Make Your Offline Sales Attribution Studies More Successful: Five Questions to Ask

Whether you are looking to grow category share or overall revenue, finding growth is one of the toughest challenges facing CPG marketers today. To effectively tackle this challenge, you need to know which campaign tactics are driving the most impact with your audience. If growth is the goal, understanding what’s driving campaign sales lift and return on ad spend (ROAS) is necessary for marketers to directly contribute to overall company objectives.

On the surface, many campaign measurement solutions seem comparable; however, given how truly hard it is to uncover growth in the industry, it’s worth digging into the details of your measurement solution to ensure that you are getting the most accurate and granular results without sacrificing speed to insight.  Below are five key questions to ask your measurement solution provider to ensure what you’re using will really help you achieve your growth objectives. 

  1. How much offline sales data does the provider have access to?  The amount of available frequent shopper data (FSP) matters because more data means more speed, granularity and accuracy. This can translate to a more accurate sales lift, better represented ROAS and deeper understanding of what’s working well to inform the actions you take during a campaign and for future ones. To break these down a bit further:
    1. Speed – The larger your FSP data set, in conjunction with product penetration, the better represented your brand and the smaller number of digital impressions required to provide an initial read of campaign results. Being able to understand campaign performance at week 5 of a campaign, for example, gives you the opportunity to shift impressions to the tactics that are performing best. If the data is less representative and you need wait additional weeks, or potentially only get to see results at the end of the campaign, you may have lost an opportunity to maximize your ROAS and sales lift.
    2. Granularity – Again, the larger the FSP data set, the lower the required impressions. When you are looking for insight and areas of campaigns to optimize toward, the deeper you can go, such as understanding how each of your three creative is performing within a specific publisher, the more granular the insights you have. This means you can take more precise action to drive the desired outcomes.
    3. Accuracy – One of the general principles of statistics is that the bigger, more relevant and more representative data set you start with for your analysis, the more accurate or confident your results are. This equates to more confidence in the decisions you are making based on the insights your study is providing.
  2. What sort of channel coverage is the FSP data set providing?  As much as 95 percent of all CPG purchases continue to take place in traditional brick and mortar outlets.  Given that, in order to maximize capturing all your offline sales, it’s critical that the data set your solution leverages covers as much of your distribution footprint as possible. Without comprehensive coverage, the solution you are using is going to have to estimate, adjust or potentially leave out sales that are occurring that your data set does not have access to.
  3. What variables and market conditions are being used in defining test and control groups?  You want to ensure your sales lift study is attributing lift only to the impact your campaign is having on purchase behavior.  The more variables outside of your campaign that are analyzed and controlled for, the better and more accurate your results. Are your current studies matching test and control groups at the household level, looking at similarities as it relates to demographics, category purchase behavior, product trips, the timing of purchase and seasonality?  From a retailer perspective, is your study accounting for assortment and promotional differences between retailers? Understanding and controlling for these variables is the best way to ensure you get the cleanest result.
  4. What methodology is used for online exposure data to be mapped to offline sales data?  Without getting too technical, there is the notion of doing a probabilistic match vs. a deterministic match.  Probabilistic means there is a strong chance that a particular exposure corresponds to a particular household based on the similarities between the values of some of the variables shared between the two entities.”  Deterministic means there is an absolute match between the values for the variables shared between these two entities, therefore it is certain this is a match.  If your study is employing a probabilistic matching process to match online exposures to households, it is possible that some false positives will be incorrectly counted as households exposed to the campaign.  This will likely reduce the impact or muddy the results of your campaign, as households are included whose purchase behavior was not truly influenced by the campaign.
  5. Does the provider have the industry expertise and demonstrated operational disciple to ensure consistent and accurate results? When it comes to leveraging a provider for sales lift measurement, it’s critical to make sure that you have complete confidence in your provider. This means working with a partner who ensures every campaign impression is being accounted for, with any exceptions being well understood and handled consistently, and that they operate transparently so results can be replicated, understood and trusted. Without a repeatable and sound operational process, it’s challenging to create the required level of partnership with your measurement provider and ensure your marketing programs will continue to flourish.

With all of its variables, campaign measurement can be extremely complex. However, if you are comfortable with your measurement provider’s answers to the five questions above, you are probably already on solid ground, and maximizing and optimizing the spend of your campaign dollars.

Do you have questions on how to make your campaigns more effective? Contact us at
SHARE: LinkedIn - Twitter - Facebook