Chances are high that your company is already doing a pretty good job of collecting data - gathering customer feedback through CSAT and NPS surveys, tracking subscriptions and renewals through your CRM, and following engagement rates via web analytics tools. And maybe you’ve been doing more than just collecting that data, too! You’ve been organizing it, filtering it, mining it, looking for that metaphorical fleck of gold at the bottom of the pan: an actionable insight. With all of that work, it probably seems reasonable that critical points of information with detailed information on customer behavior are just a click away at any time.
And sure enough, when you first begin to review findings from your data, it’s easy to think you’ve hit the jackpot right away. That is until you realize that your analysis is merely skimming the surface and not delivering anything useful for informed decision-making. Customer behavior and brand relationships are more complex today than ever, and finding clear, impactful, actionable insights to grow your business requires a deeper strategy.
Defining actionable insights
Actionable insights are the end goal of data analytics - a constellation of data points that correlate in a statistically and contextually significant way.
Another way of thinking about actionable insights is to consider how they show the relationship between a specific part of your business and a specific segment of your customers, in a way that can be leveraged to drive change and grow your business.
Surface-level quantifiable metrics like CSAT scores are often labeled as “insights” on their own, even though they just represent simple data points without actionable levers. Managers need in-depth information that demonstrates a strong cause-effect correlation between data points to take action - basic scores or averaged metrics lack specificity, context and the financial evidence necessary for action plans.
Let’s take a quick example. Say you’ve spent the last quarter gathering feedback via an NPS campaign and are reporting that your customer satisfaction has risen, your overall score has moved up by 5 points and your percentage of Promoters has increased. Congratulations!
However, without context to explain why your customers are more satisfied, let alone what changes you made to improve, that NPS report doesn’t offer anything you can take action on. For example;
- Would investing more engineering time in the mobile experience improve your NPS?
- Does the speed of customer service positively or negatively impact NPS?
- What would the return on investment be from adding a new feature?
The point is, nothing in this analysis tells you what you need to do to keep customers satisfied - it simply doesn’t translate into actionable feedback that can drive change at the bottom line.
Identify actionable insights by digging deeper
Instead of focussing on the averages, you need to turn your data into actionable insights by going below the surface to identify the context around feedback and trends. Then, apply even deeper analysis to locate the information that connects that context with your desired business impact.
Keep in mind - you’re not looking for new data, just developing a strategy for digging further into the data set you already have to uncover actionable insights.
To make the most of the data you’re gathering, it helps to leverage a fully integrated process to limit information siloing and maximize data comparison. The good news is that you don’t need to hire a team of data scientists to do this - just develop a strategy and pair it with a killer analysis tool to make the most of your CSAT and NPS campaigns.
As you start digging beneath the surface of that initial CSAT or NPS score, map out a few questions to help guide you. A few points to get you started:
First - What is motivating the positive trend? Is there a specific element of the customer’s experience, a feature set on the product, or other similar factors that can be identified?
What to look for: To dig in, take a close look at Promoters and their feedback. Pay attention to words and phrases they repeat and identify trends that suggest a correlation between experience and potential action. For example, Promoters who enjoy a specific feature and also intend to place another order in the near future. These indicate solid opportunities to explore further and find out why they love the product so much that they keep coming back.
Next - What is the impact on the customer? In other words, does this motivating element increase or decrease the chances they’re achieving a successful outcome with your product?
What to look for: Look at what customers are saying about their intentions (the same text analysis that identifies trends can be applied here) as well as their spending habits. This will help you corroborate that their positive experiences really are motivating them to engage with your product at a high level.
Additionally - Which customer demographic is being impacted? Are multiple customer groups engaging with your product similarly, or is this primarily restricted to a single group?
What to look for: It’s easy to assume that the most vocal group are those most affected, but that’s not always the case. In NPS results, for example, Detractors and Passives also have something to say - close analysis of their comments will highlight areas where they are suggesting improvement, with the intent to engage more closely with your product if changes are implemented. Strong actionable insights lead to force multipliers, or specific product modifications that have a net positive effect on multiple demographics simultaneously.
Finally - How is your business being affected by this relationship? Is the outcome trending positive (customers spend more as a result) or negative (customers are churning as a result)?
What to look for: It’s no secret that keeping good customers is more cost-effective than bringing in new ones. In your NPS data, look for trends between customers or customer groups who signal a tendency to disengage or re-engage, in correlation with verbal signals in their feedback comments. Serious Detractors will start their slide by reducing subscription levels or feature use, while genuine Promoters will renew their subscription and even reach out
Ultimately, you’re looking for these data points to identify a specific action your company can take to grow, either by capitalizing on the positive relationship customers are having with your product, or taking steps to rectify a negative relationship.
Follow a winning formula to identify actionable insights
We can break this down into a simpler format to create a flexible, easy-to-follow formula:
Find actionable insights with text analysis
The solution to finding deeper data points that can lead to actionable insights isn’t to gather more data, or even change your collection methods. In most cases, the data you need is already available, in the form of verbatim (open-ended) comments in your customer feedback.
Many organizations shy away from deep analysis of verbatim feedback because it can seem tedious or cumbersome - that’s because they’re still thinking of out-moded tagging and coding processes. While it’s true that manually tagging and coding verbatim comments is time-intensive and often complex (developing a coding hierarchy, training analysts on procedures, manually reviewing and tagging each entry), there’s a better approach - instead of tagging, implement an automated categorization system.
Thanks to developments in machine learning, you can leverage automated tools that can accurately process and categorize thousands of verbatim comments in a matter of seconds. No more barriers to digging in for important context and relational data points - just point the system at your data and then slice and dice you data as many ways as you want to uncover those deep, actionable insights.
Apply actionable insights to improve your product or service
Let’s go back to our NPS example from earlier. Let's say your organization sees an increase in Promoters since last month. To formulate an actionable insight from this, we want to understand why your Promoters (Thing X) are so happy (Effect Y), which customers are the happiest (Segment Z) and how that is affecting the business ($A), with confident projections on what investments are needed to continue this trend ($B).
Simply put - you want to know how to increase the likelihood that any actions you take will produce a positive return - how to maximize positive value ($A) with a minimum overall expenditure ($B). Most of all, you want to know this data is as accurate as possible - inaccuracies and human bias in data analysis represents a risk that you’ll invest in a project that fails to produce a positive result.
Working through the questions above and plugging information into the formula helps map the way from a basic data point - “our NPS score has gone up by 5 points over the last quarter” - to a truly actionable insight:
“Our simplified online checkout process is improving NPS by 5 points for highly engaged buyers, who are purchasing 2.5 times more frequently per month and are spending 30% more per transaction.”
Now you finally have something to work with - a clear relationship between your company and your customers that is showing positive returns, which you can build on to grow business through increased customer satisfaction!
It’s time to move away from the broad reference to basic metrics or single data points as “insights” and develop a growth strategy for your business that leverages customer feedback into actionable insights.
Far too many companies mistakenly believe that actionable insights will require complex layers of manual work, or teams of analysts developing complex formulas that ultimately deliver a low return on investment.
Instead, tap into the power of your customer feedback data with smart and flexible analytics tools that will point the way to the deeper insights needed to take your business to the next level.