How Back-End AI Creates Effortless Customer Experience

Artificial intelligence (AI) is a huge buzzword with nearly half of retailers having near-term plans to use it for improved shopper experiences. But there’s one big misconception holding retailers back from using AI to its fullest potential. Etailers commonly associate AI with customer-facing features — such as chatbots and voice-assisted ordering — but the real power of this technology is its capabilities on the back-end of the digital experience.

Eric Hansen, CTO and Founder and SiteSpect, took time to speak with RetailITInsights.com about how back-end AI helps retailers optimize their digital experiences to meet shopper needs, addresses how smarter testing strategies help brands build customer profiles, and offers actionable customer insights to help etailers spot trends and make smarter decisions in real-time

Q: There’s much hype associated with AI in the customer experience space — why do you think so many retailers are considering investing in it?

According to a McKinsey, Artificial intelligence: The next digital frontier?, companies invested somewhere between $26 and $39 billion in AI technologies last year. However, retail remains a “middle-tier industry” in terms of adoption of this technology. While Amazon is the obvious exception, the rest of the retail market is playing catch-up.

It all comes down to one thing: increasing conversions. Every online retailer hopes they can offer the right piece of content, offer, or online shopping experience to earn a better conversion rate — that is the main reason for improving customer experiences. While many metrics come into play — like increasing engagement rates and reaching new audiences — the biggest hope is that AI will be the missing link that helps retailers act faster on customer insights and find new segments to capitalize on.

Q: What misconceptions do retailers hold when it comes to AI?

Retailers commonly fall victim to two kinds of misconceptions when it comes to AI. The first, and one that is mostly relevant for larger retail organizations, is that the more AI solutions in place, the better off the company will be at improving CX.

For example, one retailer might have one AI platform that’s run by the marketing team and a separate one run by customer service — but which offers a true, comprehensive picture of each customer? Are they both using the same data or are the two systems treating customers differently? When an organization doesn’t put forward a comprehensive AI strategy — where different parts of the company use the same or similar tools to meet one overarching goal — there will be multiple versions of the “truth” which will ultimately lead to different experiences for the same customer. It’s important retailers make sure their AI strategy is all-encompassing and breaks down traditional siloes between different organizational departments.

Another big misconception many retailers hold is that AI will solve all their problems — they forget about the need to consistently test and experiment with new initiatives in conjunction with their AI tools. For example, if a retailer has one system making automated CX decisions, they will ultimately become reliant on it for every digital experience issue or update. But the retailer must ask itself if this same system will work across all channels and whether it is truly optimizing CX. It’s critical retailers continue to test and verify the AI system’s work.

Q: What are some ways retailers are using AI to improve customer experience today?

There are several ways retailers are using and thinking about leveraging AI.  In the short-term, there are obvious ways to utilize AI to drive retailers’ bottom lines:

• Personalization is paramount when it comes to improving the customer experience, and we know shoppers have better experiences and are influenced to spend more money with brands that tailor their digital content. Moreover, companies are becoming much more intelligent about utilizing Big Data and connecting it to AI to generate a comprehensive view of each customer.
• Chatbots are currently used in customer service and support, but this technology is also being developed to help customers make purchases. And what’s even more is customers may be using these tools to pinpoint and generate their own interests and potential needs.
• An important, but less flashy benefit for retailers is the use of data across all channels to further refine their understanding of customers. By taking the distinct customer insights gained from a range of sources — such as their own CRM, marketing, POS, along with other unstructured data like social media posts, weather forecasts, and local economic trends — AI can take in all this information to anticipate needs and provide predictive offers, identify trends, and find segments that were not there.

Q: AI generates a large volume of data. How is this influx of data best managed, analyzed, and leveraged?

AI both generates and consumes data. The ecosystem and relationship between AI and Big Data is akin to a brain (AI) and the food or energy (Big Data) that keeps it going. To ensure this system is continually running at a healthy speed, retailers must ensure there are members of the workforce with the right skill sets. Analysts, data scientists, system architects, and data experts are all necessary to keeping the ecosystem fed and in balance.

In the digital age, every organization knows data is the greatest vein of gold. Having a rich set of data with predictive and prescriptive capabilities will ensure retailers are driving their biggest company objective — more conversions. And most importantly, they are driving more meaningful conversions that have a higher average order value and increased lifetime value. In other words, happy and loyal customers that keep coming back.

Q: What does the future of AI in retail look like?

Soon enough, there will be a melding of AI, augmented reality (AR), virtual reality (VR), and Internet of Things (IoT) in the retail space. But with all of these cutting-edge technologies quickly entering the retail and ecommerce spaces, AI will take the lead and turn each of these innovations into an afterthought. Specifically, while each of these technologies provide a new layer of the customer experience, AI can get to the root of customer sentiment and preferences, understanding what kinds of features are appealing to them and in turn adapt and tailor the experience. For example, AR and VR could be the way a certain segment of consumers will want to shop, and AI will still be at the core of its strategy, gathering data and making the best choices, in real time, in order to accurately respond to the customer.