October 19, 2016 Last Updated 10:22 am

When do the benefits of customer analytics justify the loss of privacy?

Guest column: Matt Lindsay, Ph.D., President of Mather Economics, says that the ultimate cost of data capture for customer analytics may be a loss of trust

As more industries move towards digital interaction with their customers, a fundamental question has arisen from the ubiquitous capturing of data by digital platforms: 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 inventory. The costs are higher customer churn and lost engagement from poor customer experience.

To answer the question of what are benefits to companies of using customer data, it is interesting to compare what has happened in the news media industries in the United States and Europe. Sensitivity about using information 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.


According to the 2015 World Press Trends report, in the five years from 2011 to 2015 news media companies in Europe lost 21.3% of their circulation while in the United States, over the same time period, the loss has been 8.7%. There are several factors that affect these numbers, including the greater reliance on newsstand sales in Europe, but a significant factor has been the more rapid adoption of customer analytics to segment customers for pricing actions, retention efforts, and bundle offers. American companies are rapidly adopting customer analytics, supported by data on their visitor’s online behaviors, to acquire digital subscribers. This use of customer data by publishers for pricing strategies and retention campaigns has saved about five million subscribers that are 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 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. Excluding breaches of financial data such as credit card numbers, damages from 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 value of their personal information due to the widespread availability of those 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% of Americans on their desktop browsers. Poorly executed targeted content can also be irritating to consumers. The use of JavaScript blockers that prevents these targeting applications is another growing trend that could threaten, in concert with the 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.

A key point to remember when thinking about analytics is that these models are good at predicting probabilities over a large number of customers. They 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 customer churn, they often ask us for the list of customers that are going to disconnect their service. We tell them we do not know precisely who will stop their account, but 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 here is that analytics can be helpful to both companies and customers, and that in many ways analytics is a win-win arrangement for both groups if done correctly.

MattL-300Ultimately, the major cost of data capture for customer analytics may be a loss of trust. If degraded user experience and pervasive targeted advertising and content 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, it suggests we are better off collecting these data but using them in moderation.

Matt Lindsay is president of Mather Economics LLC, a global consulting firm that applies analytical tools and hands-on expertise to help businesses develop and implement pricing strategies

Photo: Privacy by Blue Coat Photos, used under Creative Commons Attribution 2.0 Generic.
  • Markus 1 year ago

    funnily enough, one of Mather Economics European Showcases, NRC Media from Holland, recommends to collect LESS data. At least that was one major point in a presentation, their Director Marketing and Data, Xavier van Leeuwe, gave in a recent conference in Cologne, Germany. “Don’t store data if you can’t explain why to your mother” was his guideline.

  • Matt 1 year ago

    Thank you for commenting. You make an excellent point.

    Xavier’s perspective on data collection and mine are largely consistent, although we differ a bit on the margin of where more data is helpful. We (Mather) advocate starting with the end in mind, in other words, develop a business case for the project that identifies the critical data elements to collect before starting an analytics project, which is another way of stating Xavier’s point: be able to explain to your Mother (or anyone else) why you are collecting the data. In the article, I discuss the greater application of data at the customer level in US and how it has shown a significant benefit to the customers and the publishers. Every market is different, particularly in Europe where cultures vary considerably, and there is not a universal “right” amount of data. Knowing the tradeoffs between customer privacy and improved business practices is important before saying “yes” or “no” to data project.

    Thank you again for reading the article. Best regards.