How Big Data is Transforming Marketing as We Know It

The massive amount of data being collecting on everything from driving patterns to internet searches to the functioning of equipment is altering society on a massive scale. Mining and analyzing this firehose of information is a challenge with conventional tools, but Big Data is working to sort through it and find useful trends, analyses, and ideally, answers to questions we didn’t know we had. Marketing is no exception to this. Let’s review a few ways how Big Data is transforming marketing as we know it.

Marketing Is Perhaps the Biggest Use Case for Big Data

Big data is revolutionizing marketing because the business case is so obvious. Customer analytics, new product and service innovation, and fraud and compliance are among the biggest uses of Big Data in marketing, but they are far from the only one. For example, Customer Value Analytics or CVA relies on Big Data to deliver consistent customer experiences across all channels for each customer segment.

Why collect all this information and invest in the computing infrastructure, software, and a best in class marketing analytics tool? The business case is clear. Big Data means increasing the quality of sales leads so that your salespeople don’t waste their time. Improved prospecting list accuracy and better territory planning improve the productivity of your salespeople. Big Data lets managers study win rates and performance of individual salespeople and specific engagement strategies so that they can improve both. When you sell more with the same overhead, your business earns more money.

By more accurately aligning selling strategies and marketing strategies, go-to-market costs are reduced, as well. In fact, Big Data is reducing all types of barriers so that startups and small businesses are more connected to customers and able to compete with bigger rivals.

It Is Easy to Exploit the Opportunities Created by Detailed Data Analysis

We’ve long been able to see meta-trends like a decline in sales or improvement in repeat buying. Big Data, both its collection and its analysis, allows for much more granular data analysis. Firms can now identify submarkets and track trends for a dozen different customer segments, including cases where one group’s demand goes up as another goes down. In some cases, detailed data analysis reveals market segments buying your product you didn’t know you had. That’s an excellent area for marketing to explore.

A/B testing is well-established, but Big Data lets you test multiple variables at once across several channels and more quickly determine which combinations work. By combining it with detailed information about customers, you can come up with proven marketing combinations of taglines, landing pages, content and calls to action for each specific market segment. Furthermore, Big Data enables embedding intelligence into contextual marketing.
You don’t waste money marketing to people at the wrong stage in the sales funnel or not interested in your product. You don’t send ineffective marketing to your best leads. In all cases, your marketing efforts and money are optimized, and the firm reaps the higher return on the investment in marketing.

Digital Marketing Makes Big Data a Necessity

Almost 60% of Chief Marketing Officers say that search engine optimization, mobile, email marketing, and other digital marketing is where Big Data is having the biggest impact on their business. More than half of the surveyed CMOs said that analytics was essential to their marketing strategy over the long term.

Overall Revenue per Customer Can Be Improved

Big Data makes it possible to dramatically improve revenue per customer. Many firms already have Customer Relationship Management systems. Big Data lets you take it even further.

For example, Forrester found that Big Data allows marketers to go beyond campaign execution and improve customer relationships. They’re able to improve customer loyalty and profit per customer over a lifetime. The same analysis makes it possible for businesses to understand their customer acquisition cost (CAC) and customer lifetime value (CLTV). This helps firms understand which customers are truly the most valuable and should be a focus for acquisition, though the data can be used to determine effective methods of reducing the costs of acquiring new customers.

Big Data makes it possible to systematically connect with customers through their buying journey. People receive the right types of content and ads based on their stage in the sales funnel. The business meets them in the right manner at the right time, improving conversion rates. Big Data plus predictive analysis lets businesses reliably predict how customers will respond; business can then proactively work on building a relationship and capture the customer’s loyalty.

Loyal customers stay with your company, reducing the need to recruit new ones. Big Data makes it possible to identify “churn drivers”, the reasons people leave so that you can improve customer retention. It also makes it possible to understand how to best promote the business and its products to avoid “fading”.

Another application is in pricing. Big Data makes it possible for businesses to have differentiating pricing strategies. Businesses are better able to optimize prices based on customer demographics and even the preferences of the individual customer. McKinsey & Co found that 75% of the average company’s revenue comes from its standard product line. They estimate that a third of their pricing decisions fail to result in the best possible price.

They also said that a 1% price increase translated into an almost 9% increase in profits, assuming there was a decrease in volume. Big Data lets you see where you can increase prices without hurting volume and respond immediately if it does start to decline, even as you manipulate prices across the board in an effort to maximize profits. And you can learn how to make a deal your customer cannot refuse, ensuring that they buy, without cutting prices any more than necessary. A parallel application of Big Data is the A/B testing of cross-selling and up-selling so that you can quickly identify how to increase sales.

In short, Big Data makes it possible to make better pricing decisions to maximize profits, sales, and revenue.


Big Data has a clear business case when it comes to marketing. Whether increasing profits per sale, maximizing profit per customer, minimizing selling costs while maximizing the odds of a successful campaign or simply managing digital marketing campaigns, Big Data is revolutionizing Big Data. You can’t afford to ignore its applications for your sales, marketing, and customer support departments.

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