​The Two Essential Use Cases Of Big Data In Marketing

How advertising campaigns might be focused, highly effective, and cost efficient


Progressive companies are leveraging information that they obtain from their website analytics, POS systems, CRM, and a variety of other sources to improve customer experience. However, when it comes to using the same data to attract new prospects, most businesses just don’t have the expertise to know what to do with that information. According to a recent survey conducted by Qrious, up to 30% of marketers claimed that their organization does not fully understand how to obtain value from the data they have.

So let’s add some clarity here. Big data analytics helps companies to accomplish two tasks. The first is the collection and storage of relevant information. The second involves leveraging various algorithms to analyze the collected data and obtain meaningful and actionable insights. The latter can then be used by to create advertising campaigns that are tightly focused, highly effective, and cost-efficient.

Dima Midon, CEO at TrafficBox, illustrates it the following way: 'In advertising, customers have the upper hand. They have nearly complete control over what they will consume. Targeting advertising to the wrong audience is like throwing money out the window. Big data allows advertisers to clearly define who their audience truly is and what kind of marketing creative they are most likely to engage with.' 

Understanding Consumer Behavior

By using big data, advertisers can navigate past the assumptions that can lead to wrong conclusions. For example, without big data, a company may create a category of customers they believe are most lucrative. They may then target these customers with special offers and incentives because they perceive their spending patterns make those customers particularly valuable.

Then, when they begin using big data, they start to gain true insights into customer retention cost, satisfaction, and even the average value of each transaction with customers in this group. They also obtain the same information about the customers they aren’t targeting. What they may find out is that without the assumptions, their target audience segment may not be as valuable as they once thought.

Using Big Data For Customer Retention

Not only can big data be used to correct false assumptions about customer value, it can also help to identify opportunities to reach out to existing customers who are likely to be most valuable over time. This information can then be used to quickly build advertising campaigns that target these customers with messages and offers that are truly valuable to them.

For instance, L’Oreal Canada has paired the existing customer data they had about their target customers and look-alike modeling that allowed them to discover similar clientele and reach them during their advertising campaign. As a result, they managed to drive twice more revenues than anticipated and achieved a 2,200% return on ad spend.

The lack of proper data leaves a lot of room for guesswork when it comes to predicting what customers want, and determining how to target them with paid advertising. When big data is used effectively, that changes significantly. Because big data pulls in information from a wide variety of sources, not just the company’s own information repositories, the insights gained are much deeper and demonstrably more useful.


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