Addressing Convenience Store Fragmentation, Data’s Emerging Role
Ten years ago, Path to Purchase Institute sibling brand Convenience Store News published an article titled “The Year of Retail Fragmentation,” and in it wrote, “As we close out the year and look to 2015, it is evident that retail has never been more fragmented. Today’s consumer has many options and is shopping at more places than ever before. … When you add urbanization, a growing aging population with a preference for smaller formats, and the rise of single and smaller households, it’s no wonder that even big-box retailers are working hard to get more ‘convenient’ by focusing on smaller and express formats.”
While so much has changed in the industry, somehow it can still feel like not much has changed, as a bulk of that article still feels relevant today.
In convenience retail, fragmentation means tens of thousands of independent stores, making it harder for brand advertisers to reach regional and loyal customer bases consistently or track data across locations.
The Fragmented C-Store Landscape
Data on the 2024 Convenience Industry Store Count from the National Association of Convenience Stores (NACS) and NielsenIQ found that there are 152,396 c-store locations in the U.S., a 1.5% increase from the 2023 store count, with most of these sites operated by small businesses. The data also showed that around 63% of c-store sites (or 96,156 locations) operate between one and 10 stores, with the vast majority being single-store owners. Rather than a few large chains, the sector is largely made up of many small, independent operators.
The second largest cohort is companies with more than 500 locations. This segment includes fewer than 20 businesses. This fragmentation is a crucial consideration for brands and advertisers seeking to reach local markets.
How C-Stores & Solution Providers Are Addressing Fragmentation
For CPG brands and advertisers, that data emphasizes the importance of targeting these smaller-scale operators and the challenges in doing so. To address this, c-store operators and industry entities are focusing on three main strategies:
- Retail media networks (RMNs): Smaller c-stores can participate in digital advertising ecosystems similar to those of larger retailers, though it comes with challenges (e.g., budget limitations & the need for specialized technology). RMNs allow CPGs to segment and target ads to shoppers visiting c-store locations, extending beyond traditional in-store promotions to digital and omnichannel touchpoints.
- Localized and hyper-targeted campaigns: CPG brands are increasingly employing hyper-targeted campaigns that resonate with local shoppers’ preferences. Given the high frequency of c-store visits, localized promotions and incentives can be more effective. By leveraging data analytics, brands can craft region-specific or store-specific promotions that appeal to the habits of local consumers.
- Data partnerships and aggregation: Major players in retail media and data services, like Rippl (the media network powered by purchase data and audience platform Bridg), are partnering with technology and software providers to help aggregate SKU-level data across thousands of independent stores. As a result, this provides CPGs with precise, “deterministic” data on individual purchase behaviors.
A Closer Look at Rippl’s Approach
Announced first to P2PI, Rippl recently partnered with National Retail Solutions (NRS), a point-of-sale (POS) hardware and software provider primarily to the c-store market, and another software provider in the sector, PDI Technologies. Both companies have access to a lot of c-store shopper data through their retailer partnerships, many of which Rippl also works with. The goal of the partnership is to offer advertisers access to deterministic purchaser and SKU-level data (not based on surveys or panels) across more than 50,000 independent c-stores, about a third of all c-stores in the U.S.
As a result, Rippl now has more than a hundred million individual shopper profiles with deterministic purchase data on individuals that have generally been hard to reach for the advertising community.
Additionally, Rippl is helping many of its retailer partners unlock the scale of some of the bigger retailer media networks/capabilities. This helps its c-store partners better understand their customers and work better with their CPG partners.
P2PI recently interviewed Bridg’s Jared Luskin, head of partnerships, and Steve Dietch, head of business development and marketing, about this gap in the market and how it’s addressing this fragmentation through strategic, data-driven partnerships. We also spoke with PDI Technologies’ Brian Jefferson, senior vice president, business development, and Jeff Hassman, vice president and general manager, data services, as well as NRS’ Suzy Silliman, SVP, data strategy and sales, and Brandon Thurber, VP, data sales.
“Now, the advertising community has access to individual SKU-level purchase data and enriching attributes — essentially data fidelity — that didn't exist before,” Dietch said. “[Advertisers] now have a view into product-level behavior that gives insight into frequency, spend, customer lifetime value, competitive dynamics, campaign performance and segmentation and cohort analysis.”
Rippl takes POS data directly from its clients. In this context, Rippl is taking data from NRS and PDI that they've sourced from more than 50,000 c-stores across the U.S. and running it across Bridg’s cookieless identity resolution capabilities to identify, understand and engage in-store customers that aren’t part of loyalty or rewards programs. Rippl also combines that data with third-party data, such as demographics, socioeconomic and lifestyle data.
“Rippl is powered by Bridg's superpower, which is our ability to identify an individual behind a transaction based on the payment information that they've provided,” Dietch added.
“By being part of Rippl’s data/media network, we provide larger brands and advertisers with a unique channel to engage consumers through trusted local retailers,” NRS’ Brandon Thurber said. “This partnership creates a bridge, enabling big brands to tap into the loyalty and reach of locally shopped independent stores while supporting the sustainable growth of these essential businesses.”
How This Approach Will Impact the Highly Fragmented C-Store Market
While some large c-store chains do have retail media networks, Luskin said, “these partnerships really allow us to aggregate up that really underserved, underdeveloped portion of the market to allow CPGs who sell a lot of their products in these small-format stores to be able to use insights and analytics to understand those shoppers better, to be able to target those shoppers [through activations] and then measure the results.”
“From our perspective, it is a big scale-play,” he added. “It's consolidating that incredibly fragmented market so that if you are a CPG company, you don't have to try to source that data from a number of different partners. You can access that data all in one place.”
“C-store shoppers have generally been excluded from media audiences due to lack of reliable data,” NRS’ Suzy Silliman said. “Through Rippl, advertisers can now have a more complete and comprehensive deterministic syndicated and custom audiences by the inclusion of the c-store partner data, including the typically underrepresented urban shopper segment, which is represented through the NRS data.”
How Deterministic SKU-Level Data Moves the Needle
Deterministic SKU-level data “takes the guesswork out of the process and improves efficiency and effectiveness of the campaigns,” Silliman said. “And with the availability of this data also for measurement, it provides a level of transparency that supports reliable ROI calculations.
It allows advertisers to personalize and go “well beyond any of the limited loyalty programs,” Dietch said. “If you're only limited to loyalty, then you've got a problem of fully understanding and being able to reach other people.”
Dietch said that what Rippl and its partners are bringing is a massive scalable data set that’s updated daily and can help advertisers personalize based on actual purchase behavior. The data can also provide measurements, whether it be a return on ad spend or where available incrementality, which “is the holy grail of measurement from a campaign perspective."
In most other retail media networks, advertisers are limited by access to the data and the fidelity (i.e., panel, survey, loyalty-only data, and the non-standardization of the measurement piece as it goes.
Additionally, when asked what some of the most useful insights on c-store shoppers are, Silliman said “With trips, spending and units up year-over-year, these consumers demonstrate strong support for local independents. Interestingly, brand rankings and item preferences often differ here from national trends, giving advertisers a unique opportunity to connect with highly engaged, community-focused customers.”
From PDI’s perspective, “the SKU-level data provided by PDI empowers advertisers to target segments of consumers with a higher degree of certainty and confidence,” Jefferson said. “Basket composition in convenience is exceptionally powerful, allowing advertisers to market and promote the right product combinations and pricing that will help to drive their desired sales outcomes.”
In terms of impacting the future of retail media in the c-store sector, Jefferson said, “This collaboration enables independently owned and operated convenience stores and smaller chains to access advertising dollars by connecting them to a broader network of retailers. It adds scale that these businesses traditionally don’t have on their own.”
Hassman noted, “In addition to allowing advertisers to target customers based on their purchase behavior, this collaboration allows advertisers to see behavior changes within the same cohort of consumers, providing direct attribution to their marketing efforts.”
“The ability to link targetable consumer profiles with actual purchase data in open loop systems is a gamechanger,” Hassman added. “It allows advertisers to meet consumers with targeted, relevant messages and link those efforts back to changes in purchasing behavior across retail channels.”