As we become more connected to technology, we use more tech-based products and have access to more products and services from around the world. This means that businesses need to connect to customers through a variety of channels, and become more customer-centric than in the past to stay competitive.
The only way to get there is by listening to your customer feedback, and using it to drive almost everything you do. Because, without customer insights, how do you know what’s going right or wrong with the products and services you offer?
Customer insights, or consumer insights, are perceptions and knowledge gained from analyzing customer data as it relates to their relationship with a company, with the goal of improving customer experience (CX) and a customer’s perception of their products and services.
Market research compares consumer/customer data to the customer’s place within the overall market – demographic fit, competitive research, new openings in the market, etc. Market research is the “what is happening” with customers within a given market. It is the statistical, quantitative data of sales and demographics.
Customer insight, however, uses these statistics plus a customer’s direct relationship with your company – qualitative feedback data of personal opinions and perceptions – to understand how they “feel” about your company and predict how they may react or what your company may be missing to give customers satisfactory value for their purchases. Customer insight is the “why is it happening” and “what might happen in the future” of customer analysis.
In a nutshell, customer insights are what you learn from the customer data you analyze in order to make them happier with your company, or make your product or service more relevant to them. You want to gain a deeper customer understanding about what they think and feel.
Consumer insight analysis is important to follow the needs of your customers and the whole customer journey, to understand what your company does extremely well and what are particular customer pain points. Open-ended survey questions, for example, rather than close-ended “on a scale of 1 to 10” questions can uncover data and perspectives you may have never even thought of.
Performing a full customer needs analysis can uncover consumer insights from internal data, like support chats, emails, and surveys, and from unsolicited customer opinions on social media, online reviews, and all over the web. There are numerous ways to gather the data you need for a customer insights analysis, and we’ll go through that a little later, but first, what can you use your customer insights for?
Take action with your customer insights to:
Productboard’s 2020 Product Excellence Report tells us that 52% of leading product managers say their teams’ new products and features are primarily inspired by customer feedback, yet only 10% feel that they actually use all of the available feedback sources.
You may have designed a product that you feel will perfectly fit the needs of your customers – years of R&D, testing, and trials – but some customers may use a product completely differently than others. And, even if the product is generally usable but not built exactly for their needs, you may never know because there may be no process set up for customers to send product feedback directly to you.
Customer insights analysis allows you to reach out to customers to understand exactly how they use your products, uncover easily fixable bugs, and maybe even find new use cases or features you hadn’t considered.
Understanding your customers’ needs and your company’s product shortfalls could be as easy as performing regular email, in-app, or in-store customer satisfaction surveys.
Learn how to target your customers exactly where they are and anticipate their needs. With AI tools that extract customer insights from huge datasets and analytics tools that show you individual customer behavior, you can go from targeting demographics to targeting individuals.
Wrapped playlists come out at the end of the year – showing users’ most listened to artists and songs of the year. The Spotify app allows you to easily share your playlist on Instagram and Facebook, so friends can see what you’ve listened to most and even click directly in the post to have it open automatically in the Spotify app. Wrapped playlist postings have become hugely popular, allowing customers to share their personal preferences and Spotify to execute a massive, organic social media campaign.
Follow your competition throughout social media, in the news, and on online reviews. Perhaps your competition just released a new product and customers are leaving a huge amount of feedback. Machine learning tools, like sentiment analysis, allow you to analyze users’ reactions to the release, right down to individual aspects and features.
Maybe they got one key feature wrong, giving you the opportunity to swoop in with your own fix. Uncover the strengths and weaknesses of the competition and how you stack up. Other text analysis tools, like keyword extraction, can find out what customers are mentioning most often – new industry buzzwords, important features, etc. – to uncover emerging industry trends and new use cases.
This can be a tough one to face, but analyzing negative feedback often has the most positive outcome. Analyzing customer insights will help you understand why your customers are leaving.
It could be as simple as customer support – customers want to be able to reach you 24/7, without too much effort. They expect omnichannel support, so instituting chatbots or performing social media listening may be all it takes to keep you in touch.
In SaaS businesses, for example, customer churn is generally due to one of three factors: subscription cancelation, leaving for the competition, or non-renewal. Simple CSAT surveys can help understand why customers are canceling, competitive analysis can dig into why they’re choosing the competition, and a customer feedback loop will keep you in better contact with your customers, so you don’t lose them to simple delinquent communication.
The more you know about your customer base, the better your products will fit them. When you really dig into CX from start to finish, you’ll uncover the individual points of the customer journey. It’s important to view CX as one continuous process with steps along the way.
Customer insights can be particularly helpful to put yourself in your customers’ shoes, relieve pain points, highlight the positive with social marketing, and “close the loop” to let customers know that you’ve enacted customer service requests and complaints, or so they simply understand that they have your ear.
There’s a lot of customer data out there, and extracting customer insights may seem overwhelming. When you’re working with strictly quantitative data – sales, income, demographics – spreadsheet tools, like Excel and Google Sheets can take care of most of it.
However, when you’re working with qualitative data from open-ended focus group questions and surveys, or emails and social media data, it can be a bit harder to analyze. Fortunately, qualitative data analysis, or unstructured data analysis, isn’t all done by hand anymore. You now have the power of machine learning on your side.
MonkeyLearn is a SaaS text analysis platform with easy-to-use AI tools that can start you on your customer insights journey right away. And once your tools are in place, you can train them (usually in just a few steps) to the needs and criteria of your business. MonkeyLearn is a start to finish solution to gather data, integrate tools you already use, and analyze it to your specifications for real-world, real-time customer insights.
Request a demo from MonkeyLearn to see how you can build your own customer insight strategy, starting today.
March 4th, 2021