As the initial fallout from Covid-19 fades into the past, and the prospect of a second wave becomes apparent, it’s not too soon to say the old world of retail won’t be coming back.
That’s not so much a function of why the coronavirus hurt retail (lockdowns and social-distancing rules) as it is about what the coronavirus taught us about retail: that consumers could seamlessly move most purchases to online. The latest figures from the IMRG Capgemini Online Retail Index, which tracks online sales performances of more than 200 retailers in the UK, found that by early June online sales were at their highest in 12 years. Meanwhile, surveys by PYMNTS show that 52 per cent of people who moved their grocery shopping online say they won’t return to their old patterns, while a full 60 percent of consumers who moved their non-grocery purchases to digital say the same.
It turns out that although buying is essential, shopping isn’t.
For the better part of a decade, the retail industry has emphasised the joy of shopping. Experiential retail became more than a catchphrase and turned into a sort of rallying cry. There was a sense that all retail needed to do to enter a new era of prosperity was to make shopping more interesting, more entertaining, more something.
The coronavirus killed all that. No one is looking for ways to spend more time in stores now.
The world learned that retail could be reduced to the essentials: workers, groceries, medicine, and so on. And that almost everything else was superfluous or just silly. We learned that although there are things we must buy, and other things we want to buy, we don’t necessarily want to spend time shopping for them in crowded department stores with other people.
And not even the most fascinating “experience” will change that.
What’s left? What’s next?
So how can a retailer make money in this post-experiential era? How can retailers help consumers buy, but not “shop”?
The answer is simple, but not easy. Retailers should dedicate themselves to mastering two key concepts in e-commerce: understanding intention and clearing the path.
The rise of machine learning in e-commerce has led to a slew of remarkable innovations. But none will have more significance in the post-coronavirus world than the ability to predict user intention and respond to it in real time.
When you visit a retailer’s website that uses predictive intelligence, the site knows what you’re likely to do and behaves accordingly. The site “clears the path” and offers a clean interface to someone ready to buy. By contrast, it shows ads and landing-page varieties to someone who is unlikely to convert.
That’s happening now. At <intent> we’ve used our Predictive Intelligence Platform to build thousands of such models for e-commerce companies. The models boost revenue and reduce inefficient ad spending. And they run on first-party data, meaning they meet privacy regulations in both the EU and the US.
Experiential retail was aimed at getting consumers to linger. Understanding intention and clearing the path is aimed at the opposite. The idea is to make the buying process as fast, simple, and seamless as possible.
Sophisticated businesses have learned that these twin pillars of intention and optimisation have applications across the digital landscape. Worried about ad spending? Retargeting? Looking for new revenue? Need to improve customer acquisition? All of this can be done if you understand what a consumer is likely to do and then make it easier for them to do it.
What’s your intention? What is your path?
An entirely new era is beginning in retail that requires all new skills and technology for businesses. So where should a retail executive start?
The next step is to adopt a highly sophisticated approach to e-commerce, built with machine learning, powered by first-party data, and capable of understanding intention and clearing the path in real time.
Find a technology partner that can help with that, and you’ll have also cleared the path for your company to survive and thrive in the future.
To learn more about how you can have a predictive intelligence platform for less than the cost of hiring a single data scientist, visit intent.com
Richard Harris is Chief Executive Officer and Co-founder of <intent>, the real-time predictions platform for digital business. uses machine learning to predict a user’s likelihood to convert in real time, which helps fuel more efficient traffic and customer acquisition, media monetisation, and smart personalisation.