8 signs your organization suffers from data illiteracy

Sure, we all claim to be data driven marketers. But being a data driven marketer does not mean using data to send e-mail campaigns or merge names and addresses on envelope labels to send out direct mail. Being a data driven marketer means driving decision making, using insights to create better and more relevant campaigns, and being able to sense and predict your customers next best actions.

To become data driven, organizations need to adopt a new mind-set. One that allows to make decisions based on facts. And not based on gut feeling of senior management, often referred to as HiPPOs (Highest Paid Persons Opinion). Studies show that organizations that have adopted a data driven approach to decision-making:

This mind-set is not adopted overnight, it needs to be cultivated throughout the organization and coveted by management. The problem however is that the majority of senior management has a bad case of data illiteracy. Simply statistics is not something they teach at MBA’s. So data driven initiatives do not stand a chance if management is not on this page.

Knowing your organization suffers from data illiteracy offers you a head start in solving the problem? We’ve listed a couple of tell-tale signs:

Your boss’s favorite quote is: “There is Lies, damned lies, and statistics”

This quote that’s supposedly from Mark Twain and indicates statistics can be used to mask poor arguments. But if this leads to dismissing the use of statistics altogether this is clearly a sign of data illiteracy.

Marketing (campaign) performance analysis is done on an ad hoc basis

There are no regular intervals or processes that prescribe when campaigns are evaluated. These are usually done when management asks for them.

No one ever asks for numbers to prove a point

No need to clarify this one. This clearly shows data driven decisioning is not embedded in your organization yet.

Analysts are not involved in the campaign evaluation process

Marketers can be quite proficient in using the reporting tooling and/or agencies to provide them with. But visualizing, reasoning and creating a deeper understanding of the data is typically something marketing and analysts should do together.

Decisions are solely based on experience, not on facts

Your organization has lots of experienced people all knowing what works best. It’s hard to beat experience in decision making, unless you’ve got numbers to prove them wrong.

Campaign performance evaluation starts after campaign finish

If you start to think about what to analyze after a campaign already has begun, chances are you’re missing out on valuable data you could have had. If you only had thought about measurement beforehand…

No budget is allocated for insight generation

For proper analysis you need data, tools and brains. This means your company needs to collect and prepare data in data centers, invest in BI, visualization and analysis tooling, and hire or train people for the job.

People start to look weary when you talk about statistical significance

Sure, no need to technically explain p value, but a little sense of what significance means and ability to assess experiment size should be knowledge management possesses.

But how do you create a data driven culture where management shows leadership, opinions are validated, testing is business as usual and everyone acts on goals and statistical proof? We believe that an analyst should reside in your marketing teams to give you insights, challenges, tests and innovations. Also there should be educational programs to teach critical thinking and statistical skills and management should show leadership and a goals first approach. Or just start small and let numbers speak for themselves!

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