Not all valuable feedback gathered is solicited in the form of surveys, focus groups, or interviews (also known as direct feedback in the CX world). There is a wealth of unsolicited—or indirect feedback—in call centre recordings, social media feedback, and web chat transcripts. A company can also use inferred feedback by tracking customers’ behaviours, contact frequency or purchasing habits.

This post is all about going beyond direct and indirect survey options and questionnaires, and expanding your program to include inferred feedback. When you meet customers where they are, however and whenever they’re interacting with your brand, you are opening the door to big picture understanding, big picture improvements, and, most importantly, big picture results.

So, What’s Inferred Customer Feedback All About?

According to Gartner analysts, inferred feedback is operational and behavioural data associated with a customers experience or customer journey, like a website’s clickstream data, mobile app location data, contact centre operational data, or ecommerce purchase history. 

Bringing Inferred Feedback to Life 

As an example of all three feedback sources working together, let’s imagine a shoe retailer’s CX team launching a new release sneaker in store—and they’re on the hunt for actionable intelligence. There are multiple touchpoints along the journey to analyse in order to launch this product successfully.

When customers buy shoes (or anything else) at the store, they are given scannable QR codes on each receipt for direct feedback. They might take the survey, rate their in-store experience, and say they buy shoes there every 12 months, on average. 

For indirect feedback, the CX team would also look at reviews on their mobile app, Facebook, Instagram and YouTube to see what customers are saying about the latest and greatest sneakers. We can use text analytics tools to find common data themes as well as positive, negative, and neutral sentiment in a customer’s verbatim feedback. The CX team can also look into web chat notes, which might show how many people have contacted you asking for more details, stock levels or sneaker quality in the past. 

The last step is to look at inferred feedback. When it comes to sneakers, it will be useful to look at purchase history through a CRM, a loyalty program, or a  customer’s store account, which will show an important operational and segmentation piece of the puzzle. From your analysis, you might learn a few things:

• the average repurchase cycle is 18 months
• those customers purchasing more frequently are your fanatics, more likely to be singing your praises and spreading the word
• your neutral customers are being nice and predictable
• the skeptical, non-loyalists come and go as they please

When you combine this behavioural insight with the direct and indirect feedback that corresponds to each segment, you are painting a better picture of what is driving customers to act in certain ways. 

Are the fanatics more forgiving of experiences, more excited, or even demanding more of you? What does this intelligence tell you to do? Increase stock levels, super-charge loyalty bonuses, or pivot?

When you put all of these pieces into your data lake, you now have all the information you need to form a rich, single view of the customer. From there, you can start making sense of the data and creating a world-class action plan. 

How Do I Take Action on Inferred Customer Data? 

A problem many businesses are facing is how to link all sources of collected feedback together, turn it into something they can act on, and truly transform their business. Luckily, we have a few tips for going beyond insights to take action:

Action Step #1: Get the Right Reports to the Right People

When it comes to bringing inferred data to life, optimised reports are a superpower. Spend the time up front to figure out which insights deliver relevant, actionable, and effective intelligence, then to get that intelligence to the right people. We recommend creating reports that are customised, metric-specific, and delivered in real-time, and then looking for those CX advocates in your business who have the power to do something with them.

Action Step #2: Put Your CRM Data to Work

Integrating CRM data with your traditional feedback data can be a game changer. It helps you understand more about the customer to create more informed, personalised interactions that can boost average basket size, increase purchase frequency and drive brand advocacy to new levels. 

Action Step #3: Resolve Issues Quickly

Your inferred data will show when customers are at risk of churning. This is a great opportunity to intervene quickly, and turn an unhappy customer into a lifelong advocate. One of the most important actions your CX program should take is responding to customer issues quickly and efficiently, be it negative feedback, a bad social review, or knowing a customer had a difficult time processing a refund.

If you’re looking forward to leveling up your retail customer experiences, check out this white paper: “How to Modernise Your Customer Feedback.”