas entering the scene. The ultimate destination of the video streaming course may not be perfectly clear, but its power over how users consume media is unquestionable.
E-Commerce Microservices vs. Monoliths - Understanding the Differences
Modern E-commerce is challenging to navigate if you don’t know what you’re doing. Customer expectations are sky-high, demands and trends can change every other month, and new technologies flood the market with fresh solutions.
Multiple communication channels, omnichannel marketing, and offering new ways to buy are the principles that dominate E-commerce. But not everyone can keep up with this hectic pace, and it’s not for a lack of trying.
Sometimes the issue falls on the architecture used to compete in the E-commerce space. The software solutions that stand out are called monoliths and microservices. And despite their intuitive designations, they might not work how most business owners think.
E-Commerce Microservices 101
Microservice architectures used in E-commerce are built upon loosely connected services that work together to create a stable operations system. Microservices are generally modular and connect via API gateways to generate a flexible and scalable service suite. But all services can run independently from each other and don’t have to overlap much.
Although some refer to the term microservices as nothing but a buzzword, it’s quite a popular E-commerce trend with significant advantages. For example, Amazon, eBay, and Uber have switched from monolith to microservice architectures over the years. Netflix did the same, and so did Spotify and the choice of going towards microservices is even evident in the small business sector.
Over half of U.S. companies that make between $5 and $50 million see the switch to microservices and APIs as a matter of urgency. But that doesn’t mean there aren’t plenty of companies with over $50 million in revenue that shares the same thoughts.
Due to how they work, microservice architectures allow businesses to be more innovative. In E-commerce, this often means supporting mobile commerce and increasing its reach through various apps that can sustain steady or accelerated growth.
Microservices Pros and Cons
Adopting a microservice architecture isn’t a perfect solution. There are pros and cons worth weighing before making a clear decision.
Microservices Pros
In short, microservices offer three distinct advantages.
- Agility
- Superior customer experience
- Easy maintenance
Microservice systems can have many more components than monoliths. But they also operate independently, leaving ample room for new integrations, innovation, etc. With implementations being easier, using microservices makes companies more agile and flexible. They can tackle modern E-commerce challenges with contemporary solutions and can grow continuously without significant drops on workflow, production, etc.
The customer’s shopping experience is one of the main draws of online consumers to certain stores and E-commerce platforms. People want options, fluid navigation, cross-platform compatibility, interactivity, etc. These are things that only an open API approach, delivered by a microservice architecture, can deliver.
Lastly, maintenance is easy despite the complex nature of microservice systems with multiple independently operating components. If one element of the service suite fails, the others don’t have to suffer. Components can be isolated and repaired without affecting the connected ones. The nature of microservice systems allows for shorter downtimes and faster fixes.
Microservices Cons
The top three cons of microservice systems include the following:
- Technical expertise is needed
- It requires an infrastructure change
- A mindset change is mandatory
While maintenance is quick and easy to perform, not everyone can do it. A microservice architecture involves many moving parts, and each one can have its own code base and environment. Sometimes in-house teams are ill-prepared for this and trusted service providers become mandatory to manage and maintain the entire ecosystem.
Many microservice infrastructures need significant adjustments and changes that aren’t always compatible with a company’s wider infrastructure. Existing monitoring tools and other elements may need changing and implementation by trusted and experienced technicians.
Finally, moving from legacy ERP systems to microservices implies on deciding to do things completely differently. Not everyone easily changes their mindset, even when they know it’s for the better.
E-Commerce Monoliths 101
Monoliths work very differently than microservices. If microservice architectures contain service suites, monoliths are individual units built of four components. A monolith contains the following.
- Databases
- Business logic
- Data interfaces
- User interfaces
But the main distinction is that a monolith is deployed as a standalone solution or individual unit.
Original monolithic E-commerce solutions or platforms were developed for E-commerce brands with a limited audience reach. You can think of SalesForce, WordPress, Magento, Hubspot, and others as monolithic architectures.
Traditionally, monolithic E-commerce catered to brands that would reach customers through desktop computers. They offered a narrow solution that still allowed companies and brands to micromanage all aspects of the online shopping experience, like processing transactions, managing stock, etc.
In the early days of E-commerce, monoliths were all the rage. Such architectures provided businesses with simplified solutions to manage the front and back end. Naturally, monolithic architectures could look very different. For instance, Uber relied on a monolithic system when it initially offered its services in a single city.
But over time, E-commerce advanced considerably. The arrival of mobile technology (tablets, smartphones, smart watches, etc.) created a new way to approach online shopping. It changed things for many businesses; even giant companies admitted to feeling stuck or lacking scalability.
Make no mistake. Many ERP vendors still offer monolithic solutions and have long-standing contracts with companies churning over $50 million in revenue. Therefore, monolithic architectures are still very much in use today, despite many brands and companies agreeing they see microservices as the better option.
Over 70% of U.S. merchants doing at least $5 million per year say that monolithic systems make it almost impossible to integrate superior E-commerce solutions. Over half of those making over $50 million agree. As robust as a monolithic architecture can be, it makes it very difficult to work with multiple vendors. It isn’t easy to create the ultimate user experience by adopting different apps and digital solutions.
The current E-commerce environment is highly competitive. And while monoliths have their uses, they can lack the flexibility to support certain industries’ profit from the rise of e-Commerce.
Monoliths Pros and Cons
Although obsolete in some areas, monolith architectures still have advantages and disadvantages in modern E-commerce.
Monolith Pros
Let’s look at the three main positive aspects of monolithic architecture.
- Simplicity
- Built for the long term
- Great for startups
E-commerce software built on a monolithic architecture is one of the easiest choices to make. It’s a single system, single deployment, and offers much-needed peace of mind.
Monolithic systems, such as legacy ERPs, aren’t deployed quickly. However, they are designed to stay in place and sustain E-commerce solutions for the long haul.
Startups, or small and micro businesses, often enter the market with a narrow vision of what they want. In these scenarios, monolithic architectures can help startups focus and avoid making new changes and implementations on the fly.
Monolith Cons
Now let’s look at the main disadvantages of using monoliths.
- Outdated solution
- Cascading issues
- Low scalability
Fewer and fewer top vendors rely on legacy ERPs and monolithic architectures. Modern E-commerce businesses must eventually adapt to microservices to offer better functionality and customer experiences.
System crashes are more prone in monoliths than in microservices. But the bigger issue is the interlinked nature of the monolith components. If one fails, the entire ecosystem is at risk of cascading failure. This means that making repairs and minimizing downtime isn’t easy or cheap.
Lastly, scalability isn’t realistic, at least at the rate at which modern E-commerce demands companies to grow. Integrating other platforms into the monolith API can be grueling work and take months to achieve. That’s without considering the expertise required to make changes.
When to Use Microservices
Microservices make the most sense for a fast-growing company or an ambitious brand with the capability to scale fast. Additionally, it serves companies that must meet strict customer demands regarding modern tools and accessibility.
When to Use Monoliths
Implementing a monolithic architecture may seem like a waste of time, given modern E-commerce expectations. However, monoliths may still be a good solution for years to come for companies just starting out that don’t expect rapid growth.
Microservices vs. Monoliths – Which Is for You
Both microservices and monoliths see plenty of use in today’s modern E-commerce environment. By all accounts, there are more monoliths deployed compared to how many brands and companies use microservices. But the majority of players recognize the need to eventually transition to microservices from monolithic architectures.
This begs a simple question – Is it worth going with a monolith architecture only to have to make a significant change somewhere down the line? Many would argue that shouldn’t happen. Although monoliths can provide sustainable solutions for years to come, there’s no telling how the E-commerce field will look in the next couple of years.
New disruptive technologies and trends can shake up the E-commerce industry at any moment. In those situations, monoliths can remain stable but stunt the potential of companies and brands to acquire customers and compete in their markets.
Microservices offer the best solution by far in just about every scenario. And who doesn’t want the ability to accelerate growth at will? Microservices provide the edge many monolith and legacy ERP users crave in today’s environment.
Data Science Projects Every eCommerce Needs to Know About
The amount of data available online grows bigger after every click. To make sense of the huge amount of information, eCommerce business relies on various data science techniques. If you wish to learn from your customer’s past activities or purchases to provide them with a new service, data science can help. And if your main goal is to boost customer retention, there are plenty of other data projects you can try.
In truth, eCommerce businesses are some of the biggest consumers of data science techniques, and the ones that don’t experiment with them are more prone to fail. In this article, we prepared the top nine projects you should try if you run an eCommerce business.
1. Recommendation System
If you ever made a purchase on Amazon or any other eCommerce website, you most likely noticed the “Recommended products” section as you scrolled a page. Over the past few years, more eCommerce businesses have started implementing sophisticated recommendation systems to add value to the company and generate more revenue.
A recommendation system filters choices for specific users depending on their past searches or purchase data. It allows a user to have a personalized website experience by being offered products they’re interested in based on their previous consumer action.
There are plenty of ways to use the recommendation system. A user looking for a new iPad on Amazon will most likely be interested in frequently used accessories like a detachable keyboard, protective covers, etc. These items can be represented as “Recommended products,” which the consumer can easily add to the basket.
Three main ways to set up a recommendation system include collaborative filtering, content-based filtering, and hybrid filtering.
Collaborative filtering is about giving recommendations based on user activity data on the website as well as by analyzing their similarity to other users’ activity. This is a frequently used technique as it only searches to find similarities among different interests of users.
Content-based filtering offers recommendations based on an item’s description and the user’s profile. The recommendation depends on the products users have browsed for or liked in the past.
Finally, hybrid filtering is the combination of the two methods above. Many eCommerce owners can make separate predictions with the two techniques and combine the results later or use the results from one technique as input for the other.
2. Customer Lifetime Value Model
Many eCommerce businesses rely on the customer lifetime value model to predict the net profit coming from their future relationship with a customer. This model calculates how much someone can bring to the company’s revenue in the long term. The figure is calculated with the help of the purchaser’s history and interaction with the eCommerce website or similar businesses.
The formula is pretty simple – you just need to multiply the average order value, number of repeat orders, and the average customer lifespan. The average customer lifespan is the amount of time during which the person would remain your customer.
The customer lifetime value model makes it easier for companies to determine which type of customers to focus on and how much revenue they could get in the future. If a certain type of customer is sure to bring more than $3k in revenue each month, while others could only bring $500, the company can retarget their marketing efforts towards the first group.
There are other benefits of this approach as well:
- Business marketing strategy optimization and adjustment
- Definition of objectives for a company
- Bringing cross-selling or up-selling decisions following a purchase
- Helps decide the cost of attracting customers
3. Customer Retention-Churn Model
If you’re an eCommerce business owner and want to add value to your company, consider starting a Customer Churn model. This project is highly related to customer retention, which is all about the ability to keep your customer for a longer period.
Once you have high retention, you can expect more regular income and more sales from a single client. Also, those customers often bring new clients as word of mouth is by far the best marketing tool. Finally, a high retention rate is a sign that your customers love your marketing efforts and products.
The churn model is the most effective way for you to achieve higher customer retention. In a nutshell, this project helps you identify clients who are likely to switch to a competitor’s website. When you identify such a user, you can take action to keep them with you. This model works with a range of metrics, including the number and percent of the lost customers, percentage of recurring value lost, and value of recurring business lost.
Some benefits of this model include helping maintain customer lifetime value, identifying churn customers, or helping track business progress.
4. Detecting Fraud
Privacy and security are becoming a hot trend in recent years. Ecommerce businesses that only focuses on bringing more customers to generate more revenue without protecting their security is more likely to fail. Fraud detection is a multi-million-dollar business that only grows in popularity year after year. With more companies being victims of some sort of economic crime, it’s becoming imperative to invest in fraud detection projects.
The most common types of fraud include identity theft, clean fraud, triangulation fraud, chargeback fraud, friendly fraud, and merchant identity fraud. This list gets bigger by the day. So, to make sure your eCommerce channel runs successfully and without fraudulent activity, it’s crucial to start applying security measures to avoid losing customers.
In order to use data science to solve these issues, you first must identify potential fraud segments. This can include shipping addresses that differ from the billing ones, multiple same-item orders, unexpected international orders, and multiple same-address orders with different cards.
You can detect these activities with the help of data science and machine learning. For example, data mining can help you validate, detect, and correct errors as well as fill up incorrect or missing data. Clustering and classification can also help detect anomalies. Finally, you can match algorithms to eliminate false alarms, predict future transactions, or estimate risks.
All these activities are crucial for boosting your company’s revenue and customer retention, as well as reducing the number of questionable transactions.
5. Improve Customer Service
A happy customer translates to a happy business. To be successful in your eCommerce business, you need to maximize your efforts in building an easily accessible, comprehensive, and helpful customer service.
For example, more businesses have started implementing chatbots into the customer service experience. These bots use natural language processing to make communication easier and can also serve as great sources of audio marketing.
Also, data science can help you extract the ratings and reviews from your website and understand why you received negative feedback. Your data scientists can segregate the reviews and perform sentiment analysis to boost your customer satisfaction by leaving a more positive impact on the clients.
6. Price Optimization
Product price has a huge impact on its demand and profit. eCommerce businesses can rely on big data analytics to predict customer segmentation with a price change response. It’s also advisable to analyze the cost of the competing products to come up with a suitable price for a product or service.
Properly done, price optimization can boost your profit and revenue and let your eCommerce business grow its market share for particular products.
7. Inventory Management
Customer retention depends on product availability. It’s crucial to meet the needs of your customers on time, and inventory management can help you achieve that. This is the process of stocking goods in a healthy condition and place for future use.
However, keeping track of a supply chain is becoming more challenging in the modern globalized world. Using inventory data science and analytics can help you get rid of product scarcity when you most need them.
The combination of data analysis, predictive analysis, and machine learning can help detect patterns and supply chains for your inventory management. You can track the patterns for your most in-demand items and set up inventory strategies with machine learning algorithms.
8. Warranty Analytics
Warranty claim analytics is important because it comes with information about the reliability and quality of products. This can help manufacturers identify early warnings and abnormalities in their products and prevent them from failing in the business.
Two main techniques here include data mining and text mining. These tools can help identify problem areas in claims patterns for a product and convert data into insights, recommendations, and real-time plans.
9. Customer Sentiment Analysis
Customer sentiment analysis is a widely used tool for eCommerce websites that helps gather all feedback from customers. Data specialists and marketers have found new ways to help retailers transcend old-fashioned in-person surveys and now use social media, analytics, and machine learning for gaining deeper insight into client sentiment.
Most analyses of this type use natural language processing, negative or neutral sentiments, and text analysis. The project involves extracting data from different forms, social media, online reviews, or online surveys.
Data Science as the Essential eCommerce Companion
Thriving in an eCommerce world today is virtually impossible without proper data science techniques and projects. As the amount of information available online is becoming too overwhelming for a person to handle, sophisticated algorithms and machines can help.
Fortunately, data science has developed so fast over the years that you can now use it to enhance almost every aspect of your business. Hopefully, this article has given you some good ideas to help you get started.
The Important Role of Big Data Analytics in Cybersecurity
With the increasing reliance on technology in both our personal and professional lives, it’s no surprise that cybersecurity has become a hot-button issue in recent years. As more sensitive information is stored online, the risk of data breaches and other cyber attacks grows. That’s where big data analytics comes in.
By harnessing the power of large data sets, businesses and organizations can identify patterns and trends that could be indicative of a security threat.
In this article, we will discuss the important role of big data analytics in cybersecurity.
What Is Big Data?
Before we can dive into big data analytics, it’s important to understand what big data is. Big data is simply a term used to describe data sets that are too large and complex to be analyzed using traditional methods. Big data can come from various sources, including social media, sensors, transaction records, and more.
One of the challenges with big data is that it can be difficult to store, manage, and analyze. That’s where big data analytics comes in.
Big data analytics is a process that helps organizations make sense of their big data. By using special tools and techniques, businesses can uncover hidden patterns, correlations, and other insights that would be otherwise difficult to find.
How Big Data Analytics Works
Big data analytics involves four main steps:
Data Collection
The first step in any big data analytics project is data collection. In the context of cybersecurity, this typically involves collecting data from a variety of sources, including network traffic data, system logs, application logs, and security event logs. This data is then stored in a central repository where it can be processed and analyzed.
Data Processing
Once the data has been collected, it needs to be processed to be useful for analysis. This typically involves extracting relevant information from the raw data and transforming it into a format that can be analyzed. After extraction and transformation, the data is loaded into an analytical tool such as a statistical software package or a machine learning platform.
Data Cleaning
Before analysis begins in earnest, the data needs cleaning. This involves identifying and removing any invalid, duplicate, or incomplete values from the dataset. It may also include standardizing the data format so it can be easily analyzed.
Data Analysis
The final step is to analyze the data using various methods such as statistical analysis, machine learning, or text mining. This allows you to uncover hidden patterns and relationships within the dataset that can be used to improve security.
Applications of Big Data Analytics in Cybersecurity
Here are a few of the ways big data analytics is helping businesses and organizations in the fight against various cybersecurity threats:
Development of Predictive Models
Predictive modeling is one of the most powerful tools in the big data arsenal. Predictive models are mathematical models that analyze large data sets to identify patterns and trends. These patterns and trends can then be used to predict future events.
For example, let’s say you run a website that sells products online. You collect data on every customer who visits your site, including their purchase history, browsing behavior, and demographic information. This data can then be used to build a predictive model that will allow you to identify customers who are likely to make a purchase.
This same principle can be applied to cybersecurity. By analyzing data from past security breaches, it’s possible to build predictive models that can identify vulnerabilities and potential threats. These models can then be used to prevent future breaches before they happen.
Intelligent Risk Management
One of the most significant benefits of using big data analytics for cybersecurity is that it enables organizations to manage risk more intelligently. By analyzing large amounts of data, organizations can identify which assets are most at risk and take steps to protect them accordingly.
In the past, risk management was largely a manual process that relied on human intuition and experience. However, this is no longer sufficient in today’s rapidly changing digital world. With big data analytics, organizations can use machine learning algorithms to identify risks and take steps to mitigate them automatically.
This is a much more efficient and effective way of managing risk, as it frees security teams to focus on other tasks. It also reduces the chances of human error, which can often lead to costly security breaches.
Monitoring and Automation
Another way in which big data analytics is being used in cybersecurity is through the use of monitoring and automation systems. These systems are designed to collect data from various sources (e.g., network traffic, user activity, etc.) and then use that data to identify anomalies that could indicate a security breach.
Once an anomaly is identified, the system can then take action to mitigate the threat. For example, suppose a user suddenly accesses sensitive data that normally wouldn’t be accessible to them. The system could automatically block their access and send an alert to the security team.
Real-Time Intrusion Detection
Another huge benefit of big data analytics is that it enables organizations to detect intrusions in real time. By continuously monitoring network traffic and activity logs, security teams can quickly identify when an attack is taking place and take steps to contain it before it causes serious damage.
In the past, intrusion detection was primarily a reactive process that relied on humans sifting through large amounts of data to identify anomalies. However, this is no longer feasible given the sheer volume of data that needs to be analyzed. With big data analytics, organizations can use machine learning algorithms to detect intrusions automatically and raise alerts accordingly.
This allows security teams to respond quickly and effectively to attacks, minimizing the damage caused by them. It also helps to prevent future attacks by giving organizations a better understanding of how attackers operate and signs of an impending attack.
Better Use of Resources
Big data analytics can also help you use your resources more effectively. By understanding where your vulnerabilities are, you can focus your resources on fixing those vulnerabilities instead of wasting time and money on things that aren’t a problem.
In addition, big data analytics can help you automate some of the tasks associated with cybersecurity, which will free up your staff to focus on more essential tasks.
Threat Visualization
One of the most important roles big data analytics plays in cybersecurity is threat visualization. To properly defend against cyber-attacks, you need to be able to see the origins of the threats.
By analyzing large data sets, security analysts can create visualizations that show which regions or countries are most often targeted by hackers. This information can then be used to bolster defenses in those areas or target educational campaigns at users in high-risk areas.
Faster and More Effective Responses to Attacks
In the past, businesses would often only realize they had been attacked after the damage was done. But by constantly monitoring their data, companies can now detect attacks as they’re happening and take steps to mitigate the damage.
This allows businesses to get back up and running more quickly after an attack and avoid the costly downtime resulting from a security breach.
Improved Collaboration Across Teams
To effectively prevent cybersecurity threats, businesses need to have a coordinated effort between their IT, security, and marketing teams. Companies can use big data analytics to ensure everyone works together towards a common goal. This helps to avoid silos within organizations and ensures that everyone is on the same page when it comes to cybersecurity.
Enhanced Security for Sensitive Data
Big data analytics can enhance security for sensitive data by identifying patterns and trends that may indicate a security breach. For example, if an employee suddenly starts accessing a large number of files that they have never accessed before, this could be a sign that they are trying to steal data. By monitoring employee activity, big data analytics can help to identify potential security threats before they occur.
Additionally, big data analytics can be used to monitor user activity and identify patterns that could be indicative of attempted unauthorized access. For example, a sudden spike in failed login attempts from a particular IP address could indicate that someone is trying to hack into the system.
Protect Your Data
Organizations that use big data analytics for cybersecurity purposes often have a risk management strategy in place to protect their data. This strategy typically includes regular backups of data, encryption of sensitive information, and strong security protocols. However, even with these measures, the possibility that cybercriminals could find a way to access and exploit the data remains.
For this reason, it’s essential to have a failsafe measure in place, such as a disaster recovery plan. This plan should outline how to recover from a ransomware attack or any other type of big data breach. Having a plan in place can ensure your organization is prepared for any worst-case scenario.
It is also important to educate employees on the importance of cybersecurity and make sure they are aware of the risks associated with big data. Taking these precautions can help protect your organization from the potentially devastating effects of a cyber-attack.
The Use of AI in Cybersecurity: Everything You Need to Know
Artificial intelligence (AI) has recently been a game-changer for cyber security. With the growing volume and complexity of cyberattacks, AI allows companies to stay ahead of threats. If you’re wondering exactly how cybersecurity benefits from artificial intelligence, you’ve come to the right place. Keep reading to learn everything you need about using AI in cybersecurity.
Why Do We Need AI in Cybersecurity?
With an increasing number of companies and individuals forgoing the face-to-face business approach, cyberspace is growing at an unprecedented rate. Unfortunately, this also means that the cyberattack surface is equally as massive.
The vast attack surface is just one of the challenges modern enterprises face that can’t be solved using a simple human intervention. Other challenges include the following:
- A huge number of devices per organization
- A lack of skilled security professionals
- Massive amounts of data
- Many attack vectors
Artificial intelligence has become essential to information security as the only viable solution for these challenges. Unlike human employees, AI technology can quickly analyze millions of data sets and detect and respond to many cyber threats.
How Is AI Used in Cybersecurity?
Generally speaking, artificial intelligence is a fragmented field employing many different approaches to target specific problems. AI solutions for cybersecurity are no different. There are several ways in which AI is used in cybersecurity to ensure a risk-free and secure environment.
Detecting Threats
Traditional software systems have long stopped being able to keep up with the sheer amount of new malware created regularly.
In contrast, AI systems are programmed to detect malware, regardless of the number of malicious activities and whether they’ve encountered them before. The systems will run pattern recognition, allowing them to identify the slightest attack before it impacts the network.
The more data is fed to the AI system, the more cyberattacks, anomalies, and prevention strategies are learned. As a result, they can prioritize their responses based on what is most likely to attack the organization. This way, the AI systems don’t waste any time on security alerts that turn out to be false positives.
Adequately Responding to Incidents
While detecting an incoming threat is the first step in protecting the organization’s system, appropriately responding to security alerts is crucial.
AI technologies curate threat intelligence from millions of blogs, research papers, and news stories. These comprehensive sources allow them to cut through the noise of unimportant daily alerts and adequately respond to more severe threats.
More importantly, AI-powered systems can respond to incidents quicker than humans ever could. As time is of the essence when sensitive information and data are threatened, reducing response time is one of AI solutions’ most prominent benefits. A quick response will undoubtedly save your network from irreversible damage.
Battling Bots
Although bots are omnipresent on the internet and often disregarded as harmless, this isn’t always the case. In fact, bots can be a serious menace when created with malicious intent. Most commonly, “bad” bots can take over accounts by stealing the owner’s credentials, creating bogus accounts, and committing data fraud.
AI systems can be trained to build a thorough understanding of the website traffic, thus allowing them to distinguish between the bots and the human users. The next step is to separate the “bad” bots from the “good” bots, such as search engine crawlers.
By observing the behavioral patterns of users, AI helps cybersecurity teams modify their strategy accordingly and stay ahead of malicious bots.
Assessing Breach Risks
Thanks to AI-powered systems, an organization can compile an accurate IT asset inventory detailing the following:
- All the devices used within the organization
- All users and their level of clearance
- All applications used and their access to various systems
Artificial intelligence will use these records to predict how and where the organization will most likely be compromised. As a result, the organization can adequately allocate resources to the most vulnerable areas.
Efficiently Protecting Endpoints
The more employees work from home, the more threats to endpoint security.
Basic solutions such as VPNs and anti-virus software can protect the system against certain attacks. However, they typically work based on signatures, meaning you must always keep up with the latest signature definitions. If there’s any lag in updating these software solutions, a malware attack can go unnoticed.
AI-driven endpoint protection tackles the issue in a different, more reliable manner. It establishes a baseline of behavior after being trained repeatedly. If anything unusual happens, the AI system will flag it and take appropriate action. This proactive approach dramatically improves endpoint security.
Securing Authentication
Nowadays, most websites offer a user account feature where individuals can log in and access their services or products. Visitors typically fill in contact forms that can contain sensitive information. Therefore, it’s crucial to ensure that such information remains secure. In addition, the whole network can be at risk if an attacker gains access to a user’s account.
Artificial intelligence is used to secure authentication every time a user logs into their account. It employs various tools, with the most universally used ones being the following:
- Facial recognition
- CAPTCHA
- Fingerprint scanner
After collecting data using these tools, the AI system can decide if the log-in attempt is genuine or not.
The Benefits of Using AI in Cybersecurity
Artificial intelligence presents many advantages in cybersecurity. It helps organizations fend off cyberattacks more effectively than manual techniques or conventional software-driven solutions.
AI Continuously Learns
AI consumes massive data artifacts that allow it to improve its knowledge constantly. Furthermore, these technologies draw data from past experiences to pinpoint vulnerabilities in the system.
Once an AI-powered solution is properly trained, it continues to gather data independently from across the organization’s information systems using machine learning and deep learning. After that, the collected data is analyzed and used to identify relevant patterns in the business network’s behavior. As a result, it can promptly react to deviations from the learned norm.
AI Finds and Responds to Threats Faster
AI can assess the organization’s system much quicker than any cybersecurity personnel. These intelligent solutions can take only seconds to analyze the relationship between threats, such as suspicious IP addresses or malicious files. This helps significantly increase the organization’s problem-solving abilities.
It’s worth noting that not detecting a threat isn’t always the issue. Sometimes the sheer number of simultaneous attacks makes it impossible to respond promptly without using AI.
As with many other benefits, this impressive speed is also made possible by the massive amounts of risk data the AI-powered system analyzes.
AI Can Handle a Lot of Data
Although giant corporations usually face most risks, even mid-sized companies deal with a substantial amount of traffic. This means the cybersecurity personnel can’t keep up with the daily data transfer. Luckily, AI solutions can skim through massive chunks of data to identify potential threats hiding in the sea of traffic.
AI Improves Cyber Security Reporting
AI can also help understand the impact of an organization’s security processes by identifying its strengths and weaknesses. This can allow organizations to report relevant information to all the involved parties, including:
- Stakeholders
- End users
- Security operators
- Auditors
- CISO, CIO, and CEO
- Board of directors
The Downsides to Using AI in Cybersecurity
Artificial intelligence has a huge potential to continue improving cybersecurity. However, no system is inherently perfect, so there are also some downsides to using artificial intelligence in this field.
AI Can Be Inadequately Trained
As mentioned in the article, most benefits of using AI in cybersecurity heavily rely on feeding massive data sets to the system. These data sets aren’t always easy to come by and sometimes require more investment than an organization can afford.
Without an adequate volume of data, AI solutions can render incorrect results and false positives. Furthermore, the systems can use inaccurate or manipulated data. Failing to notice data manipulation can lead to potentially disastrous consequences as the organization fights to retrieve the correct data.
Adversaries Can Use AI
Cybersecurity professionals can use AI to minimize the cyberattack surface and reinforce good practices against malicious activity. Sadly, cybercriminals can also get their hands on AI systems and use them to attack a network.
Adversarial AI causes artificial intelligence models to misinterpret system inputs and open the door to the attacker. Simply put, the attackers can target the data used for training the defensive AI systems and disable or change the warning flags.
Alternatively, hackers can use AI to develop mutating malware that can avoid detection, thus foiling security algorithms.
Driving Cybersecurity Forward
Even with its downsides, employing artificial intelligence to strengthen cybersecurity will be imperative for most modern enterprises. After all, humans can no longer adequately protect the vast cyberattack surface.
A properly trained AI will help identify and prioritize risks, direct incident response, reduce breach risk, and compile and provide the much-needed data to the cybersecurity personnel. As a result, it will enhance the performance of the security teams and pave the way for a cyber-safe organization.
How e-Commerce Is Transforming Marketing
In the world of business, e-Commerce and marketing represent two intertwined branches. The development of one directly affects the other. As part of a global digital transformation and the rise of e-Commerce, online shopping has become more prevalent than ever.
These evolving e-Commerce trends have altered the consumer’s experience, which has had a direct impact on how businesses do marketing. Among other things, these changes have led to a fusion of these two branches of business, referred to as e-Commerce marketing.
In this article, we’ll discuss the different ways e-Commerce is transforming marketing. Not only will we examine changes that have already taken place, but we’ll also examine the joint future of these two business practices.
1. Digital Marketing Is Becoming More Diverse
Digital marketing has been around for some time, but it’s always evolving. More and more consumers are choosing online shopping over traditional shopping in brick-and-mortar stores. In other words, e-Commerce has made online shopping easier and more accessible to the consumer. For this reason, businesses must adapt their digital marketing strategies to meet the consumer’s ever-changing needs.
Just think about why people prefer online shopping. There are more products on the store’s website than in the physical store, you can browse through the pages at your own pace, and you don’t have to leave your house to buy something. Of course, there will always be people who prefer in-store shopping, but the growing interest in online shopping is undeniable.
This has led to the development of different digital marketing channels, including social media marketing, content marketing, search engine optimization, paid search ads, affiliate marketing, pay-per-click, email marketing, retargeting, mobile marketing, and so on. All of these branches of digital marketing have the same goal – to increase e-Commerce sales.
2. Every Business Is Expected to Have a Website
It doesn’t matter what kind of business you own. Whether it’s a dentist’s office or pool cleaning services, you must have your website.
Because we, as consumers, have access to a growing amount of information, it’s only natural we use it to search for things we’re interested in. This particularly applies to customers who want to buy something from a business for the first time.
There are many reasons why your business should have a website. It’s the best way to build and showcase your brand. In addition, it drives organic traffic to your website, which leads to an increased conversion rate. Most importantly, it shows your customers that your business is credible.
To put it simply, the more people visit your website, the more successful your business can be. The good news is that you don’t have to be a tech expert to make your website. You can always outsource someone to develop and design your website. After you design your website, you can incorporate it into your marketing strategy.
3. Social Media Presence Plays a Crucial Role
To be successful, boost website traffic, and acquire more clients, a business needs to have a social media presence. The average person spends two hours and 27 minutes on social media every day. This is a great opportunity for marketers to increase brand awareness.
There’s a plethora of social media channels a business can benefit from, including Instagram, TikTok, Twitter, Facebook, LinkedIn, and more. Not only can you make an account on all of these social media outlets, but you can also create paid ads to cast a wider net. It’s the best way to get in touch with your target audience.
Social media marketing also makes your business more accessible to your clients. Let’s say you own a clothing or beauty brand business. People are more likely to search for you on social media before going to your website. They can also reach out to you and ask you questions about certain products, which allows you to build a strong relationship with your clients.
4. Your Website Must Be Mobile-Friendly
Your website must be mobile-friendly. You might think that people mainly use their computers for online shopping since they have bigger screens. However, many people prefer online shopping on their smartphones and tablets.
Since a great majority of consumers shop online using their mobile devices, this fact gave rise to mobile marketing. There are many advantages of mobile marketing, from greater accessibility and SMS promotion codes to location-based marketing and in-app marketing. This marketing strategy pays off because it’s more personal.
Email marketing is one of the most effective forms of digital marketing. This accounts for welcome emails, newsletter emails, confirmation emails, promotional emails, dedicated emails, and similar. The reason email marketing produces better results than other types of marketing is that it’s sure to reach your target audience. With other digital marketing strategies, the target audience may or may not see the marketing content.
Another reason a business should have a mobile marketing strategy is that mobile marketing is less expensive than other types of digital marketing.
5. Access to More Data and Analytics
The development of e-Commerce and digital marketing has helped businesses grow in several ways. One of the most important advantages of these two business modes is access to more data and analytics tools. This is one of the reasons traditional marketing simply can’t match digital marketing.
Almost all online platforms and social media accounts give you the option to track the results of your performance. Analytics tools can tell you all sorts of information about your online business. For example, you can find out how many people visit your website, click on your ads, buy a product from your website, or follow you on social media.
Businesses can then use these analytics results to create a marketing strategy to improve their business and increase its conversion rate. For example, analytics tools can let them know at what point customers are choosing to abandon their shopping cart and exit the website. Understanding consumers’ online behavioral patterns will help businesses understand what part of the website needs the most work.
6. The Growing Importance of Content Marketing
One of the most important forms of digital marketing is content marketing. But how are content marketing and e-Commerce related? Content marketing isn’t only about promoting a product. It’s also about telling a story your target audience will respond to. This strategy gives consumers a chance to buy the product or service willingly.
Content marketing is also realized through the content itself, which can be posted on blogs, social media posts, websites, infographics, videos, and e-books. The content needs to be relevant, engaging, and useful, whether you’re using it to convey a message or tell a story.
Content marketing is closely intertwined with Search Engine Optimization (SEO). This form of marketing is used to optimize a website’s performance with the use of designated keywords. If you use relevant content that’s somehow connected to your business, you’ll drive organic traffic to your website. The whole point of SEO is to rank high on search engine results pages (SERPs).
7. Personalized Customer Experience
Customer experience is one of the most important aspects of a successful online business. Since e-Commerce has changed the way companies conduct business, it created a whole different shopping experience.
An e-Commerce business relies on its customers to earn revenue. That’s why building a long-lasting relationship between the brand and the consumer is the number one goal of e-Commerce businesses. Customers who are happy with their initial purchase and the entire shopping experience are more likely to return to that business. This builds brand loyalty.
Since online shopping has become more accessible than ever, consumers are expecting a seamless shopping experience. That’s why your marketing strategy has to be strong – your business must stand out from your competition. That’s one of the downsides of e-Commerce and digital marketing. Businesses are always expected to keep up with new trends to meet their clients’ expectations. Some businesses may even be required to revamp their whole business model.
8. The Emergence of Augmented Reality
Technology will only continue to advance, which will result in completely new forms of e-Commerce and marketing. Augmented reality is generally a new buzzword, but we’ll definitely be seeing more of it in the near future. So far, we’ve seen AR in the form of glasses and headsets, forms that make them more popular in the video game industry.
Augmented reality will give e-Commerce and digital marketing a whole new meaning. AR makes online shopping more realistic for the consumer. For example, customers will be able to see how a product would look in their house with just their smartphones. You may have seen this in the form of makeup filters on social media apps.
It’s speculated that e-Commerce will be possible in the Metaverse, a 3D virtual world being developed by Facebook founder Mark Zuckerberg. The Metaverse is still a new concept, and it’s difficult to explain because it doesn’t exist yet. That being said, when it arrives, it will revolutionize how we do business and market products.
The Future of Marketing Through e-Commerce
E-commerce hasn’t only altered the way we shop. It has also made a huge impact on how businesses do marketing. From digital marketing trends to advanced technology, the development of e-Commerce has directly affected marketing. Moreover, it’s expected to become more diverse, accessible, and complex in the future.
The Future of Crypto Beyond 2023
It’s been a wild ride for cryptocurrencies over the past few years. We’ve seen prices soar and crash, and new coins and technologies enter and exit the market with breakneck speed. But what does the future hold for cryptocurrencies?
This article discusses a few predictions for what we might see in the next few years. But first, we’ll take stock of what has already happened.
Notable Developments Over the Past Decade
It’s been more than 10 years since the first cryptocurrency was created. During that time, the cryptocurrency industry underwent major changes and developments.
Here are some of the most notable ones:
The Rise of Bitcoin
In 2008, an anonymous person or group of people going by the name Satoshi Nakamoto released a white paper detailing a new peer-to-peer electronic cash system called Bitcoin (BTC). The following year, Nakamoto mined the first ever Bitcoin block, known as the genesis block, and the Bitcoin network went live.
Since then, Bitcoin has gone from strength to strength. Its price has skyrocketed, reaching a peak of almost $70,000 in November 2021. While it has since dipped back to around $17,000 at the time of writing, that is still an incredible increase from its original price of just a few cents.
Moreover, Bitcoin remains by far the most well-known and widely used cryptocurrency, with a market capitalization of over $370 billion.
The Rise of Altcoins
While Bitcoin is the most famous cryptocurrency, it is not the only one. There are now thousands of different cryptocurrencies in existence, collectively known as altcoins.
Some of the most popular altcoins include Ethereum, Ripple, Litecoin, and Monero. These coins have all seen significant increases in both price and popularity over the past decade.
The Initial Coin Offering (ICO) Boom...and Bust
An ICO is a fundraising method whereby startups offer investors crypto tokens in exchange for funding. This method became extremely popular in 2017 as a way for blockchain startups to raise money quickly and easily. In that year alone, over $6 billion was raised through ICOs.
However, the ICO craze ended abruptly in 2018 when the U.S. Securities and Exchange Commission (SEC) cracked down on several fraudulent ICOs. As a result, ICOs have become much less common in recent years.
The Rise of Decentralized Exchanges (DEXs)
A DEX is a cryptocurrency exchange that does not rely on a third party to hold or manage customers’ funds. This type of exchange offers several advantages over traditional centralized exchanges, such as improved security and privacy and greater control over one’s funds.
Over the past few years, DEXs have become increasingly popular as more and more people look for alternatives to centralized exchanges such as Coinbase and Binance.
The Future
While the crypto industry continues to evolve and mature, we can expect to see even more exciting innovations and developments in 2023 and beyond. Here are a few:
More Regulations on the Horizon
As the industry matures, regulators have begun to take notice. In 2018, for example, the SEC released guidance clarifying that some digital assets could be considered securities. Since then, more guidelines have been published.
But that doesn’t mean the industry is out of the woods yet on matters of regulation. There are three reasons we should expect more regulation around cryptocurrencies in the years to come.
First is the issue of taxation. At the moment, there are no clear guidelines on how cryptocurrencies should be taxed. This has led to a lot of confusion and ambiguity among both individuals and businesses who hold or transact in cryptocurrencies. As the market matures and grows, governments will likely want to get a piece of the action by implementing clear taxation rules.
Another reason why more regulation is coming for cryptocurrencies is money laundering. Due to the anonymous nature of many cryptocurrencies, they have become a popular tool for criminals to launder money. Governments will likely implement stricter know-your-customer (KYC) and anti-money laundering (AML) regulations for cryptocurrency exchanges and other businesses operating in the space to crack down on this activity.
Finally, there’s the issue of investor protection. At the moment, there are very few protections in place for investors who buy into ICOs or trade cryptocurrencies on exchanges. This leaves them vulnerable to fraud and manipulation. As the market matures, regulators will likely step in to create a more level playing field and protect investors from unscrupulous actors.
More Institutional Investors
One of the key factors that will drive cryptocurrency growth in the coming years is increased institutional investment. Currently, most crypto investors are individual retail investors. However, we’re seeing more and more institutional investors getting involved in the market.
For example, hedge funds and venture capital firms are starting to invest in cryptocurrencies. We are even beginning to see some traditional financial institutions dip their toes in the water with investments in blockchain technology.
As institutional investors start to put more money into cryptocurrencies, we’ll likely see an influx of new capital that will help to drive up prices and increase mainstream adoption. Additionally, these institutional investors will bring a greater understanding of financial markets and a long-term investment horizon, which will help to add stability to the market.
More DeFi and DAOs
Cryptocurrency observers and analysts contend that decentralized finance (DeFi) is likely to be the highest growth area of crypto in the years ahead. DeFi is a catch-all term for financial applications built on blockchain technology. It includes everything from lending and borrowing platforms to stablecoins and tokenized BTC.
Decentralized finance has been growing in popularity over the past few years, as it offers a number of advantages over traditional finance.
For one, DeFi is accessible to anyone with an internet connection— there are no geographic boundaries or KYC requirements. DeFi platforms are also usually built on open-source protocols, which means they’re transparent and auditable. Finally, DeFi applications are often permissionless, meaning that users don’t need to go through a centralized authority to use them.
DAOs are another area of crypto that is worth keeping an eye on. A DAO is a decentralized autonomous organization—essentially, a company run by code rather than humans. The most well-known example of a DAO is MakerDAO, which created the Dai stablecoin.
DAOs have several advantages over traditional organizations. For one, they’re borderless—anyone can join a DAO, regardless of location. Additionally, DAOs are usually more efficient than traditional companies, as they don’t need to worry about things like office space or employee benefits.
Finally, DAOs are often more resilient than traditional organizations, as they’re not susceptible to political instability or natural disasters.
The Next Move by the Federal Reserve Could Work in the Industry’s Favor
One of the most important things to understand about cryptocurrencies is that they are susceptible to changes in the traditional financial system.
When interest rates go up, people tend to put their money into savings accounts or other relatively safe investments. But when interest rates go down, investors are more likely to spend their money on risker assets like cryptos.
To fight inflation, the Federal Reserve executed an unprecedented series of interest rate hikes in 2022. After initially increasing the rate from 0.25% to 0.5% in March, they implemented further increases, culminating in a rate of 4% in November.
While more increases cannot be ruled out, especially if inflation continues to soar, some market observers believe the Fed may have to slow down to avoid further turmoil. Recent data also indicates price pressures are showing signs of cooling.
If the Fed takes its foot off the gas, it could create a more favorable environment for investors who want to get back into the cryptocurrency market.
How Plausible Are These Predictions?
These predictions seem plausible when you consider the current state of affairs. The COVID-19 pandemic has hastened the shift from traditional finance toward digital alternatives. DeFi platforms and DAOs offer compelling alternatives to banks and other financial institutions.
Furthermore, the current economic climate is ripe for disruption, and cryptos could provide much-needed competition to conventional fiat currency.
Of course, it’s important to remember that these predictions are just that—predictions. They may or may not come true; only time will tell. Nevertheless, it’s clear that cryptos are worth watching in the world of digital assets.
So, whether you’re a seasoned investor or a complete beginner, be sure to keep an eye on these emerging trends. You might just be surprised by what they achieve in the years ahead.
The Perfect Way to Prepare for the Future
In light of these predictions, you may be wondering how you can get involved and prepare for the future of cryptocurrency.
One way to do this is by learning about blockchain, the technology that powers crypto. While cryptocurrencies are often associated with high risk and volatility, understanding blockchain can help you to see the potential for stability and growth in the crypto space. In addition, understanding blockchain can also help you to understand other emerging technologies, such as smart contracts and distributed ledger systems.
Back-End Integration for E-Commerce: What Is It and Why It Matters?
E-commerce has drastically changed how we do business and access the products and services we need. This type of commerce has long become the norm as it gives businesses of all sizes a chance to expand beyond their physical locations. However, the e-commerce purchasing experience has constantly been evolving.
Customers expect nothing less than a smooth purchasing experience from when they search for an item on an e-commerce website to when it arrives on their doorstep. The feasibility of such an experience depends on the website’s back end and how seamlessly it integrates with its front end.
So, let’s break down what back-end integration is and how important it is for e-commerce.
What’s the Difference Between Back End and Front End?
The front and back end are parts of an e-commerce website that define its design and functionality.
The front end is the part that customers see when they visit your website. It’s also the part they directly interact with, and it includes features such as search bars, drop-down menus, and image sliders. The front end is sometimes referred to as the digital storefront.
In contrast, the back end of an e-commerce website is the part that handles products, orders, and customer data. Simply put, it’s the engine of your website. The back end enables your website to respond to queries quickly and allows customers to browse products, put them in the cart, and check out.
In short, the front end defines the visual appeal of an e-commerce website, while the back end defines its functionality.
Understanding how the front and back end works together is crucial for building a seamless omnichannel shopping experience.
What Is Back-End Integration for E-Commerce?
Back-end integration aims to coordinate the front and back ends of an e-commerce website. When an e-commerce website is fully integrated, there’s an unobstructed flow of information between both ends. Plus, you can access all the necessary information from one location or database.
This connection is instrumental for a smooth-running website that allows customers to get exactly what they want as soon as they need it.
Despite how vital back-end integration is, many businesses haven’t fully embraced it on their websites. The lack of back-end integration typically results from a lack of awareness, time, or, most commonly, resources. Although completely integrating a website can be costly, failing to do so will severely impact the business’ revenue in the long run.
How to Implement an Efficient Back-End Integration?
A lot of moving parts exist when it comes to back-end integration. In most cases, it involves the software that creates the website pages, the product search engine, and the shopping cart. In addition, an electronic data interchange (EDI) system should be in place, enabling customers to receive real-time inventory information and order status updates.
With all this in mind, let’s see how you should go about integrating your e-commerce website fully.
Hire a Skillful Web Developer
After identifying your business’ shortages regarding back-end integration, hiring a skillful developer is crucial to help you resolve these issues quickly and efficiently.
There are three types of web developers that you can hire:
- Front-end developers
- Back-end developers
- Full-stack developers
Full-stack developers have experience in developing both ends of an e-commerce website. These specialists might be the best solution for a business with limited resources. They typically have a higher hourly rate than back-end developers. Still, working with a full-stack developer is more affordable than hiring separate front and back-end developers.
However, if your website is mostly in place, and you only want to target the back-end issues, it would be best to hire a back-end developer. These specialists will help you integrate your website fully, resolve technical difficulties, and improve the website’s speed. They mostly use technologies such as:
- Python
- PHP
- Java
- Ruby
When it comes to databases, they usually work with the following:
- SQL – MySQL
- MongoDB
- SQLite
- PostgreSQL
Become Familiar With Back-End Integration
No one expects you to know all the ins and outs of a website operation. However, you can immensely benefit from a basic understanding of the interaction between the front and back ends. With a healthy understanding of back-end integration, you’ll be able to see the big picture and steer your web developer in the right direction.
Instead of making unreasonable requests that lead to wasting precious time and resources, you’ll be able to collaborate with the web developer to achieve the best results for your website.
Besides the information outlined in this article, you can benefit from knowing some commonly used terms, such as:
- UI (user interface)
- UX (user experience)
- Client side (the front end)
- Server side (the back end)
This will help you identify your website’s weak points and discuss matters in-depth with your web developer.
Integrate Slowly
Achieving a fully integrated e-commerce website usually requires a phased approach. This method is more affordable, making it attainable for businesses with limited resources. Also, streamlining ordering gradually gives you time to spot potential issues early on. This way, you’ll spend less money and time ironing out all the bugs and fixes than on a fully integrated website.
The phased approach requires manual integration initially and slowly working toward a total integration where your website runs like clockwork.
That said, let’s dive into what each phase entails.
Phase 1
In the beginning, you should only sell a subset of items on your e-commerce website. Customers can order from your website, but you’ll have to integrate the back end manually. A manual integration includes:
- Printing out online orders
- Keypunching each order into an existing back-end system
- Manually entering the order status
Manual integration means that the orders will likely be fulfilled later than expected. Plus, this process requires a lot of person-hours. Although it’s hardly an ideal solution, manual integration is an excellent compromise for businesses just starting out. It gives them a relatively inexpensive way to build an integrated online catalog.
Phase 2
During Phase 1, you’ll start to distinguish your priorities. These may include offering customer-specific pricing, providing real-time links to customer service, or speeding up the process of inputting orders. Then, in Phase 2, you can introduce limited integrations based on your priorities. Also, Phase 2 is the time to start selling your entire product line on your e-commerce website.
Phase 3
Phase 3 is the time to implement a full integration with the existing back end. At this point, your system should be able to provide a shopping experience that’s as smooth and effortless as placing an order over the phone or going to a brick-and-mortar store.
The Benefits of a Fully Integrated E-Commerce Website
Thanks to their automated features, fully integrated e-commerce websites are miles ahead of their competition. Here are some compelling benefits of building a fully integrated online catalog.
Up-to-Date Product Access
An online catalog connected to your business’ back end offers your customers real-time access to product offerings and stock status.
Improved Service
When customers browse a fully integrated e-commerce website, they can immediately get answers regarding the stock status and delivery. They don’t have to waste time on hold to speak to a customer service representative, which motivates them to complete their order and make a purchase. This, in turn, allows a business to increase profit.
Specific back-end features that make this happen include:
- A shopping cart that allows them to place the order quickly and hassle-free
- A credit card processor that immediately authorizes a credit card transaction
- A transaction engine that can handle numerous orders simultaneously
- Inventory hooks that can confirm whether a customer’s order is available in real-time
- Shipping data links that offer email shipping verification
Reduced Costs
A fully functional online catalog is a valuable investment that will eventually pay off by increasing the volume of your orders. Plus, moving product inquiries and order placements entirely online will cut telecommunications charges and labor costs.
Improved Marketing Results
A successful back-end integration also offers several benefits for the company’s marketing efforts, including the following:
- Usable data for determining the effectiveness of an online digital marketing strategy
- Focused marketing improvements on how potential clients interact with marketing material
- Greater return on investment (ROI) thanks to the possibility of creating detailed cause-and-effect data
Strive for a Symbiosis Between the Front and the Back Ends
A few years back, a basic home page was all a company needed for its online presence. However, those days are long gone, and businesses must do their best to keep up with competitors in the world of fast-paced online marketing.
While back-end integration is undoubtedly the backbone of any successful e-commerce website, business owners shouldn’t neglect the front end. After all, the road from a customer’s first interaction with the website to closing a sale can be long and winding. So, both ends of the website should be up to par and able to rely on each other. Such a cohesive approach will allow these systems to make the most of their functions and the website owner to use the received data better.
Key Differences Between Artificial Intelligence and Machine Learning
Artificial intelligence (AI) and machine learning are key tech concepts today. We interact with the applications of these innovative technologies every day, be it through modern search engines, automated processes, chatbots, or intelligent assistants on our smart devices.
AI and machine learning are closely intertwined, and the terms are also often used interchangeably. However, they aren’t exactly the same. Here’s what you should know about artificial intelligence and machine learning and the key differences between the two.
What Is the Difference Between AI and Machine Learning? The Short Answer
Artificial intelligence is the ability of computers to emulate human cognitive functions like learning, problem-solving, and decision-making. This is achieved through numerous tools, one of which is machine learning. Machine learning is thus a subset or application of AI. It is the technology that enables computers to absorb information without direct instructions. Through machine learning, the system will be able to identify patterns and gather experience, which helps the system improve itself.
What Is AI?
Artificial intelligence is a complex concept as it encompasses a broad topic. The term was coined as early as the middle of the 20th century by an American computer scientist named John McCarthy. Although the history of AI reaches far back, it wasn’t until we understood how human minds work that the discipline could truly develop.
Today, we can consider AI both a multidisciplinary engineering field that creates systems that mimic certain elements of human behavior and a set of technologies that make it possible. By artificial intelligence, we refer to machines capable of acting “intelligently.”
AI is a vast field that encompasses numerous subfields. The tools used by AI to complete tasks in a human-like manner include the following means:
- Natural language processing – a computer’s ability to understand and interpret human language, which enables it to respond appropriately
- Machine learning – processes that enable computers to learn based on datasets
- Deep learning – an advanced type of machine learning that instructs computers to analyze layers of data and learn by experience
- Computer vision – the computers’ ability to interpret images by breaking them down and analyzing them
- Neural networks – systems designed based on the human brain with the goal of classifying information
- Cognitive computing – algorithms designed to interpret text, images, speech, and more, as the human brain does
Types of AI
Although there is still a lot of vagueness surrounding the field of AI, artificial intelligence is typically split into two categories. These are applied and general AI.
Applied AI is what most people think of when they hear the word “AI.” These are the application of AI in systems designed to replicate human intelligence. Applied AI is what’s used, for example, in self-driving cars. However, general AI is where the most advanced innovations are taking place today.
General AI is an emerging field that aims to create general-purpose systems that can handle any task. This is where machine learning steps into the picture.
According to another division, we can also make the distinction between general and narrow AI.
Artificial general intelligence (AGI, strong AI, full AI, etc.) is the ability of intelligent agents to learn intellectual tasks like a human can. Some also refer to systems that possess (or at least mimic) consciousness and sentience as strong AI.
In contrast, narrow (or weak) AI focuses on solving only a specific problem. Academics also refer to programs that do not possess human-like cognitive abilities as weak AI.
What Is Machine Learning?
Machine learning is a field that creates methods that use data to learn and improve processes. It is all about using data to create real knowledge. Machine learning is a key element in artificial intelligence.
Despite the concept being cutting-edge, the idea of machine learning was considered ahead of its time when it was conceived. It dates back to 1959, when Arthur Samuel, an IBM employee, considered the possibility of teaching a computer to teach itself instead of feeding information to it.
The earliest version of a “learning” machine was developed in 1960. It was designed to analyze electrocardiograms, sonar signals, and speech patterns. This early machine was taught through rudimentary reinforcement learning. A human was required to teach the machine and prompt it to reevaluate wrong decisions, which is similar to some methods used even today.
How Does Machine Learning Work?
As mentioned, machine learning is a subset of AI. Machine learning helps intelligent systems perform tasks by making predictions based on previous experiences.
Machine learning uses algorithms to build a model. The initial phase requires the user to input sample (or “training”) data. Once sufficient information is supplied, the machine learning algorithm will be able to make predictions and decisions without intervention. For this reason, machine learning is also often referred to as predictive modeling or predictive analytics.
Naturally, a large amount of data is necessary for this to work. The emergence of the internet provided the perfect source for machine learning, as it makes massive amounts of digital information readily available. Machine learning is also aided by neural networks, which are designed to classify data in the same manner as our brains do. By classifying and re-classifying information, the system continues to improve itself. The machine can learn from previous data without programmers having to do anything.
Types of Machine Learning
Machine learning has three main types: supervised, unsupervised, and reinforced machine learning. Additionally, some also consider semi-supervised machine learning another category.
Supervised machine learning is built on examples. The user provides the machine with a set of data, which contains not only the input but also the desired output. Based on this example, the machine will determine the method that leads from A to B. The machine identifies the patterns that explain the processes between the input and the output and will use them to make predictions the user can correct. The longer the process goes on, the higher the accuracy.
Semi-supervised learning uses labeled and unlabeled data to teach the machine to label data accurately.
Unsupervised learning, as the name suggests, operates without human intervention. The user won’t have to correct incorrect predictions. In this model, the machine learning algorithm studies data to identify patterns. As it processes more and more data, its decision-making ability improves.
Finally, reinforcement learning essentially involves trial and error. The machine learning algorithm explores various options based on a set of inputs and compares results to determine the most optimal process. This model lets the algorithm learn from experience.
Key Differences Between AI and Machine Learning
Artificial intelligence and machine learning are complex disciplines. Here are some main differences between them to help you better understand their relation.
AI
- AI is an interdisciplinary field.
- AI has an extensive scope.
- The goal of using AI is to create intelligent systems that can perform a range of complex tasks.
- AI provides a computer with the ability to mimic human cognition.
Machine learning
- Machine learning is a subset and application of AI.
- It has a narrower scope.
- Machine learning disciplines aim to design machines that perform the specific tasks for which they are trained.
- Machine learning allows computers to learn based on data and patterns.
How Do AI and Machine Learning Interact?
As we mentioned, AI and machine learning are closely intertwined. While AI is used by computers to perform tasks in a human-like way, machine learning provides the means for it to develop its intelligence. AI systems are designed using a range of techniques, including machine learning. In fact, machine learning has become one of the most important ways artificial intelligence has been used in recent years.
Applications of AI and Machine Learning Across Industries
Today, both AI and machine learning applications are all around us. Whether you’re doing a Google search, scrolling your algorithm-driven social media feeds, or checking out Netflix’s recommendations, you’re inadvertently interacting with machine learning models. Have you noticed that the recommendations on such platforms get better and better the longer you use the service? This is because the machine learning algorithm keeps collecting more data and making more accurate predictions based on your habits.
These technologies have found their way into almost all industries, including retail, healthcare, banking, customer service, transportation, and manufacturing. According to an IBM survey, 35% of businesses have already implemented AI in their processes globally. Another 42% are exploring the option. AI and machine learning are the driving force behind chatbots, language translation apps, predictive text, self-driving cars (like Tesla), AI assistants (like Alexa and Siri), and many more tools that have become a part of our everyday life in the 21st century.
The Future of Intelligent Machines
As AI and machine learning are becoming necessary technologies for all businesses hoping to keep pace, learning the difference and relation between the two concepts is crucial.
AI implementation can not only help businesses collect and analyze data more efficiently, but it also increases operational efficiency and improves decision-making. Its rapid development is already opening up new business possibilities and will undoubtedly shape our future.
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