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Fishing in the Data Streams for Better Marketing Decisions

Fishing in the Data Streams for Better Marketing Decisions

Horst Feldhaeuser

fishing boat

Manually wrangling heaps of data to better inform your marketing efforts isn’t a tenable solution—here’s how to find the right technology to do the proper legwork

There are many different names for all the data that’s floating around out there. “Big data” was a hot term a few short years ago, referring to extra-large data sets that could be analyzed for patterns and trends. Of course, there are many other sources such as standard marketing research data from surveys, direct customer feedback, sales data, social listening, you name it—if it happens online, data is created. “Data lake” is a term coined by data scientists to define a large central location that stores unstructured (and less frequently structured) data. We can add this term to our growing list of data streams.

The bottom line is that no matter what you call it, marketers must bring this data all together for the very best decision-making. In today’s “unreal reality,” there’s been a lot of generalized talk about the changing consumer and the importance of keeping up with them. It’s not a reach to say that many are behaving differently, feeling unsettled and uncertain, and being bombarded by news and events they could have never foreseen. This is affecting metrics that marketers count on for decisions. What it means, practically, is that we need all the data.

Think about all the places that your customer may be leaving feedback. They are constantly taking actions and expressing sentiments that feed into your lake of data. You must combine this granular data with the larger picture, like aggregate data from the marketplace as a whole, in order to gain a baseline understanding. Just to make things more fun, you must be able to easily update this information as new data comes in.


Manually wrangling this amount of information is not possible. The only way to stay on top of this massive amount of incoming data is with the right technology. There are many things to consider when making an important choice about the system or platform that will help you keep up.

Get a Handle on the Data Streams

Companies with multinational operations can have data across geographies pertaining to retail sales absorption rates, consumer feedback, survey questionnaires, qualitative shopper information and much more. Getting this incoming information out of silos and into a system or platform that can handle all of it—in all its various formats—is the first step. When you are dealing with market research data and analysis, there are even more layers of complexity. Ask yourself where your data is coming from, and where you have missing pieces that a new stream can help to fill in. Then find technology that can handle it all, in all its beautiful diversity.

Synthesize the Data

When merging data coming from multiple outside sources, or simply seeking to combine internal projects for comparison and a birds-eye view of the business, there will be alignment challenges. Data from disparate sources will not match up perfectly in a spreadsheet row or column as the labels will differ depending on where the data is coming from. It will need to be harmonized into one usable data set by following a master labeling format—aligning labels from all the streams. There is absolutely no way to combine these without using technology. This is a critical priority for businesses looking to make data-driven decisions. Make sure whatever system you choose doesn’t require a heavy manual load to match up data into a usable format, and that it is able to automatically learn and implement alignment rules going forward.

Democratizing the Data

Once the data is brought together for a comprehensive view, the next step is to analyze and share it across the business. The right technology can make it easy to look at all the harmonized data, compare combined projects over time, and build a truer representation of audiences, market performance and other key data points. There is no need for stakeholders to look at fragmented views of important business data. And there is no need for stakeholders to slog through data views that they don’t need, they can have customized views when you use the right system. Ask yourself who needs to look at the insights from your hard work, which specific insights they need, and how they need it delivered. Can you add more people to your stakeholder list so they are also able to make data-driven decisions? With the right platform, everyone can join in on the fun.

Your business has its own streams of data that must be handled, at the very least, with these basic steps. When you add the complexity of remote work and other new demands, completing these steps efficiently and effectively can become an uphill battle. However, in an ecosystem that is moving at record speeds, with a consumer who is becoming ever more complex, having holes in the data is simply not an option. Identify your data streams, bring them together and use the right technology to understand what your customer needs today.

Photo by Egle Sidaraviciute on Unsplash.

Horst Feldhaeuser is group services director for Infotools. He is a multi-award-winning research professional with more than two decades of experience in market research, marketing and business consulting.