By Jay Given, VP, Retail & Brand Strategy, Affinity Solutions
In part one of our Outcomes Collective series, we established the importance of retail media measurement and addressed common industry challenges like a lack of universal definitions and accounting for incremental sales lift.
With hundreds of retailers entering the Retail Media space, recognizing the nuances between retail categories and shopping channels is critical. Measuring outcomes requires accounting for differences not only in products themselves but also the types of retailers running campaigns. Each retail channel has unique dynamics that influence customer behavior and purchase cycles, adding another layer of complexity to measurement.
Feeling overwhelmed? In this segment, we’ll provide a clearer understanding of how your product, sales channels, and marketing methods influence effective ad campaign measurement.
One Size Does Not Fit All: Product Categories and Channels Matter
What a shopper buys frequently can tell you a lot about their overall spending habits. Retailers looking to prove the return on their media network’s ad-spend should build dynamic exposure and purchase attribution methodologies given the difference in purchase cycles and the nuances of the consumer journey.
For the non-measurement folks in the room, we’re going to be discussing exposure and purchase attribution a lot, so to ground us:
Exposure vs. Purchase Attribution
Exposure attribution is the period of time prior to a conversion event (like a purchase, lead form submission, or website visit) during which a user’s exposure to an advertisement is considered eligible for attribution to that conversion. In other words, how far back in time you look at ad views or clicks to give credit for a conversion. This window helps determine which ad interactions are most likely to have influenced a conversion. It acknowledges that users may see or click on multiple ads before finally converting, and it sets a limit on how long ago those interactions can be considered influential.
Purchase attribution is the period of time after a user’s exposure to an advertisement during which any subsequent purchases made by that user can be attributed back to that initial ad exposure. This is particularly relevant for measuring the long-term impact of advertising and understanding customer lifetime value. This window helps advertisers understand the delayed impact of their campaigns and identify if initial ad exposures lead to future purchases beyond the immediate conversion event (for example, clicking on an ad). It’s crucial for evaluating the effectiveness of branding campaigns and customer acquisition efforts.
Product Categories
Retail products fall into two main categories: high-frequency, low-ticket items and low-frequency, high-ticket items. I will buy earrings more often than I will a microwave, but I’ll do more research before purchasing my microwave. If I’m exposed to an ad for an earring and a microwave on the same day, I’m most likely going to purchase the earrings sooner than I will the microwave. However, if my microwave breaks and I urgently need to replace it –my conversion timing drastically decreases. In the moment of need, the microwave brand that comes to mind as a result of previous brand exposures (as well as a good deal), will most likely be the one that I go for or at least conduct more research on.
High-Frequency, Low-Ticket Items: These products are purchased often and generally at a lower-prices point including goods like groceries and consumables. Because these products generate vast amounts of transaction data, ROAS calculations are more straightforward. However, exposure attribution windows should be shorter to reflect the fast purchase cycles. Purchase attribution should also account for rapid replenishment behaviors, ensuring incremental sales are not conflated with habitual purchases.
Low-Frequency, High-Ticket Items: Products like appliances, furniture, or luxury items that involve longer purchase cycles and higher levels of consideration fall into this category. Exposure attribution windows here should be extended to account for the research-intensive nature of these purchases. Purchase attribution windows should reflect the extended timelines, capturing any delayed conversions resulting from ad exposure.
Retail Channels
The product category often influences where and how consumers purchase. The ever-growing number of retail channels is great for consumer versatility but trickier for advertisers trying to understand consumer behavior. To effectively measure outcomes, it’s important to curate your methodologies based on your retail channel.
Mass Retailers
For mass retailers, focused on a wide range of products, measurement strategies span diverse product categories from groceries to apparel to toys. As a result, exposure attribution windows should vary by category. Purchase attribution requires flexibility due to mixed purchase behaviors. (How many times have you walked into Target with toothpaste and vitamins on your list, only to walk out with a decorative pillow, a plant vase, or another candle?) Measuring outcomes for these retailers requires agility and dynamic methodologies.
Specialty Retailers
Stores specializing in categories like electronics, beauty, or sports require tailored approaches that account for niche customer behaviors. For example, exposure windows should align with the higher research activity in electronics or sports categories, while purchase attribution might extend well beyond the campaign flight for big-ticket items.
Luxury Retail
Higher price points and longer decision cycles warrant multi-touch attribution models to account for the entirety of the customer journey. With longer research cycles, clean room environments are beneficial to commingle different exposure sources and analyze cross-channel impacts. Exposure windows here can extend to capture the prolonged consideration phase, with purchase attribution also reflecting the often-delayed nature of these transactions.
Grocery Stores
Because fast-moving consumer goods dominate this space, exposure and purchase attribution windows should be shorter to account for speedier consideration to purchase time periods.
Home Improvement
Home improvement often involves research-intensive purchases (similar to Luxury Retail) that span online and in-store interactions, making it critical to incorporate diverse touchpoints in measurement and different exposure sources. For example, wood finishes, paint colors, or fabrics may look and feel different from how they are displayed or described online versus in person. Exposure windows might range based on campaign length, depending on the complexity of the purchase, while purchase attribution may require extended timelines to capture offline interactions.
eCommerce
Online retailers benefit from a wealth of first-party data, but they face challenges like high cart abandonment rates and difficulty tying ads to in-store conversions when omnichannel strategies are involved. Exposure attribution can often align with campaign duration, while purchase attribution windows should consider retargeting effects and delayed conversions.
Brick-and-Mortar (B&M)
Physical stores often struggle with measuring outcomes due to limited access to customer-level data. However, loyalty programs, integrated POS systems and credit card data can help bridge this gap. Exposure windows for B&M campaigns may align with event-based marketing, while purchase attribution should account for time-to-store visit delays, extending past the campaign’s duration.
Accounting for different channels and consumer behavior will result in greater efficiency and more precise measurement. Here’s where I’d start:
Call to Action: Tailor Your Measurement Approaches
Retail Media Networks (RMNs) will enable more informed decision-making and higher confidence in incremental impact from their advertisers by considering the following:
- Redefine ROAS calculation by category and purchase cycle. Retailers should calculate ROAS with dynamic exposure and purchase attributions tailored to specific categories and purchase behaviors. For example, high-frequency items should leverage shorter attribution windows, while low-frequency, high-ticket items may require extended exposure windows and longer post-purchase tracking.
- Leverage clean rooms for privacy-compliant insights. Using clean room environments can ensure accurate matching across data sources and privacy compliant commingling of exposure data from different media partners to provide holistic insights. By securely analyzing cross-channel and cross-category data, clean rooms enable retailers to validate incremental ROAS, monitor total ROAS for in-flight optimization, and improve long-term audience segmentation strategies across many channels outside their O&O inventory.
- Understand and align on success: Retail Media is not a monolith. Too often it’s placed as a lower funnel tool when its benefits extend across the purchase cycle. Advertisers must recognize that Retail Media impact extends beyond immediate conversion. Branding levers included in Retail Media campaigns will increase awareness, positive perception, and long-term customer loyalty. Measuring short-term success and long-term value requires a blend of attribution methodologies. While exposure attribution remains crucial for understanding which touchpoints build awareness, purchase attribution needs to be viewed through a wider lens, considering the delayed impact on sales depending on where the consumer is in their purchase journey.
- Measure the halo effect. Retailers need to account for the “halo effect,” where successful advertising of certain UPCs positively influences sales of other products within the brand’s portfolio. Measuring this impact requires sophisticated analysis of different UPC groupings. Retailers can consider extending purchase attribution windows to capture the broader benefits of enhanced brand equity over time via customer long-term value analysis.
- Combine 1P and 3P data for market context. Combining first-party data from brands and retailers with third-party datasets enables retailers to see beyond their four walls. By incorporating total market impact, retailers evolve into formidable media partners. Advertisers can move beyond siloed metrics and assess overall audience penetration, competitive dynamics, and true incrementality. Reliable, trusted and consented third-party data can also open new revenue streams for RMNs by providing outcome-based targeting and measurement solutions for non-endemic advertisers- a category retailers must win to continue fueling RMN growth.
- Enable cross-category and channel aggregation: Agency holding companies and Retail Media aggregators play a critical role in harmonizing data across diverse platforms. Especially for smaller or regional retailers who are competing for ad-budgets with larger players. Retailers should consider participating in an aggregated system to generate more advertiser demand and conversion opportunities. To facilitate an even playing field and contribute to market benchmarks, retailers should build dynamic attribution models. That way they can be agile to their advertiser demands as well as provide results that can be comparable to other RMN offerings in an apples-to-apples fashion.
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