Are we in danger of data fatigue?

Lotame senior director of data Evgeny Popov
By Lotame senior director of data Evgeny Popov | 25 August 2017
Evgeny Popov

While I’m too scared to use the cliché “Big Data” word, it is evident that we live in the era of overwhelming data volume. Brand marketers are trying to bridge all siloed data sets and make sense of the “big picture”, however unable to drive meaningful and actionable insights from myriad of visualisation tools and dashboards. That's coupled with a sense of frustration and skepticism every time a new company talks about 'customer management platform' or a 'data management system'. These terms are thrown around like bouquets at a wedding.

What is data fatigue?

Data fatigue refers to the indications of being overawed and hyper-interested at the same time. Every CMO I’ve spoken with have data or data strategy as number one on the priority list, while actually the data ecosystem growth velocity is not helping them to be effective in making right business decisions. There is an evident influx of new data vendors, which inevitably creates fatigue as marketers need to spend more time trying to wade through the fields and separate the wheat from the chaff. Even if they are successful with the latter, the volume of information and data points captured does not always translate to business outcomes. In fact, research shows that only 15% to 20% of data is “useful” and can push the bottom line.

To avoid the current epidemic of data fatigue, here's five tips of data dos and data don’ts:

  • Only use data sets which are directly linked to business objectives and KPIs i.e. customer lifetime value, engagement, units of attention, recall, sales, clients churn etc.
  • Only focus on insights which are actionable. There is no benefit in visualising and crunching data which you are unable to apply to drive outcomes.
  • Don’t build 'good to have' eye-candy dashboards. Unless there is a direct correlation to the revenue or a vital indicator which helps obtain a measurable and quantifiable outcome.
  • Humanisation of data insights is the key. Data on its own never helped anyone.
  • Align KPIs with data strategy. While answering the most imperative question -“What objectives measure the success of your business?”, find out what those KPIs are and look for ways to correlate your research analysis against on-boarded data sets.

No marketer needs to be sold on why data is important, nor do they need to be sold on why they need a data management platform (DMP). They are looking for practical explanations, in their terms, of what steps they can take to link business objectives with data strategy, and the most optimal way to surface these insights by the likes of visualisation tools and BI utilities.

By employing previously defined framework of the 'dos and don’ts', marketers can focus on the right strategy to make data work for them by answering pivotal business questions instead of showing pointless graphs.

To conclude, don’t expect the data to do all the work - keep a human in the loop to exercise intuition and find the growth opportunities. Make sure you focus on actionable data which is directly connected to revenue. And before you start building a brand new flashy dashboard, look around, you might be surprised how many internal insights are already available at your disposal.

Combating data fatigue is not easy, it requires a lot of work.

Happy data mining.

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