Marketers are the store managers of the online retail world: it’s up to them to ensure that visitors are having a good time and finding what they need. The challenge is insight: online store managers find it much harder to see what’s really going on in the shop, compared to their real world counterparts. It’s not immediately obvious why a particular product isn’t selling online, or how customers are getting lost or sidetracked on their way to the checkout.
That’s why, over the past few years, companies in a variety of sectors have focused their attention on enhancing their user experience (UX). Often seen as a qualitative measure of how users ‘feel’ while on websites, UX has historically been difficult to measure. However new analytical techniques, powered by AI technologies, are helping businesses optimise their UX and improve their bottom lines in new and important ways.
The importance of UX
Forrester predicts that delivery of a superior user experience could add up to $1 billion collectively to business’ bottom lines, while some analysts are even predicting UX to overtake price and product as the key consumer brand differentiator by 2020.
We tend to think of user experience as a fundamentally human discipline: after all, it’s all about predicting how humans are going to react to particular aesthetics or website structures. Now more businesses are seeing UX as something that not only can be measured, but must be measured.
Metrics and tools like heat maps, mouse hover time or scroll rates can give marketers and product specialists insights into how people are actually using websites in the way they do. However the challenge is turning these insights into something actionable. Combining these with advanced user journey mapping can provide essential insight to inform marketers as to why people are dropping out of the site at certain points, while next-generation element ‘zoning’ of key elements on a certain page can give employees and much more micro and detailed overview of page performance (such as revenue generated or hesitation rate per ‘zone’) at a glance.
Based on what we know about UX, you wouldn’t think the marriage of automated analysis and artificial intelligence would be a happy one. However that’s exactly what the future holds for these forms of online analytics.
There’s a real shortage of data scientists in the job marketplace at the moment: McKinsey reports that in the US alone there will be nearly half a milion data science jobs by 2018, with only 200,000 qualified candidates to fill those roles. What is needed is a fundamental rethink of what the data scientist role is for, and whether part of that can be exported to automated tools.
Today’s AI technologies can be used as ‘early warning systems’, providing the role that often falls to the data scientist of raising the alarm when a particular page or user journey on the website is performing badly. Data scientists, often highly overworked, don’t need to be used for this kind of task, as it can be easily automated. AI technologies can be used to reduce this workload, by disseminating information across far wider teams than was possible before. This ultimately helps everyone save the most precious resource of all - time.
Some companies, such as ContentSquare, are taking this even further by offering interactive AI-powered recommendation tool for automated UX advice. These tools can pick up the highest or lowest performing areas of a website automatically, and flag them to digital teams as areas of the site that require further attention.
Looking to the future
In the coming years businesses will find it progressively easier to eliminate intuition from the product and marketing development cycle through a powerful combination of UX analytics and AI-driven automated recommendations. These technologies will save marketers time, while also empowering more people on the team to get involved with the data explaining how and why customers are behaving in the way they do.
With UX more deeply ingrained into how websites are designed, we’ll begin to see new types of KPIs emerge, KPIs which will assess not just how the website is performing, but the underlying usage patterns which determine that performance.
AI technologies are no replacement for human expertise, but can, when applied correctly, help empower teams by cutting out administrative tasks and spreading insights further within the business. These benefits are ultimately all in the service of one thing: helping businesses better serve their online visitors and converting browsers into buyers.