Using Data To Drive Your Business Decisions


Founder and CEO of Rep Data, providing a full-service, consistent and reliable data collection solutions for market research.

We all know what they say when you assume something. It’s rarely the best course of action, and more likely than not, you end up with an inaccurate result. Business decisions are no different than run-of-the-mill determinations you make daily: They’re often influenced by biases and preconceived notions that can negatively alter the desired outcome.

In today’s information-driven environment, we have the luxury of removing emotional impediments and focusing on raw data to guide decision making. Where preconceptions used to blow us off-course, data now helms the ship. While many seem slow to catch on—with only 25% of enterprise businesses saying all their decisions are driven by data in a recent S&P Global study—most (90%) say data is of increasing importance to their business overall.

Trying to keep up with the evolving nature of target audiences can be daunting. There are instances when you’ll guess right based on past behavior, but without solid consumer insights, you could be leaving too much to chance. Imagine building a house without carefully measuring the wood: You’ll probably get something right, but the building could collapse. Measure twice, cut once; don’t waste time trying to anticipate what a demographic wants when you can collect factual data that gives you precise dimensions.

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The Cost Of Doing Business Without The Right Data

Designing a product, service, solution or communication based on assumptions is time-consuming, and the cost of implementing these strategies without a data set to guide your business can lead to lost revenue. There’s no guarantee that your systems will resonate with your intended audience, and a demographic rejection could set you back significantly and damage your brand’s reputation. In fact, some studies actually show that “68% of companies that increased revenue over the last 12 months used market research to do so.” It’s one powerful tool in your data toolkit that shouldn’t be underestimated.

Take the Google Glass fiasco of 2012. Google assumed that their wearable tech would make a splash with consumers on the strength of their brand alone. A lack of research into customer sentiment caused the clunky eyepiece to fail because Google didn’t consider whether its target audience needed or even wanted to wear internet-enabled headgear. The market made it abundantly clear that they did not, and Google pulled the product from the consumer market after two years of lackluster sales.

Had Google used the large amount of existing data that they had at their fingertips and collected relevant consumer data, they may have saved themselves time and a lot of money by delaying the launch or tweaking the product to represent something closer to customer demand. Google has an impressive suite of products, so the flop barely registers with audiences anymore. Smaller brands don’t have the same margin for error, which is why doing the legwork to understand a demographic on a data-specific level is so important.

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Using Data, Not Assumptions, To Find Success

Today’s world provides us with a vast sea of data, and the most successful brands, whatever their size, are using that data to their advantage. Relying on preconceived notions, assumptions or internal biases was never a good idea, and it is an even worse one in today’s reality, where consumer audiences are evolving rapidly.

By using the data streams you likely already have available to you, such as sales, product review or customer feedback data, you can start to better understand the landscape in which you are operating. You can complement these data streams with targeted consumer insights gleaned from sources such as surveys, focus groups, neuroscience techniques, product testing and more. Bring it all together, and you have a data-focused foundation for making decisions.

To avoid a Google Glass-esque fiasco, here are some best practices to consider.

• Fully utilize the data you already have at your fingertips. This means everything from examining sales data to see where and to whom specific products are selling all the way to mining and analyzing unstructured text data from product reviews and social media to understand sentiment and predict behaviors.

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• The loss of cookies is approaching, so plan ahead for the change. If you haven’t come up with a strategy to boost customer experience and personalize your product offerings without the use of cookies, then it is past time to determine a new approach. A report my company published with Loyalty Research Center (download) explored some paths that leading marketers are taking in the face of this new landscape.

• Integrate a robust market research strategy into your data mix. While choosing the methodology is one thing, finding the right audience is entirely another. Surveying people who are outside your specific target demographic provides fairly useless data. Proper audience profiling—plus the ability to actually access the right respondents—will give you research findings and higher-quality consumer data that can complement your additional business data streams.

It is a data-driven world. Use that to your advantage and plan a strategic data program so you can make better decisions on product launches, brand messaging and much more. A brand built on assumptions will be washed away by the flood of evolving consumer sentiment. There is a better way.


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