If you’re just getting started in building a voice of the customer program, this article on how to gather customer insights is for you. Already have an initiative in place? The following tips might be a useful refresher.
What do customers love—and hate—about your products? Where are they most likely to give up during the ordering process? How does the product they receive compare with the one they imagine when they order from you?
No matter what business you’re in, you likely ask these questions every day. You probably already have the answers in your customer feedback data.
Customer feedback can confirm what you think you know about your customers—and deliver insights that you never could have predicted. You’ll need to consider order data, phone and online interactions, web traffic, customer surveys, and other data sources.
For instance, when Apple used data to find out which of its new iPhone features customers liked and used the most, they found a surprising winner: the Do Not Disturb feature. The ability to turn all the phone’s notifications off for peace and quiet was more popular than high-profile tech innovations like the iPhone camera or the Siri voice assistant. Are similar insights hiding in your data? Probably. Only a rigorous customer insight program can unearth them.
Ready to get started?
A customer insight is the result of a data-driven process for finding out how your customers think, feel, and react to your products—and using this information to drive growth.
It’s different from market research, which gathers knowledge and statistical information about customers or markets. Market research can tell you who your customers are, where they live, and how much money they have to spend, but it can’t help you motivate them to buy your products.
To gain insight into how your customers feel about your products, start by analyzing data, including:
Orders. What are people buying? When do they buy? What items do they buy together? What does adding a new product do to existing sales? When do people drop out of the order process if they do? How do sales, discounts, and other promotions affect sales? All this data is embedded in your organization’s order flow—and quantitative analytics can reveal patterns for growing revenue.
Web traffic. Web data can tell you what customers are interested in even if they don’t complete a purchase. It will help you pinpoint where customers come from—whether search engines, email marketing, third party sites, or other sources. It can tell you what they look at and for how long, and where they are likely to go once they’ve viewed your products.
Customer support tickets. In addition to facilitating better customer service, customer support tickets are qualitative data you can analyze for deeper insights. You can learn a lot about your customers by looking for trends in chat interactions, email customer service responses, and social media conversations.
Surveys. Companies frequently use different types of surveys to further understand their customers. Net promoter score surveys measure customer loyalty and likelihood of recommending your brand to friends and acquaintances. Customer satisfaction surveys track how your customers feel about your products, your brand, and your customer service capabilities. Surveys can be customized to your unique business needs. A good data partner can help you ask the right questions to unlock hidden preferences and attitudes and develop products and marketing messages that address customers’ real concerns.
Reviews. Customer reviews give a glimpse into how customers experienced your product or service, sometimes in great detail. Beyond providing a ratings score component, reviews are a rich source of insights because they’re unprompted and often highly descriptive opinions from customers.
But that’s so much data, we can hear you saying. It comes to us in all different formats, from text to numerical stats to voice recordings. How can we make sense of it?
It’s important to look at all data holistically, so that you can see patterns that emerge across multiple data sources and types. But to do that, you’ll need to translate unstructured information like customer reviews and customer service interactions into quantifiable data that can be compared and analyzed. By making all of your data as quantified as possible, you can identify broad, consistent trends, rather than simply relying on anecdotal evidence.
It helps to automate these processes, so that they happen continuously in the background, ready to provide information when you need it. That can empower your voice of the customer teams to dig into the factors that motivate and inspire customers, without having to pore over endless chat screens and customer reviews. And it provides data-driven evidence specifically for product teams to design, refine, and add new features that delight your customers.
Like any business initiative, a customer insights program should deliver measurable results that can be monitored over time.
For customer service teams, you should be able to see improvements in:
For product management teams using customer insights, key results usually include:
For marketing, growth, and sales teams, successful initiatives based on customer insights can be seen in:
All of these metrics should be built into your program and should represent your company’s unique goals for customer insight initiatives.
Complement your customer insights action plan with: