As a marketing professional, you are likely familiar with the term “data-driven marketing.” This approach to marketing relies on data to make decisions about targeting, messaging, and other key aspects of the marketing mix.
There are two main types of data that are used in data-driven marketing: descriptive and predictive. Descriptive data describes what has happened in the past. Predictive data, on the other hand, can be used to identify trends and make predictions about what will happen in the future.
First, descriptive data can help you to understand your customers and your marketing performance. By analyzing past customer behavior, you can identify patterns and trends that can be used to inform your marketing strategies. For example, if you notice that a certain segment of your customer base is more likely to purchase after seeing a certain type of ad, you can focus your ad budget on that type of ad in the future.
Additionally, descriptive analysis can be splited into “prescriptive” too, to measure the success of your marketing campaigns. By analyzing how customers responded to a campaign in the past, you can determine whether or not it was successful and make necessary adjustments for future campaigns.
Predictive data, on the other hand, can be used to identify opportunities and make decisions about where to focus your marketing efforts. By analyzing trends, you can identify potential new markets or customer segments that you can target. Additionally, predictive data can be used to estimate the likelihood of success for a particular marketing campaign or strategy.
Overall, both descriptive and predictive data have their benefits in marketing. Descriptive data can help you to understand your customers and your marketing performance, while predictive data can be used to identify opportunities and make decisions about where to focus your marketing efforts.
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