Incrementality in retail media refers to the sales that would not have happened without the influence of your advertising campaign. The holidays are prime time for brands to gain new customers, capitalizing on the increased traffic both in-store and online. In 2024, even though we’re facing a shorter shopping period and ongoing inflation challenges, there is still an enormous opportunity: a report by the NRF (National Retail Federation) predicts 2024 holiday sales will grow between 2.5% and 3.5%, equating to a spending spree of $980 billion in the US market alone.
Whether you’re promoting products this holiday season or aiming to capitalize on the heightened traffic, Black Friday through Cyber Monday is the time to make sure your advertising dollars are pinned on growth. Measuring incrementality in retail media and understanding the most effective channels and ad types for incremental lift are key to:
- Creating high growth campaigns—finding your unique formula of channels, ads, products and audiences—that will boost incremental sales.
- Reducing wasted spend by not serving ads to shoppers who would have bought your product anyway.
In this article, we will cover:
- Why traditional advertising measurements such as ROAS and attribution model
ling fall short when measuring the true impact of your retail media advertising campaigns. - The complexity and pitfalls in retail media incrementality measurement and the technologies that are helping to simplify it.
- Best practices for measuring incrementality and gaining competitive advantage during peak shopping events.
Attribution and ROAS vs incrementality in retail media measurement
Advertising KPIs like ROAS (achieved simply by dividing sales by the cost of the retail media campaign) will give you a quick indication of how your holiday ad campaigns are performing but it doesn’t show incremental lift in retail media.
Attribution modeling is more sophisticated and might include multi-touch attribution (MTA), which assigns value across different touchpoints, or last-click or first-touch models which attribute sales solely to the first or last engagement. But it doesn’t help you answer that all-important question: “Would I have made those sales without my advertising campaign?”
Why ROAS and attribution modeling fall short when measuring retail media effectiveness
Advertising ROI can be measured in various ways including ROAS and attribution modelling. ROAS can be measured simply and fairly quickly, and it allows you to make immediate adjustments mid-campaign. MTA provides deeper insights but it takes longer to gather the necessary data. Neither ROAS nor attribution modeling will give you the most important measure if your goal is growth—incremental lift.
Five pitfalls to avoid when measuring holiday campaigns
#1 Serving premium ads to the wrong shoppers
Designing a campaign focused on high ROAS can lead you to spend more on serving ads to shoppers who are already customers, not to customers who are new-to-brand or would not have bought your product without ad engagement. Peak sales events can amplify the problem because traffic is high and advertising costs are premium.
#2 Focusing on efficiency rather than effectiveness
ROI is primarily an efficiency measure; it reflects how well you’ve managed your campaign but not how effective your media strategy is. Your ROI will increase when you spend less and decrease as you spend more. You can see why ROI—without understanding incremental sales impact—could lead to false-positive results and limit growth.
#3 Measuring advertising effectiveness without context
Measurements like ROAS and attribution modeling do not consider wider factors that might influence sales such as brand equity, stock availability, price, buy box status, search rank, reviews or price. Being able to blend data from digital shelf performance, retailer platforms and advertising tools will help you segment those true, ad-driven purchases from those shoppers who have been influenced in other ways.
#4 Ignoring the influence of one channel on another
Attribution modeling and ROAS are often used as a way of measuring a single channel’s performance. Even though attribution is calculated differently by each retailer, you can still benchmark the performance of one channel vs the next and create an aggregated score. However, this method doesn’t help you see how channels are working together, and these are really useful insights for omnichannel advertisers.
#5 Beware the limitations of attribution windows
When measuring attribution over time, using historical data, retail media networks offer attribution data in a predefined window of time, usually 28 or 14 days. If your sales cycle is longer, your attribution analysis will not capture all the touchpoints.
Why measuring retail media effectiveness is challenging
Being able to measure incrementality in retail media is key to understanding the true impact of your holiday advertising campaigns, however, this kind of complex, contextual analysis of advertising effectiveness isn’t easy:
- Properly attributing influence on sales means blending data that goes beyond advertising exposure and into other territories like product availability, price, or merchandising. This can be ‘noisy’ work unless you have tools to process this data and present it in a meaningful way.
- No two retailers offer the same set of signals when it comes to first-party data; arriving at a true channel comparison or aggregated performance score is fraught with complexities. Measuring incrementality through cross-channel testing can be challenging, as is understanding the nuances of cross-channel influence.
- Shoppers behave differently on different channels, largely determined by each retailer’s interface, search algorithm, taxonomy, promotions, and many other variables.
- While attribution modeling gives credit to different touchpoints, it doesn’t tell you the impact of advertising on incremental sales and growth unless you can segregate your customers into those who have only been served an ad and those who may have been influenced by other factors. If you can successfully identify this group, then you can begin to build your next growth campaign based on which ads they engaged with, where and when.
How Pacvue’s Incrementality Console helps you measure incrementality in retail media
Achieving incrementality measurement in retail media is fast becoming the advertising sector’s Holy Grail. You can gain enormous advantages when you’ve cracked how to:
- Measure the impact of ads in relation to growth
- Optimize your budget by focusing on ad types and channels that drive incremental lift.
- Enhance the effectiveness of your growth campaign by continually improving the multi-media mix by channel.
Why Pacvue’s approach to complex incrementality measurement is offering advertisers truer insights in a more accessible way
If measuring incrementality was easy, we’d have cracked it years ago. It’s not easy and no one has come up with the perfect solution, but there are some tools that will help you get closer to the insights you need than others. There are a number of incrementality tools and methodologies to choose from although many use fixed formulas or accommodate only a limited number of data sources. Other tools need you to do a lot of data manipulation to extract the clear picture you need before making expensive budget commitments. Pacvue’s Incrementality Console addresses those shortfalls and offers:
- A reliable incrementality measure
- Unified cross-channel insights
- A single source of truth that ties together signals from many sources into a single ecosystem.
How Pacvue’s Incrementality Console works
With Pacvue’s Incrementality Console, you can add data from ecommerce, 1st party retailers, media management systems, offline commerce, and many more data sources.
Pacvue analyzes this data using our propriety, advanced machine learning technology, designed by Pacvue’s own experts with all their combined years of experience in retail media measurement.
The algorithm runs many times before confidently delivering data you can rely on. It takes factors like seasonality or promotions into consideration so that you can budget and plan for Black Friday, Cyber Monday, Prime Day and other tentpole events with added confidence.
These insights are visualized in one dashboard that measures incrementality in retail media and also allows you to drill down by brand, ad type, channel, or campaign tag. The ability to compare ROAS and iROAS in a single view helps you clearly see which ad types, which time ranges and which channels are contributing most to incremental sales.
Conclusion: Why incrementality measurement in retail media is an ongoing challenge, but one you can’t ignore
There is no perfect retail media incrementality measurement model for advertisers operating in an omnichannel world (yet), but some tools will help you get closer than others. Pinpointing exactly why shoppers bought your product is not straightforward, but being able to isolate purchases that could only have been influenced by your ad campaign (then analysing why, how, when and where the sale happened), gives you an enormous advantage. The more accurately you can measure incrementality, the more profitable your marketing will be.
Pacvue is a platform for advertisers (brands and agencies) to manage their digital commerce and retail media strategies. The Pacvue Incrementality Console and iROAS Dashboard is an integral part of the Pacvue platform, offering customers a unique advantage when it comes to optimizing retail media budgets for incremental lift. If you’d like to find out more, we’d be happy to show you how it works.
