Act like an analyst, think like a boss.

Written by 2:20 pm Digital Focus

Web Analysts are blessed with an immense amount of data, and an amazing amount of valuable metrics to understand business performance. Yet our heroic efforts to report on these metrics lead to little business action. As I discussed in my previous article “The decision gap” and how our focus on irrelevant data has limited us in terms of the immediacy and clarity as to what to do next. Today I want to dive deeper into what makes data irrelevant and what we should be focusing on instead to limit or shorten that decision gap.  

Look I get it, with the millions of data points, as a business leader you have a right to access every bit of it. But does that necessarily mean that it all matters to you and your businesses overall objectives? Sifting through hours of data will much faster lead you to data fatigue than a conclusion. There is nothing hugely bottom-line or impacting we can learn from every data source.  

What we should focus on?

Ultimately you should be focusing on data points that support some sort of return on investment, either directly or indirectly. If you are in the business to sell a product or service and you do not play in the e-commerce space, then the closest metric to a lead that you may have could be a “contact us” form submission, a request for a “callback” or quite simply a “member registration” form. It is that action a user takes that alludes to some sort of intent or interest in your product. Metrics such as Visits to your website, time spent on a page etc are contextual metrics that help you build on the story the data is trying to tell.  

Be careful what you infer! 

When you present a large number of Visits or Page Views or Followers, what you are essentially inferring, is that more is better. You are inferring something that is not there: success. You are hypothesizing, when you report that data, that these large numbers mean that customers are happy, and business is successful. I believe it is dangerous to make that inference.  

By building your research and statistical report around the core and supporting KPIs, it helps you to focus on what is important. Removing the inference by doing the work upfront to understand what the business actually needs.  

Why not seek direct success indicators? Instead move closer to metrics that sit almost on the same level as your business objective, metrics that your executives and decision-makers can actually understand.  

The following conditions are what I believe we should be focusing on to ultimately shorten that decision gap at exec level: 

  • Force strategic analysis of metrics that contain data material to the business bottom-line! 
  • Focus on data with a direct customer voice so we don’t need to infer and look at data with our own biases. Listen to what the customer is saying. 

Focus on task-completion rate over conversions 

Task Completion Rate is the percentage (%) of people who come to your website and answer yes to this question: “Were you able to complete the task you came to this website to do?” 

Combine that with the Primary Purpose question (“Why are you here?”) and you have a gold mine of fantastic data. Why people come, how much you let them down. No guessing. No making stuff up. No inferring things from Time on Page or % Exits! 

Viewing data through a humancentric lens allows you to influence human behaviour in a way that affects the change and outcome that you need. By just digging a little deeper, thinking like a business executive and a customer yet using your analyst mind, you start to understand what matters and what does not and better yet what decision you can impact.

Whilst business analysts can help in the transitioning of the ‘thinking-culture’, I also believe education plays a bigger role in moving ahead on this path. I am of the opinion that we should not only be guiding businesses as to which metrics to focus on; we should also be teaching our internal teams how to think about adding business/economic value and let the metrics flow from it.  

Tags: , , Last modified: June 3, 2020
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