Digital Marketing Data

Questions every marketer should ask of their big data investments

By Lena Bourgeois, Vice President of the Consumer Market Group

July 24, 2015 | 4 min read

The phrase 'big data' has been on the tip of everyone’s tongue lately. It’s the kind of phrase that’s gone from the boardroom to TV commercials seen by consumers. It’s also seen as a magical elixir for marketing executives – an expensive initiative that looks and sounds good in presentations, but may not have actually solved anything.

The truth is that too many big data initiatives today are put in place without any specific outcome in mind. They can amount to $50m investments that allow executives to pat themselves on the back, even though they failed to move the bottom line.

That’s all preventable though. Marketers just need to build their data initiative with some clear ideas in mind. There are really two pieces to successful big data strategy – asking the right questions, and then putting the answers into action.

The first step with any big data initiative is figuring out the purpose of the initiative. It’s the big 'Why?' As stated above, big data efforts can cost upwards of $50m. Clearly, these are not designed to deliver quick fixes. If the chief executive or chief marketing officer is asking a big data question at the moment they need it, such as why they are losing customers, then it’s already too late (and that question is likely going to be a very expensive one).

Big data is about using numbers to change, improve or add – it’s for accomplishing something. Data crunchers don’t necessarily understand marketing strategy, so they need direction. Before even building infrastructure, begin with the fundamental questions about outcomes. Is the purpose to turn the brand into a market leader? Is it to change the brand identity? Is to build a new brand? A big data initiative can only give the answers it’s designed to provide.

Once the questions are in place, brands must assess if those questions can even be answered by the data on hand, or if more is needed. The data they already have represents what a brand knows. Brands must then identify what’s missing – and what they don’t know – before building their data team and initiative.

Another important question is 'when?' When a big data operation is built around a set of goals, those goals must be accomplished in a set time period. Yet most initiatives I see don’t have a set time, putting those brands in danger of simply spinning their wheels. Data scientists will continue to probe ad infinitum without a direction, out of sheer intellectual curiosity. Giving them a direction is crucial.

The final question to ask is if the data is actually usable. The central question to any data initiative is figuring out the difference between what a brand can do and what they should do. In short, which techniques, answers and insights are actionable and will help accomplish the stated goal?

Even once big data initiatives produce insights and answers, it’s important to question those answers. Academic analytics are not the same as marketing analytics, and data scientists hired straight from graduate school often only have experience in research-based work. They may end up implementing innovative analytics that aren’t practical in a commercial business, solely because that’s their only experience to date.

It’s important to be critical before building big data infrastructure. Failure to do so could result in a big investment on something that doesn’t work, and could jeopardize the whole initiative. While throwing around the phrase 'big data' certainly feels good, actually knowing the answers to valuable business questions feels that much better.

Lena Bourgeois is vice-president of the consumer market group at IXI Services, a division of Equifax

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