What Marketers Can Learn from Pre-Purchase Consumer Data

A research paper by Elisabeth Honka, Stephan Seiler, and Raluca Ursu explores the wealth of information embedded in consumer pre-purchase behaviors—such as online browsing and in-store navigation—and offers insights on how marketers can harness these behaviors to optimize retail strategies. Published in the Journal of Retailing, the study underscores how pre-purchase data can refine understanding of consumer preferences, influence marketing tactics, and predict market outcomes.

Why Pre-Purchase Data Matters

Pre-purchase data refers to the steps consumers take to gather information before making a decision, such as visiting product pages or moving through store aisles. These activities reveal consideration sets—shortlists of products consumers might buy—offering a granular look at decision-making processes. For instance, the researchers note that in many markets, consumers search significantly more than they purchase: 9.5 times more for apparel and 15 times more for shoes in the cited studies. This discrepancy underscores the potential of pre-purchase data to bridge gaps in understanding consumer intent, even when actual sales data is sparse.

The research highlights two consistent patterns:

  • Consumers search fewer products than expected. Average consideration sets are often smaller than three, varying by product category.
  • Search behavior outpaces purchase behavior. This reveals a rich dataset that can predict preferences even when purchases don’t occur.

Applications in Marketing

1. Estimating Consumer Preferences

Traditionally, consumer preferences have been inferred from sales data. However, search data reveals choices consumers considered but ultimately rejected, providing secondary insights akin to surveys about second-best options. By tracking the sequence of searched products, marketers can refine models of demand, identify substitutes, and anticipate preferences. For example, search patterns can help retailers understand why certain products are co-searched, even when they appear dissimilar on the surface.

2. Guiding Marketing Decisions

  • Pricing Strategies: Pre-purchase data can help retailers adjust prices dynamically, targeting consumers with tailored promotions based on what they’ve searched.
  • Search Costs and Visibility: Retailers can influence which products consumers find through tools like rankings, recommendations, and advertisements. Products with higher visibility tend to dominate consideration sets, emphasizing the importance of designing search-result pages or store layouts to nudge consumers effectively.

3. Enhancing Retargeting Efforts

By analyzing products that consumers searched but didn’t purchase, companies can improve retargeting ads. Studies show such data is more predictive of future purchases than demographic information, making it invaluable for personalized marketing.

Understanding and Influencing Search Behavior

The paper delves into how retailers can manipulate search costs to affect consumer behavior. For instance, reducing search costs—through better rankings or simplified navigation—increases the likelihood of products being searched and considered. Advertising, when aligned with search data, can also shape behavior throughout the purchase funnel, from initial consideration to final purchase.

Challenges in Leveraging Pre-Purchase Data

The analysis requires sophisticated models that account for consumer rationality and expectations. For example, not all products are equally visible in a store or on a website, leading to biases in what consumers search. Moreover, disentangling whether a consumer’s choice is due to genuine preference or manipulated visibility requires rigorous data and statistical tools.

Implications for the Future of Retail Marketing

This research underscores a shift in focus from sales to consideration. Pre-purchase data offers a detailed map of the consumer decision-making process, enabling retailers to anticipate needs, enhance product discovery, and personalize offers. The findings advocate for a holistic approach where every interaction, from search to purchase, informs marketing decisions.

As technology continues to advance, tools like eye-tracking and clickstream analytics will provide even deeper insights. Marketers who integrate these findings into their strategies will likely have an edge in an increasingly competitive landscape.

For marketing professionals, the key takeaway is clear: understanding how consumers search is as crucial as understanding what they buy. The full potential of pre-purchase data lies in its ability to illuminate not just the end of the journey, but the critical steps leading up to it.