Chatbot success 101: Why a single customer view is a?must

By Fang Cheng, CEO, Linc Global

It’s not easy to give customers what they want in places and mediums that are most familiar to the retail industry, let alone on emerging channels like chat and voice. When 1–800-Flowers.com launched its chatbot, it was hailed as an example of capturing commerce interactions on a new channel and giving customers the convenience they crave. As Forrester has since identified, however, the chatbot “forgets users’ information if they try to return to their task the next day — despite displaying the previously entered data earlier in the Messenger conversation.”

Aggregating and analyzing customer data and using it to tailor your customer engagement efforts was simpler when shoppers were only coming into your bricks and mortar store, calling you or ordering from your catalog. Today, they’re also tweeting at you, asking Alexa to reorder more of your product and signing up for text notifications about shipping status. The push to gather all of these fragments of customer data together into a single view has become more urgent than ever and silos are no longer an option.

The need for retailers to have a single customer view to ensure a consistent positive experience across all the channels via which they interact with shoppers has only grown more critical as the number of channels and the volume of customer data generated has increased. With the current ascent of conversational commerce, it’s now at an all-time high. In fact, if you aren’t integrating your conversational channel technology into your quest for a single customer view, you’re courting disaster.

Here’s why.

You’re frustrating customers

Memento is a great neo-noir film from 2001. After being attacked during a bungled home invasion, the protagonist loses his short-term memory. If he doesn’t write something down (or, more cleverly, tattoo it on his body), it vanishes from his mind within 15 or 20 minutes. This makes solving his wife’s murder and avoiding those unscrupulous people who would take advantage of him understandably difficult. What works on the big screen, however, proves maddening when it comes to customer service. A chatbot that doesn’t have context about the customer they’re interacting with and that shopper’s buying history with your brand can make the customer feel as if they’re talking to a brick wall. “We are living in an attention economy [in which] contextual relevancy earns you the permission to engage,” declared Constellation Research’s R “Ray” Wang at the recent Adobe Summit.

Shoppers don’t want chatbot interactions that exist in a vacuum. When they’re escalated from a bot to a person, shoppers also don’t want to start explaining their issue from the beginning or have to provide their order number. They’re seeking smart, personalized and seamless experiences that are able to effectively meet their needs quickly. A chatbot that isn’t plugged into your customer data and isn’t able to learn from and add to that body of knowledge based on its interactions with customers can’t deliver that. It merely frustrates customers and a frustrated customer is unlikely to be a repeat customer. To avoid this frustration, your intelligent chatbot should pass customer and inquiry data through to a human agent if it hands off for more specialized service and it should instantly know a customer’s order history as soon as the chat starts.

You’re leaving money on the table

According to Gallup, engaged customers represent a 23 percent premium over average customers when it comes to wallet share, profitability, revenue and relationship growth. Engaged customers buy more from you, they buy more often and they’re more likely to recommend your brand to others.

So, how do you increase customer engagement? You leverage the data you have about customers to personalize their experience with you across channels. When it comes to conversational channels, this means that your bot is able to draw on your single customer view to know what a particular shopper has bought (and returned) in the past and what shoppers of a similar profile have bought. It can cross-sell and upsell (How about a belt to go with those pants?) and suggest complementary products or repurchases of past orders (It’s time to replace that mascara.) based on the customer’s own history, not product-to-product relationships.

Unlike simply sending a personalized email rife with product recommendations (Need more shoes because you just bought shoes?) that may or may not get opened and read, your chatbot is engaging with a shopper in real time and reaching them at the moment they’re thinking about you with their wallet open. This is when you want to muster the full power of your single customer view to make this experience as pleasurable for the shopper and as profitable for you as possible.

You’re missing vital info

Is your current depth and breadth of customer data comprehensive or granular enough to allow you to create the kind of experiences that delight shoppers and build long-term loyalty? If it doesn’t integrate data from conversational channels, it absolutely isn’t.

To date, only 20 percent of marketers say their brand has an actionable single customer view. Chatbot interactions are a rich and largely untapped source of info to build out this holy grail. In those bot-to-human engagements, you’re learning how shoppers talk about and describe your products (vs. how you talk about and describe them), what their most common post-purchase questions might be, how frequently they check for shipping updates, etc.

If you’re not capturing this intel and engineering your bot to “learn” from it, you’re missing out on a goldmine of interaction-based data that allows you to continuously update your customer personas, which in turn allows you to deliver a more contextual, personalized experience — exactly what the majority of customers seek in return for all the data they furnish you with.

New channel, same customers

?Your conversational channel assistants cannot exist like decommissioned satellites orbiting the earth but no longer beaming data back home. If you’re going to take full advantage of the power of AI to give you a customer experience advantage, your chatbots need to inform and be informed by your quest for a single customer view. After all, you’re giving service and support to the same customers who see your order confirmation emails, browse your website and tweet you a question about a product. Success hinges on recognizing this fact and engineering your chatbot accordingly.

This article was originally published on www.RetailCustomerExperience.com.