Your personalization engine needs to include human-power
Automated personalization and recommendation tools are great at helping shoppers and increasing sales, up to a point. These tools can make it easy for shoppers to find alternative items that may fit their needs a bit better. They can propose complementary products that help raise average order value. They can adjust the selection of items from a catalog that are presented to each shopper to highlight those most likely to be of interest.
But often, shoppers have needs or preferences that can’t be inferred from their browsing history or the profile data you can collect on them. There’s no way a personalization engine can know that, this time, I’m shopping for a present for my mom, not for me. And if I was shopping for a present for mom last time I was here, the engine may easily think I’m an 85 year old grandmother rather than a 47 year old guy. But even if I’m just shopping for me, how is a personalization engine going to guess that our coffee machine is dying and it’s time for a new one? Or that I’ve just become interested in sous vide cooking? Or that I had a bad experience with customer service from a particular brand a while back and I’d rather not give them my business? How do you personalize the shopping experience for these visitors?
That’s where humans come in. There’s still no substitute for the dialog that happens between a shopper and a great sales associate. The shopper articulates her needs, and the associate suggests a targeted, creative selection of products to solve them. That’s personalization! Sure, it’s old-school, but it’s still the gold standard.
However, this sort of human-powered personalization is expensive to provide – online as well as in stores. Further, not every sales associate has deep product knowledge or the gift of making that knowledge really useful to shoppers. The things you can do to improve the performance of associates – higher pay to reduce turn-over and training to increase knowledge – make the cost problem worse. Provide fewer associates and the customer experience declines – whether it’s live chat or in a store, shoppers don’t like to wait. And then there are the challenges of addressing spikes in demand, like the holidays.
The solution lies in a hybrid approach to recommendations that combines the ability of humans to come up with creative suggestions with the ability of technology to re-use that expertise and deliver it economically:
- First let your shoppers express their needs by submitting questions on your site. “I’m looking for a birthday gift for my 85 year old mom. Here’s some info about her. What would you suggest?” “We need a new coffee machine. Here are some things we want from it, and here are some things we want to avoid. Which ones should we consider?” “I’ve narrowed down to 3 sous vide cookers. Which is going to work best for me?” (This means your system needs to support multi-item comparison questions!)
- Then get those questions answered from the most appropriate sources for the question – past customers with relevant experience, your in-house experts, manufacturer reps, and independent experts. Provide the broadest possible range of answers and opinions, and make it clear what the perspective and background is of each person answering. And be sure you deliver those answers fast – that keeps the person who asked happy, and it also makes other visitors a lot more likely to ask their own questions.
- Finally – and here’s the key ingredient – put that Q&A dialog in a knowledge base and connect that knowledge base to your question submission form so that the next time a shopper has a similar question, they will immediately see if their question has already been asked and answered. Those future shoppers will receive INSTANT answers to their questions, and that is accomplished with zero additional work for your staff.
With this approach, you can quickly build up a knowledge base that incorporates the combined wisdom of your customer community and your own product experts, delivering the benefits of true human-powered recommendations with the scalability and cost-effectiveness of automated systems. You’ll also find that you have created a valuable resource for your internal customer support team. And you’ll have the foundation for providing automated, self-service customer support on mobile devices and kiosks.
So don’t limit your personalization and recommendations strategy to automated systems, and don’t give up on human-powered recommendations just because it’s expensive. Take a hybrid, Q&A-based approach to deliver the best of both worlds.