With customers increasingly moving away from brick-and-mortar stores for their shopping, finding new ways to personalise the customer experience has never been more important. In this Q&A with RetailTechNews, Aaron Glazer, CEO, Taplytics (pictured below), explains the role AI can play in ensuring retailers continue to tailor experiences in the mobile age.

RetailTechNews: Can you briefly explain how the Taplytics technology works, and how it is helping retailers?

Aaron Glazer: The Taplytics Experience Cloud is a portfolio of experimentation, engagement, and analytics solutions that help retailers create holistic, data-driven user experiences. It helps brands craft journeys that weave in and out of each digital channel. We help these brands engage with users to guide them through journeys, analyse how users are interacting with each touchpoint, and experiment with different versions of the experience to identify which ones delight users most.

The creation of 'magic moments' empowers retailers to build relationships with their customers that improve brand perception, loyalty, and ROI. Consumers have already moved to mobile, so it’s imperative retailers keep up. A retailers mobile app is the new front door of their business; so the magic of the brick-and-mortar store needs to be recreated in their hand.

How are retailers currently leveraging AI to automate personalisation?

AI has become a useful way of recreating the 'magic moment' of an excited greeter welcoming you at your favourite store on a mass scale with software. Specifically, that 1:1 experience that can make you feel at ease and excited about the decision you’ve made to shop there.

Aaron Glazer, CEO, Taplytics

With AI, these types of 1:1 experiences can be created through digital channels. As customers bounce from web, to mobile, to in-store, and back again, the amount of data from these touchpoints grows. Companies are processing these data points through AI to predict and contextualise each part of the customer journey.

One way AI is currently being leveraged is to predict purchasing intent. Retailers are improving their predictions to either send customised messages, like email and mobile push notifications, to help the user to execute an action that will increase their chance of purchase, or to customise the user interface by making smart suggestions on other items that may influence the user to make a larger purchase.

Amazon is a great example of a brand that is already doing this. If you’re logged in and viewing specific items, they will send you custom emails with the items you have viewed. They also customise the homepage with those recently viewed items so you can visit the product page right from the homepage without searching. To even further influence purchasing decisions, they show a Frequently Bought Together section on top of their suggested items section to get customers to products that they would want faster.

How do you think this will change in 2018?

The growth of online has made it easier for brands to offer new products, but also has made it easier for others to copy and saturate the market with similar products. Product differentiation has disappeared and brands now are shifting their focus to improving customer and brand experiences to drive value to their customers in 2018.

AI will naturally play a large role in offering customers better brand experiences. We will see more contextual and personalised communication through content. Retailers will look towards improving the personalisation of everything from offers, to graphics on digital properties, to the content in the communications they send to you. This will all be to reduce friction of purchase and, ultimately, lead to higher velocity purchasing cycles.

Beyond automated messaging, how is AI currently improving overall customer experience?

When brands think about the act of personalising their customer journey, many focus solely on personalised communication and messaging, which AI has pushed with trendy chatbots. However, the customer journey isn’t only about communicating effectively, but also delivering 1:1 experiences that will keep customers engaged and coming back. This includes everything from cross-channel experience personalisation to optimisation according to what the customer is looking to gain from their experience while using the platform.

The problem is that many brands don’t know where to start making these improvements. AI can make this learning process more efficient by helping identify areas of opportunity for improvement. The technology has the capability to recognise which elements of web pages and apps have the power to capture customer attention, add value, and create conversions according to previous user journeys and experiences on other successful sites. For brands, like traditional retailers, that are adjusting to the digital revolution, this is a powerful way to learn how some of the more forward-thinking brands in the space are capturing their audience’s attention.

Looking ahead, what aspects of customer experience do you think AI can help improve further?

From a customer’s standpoint, in-store and online experiences are slowly becoming one in the same. Odds are that if you’re a large retailer, your customer is on your mobile app, website, or that of your competitors. AI will quickly evolve to the point where it will be able to predict your afternoon latte from your morning espresso.

However, there is the flip side of improving customer experience via AI – it can be used to help brands understand the gaps they need to fill in. To craft an experience that is natural and consumed by real people, the technology shouldn’t be relied on to automate processes. For suggestions and insights, yes it’s helpful, but AI can’t – and won’t – automate the way you go through the user journey.  

Instead, AI should be looked to increase internal efficiencies by identifying where experiences can be improved. It can then be left to the team to come up with the solution that will best suit the needs of the customer.This content was originally published in RetailTechNews.