The information age began in the 1950s with the invention of transistor technology, then hop-skipped through the miniaturization of computer technology in the 1980s. Today, it's marked by, well, too much information. With increasingly rich data from a dizzying array of sources, marketers can now capture more information on customers and competitors than ever before and use that data to drive actionable insights.

Why, then, do marketing analytics contribute so little to firm performance? A 2020 survey of Chief Marketing Officers (CMOs) showed that despite steady increases in spending on analytics over the past eight years and even higher expectations for increased spending in the future, the contribution of marketing analytics to company performance has been, on average, fairly low.

The disconnect comes down to this: “The use of new data, in itself, is not a growth strategy,” says Oded Netzer, the Arthur J. Samberg Professor of Business and a Chazen Senior Scholar, in a recent paper published in the Journal of Marketing. “Rather a firm's marketing data collection efforts and analytics must align with its growth strategy.”

One reason this alignment doesn't happen is something called the “streetlight effect.” Often told as a joke, of a drunk searching for his keys under a streetlamp instead of the dark alley across the street where he lost them, the same principle applies when managers over-rely on data that's readily available. Instead of carefully considering which data sources and analytics are likely to drive the firm's growth strategy, marketers too often set their sights on data that is easy to access, measure, and apply, or on analytics their competitors explore.

The streetlight effect can cause major missteps, such as leveraging big data for small problems or, even worse, neglecting critical information altogether. For example, one study cited by Netzer and his coauthors shows that observing sales and promotion data often primes managers to focus on short-termism, prioritizing advertising and promotion investments that are easier to estimate from data, over distribution or product line investments, despite the fact that advertising elasticity is often much lower. In other words, a dollar spent on improving distribution or product line often yields higher return than a dollar spent on advertising.

Why the Streetlight Effect Dims Knowledge Discovery

It's easy to succumb to the streetlight effect, says Netzer. Among the reasons:

  • Data innovations are often thrust on marketers, who then scramble to leverage these data. Case in point: Customer relationship management (CRM) programs enable marketers to track the entire history of interaction with their customers. However, most CRM data contains little information on interactions their customers have with competitors or how customers' needs and wants evolve over time. This can lead to growth strategies that are overly inward- and backward-looking and neglect the importance of considering competitive forces and changes in the marketplace.
  • Clickstream data (tracking a user's clicks online) enables marketers to have a nearly 360-degree view of a consumer's virtual journey. However, customer touchpoints are not equally trackable across channels. Discrepancies in measurability between digital and offline media (including TV, radio, print, and outdoor) may cause overreliance on online promotion channels, not necessarily because of their higher effectiveness but due to their higher measurability.
  • Social media offers firms almost immediate access into consumers' opinions and views. However, before replacing traditional and more labor-intensive methods of collecting consumer insights, managers should consider the risk of self-selection in social media data, both in terms of which customers participate in social media and what information they selectively choose to share.

When Data Drives Competitive Advantage

According to Netzer and his colleagues, firms should align their data and analytics with three growth levers, informed by the customer equity framework, which suggests that a firm's growth comes from acquiring profitable customers, making more money from existing customers, and retaining profitable customers:

  1. Customer acquisition: Harvesting social connection data gives marketers the ability to identify potential customers who are connected to existing customers and/or have preferences and motivations similar to existing, profitable customers.
  2. Customer development: Using clickstream data and other business intelligence data, companies can go beyond simply tracking a customer's purchases with their firm and estimate how much that customer spends with competitors. Firms can leverage that data to increase their share of customer expenditures in a given category or industry (often referred to as customer share of wallet).
  3. Customer retention: Firms have traditionally relied on purchase and usage data to predict customer churn, but little attention has been given to mitigating it. Underutilized data sources, including unstructured data and causal data, are more difficult to gather and work with than traditional transactional data but can be extremely useful in identifying impending customer churn and mitigating it.

Read the full paper, “Capturing Marketing Information to Fuel Growth” in the Journal of Marketing (requires subscription).