Your customer feedback is a gold mine. The rock faces are your raw feedback, and the gold hidden within represents insight into your business and customer experience. This actionable insight has the potential to revolutionize the way you do business.
Of course, not all business data generates actionable insights, and not everything within that rock is the pure metal you're looking for.
Imagine knocking down the stone. Two gold nuggets fall. They analyze them for purity. A nugget is small and of low quality. We'll take it anyway. Another is large and rich in purity. We will report this to headquarters.
In this metaphor, the difference between these two nuggets makes a finding generic (not actionable) or actionable. By distinguishing between the two, you can arm your decision makers with all the data they need to make informed decisions without cluttering the table with copious amounts of junk.
if you stayAnalysis of your commentsbut still not sure how to proceed, this post is for you. Here we share how to distinguish actionable data from non-processable data and explain three types of actionable information.
What are actionable insights?
Actionable insights are meaningful insights that result from data analysis. They make it clear what action needs to be taken or how you should think about a problem.Organizations take advantage of practical insightsto make data-driven decisions.
However, not all findings can be implemented. Actionable insights do not come from more information or more data. To state the obvious: insights, information and data are not the same.
In short, data is raw, raw information in the form of numbers and text. Data can be both quantitative and qualitative and can be found in spreadsheets or computer databases.
Information is data that has been organized and contextualized in an easy-to-use format. This can be in the form of reports, dashboards, or visualizations.
Knowledge is created by analyzing information and then drawing conclusions and making decisions based on them.
Why practical knowledge is important
Actionable insights are important because you can use them to make well-informed strategic decisions. These decisions can lead to specific positive results for your business. Unlike generic advice or consulting, your insights are tailor-made for you—derived directly from your actual sales data or customer feedback.
For a data-first organization, actionable insights are key to improving product and operational processes. When a company claims to be data driven, everything should mean thatexecutive decisionsbased on real data.
Today's progressive companies say they want to be data driven.Forsterreports that 74% of companies say this is a goal, when only 29% of those companies actually successfully create actionable analytics. But it is worth continuing.
Companies with data-driven strategiesthey have been shown to have a ROI five to eight times higher than companies that do not. The missing link for organizations looking to drive business results from their data is actionable insights.
3 Places to Get Actionable Information
qualitative data, like B. Customer feedback is full of insightful and practical insights. Get answers about why customers behave a certain way compared to numerical data.
Here are 3 sources you can use to collect customer feedback:
1. Net Promoter Score Surveys
Net Promoter Surveys (NPS) allow you to ask what your customers think of your products and services. ThisSurveyit can sit permanently on your website or be an interactive form at your event. Because you can decide which questions to ask in surveys, you have the ability to target potential pain points. The danger, of course, is asking leading questions that don't provide any real information. Hecorrect questionswill always be open and impartial!
2. Online reviews
Online reviews are a great place to gather feedback.Text Analysis Solutionsasthematicthey are invaluable for analyzing this type of data and turning it into insights. You can also take advantage of your competitor's online reviews for information. First, look online for public product reviews of your competitors. Then load the reviews into your text analytics product and analyze the reviews. In a product like Thematic you can also compare the results with your own analyzed comments.
3. Social networks
Another great place to get valuable information is from your mentions on social media. Analyze them alongside what your customers are saying on relevant forums and websites.
This gives you actionable insights
Whether you use oneNPSSurvey to collect customer feedback or anything else, you need a reliable solution to get actionable insights.
The ideas are hidden in the writing, aren't they?Freitextantworten, where customers explain why they gave you a certain score or what they don't like about your product or service.
Verbatim words can be difficult to parse manually. For this reason, people use Natural Language Processing (NLP) methods to ensure that the analysis is as accurate as possible.
thematicFor example, it uses a combination of NLP and machine learning to analyze feedback responses word for word. Heturns them into themes and ideasthis can drive decision making.
But no one will take your place behind the wheel. Only a real person who understands the context of your business can make the final decision on what data is actionable and what is not.
The difference between insightful and uninformative data
When it comes to understanding data, the holy grail is generating actionable insights. But what can count as insight?
Which of your data outcomes are actionable? Candata analysisOffer actionable information? Let's get to the bottom of this by looking at some examples from a fictional school.
Non-informative data
Non-informative data is all that is old news to you; something you already knew was a problem.
If you are running a school, the fact that some students are struggling with test overload would not be considered revealing. This is well known and will not help you in any way.
Insightful data
Insights or "insights" are anything you didn't know or had a hunch or suspicion about. Insights are findings that confirm or contradict your existing knowledge. You can confirm your suspicions or quantify the importance of existing knowledge with deeper context.
Using the school example, your analysis might reveal that not just some, but 90% of students report test overload. These are illuminating data and worth pondering. Some students might say that they would like tests to be distributed more evenly. This is actionable information that you can use to troubleshoot the problem.
Actionable insights can be translated into concrete actions that lead to adjustments and actions. You can also confirm that no action is required. Companies must ask themselves: What can be done? What has not yet been implemented?
As a general rule of thumb, if you can add "and therefore" to the end of a finding and then complete the sentence, it's an actionable idea.
How applicable are your findings?
As an exercise, try to find examples of know-how in your organization. To get you started, we've put together a few examples below.
- Our NPS score is down 15 points this month.
- Passengers complain about missed flight connections.
- 20% of customers talk about price.
- Buyers say that the clothes a competitor sells are of better quality.
- After the ban on plastic bags, people speak more positively of our brand.
- 30% of your critics mention that your competitor has an easier-to-use product.
Perhaps surprisingly, the first 3 examples above are not actionable for the business and do not provide meaningful information.
This is because these results are obvious and do not provide an idea of "why". It's great to know that my NPS went down 15 points, but why did it go down? The why is probably the actionable idea.
Points 4-6 are valid examples of useful insights that can lead to data-driven decisions.
3 types of actionable information
1. Insight > Personalization > Action
Critical thinking is crucial to turning knowledge into action. For example, you could address the lack of parking on campus by working with your city government to improve public transportation. Unlike the obvious option of providing more parking spaces.
This could make it possible to offer a scholarship to environmentally conscious students and reduce the number of students traveling to campus.
2. Information > No action required
Not everything is worth measuring, but data analysis can confirm assumptions. This analysis can lead to insights that are not actionable but are critical to the context of your business.
For example, you may think class size is an issue, but if students don't mention it, no action is needed.
3. Insight > Reconsider the strategy
Data analysis can also help to validate if the implementation of a strategy is working or not.
Imagine the scenario where students complained about unhelpful university staff last term. After you take steps to change that, next quarter's results will show whether or not the actions you took worked. If not, they need to be reconsidered.
Or if your customers say your competitor makes better quality clothing, that's an important idea to act on. By asking for feedback in a follow-up survey, you can gather more information about why your customers feel this way. You can then examine exactly what your customers appreciate most about the quality of your competitors' clothing.
If your business is a supermarket chain and you ban the use of plastic bags for some franchises, it can have a positive impact on your customers. Your customers can feel like they are doing something positive for the environment by choosing to shop at your supermarket.
As an action, you could build on the successes of those few franchises and drive this change across all stores.
Can today's software extract actionable insights from data?
Despite all the promises, no software solution available today can take data and turn out actionable, actionable insights.
This is because separating useful and insightful knowledge from other types of knowledge (eg, non-actionable/insightful, non-actionable/non-insightful, and actionable/non-insightful) requires two types of knowledge:
- objective knowledgeof difficulties related to various actions,
- subjective knowledgeWhat is old news and what is really revealing.
Finally, AI can classify objective knowledge by reading materials that have been published over the years and years. AI agents can even develop the ability to classify subjective knowledge over time by collaborating with the users of their software.
Advances in AI mean we're getting closer, but it's still imperative that a real person validate the analysis and decide what's actionable.
So how can today's software help us get actionable insights?
What AI can do today is the ability to examine data more efficiently. You can drastically reduce the time it takes to turn feedback into information.
NLP algorithms allow us to understand people's comments by turning them into topics that can be analyzed, such as: B. Numbers. This data is then presented visually to show differences, discover correlations, and spot trends.
When evaluating an AI solution, use the following questions:
- Can this solution tell you things about your business that you don't already know?
- How easily will you be able to separate the signal from the noise?
- Will you be able to spot trends in the data without having to specify them in advance?
If that sounds complicated, you've come to the right place!Check out our free buyers guideand learn to ask the right questions when evaluating feedback analysis solutions.
Be sure to book demos with vendors to make your choice easier. Ideally, request a trial version of the software; You want to be sure that it works with your data.
Once you've identified your main competitors, you can start creating a Request for Proposal (RFP). If you need help with that, we've createda specific guide to RFP for text analysis software- including RFP templates.
And of course, we'd love to show you how Thematic works its magic with your data.book a demowith our team and let's analyze!