Guest Post: Using AI to Deliver Anticipatory Customer Service
Service that succeeds in meeting the baseline expectations of your customers– what I call satisfactory customer service–consists of four elements. Customers tend to be satisfied with a business if they receive, consistently,
- A defect-free product or service. (I define defect-free here as designed to perform correctly within reasonably foreseeable circumstances.)
- Delivery of that product or service in a pleasant manner.
- Timely delivery of that product or service, and a timely response to inquiries related to it.
And, because points 1, 2, and 3 may at times misfire…
- An effective approach for problem resolution.
Satisfactory customer service is important to be able to deliver but unfortunately has some limits to its business value. On its own, satisfactory customer service is generally not enough to ensure a high enough level of customer engagement to spark loyalty or create a true ambassador who will spread the word about your business. It tends to get taken for granted and leaves your business in the realm of the interchangeable commodity. While it is, of course, far preferable to satisfy customers than to be thought of poorly by them, it’s not the complete commercial win that you might hope it to be. That’s why the goal of exceptional customer service is worth pursuing.
Customer service becomes exceptional once you move the ball beyond the reactive four elements above into the realm of the anticipatory. Anticipatory customer service means to serve, as the Ritz-Carlton Hotel Company aptly puts it, even the unexpressed needs and wishes of the customer. It’s one of the most effective ways to delight a customer and boost customer engagement and, ultimately, brand loyalty.
Anticipatory service is typically and traditionally delivered by empathetic, trained, knowledgeable humans who pick up on customer sentiment and desires even when they haven’t (yet) been voiced.
But it can also be delivered by systems and technology that have been designed in an empathetic manner.
A particularly apt example along these lines is what AI can do when it’s designed to be proactive. Looking at Bold360’s latest iteration gives us a chance to see how AI can be used to rise to the anticipatory challenge.
For example, knowing that a customer came to your clothing site by clicking within a particular email campaign (let say a marketing piece regarding the fall sweater line) a Bold360-powered bot won’t waste the customer’s time with a generic “Hi, how can I help you?” like an old-school bot might do. Rather, it will provide information relevant to someone with an interest in that campaign such as, “I see you’re interested in our new fall line of sweaters; would you like to explore the new colors and patterns?” Or, knowing that every autumn a particular customer tends to buy new riding boots, when that customer logs into the Saks site this September, it might offer her a look at this year’s boot collection. Or, when a customer browses a travel site and lingers longingly on the beach vacation offerings, they might be offered perfectly pinpointed content such as videos and articles that can help them decide on the sandy, all-inclusive resort destination that’s most likely to hit the spot.
In the end, it’s important to keep in mind the “why”, because it’s quite possible to get wrong. It should not be to have further interactions for the sake of having them — but to instead provide value to the customer. If you, instead, focus on 100% on the needs of the company (i.e. what you think the visitor should be interested in) or offer faux-anticipatory service (dividing visitors into too-few buckets and overly generalizing your interactions as a result), you won’t get very far. Being customer focused in your proactive AI design and deployment will allow you to deliver next-level customer service that can meet unexpressed desires, answer the unvoiced question, and bring your brand into your customer’s heart of hearts.