In this article, we cover what are Actionable Insights, the advantages, and disadvantages of using them in your business, as well as looking at some example Actionable Insight tools.
What are Actionable Insights?
An actionable insight is information that provides practical recommendations or guidance for making informed decisions and taking specific actions to achieve desired outcomes. These insights are derived from analysing large amounts of data using techniques like data mining, statistical analysis, or machine learning. Businesses, researchers, and individuals seek actionable insights to gain a competitive edge, improve performance, solve problems, or discover new opportunities.
The term "actionable" signifies that these insights can be readily acted upon. They offer clear directions or steps to follow and directly influence decision-making or problem-solving processes. By leveraging actionable insights, organisations and individuals can make informed choices, streamline processes, increase efficiency, and drive positive outcomes. Applying these insights allows for proactive decision-making and the ability to capitalise on growth prospects.
How to Get Actionable Insights
Data is in abundance, and whether we are viewing it in a personal or business capacity, knowing what to do with it can be daunting. Actionable Insights unlocks your data, and supports you to complete an action in order to reach a desired outcome. It aims to leave nothing for interpretation.
A good way to think of Actionable Insights is to consider it the tip of a hierarchy pyramid.
1. Data
At the pyramid base, sits ‘Data’. Data on its own is raw, made up of numbers, text, or a combination of the two. It sits in databases, with the most recognisable form in businesses seen through the lens of a spreadsheet. No context is given, and it sits there more as a record. An example of this would be a database of competitor products and prices. The database by way of example could include columns such as Product ID, Product Name, GTIN, Competitor Name, Competitor Price, Competitor Web Address, and a Date Stamp. Viewed in this manner, it is not massively useful, unless you know what you're looking for.
2. Information
This is where ‘Information’ comes in, at the pyramid middle. Data is processed, aggregated, and presented in reports and dashboards in order to give the viewer that previously elusive context, so they can access it in a more user-friendly way, and start the process of identifying what the data is telling them. It is storytelling of sorts. An example of this would be a Segmentation Chart, which takes the database of competitors' products and prices that we spoke about in the previous paragraph, and presents the user with a bar count of the total products at each incremental price position away from the average market price e.g. how many products are priced 5% above the market average price, how many products are priced 10% above the market average price and so on.
3. Insights
‘Insights’ can then be gleaned from analysing this Information, as the data now has some context. In the example provided, it is now possible to quickly identify the average market position relative to their competitors (In this instance, on average, the majority of products are priced at the average market price, confirmed by the bell curve showing most of the products at 0), and how many products are at either extreme position i.e. a lot more expensive than the average competitor price, or a lot cheaper than the average competitor price. The user has now more of a focus of where to look. A number of products are massively priced away from the average market price, so this is a good starting point. But again, it still requires some interpretation and understanding of the underlying data set.
4. Actionable Insights
'Actionable Insights' at the tip of the pyramid aim to provide you with an answer. A recommended action, so that decisions can be at scale, and there is limited area for misinterpretation. For example, they may be presented as a product tag that states - 'Increase Price - you're the lowest price in the market'. Stronger actionable insights will aim to challenge your previous assumptions and push you outside of your comfort zone, or make you aware of things that you would not have considered on your own. For example, they may be presented in a product tag that states you have metadata errors, such as e.g. 'Provide GTIN - you have low google search relevancy'. It does not stop there. Done correctly, it should monitor the action taken, and assess whether the action has worked.
The Advantages of Actionable Insights
- Actionable Insights can speed up your decision-making, as they cut through the noise and present succinct messages to the user.
- Actionable Insights work particularly well, where you have to made a large number of decisions day in, day out, as again, they help you to focus on what matters.
- To use Actionable Insights, you do not necessarily have to be a subject matter expert, meaning more of your team can be involved in the process, de-risking it.
- They are a smart way of enabling you to track the impact of your decisions.
The Disadvantages of Actionable Insights
- Actionable Insights can lead to confirmation bias, i.e. focusing on the insights that are consistent with existing beliefs, and ignoring the insights that are not consistent. Therefore users must be open to completing actions that might not have been done if they were relying on "gut feel".
Example Actionable Insight Tools
- Ubersuggest provides Search Engine Optimisation Tools. It's dashboard or recommendations is a perfect example of Actionable Insights, both in recommended steps and in tracking SEO progress.
- Heap provides users with insights to improve page conversion and improve user retention. Their on-screen pop-ups provide actionable insights.
- Blackcurve provides users with competitor pricing insights. The reports provide users with actionable pricing insights via product tags.