In an age where data is at our fingertips, it’s easy to get caught up with the overwhelming amount of data available. How do you get the most value out of your data?…. By ensuring that data analysis provides actionable insights.

Knowledge is power

Data is available across a variety of valuable sources from transactional in-store and online data, to online search, loyalty schemes, social media, customer ratings. With so much data available, one of two things often happens: data is analysed for analysis’ sake; or you dont know where to start, therefore the data is left unharnessed.

If knowledge is power – then actionable insight is the holy grail. Many businesses have so much data they do not know what to do with it. In other words, it’s not the gathering of information or data, but the knowing what to do with it!

Data Analytics Industry

The data analytics industry is big business with spend increasing. ‘42% of marketers are going to allocate budget to help understand and action their data source’ (redeye).

Big data and business analytics revenue worldwide in 2019 was £189.1bn USD, associated software revenue worldwide 67bn USD. (source ONS)

So firstly, what are actional insights and why is it important that data analysis results provide actionable insight? ‘Actionable insights are meaningful findings that result from analysing data. Your data results should make it clear what actions need to be taken or how to think about an issue.’

With increased data, it can be easy to lose focus, become obsessed by ‘vanity metrics’, and fail to generate actionable insights for your business. (Smartinsights)

Scoping out the project

So how do you ensure that data analytics projects will provide actionable insight ? The insight that helps you to define your future strategy – the ‘SO WHAT’ we call it. Any analysis project needs to provide specific answers that you can put into context of your key objective.

Qualify what you want to understand from the data, what business pain point do you have? What are you trying to understand? What question do you need to get to the bottom of, what stats would help you to make informed and balanced decisions? Do you want to quantify, validate, or identify X/Y/Z?

If you can pinpoint what insight you need and why, you can then develop the right data analysis methodology. This will help gain the insight and stats you need to derive actionable insight.

Key things

  • Relevancy – Ensure the data you use is going to validate your project hypothesis not just give interesting information.  
  • Context – avoid confusion by adding context to your results providing answers not more questions.
  • Clarity – Interpret data in a digestible way. Clear insights communicated well will aid decisions and action. Data visualisation is a good tool to help demonstrate and interpret data (MarketView is a good example of this)
  • Integration – analysing different data sets together can provide a fuller picture.
  • Shared Learning – Insight shared across the business will provide better efficiencies and shared intelligence and consequently, also shared learning.
  • Clear objective – If using externally agencies, ensure you provide a clear brief for your project – detailing ‘The What’ and ‘Why’. As experienced consultants, they can highlight how best to tackle your project and ensure it will produce actionable insights.

Actionable Insights Examples

Projects where actionable insights can drive business growth:

Customer profiling

It could be redefining the profile of customers who are purchasing your brand. Measuring and analysing who is buying your products, where and how. The result is you can use this insight to align your future strategy, merchandising, POS promotions, and category alignment.

Brand activation

If you want to undertake brand activation, you will need to understand which are the best stores or outlets to initiate activation. Layering your brand profile against existing stores to identify and prioritise which outlets are closer aligned. You can then understand which stores offer the best sales potential by footfall, occasion drivers etc.

Store segmentation

Analysing different data sets to gain a full picture model of what typifies ‘picture of success’, what store attributes, catchment demographics, proximity drivers, impact sales across stores. By analysing different sets of data together, you can gain a full picture of different segments of stores, and what best to stock based on shoppers and occasion drivers for specific types of stores.

Therefore, with all data analytics projects, the SO WHAT? is the question that needs to be addressed and acted upon. Data analytics is powerful IF a business utilises the insight.

If you have a data & insight or research project you want to talk about please email us or call our office – we would love to hear about your project.

Read related articles: