Internet of Behaviour & Other Top Web Trends in 2024
The web development landscape is constantly evolving, and it’s essential to keep you finger on the pulse to stay competitive. So, we’re breaking down the top emerging trends you’re likely to see in 2024, and how other businesses are making the most of them right now.
Internet of Behaviour (IoB)
Internet of Behaviour (or IoB) is a system that you likely
encounter every single day, yet it’s nowhere near as recognized as technology
like AI – yet. IoB is our first prediction for one of the biggest trends in
2024, and it’s key to the ways we monitor trends in the future.
Internet of Behaviour involves the collection and analysis
of data related to human behaviour, from a range of sources. Smartphones,
wearable tech, home appliances, and more all gather huge amounts of data about
what we do and how we like to do it, but IoB is an innovative way to process it
– developers leverage AI algorithms, behavioural analysis, and human psychology
to analyse patterns in real time.
One of our longest standing customers is a leading software house,
specialising in personalised customer offers and working with the likes of JD
Sports, Asda, Sainsbury’s and John Lewis. They’re the ones powering supermarket
incentives such as the new loyalty schemes with Asda Rewards, Tesco Clubcard
and now the Halfords Motoring Club.
The results of utilising IoB speak for themselves; 89% of marketers
see a positive ROI when they use personalization in their campaigns, and
EagleEye alone process over 350 million personalised offers per week. The
results of this level of personalisation mean that the market is projected to
reach $2.7
billion by 2027 – so getting ahead of the competition in 2024 is sure to
pay off.
Artificial Intelligence & Machine Learning
While it’s been an ever-growing constant in the IT world, AI has
recently taken on a life of its own in the cultural zeitgeist too. Another key
field is machine learning, although it’s arguably less talked-about.
Distinguishing the difference – and how to use them – will be key in
2024.
What is the difference between AI and machine learning?
In its simplest form, artificial intelligence is focused on developing
machines or software that can mimic human behaviour; the infamous ChatGPT is a
well-known example. The term ‘AI’ is often used as an umbrella term.
Machine learning is a branch of artificial intelligence, which is less
concerned with mimicking us and more focused on identifying patterns to solve
problems. It uses data and statistical algorithms to make more accurate
predictions, the result of which is a computer that can ‘learn’ without being
explicitly programmed. The uses of this kind of technology are endless, from
self-driving cars to fraud detection, which explains the boom in machine
learning jobs in the last few years – in fact, the global ML market is expected
to reach $117.19 billion by 2027.
Wondering where this fits into your business? There are already a wide range of industries making the most of these tools, including healthcare, finance, manufacturing and transportation – and 2024 will likely see many more. One of the most popular use-cases is customer support; AI and ML are being used to provide 24/7 troubleshooting via chatbots. Machine learning allows chatbots to be more productive, responsive, and interactive, improving customer satisfaction.
Indeed, thanks to AI, businesses are understanding their customers’ wants and needs more than ever before – driving conversions. In utilizing machine learning to recognize what their customers want to watch, Netflix makes $1 billion annually from automated personalized recommendations.
This sector is only set to grow, and failing to jump on the trend will only put you behind the curve - 83% of companies say that creating AI jobs and integrating artificial intelligence is a top business priority, and it’s estimated that by 2025, there’ll be as many as 97 million people working in artificial intelligence jobs.
It’s a great time to enter the industry too; machine learning jobs can come in many forms, from software development to data science.
Severless Architecture (Cloud Computing)
Our final top trend is one that’s already revolutionising the
way we work; cloud
computing.
Serverless architecture doesn’t rely on a physical server or additional hardware – instead, data collated is maintained in the cloud. It saw a huge rise during the pandemic, and although it was driven by necessity, it meant that the advantages of serverless architecture could be more widely realised. There are three big cloud providers you’re likely to come across:
- Google Cloud Provider
- Amazon Web Services (AWS)
- Microsoft Azure
There are three main perks:
- It’s a highly scalable model. Since it doesn’t rely on physical infrastructure, serverless architecture can be scaled up or down depending on your needs without too much trouble or cost. It also means your developers aren’t spending time managing the underlying infrastructure.
- The second is availability; data is always available, even during downtime.
- Finally, it facilitates remote working. This was the big draw during the pandemic, but with hybrid and fully-remote working becoming a permanent fixture in the industry, it’s a big selling point. With traditional servers, you’re tied to a location, but with cloud architecture, data can be made available anywhere you need it. It can be accessed by employees at any time from anywhere in the world, as long as they’ve got an internet connection.
There are plenty of IT jobs that utilise or manage cloud computing: Cloud Solution Architect,
DevOps Engineer, and Backend Software Engineer
to name a few.
