How A/B testing supports in-store retail media networks

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In-store retail media networks are platforms that allow retailers to monetize their sites by selling advertising space to brands. These networks have become increasingly popular in recent years as retailers look for new ways to generate revenue and brands seek to target customers where they are already shopping. 

Protecting the customer experience

The impact of retail media networks on customer experience can vary depending on how they are implemented. On the one hand, these networks can provide customers with targeted advertising that is relevant to their interests, which can enhance their overall shopping experience. For example, if a customer is browsing for a new pair of running shoes, they may appreciate seeing ads for running gear or sports drinks that can help them achieve their fitness goals.

On the other hand, if these networks are poorly implemented, they can have a negative impact on customer experience. For example, if retailer bombards customers with too many ads or shows them ads for products that are irrelevant to their interests, this can be frustrating and lead to a poor experience. Additionally, if ads are placed in intrusive or distracting ways, this can also negatively impact the customer experience. 

Overall, the impact of retail media networks on customer experience will depend on how well they are implemented and whether they provide value to the customer. When used in a targeted, relevant, and non-intrusive way, these networks can enhance the shopping experience by providing customers with useful information about products and services that meet their needs. 

The most effective way to assess how customers are reacting to retail media networks is through A/B testing within stores. Testing a network against a representative control group can help ascertain what impact, specifically, a retail media network is having on everything from foot traffic to sales. It can measure if consumers are responding with a purchase or retracting from a purchase. Currently, many retailers only have the ability to track customer responses through loyalty programs or private label purchases. But A/B testing enables retailers to evaluate the responsiveness of every customer, getting a full picture of the retail media networks’ impacts. 

Obtaining reliable attribution data

Attribution in retail media networks refers to the process of determining the impact of advertising campaigns on consumer behavior, such as purchase decisions. Retail media networks, which are advertising platforms owned and operated by retailers, can make attribution difficult for several reasons.

Walled garden data

Retail media networks have access to a large amount of first-party data, but this data is often not shared with advertisers. As a result, advertisers may not have access to the complete picture of their advertising performance, which can make attribution difficult. Platforms such as MarketDial are impactful because they can act as a trusted third party for shared data between the advertiser and the retailer.

Multiple touchpoints

Consumers typically interact with multiple touchpoints before making a purchase, such as social media, search engines, email marketing, and in-store interactions. Retail media networks only capture a portion of these touchpoints, which can make it challenging to attribute a sale to a specific advertising campaign. Finding attribution software that can track omnichannel touchpoints, is essential to attribution. For example, being able to assess if an online advertisement led to increased foot traffic can inform marketing decisions. In-store A/B testing is a solid way to build this omnichannel bridge.

Limited attribution models

Many retail media networks use simplistic attribution models that do not account for the complexity of the customer journey, ignoring other touchpoints that may have contributed to the sale. One of the greatest values of A/B testing is that often one test paves the way for additional testing and insights, ensuring that every touch point can be explored. After it is learned that consumers responded well in store to a digital advertisement, for example, another test can build on this by examining if increased foot traffic then resulted in increased sales at a store, category, and product level. 

Offline sales

Retail media networks often struggle to test offline sales, making it difficult to measure the impact of online advertising on offline sales. Again, A/B testing is well-equipped to manage this. It can not only measure BOPIS (buy online pickup in store) and SFS (ship from store), it can also track how online marketing campaigns are impacting consumer behavior in physical stores. 

Lack of standards

There is currently no industry-wide standard for measuring attribution in retail media networks. This can make it difficult for advertisers to compare the effectiveness of different platforms and campaigns. Because A/B testing is backed by scientific rigor, it is well-poised to become the standard for measuring attribution. 

Attribution in retail media networks can be challenging due to the complexity of the customer journey and the limitations of current measurement techniques. However, by using in-store A/B testing as a bridge to promote increased data sharing between retailers and advertisers, it is now possible to gain a better understanding of the impact of advertising campaigns on both the product and the retailer. 

Increasing in-store ROI of retail media networks

Those who pay to advertise on retail media networks want to see a return on their investment. The challenge they face, however, is knowing the return on ad spend. When networks provide robust, tested attribution to the advertiser, it enables advertisers to optimize their spend towards channels with the highest return. And, advertisers are generally more willing to pay more for that ad spend because they are confident in returns that have been measured and validated through testing.  

Knowing which AdTech to invest in

Retail media networks use AdTech, or advertising technology, to reach and engage with their target audience through various digital channels. AdTech refers to the technology and tools that enable advertisers to buy, sell, and display ads across multiple platforms, including online and in-stores. 

Here are some ways retail media networks use AdTech:

Targeted advertising

AdTech enables retail media networks to target specific audiences based on demographics, location, interests, and behavior, allowing  retailers to reach the right audience with the right message at the right time, increasing the likelihood of conversion.

Programmatic advertising

Retail media networks use programmatic advertising to automate the ad-buying process and optimize campaigns in real-time. This means that ads are placed in front of the most relevant audiences and optimized for maximum performance.


Retail media networks use AdTech to retarget audiences who have previously shown interest in their products or services, enabling retailers to re-engage with potential customers and increase the likelihood of conversion.

AdTech plays a critical role in enabling in-store retail media networks to reach and engage with their target audience effectively. By leveraging AdTech tools and technologies, retailers can create more targeted, data-driven, and optimized campaigns that drive sales and revenue. It can be challenging to know which AdTech is best. A/B testing AdTech against a control group helps retailers to know how the tech is performing and which tech is producing the best results.

For a deeper dive into retail media networks, check out these resources:
Retail media networks and the MarketDial solution
The growing appeal of retail media networks
Advertising vehicles for in-store retail media networks

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