Marketing campaigns are now built around using data analytics to identify strategic opportunities and explore our options. We then “test and learn” as we implement and gather even more data to tweak our tactics. But do we have the right data? And are we using it in the right way?
These are great questions teams are raising as we manage the latest Google Analytics G4 update. Google Analytics first emerged in 2005 and has undergone many updates. As we run G4 and previous UA report versions in parallel to prepare for the transition, teams are re-assessing KPIs to ensure our goal setting hasn’t had any unintended side effects – and that the data we are gathering, analyzing and reporting are aligned with our objectives.
Remember “Goals Gone Wild”?
In 2009 an article from Harvard Business School, titled “Goals Gone Wild”, highlighted how goals can improve performance but can also “narrow focus, motivate risk-taking, lure people into unethical behaviours, inhibit learning, increase competition, and decrease intrinsic motivation.” I recall re-assessing our KPIs to ensure our goal setting hadn’t had any unintended side effects. Similarly, staff are now re-assessing how we are actually gathering data and what business decisions that data is informing.
In reflecting back on our evaluation meeting minutes, it’s like reading an annual report – the notes are key! As so many factors influence customer behaviours, we had to consider the broader context and not just the data our reports were showing. e.g. Did the weather impact the event/campaign? What about the glitch in the automation setup we had to fix? Did our marketing technology not connect the dots? It’s never just about what the computer spits out, but how we interpret and use the data.
- data can identify patterns
- data often shows us the what but not the why
- the why often needs further qualitative approaches and discussions to diagnose/learn
Are we Collecting the Right Data?
New technology has also meant the type of data points we can now gather have expanded or changed. Are you finding you are wasting time collecting supplementary data teams are no longer using to make decisions? Or it no longer provides you with the answers to new/key questions? Or even worse, it doesn’t provide you with any actionable insights?
As we discuss the changes in the analytical software options, like us, you may find some folks on the team want reams of detailed data while others were more critical of data quality. We all have heard “GIGO” complaints – Garbage in = Garbage out. As you explore the new analytic standard reports, ensure your team takes a moment to ask some important questions to improve your data and decision-making. Here are the four steps we followed to improve how we approach the transition.
- We defined clearly our data requirements under each KPI.
- We set up detailed requirements to ensure data quality
- We then met to discuss these requirements with the data owners
- We demonstrated how we plan to use the data we are getting / will get.