So What? You've Got The Data, But What Does it Mean?



This is a question many marketers struggle to answer for themselves, and for their Chief Marketing and Chief Financial Officers. Which media channels will best meet their objectives, and provide the best return on investment? With increasing pressure on marketing budgets, organizations are looking for proof their media investments are working, and for ways to get more return for less.

Without looking at all of the results in context... The ‘so what?’ of the story is missing.

It’s no longer enough to say that you believe your marketing is working because ‘X’ number of people viewed the TV show, the newspaper’s readership is ‘Y’, or we had ‘Z’ visitors to our website last month. Instead organizations are now looking for quantifiable numbers, such as, for every dollar I spend, my sales increase by $X.

To answer these questions we have Big Data, with thousands of rows and columns of data, and more and more information from multiple sources, arriving faster than ever before. By itself, this data is both overwhelming and unhelpful. To get to the answers marketers are seeking, one must:


Marketing needs to articulate its questions clearly for the analytics team. This means identifying the business and communications objectives, any concerns or opportunities, which brands or products are important, whether a regional or national focus is required, etc. From here, the analytics team can determine the right approach to analyzing the data to get to the ‘answer.’ 


Once the analytics team knows the key questions, they can decide what needs to be done to answer the questions. Do they need Attribution Modeling, Regression Modeling, Pricing Modeling, a ConJoint Analysis, or something else? For each of these types of models and analyses, different data is required, and it’s important to get the right data in the right format that is cleansed and consistent. 


The result of all of the analytical work is more information. On its own, this information provides more data that is summarized and analyzed, but not the whole story. The data might show that print advertising has a lower return on investment than digital advertising which, while interesting, may be out of context or incomplete. Without looking at all of the results in context, and without further analysis, the ‘so what?’ of the story is missing. 

the analytics team must work with the marketing team to determine the ‘now what?’


To really make all of this analytical work and the ‘so what?’ valuable, the analytics team must work with the marketing team to determine the ‘now what?’ What should the marketing team do with this new information? How does it change or improve decisions? The ‘now what’ should include recommendations for future investments, and these recommendations need to take into consideration business goals, competitive activity, seasonality, and other limitations and restrictions. For example, minimum and maximum spends in certain media channels may be contractually committed, and should be included in the final recommendations. 

Businesses have a huge opportunity if they leverage Big Data in the right way, using the right tools, and the right analytics team. If the right questions are asked, the story the data can tell will help marketing make better investment decisions that positively impact the bottom line. There is great power in knowledge. It just needs to be harnessed in the right way. 

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