The use of information through numbers has been a prevalent practice in modern businesses. Decisions are now driven by historical data being interpreted quantitatively, along with qualitative analyses. The relationship between data and decisions has been able to provide decision-makers with reasonable bases for their expectations. Marketing, as an aspect of the business, can also be driven by data.

So, What Exactly is Data-Driven Marketing?

Data-driven marketing is a method of forming marketing strategies around data gathered from the market. These data could either be customer demographics, geographic sales data, or even cultural propensities of a certain group of people. In business, marketing is mostly considered a behavioral science, predicting and altering the market’s reaction to a company or a product. Forming methods around these data would help in making informed decisions about costs, products, selling touchpoints, and even packaging. Knowing the population deeper by using numerical data allows a marketing team to properly create market segments for efficient marketing.

How is Data-Driven Marketing Used on Business?

Segmenting the market has been a common practice among businesses because it helps identify which parts of the market would be likely to be persuaded, thereby reducing the costs spent on ineffective marketing tactics. Market segments can be formed through data gathered from the market. For instance, a company selling whole milk to a community may need data on which households would be more likely to avail of the milk, thereby knowing which areas to put fliers. They could find data on which households have children who may need milk. Also, they could examine employment records from the community locals to determine which households are occupied by sole professionals who may not have the tendencies to have breakfast at home, making them unlikely customers. With the use of data-driven marketing, the company would be able to identify areas that are more likely to have new customers, thereby eliminating the marketing costs spent on putting up fliers on areas with no likely customers.

Another example is when a hardware store chain plans for product mixes in certain locations. In order to create a proper product mix and contact their suppliers, they would need sales data from previous periods per location. This would help them determine which products are more likely to sell in certain stores. They could also look at product obsolescence data in order to determine which products are not selling, therefore eliminating wastage costs on these items.

Conclusion

Marketing, as behavioral science, maybe data-driven in order to create plausible relationships between customers and their behavior. Using the data properly and creating relationships between the products and the potential customers would help in creating a marketing strategy that saves on costs in both the short-run and long-run. Data-driven marketing is also ideal in a highly vertical corporate environment because the decisions would be supported by mathematical figures. This makes the marketing team more credible to aboard. It has been a growing practice in businesses to create business decisions from raw numbers because it has been proven to have benefits to business analysis. If done right, data-driven business efforts turn profits in the long run.