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TDWI Upside - Where Data Means Business

Balancing Privacy and Profit in Customer Analytics

Collecting customer data has provided benefits to both consumers and businesses, but there are costs to using personal data. What are the trade-offs between personal data privacy and customer analytics?

As more industries move toward digital interaction with their customers and capture data via digital platforms, fundamental questions have arisen: What are the trade-offs between personal data privacy and customer analytics? When do the costs of data capture for customer analytics outweigh the benefits?

To the company, the benefits of capturing and using customer data are improved products, higher engagement and customer retention, increased pricing power, and higher advertising revenue from targeted digital advertising. The costs are higher customer churn and lost engagement from poor customer experiences.

Learning from Differences in Privacy Attitudes

To identify the benefits of using customer data, it is interesting to compare what has happened in the news media industry in the United States and Europe.

In the United States, consumers and companies have far less concern about lost personal privacy relative to their peers in Europe. Americans seem to accept that data capture occurs and that companies use information on their demographics and behaviors for a variety of purposes. Americans appear to trust companies with their data to a far greater degree than they trust government.

In Europe, these preferences are reversed. Europeans are much more concerned about personal privacy and data capture by corporations. As has been widely reported, the EU has forced Google and other companies to honor an individual's "right to be forgotten." Europeans appear to trust their governments with their data but take a wary eye toward private sector data capture.

In response to these differing attitudes, sensitivity about using the information they collect on their customers is one of the most significant differences between European news media companies and their American counterparts.

Does the reluctance to use customer data to optimize their businesses hinder European companies? The answer, at least in one respect, seems to be yes.

Results of Adopting Customer Analytics

According to the 2015 World Press Trends report, in the five years from 2011 to 2015, news media companies in Europe lost 21.3 percent of their print circulation, while in the United States the loss was 8.7 percent over the same time period.

There are several factors that affect these numbers, including the greater reliance on single copy sales in Europe. However, a significant factor has been American companies' more rapid adoption of customer analytics to segment and target customers for pricing actions, retention efforts, and bundle offers.

American companies also use customer analytics, supported by data on their visitors' online behaviors, to acquire digital subscribers. This use of customer data by publishers for targeted pricing and retention efforts has saved about five million subscribers -- worth about $1 billion a year in revenue -- versus what would have happened had they followed European standards of data usage.

The use of consumer data by companies is fundamentally driven by the profit motive, and consumers accept that their personal data will be used by companies to offer them products and services directly or to help other companies advertise to them. This social compact has worked well, providing vast consumer benefits in the form of thousands of products and services available at little or no cost.

Costs of Using Customer Data

Excluding breaches of financial data such as credit card numbers, damages from a company's use of personal data have been difficult to prove in court. Economists could argue that consumers may be harmed by the reduction in the value of their personal information due to the widespread availability of that data, and the lack of legal damages does not mean there are no costs to consumers from the use of their personal data.

Irritating targeted advertising has led to the growing adoption of ad blockers, now used by 26 percent of Americans on their desktop browsers. Poorly executed targeted content can also annoy consumers. Early efforts in predicting what customers wanted to read or watch had humorous results. For example, my TiVo thought I liked westerns after I watched the comedy "Blazing Saddles."

The use of JavaScript blockers that prevent these targeting applications is another growing trend that could threaten, in concert with ad blockers, the information-in-exchange-for-services relationship that exists between consumers and companies such as Google, Twitter, and Facebook. These trends may also threaten the content-in-exchange-for-advertising-impressions relationship publishers have with their digital readers.

Improve Outcomes by Using Customer Analytics Carefully

When thinking about analytics, remember that statistical models are good at predicting probabilities over a large number of customers. Analysts usually do not know exactly who is going to buy a shirt or stop their subscription, but they can estimate over a group of customers how many will take these actions.

In our work with companies on predicting churn, often we are asked for the list of customers who are going to disconnect their service. We tell them we do not know precisely who will stop their account, but we can estimate how many will, and we can give them the group of customers to contact to have the greatest return on investment from a retention campaign.

Using these models, individual customers are treated more carefully and precisely than they would be under a "one size fits all" process. The point is that analytics can be helpful to both companies and customers, and in many ways analytics is a win-win arrangement for both groups if done correctly.

Ultimately, the major cost of data capture for customer analytics may be a loss of trust. If degraded user experience and pervasive targeted advertising cause consumers to be more guarded with their personal data, the result may be fewer "free" products and services, less access to digital content, and a lack of data for companies to use for business optimization.

Given the experience of Europe, I suggest we are better off collecting this data but using it in moderation.

About the Author

Matt Lindsay, Ph.D. is the president of Mather Economics. Matt has over 20 years of experience in helping businesses improve performance and drive revenue through economic modeling. Mather Economics is a global consulting firm that applies a combination of proprietary analytical tools and hands-on expertise to help businesses better understand customers and in turn, develop and implement pricing strategies that maximize operating margins, grow revenue, and improve customer loyalty.

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