2019 Retail Tech Trends: AI

Each year, retailers look for technology predictions that will deliver value to their commercial strategy, a clear ROI and the ability to keep up with shopper expectations. So, will 2019 be the year of much talked about, but least understood, artificial intelligence (AI)?

We’re predicting more talk and perhaps further confusion around what AI can or can’t deliver effectively in the months ahead. The ‘talk’ will be based on fact – AI and machine learning’s ability to ingest and process huge volumes of data from multiple sources, quickly – which is shaping up to transform online retail in ways previously unimaginable. The ‘confusion’ will be in knowing where to focus energies in AI investment.

AI is transformative is because of its ability to deliver actionable insight from data, so brands will be able to respond to what shoppers want regardless of where they are and when. The list of AI-driven eCommerce tools continues expand because of this; personalisation, voice recognition, image search, chatbots and more. The knock-on effect is also team efficiency.

With growing economic uncertainty, retailers must stay competitive to survive yet it’s getting harder than ever to engage consumers and deliver experiences that will turn them into brand loyalists. This makes AI’s promise of greater operational efficiency and its ability to deliver better online shopper experiences, extremely tempting.

But knowing where to focus energies in AI investment in ecommerce can be difficult and this will be the main challenge for retailers considering AI in 2019. Many will feel immensely pressured to stay competitive with the latest disruptive technology trends, but still caged by the need to deliver a clear return on investment. Retailers that have bought into AI or are thinking of making that move, will need to learn to work smarter with it.

Retailers will have to think beyond the black box

Most first-generation AI was designed around black box solutions which still exist today and probably form the highest proportion of AI systems operational in online retail. These black boxes typically take data in and spit answers out – classic 101 AI automation for eCommerce with algorithms designed to do the heavy lifting by processing volumes of shopper data in a way that humans can’t or don’t have the time or the inclination to. This is of course hugely valuable to shopper experiences and eCommerce is reaping the rewards by being able to deliver relevancy.

However, the black box has its limitations – very few of the answers delivered provide any context or rationale for how the decision was made. This works perfectly well if you have a shopper returning to your site to buy the same, or similar items, on a regular basis. Or even a new shopper whose search intent is clear. Then the black box is doing its job – like a well- oiled engine it matches the right products to the right shopper profile based on order history, or recommends relevant items based on similar shopper profiles.

The challenge we have with this scenario is that our shoppers are human. A black box cannot compute nuances or quirks in shopper behavior and anticipate that a particular side table might also appeal to a home furnishing shopper when he’s looking for a rug.

Recognising value in people-led systems

Embedding context, creativity and rationale in shopper experiences is where retailers will win in eCommerce. However, this is a value only a trained human merchandiser will deliver.

This is where brands will need to work smarter with AI to realise its value. AI is not a standalone solution that replaces a merchandiser, rather, it can offer the ability to enhance their role and unlock greater potential.

As competition grows, to survive in retail is to be distinctive and memorable, as well as relevant. Staying ahead of trends, curating brand authority and inspiring experiences will become as important as simply pushing products. Blindly following AI won’t deliver this; retailers need to identify their specific strengths and weaknesses to implement AI in a way that engages with shoppers and makes commercial sense. A positive sign is that some retailers are now starting to address this by hiring data scientists to interrogate data and help match insights to business strategy. Data will also be seen as a way to evaluate individual and team performance to optimise outcomes.

If anything in 2019, adopting AI will force greater cross-team collaboration in efforts to eke out true value from its investment.  With shared data, CMOs, IT heads and ecommerce teams will need to join forces with each other to set joint strategies.

With this approach, it becomes easier to understand where AI automation delivers real value and insight to support a strategy for teams to act on together. Whichever direction it evolves, the fundamentals of AI will feature on the annual technology prediction lists for years to come. For now, brands who get it right will be the ones who learn to adopt and adapt in collaboration with it.