Big Data, Little Data … Who’s Got the Data?

I recently attended an interesting panel discussion put on by our local AMA chapter. The CMOs of four of the largest companies in central Iowa shared their views on a number of topics including what they are doing with “Big Data”. The levels of sophistication in their use of data was surprising.

The companies that were represented included a medium-sized retailer with 400 locations (B2C); a large financial services institution (B2C); a medium-sized agricultural seed company (B2B); and a large residential window and door manufacturer (B2C). The CMO’s tenure with their company ranged from one year to twenty-five-plus years.

The fact that the first question posed to the CMOs was about “Big Data” is telling. Everyone is talking about Big Data, even when they don’t know what it is. (For the record, Big Data refers to a combination of structured and unstructured data that can be mined to produce insights into any number of issues. “Big” doesn’t just mean “Lots”, even though many people in the media use it that way.) As the amount of data available to marketers has grown, the ability to organize and use the data has also grown in importance.

Coming from a direct marketing background, this sudden interest in data analysis is gratifying. We have been using data analysis for decades. Direct marketers use their own data as well as trading data with others to help customers discover additional products and services that they might find to their liking. We have known for many years that the more we can target the right people, the fewer people will be annoyed by receiving promotions for things they don’t want.

The increase in internet marketing has made the amount of data available to marketers grow exponentially. And the fact that much of the data available to marketers is anonymous has added an extra dimension to the complexity of the problem. Will all of the click-stream data we are able to collect actually help target people or is it just “background noise”. Unfortunately, one does not know until one does the analysis.

Not unexpectedly, the smallest company (which is B2B and sells through distributors) is making the least use of data. They don’t know a lot about their end consumers, and I suspect their customers — the distributors — would like to keep it that way. The opportunity for this company might be how they can help their distributors to use the data they collect on their customers to help sell more product to them. They can also help target their distributors’ most likely prospects and turn them into customers.

Both the retailer and financial services company are focusing on building a data infrastructure. The retailer is drowning in transactional data. They sell millions of small-ticket items each year. Their opportunity is in increasing the average sale by adding another item to each purchase (“Would you like a Slim Jim with your beer and diapers?”). The data can help them select new products or reposition existing products that their customers will happily purchase.

The financial company has a lot of data in silos and needs to put it together to get a better overall picture of their customers. Internal transactional data combined with publicly available demographic data can be combined to build powerful predictive models for cross-selling products to their existing customers. And the average price of these products makes the investment in advanced analytics a “no-brainer”.

Interestingly, the company farthest down the data path was the window and door manufacturer. They have a very long sales cycle and a high average sales price. Prospects often start researching their purchase a year before it is made. This company is utilizing their data to move people down the sales funnel and converting them to customers by collecting and analyzing their information. They are focused on the “structured” data right now but understand the need to integrate the “unstructured” social data that is out there. The high ticket price allows them to make the investment needed to move their business forward.

Four different companies, four different approaches to utilizing their data. But all four companies understand that they won’t grow without a better understanding of their customers.

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