Ad Tech Industry Faces Measurement Challenges
B2B buying decisions are shifting to channels that ad tech cannot track, making measurement infrastructure less effective. This shift matters because it affects the industry's ability to accurately attribute conversions.
Original reporting · adexchanger.com
Original: “B2B Buying Decisions Are Moving Where Ad Tech Can’t See”
Read “B2B Buying Decisions Are Moving Where Ad Tech Can’t See” at AdExchanger →
How this was written. The 5:45 Ops Desk wrote this article with a language model from AdExchanger’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from AdExchanger’s report
- The ad tech industry's measurement infrastructure is struggling to keep up with changes in B2B buying behavior
- B2B buyers are increasingly using channels that are not visible to ad tech, making measurement more difficult
- Incrementality testing is a potential solution to the measurement gap, but it has been slow to be adopted
- The use of AI in B2B buying is expected to further exacerbate the measurement gap
- The industry needs to develop a new measurement paradigm that focuses on decisions rather than impressions
The ad tech industry has developed a sophisticated system to measure and track online interactions, allowing for precise attribution of conversions. However, this system has a significant blind spot: it cannot measure influence. As a result, the industry is struggling to keep up with changes in B2B buying behavior.
B2B buyers are increasingly using channels that are not visible to ad tech, such as AI-assisted research and private peer conversations. This means that even if a buyer is influenced by an ad, the measurement system may not be able to track it. For example, a buyer may ask an AI assistant for a vendor recommendation and never visit a website, making it impossible for ad tech to measure the impact of the ad.
The current measurement system is based on tracking impressions, clicks, and conversions. However, this system is not equipped to handle the complex and often invisible nature of B2B buying decisions. As a result, the industry is overcrediting visible touch points and undercrediting invisible ones, leading to a biased picture of what is working.
Incrementality testing is a potential solution to this problem, as it measures the actual impact of marketing activity on behavior. However, the industry has been slow to adopt this approach, in part because it often produces lower numbers than traditional attribution models. This is because incrementality testing asks whether a marketing activity actually changed behavior, rather than simply attributing conversions to the activity.
The use of AI in B2B buying is expected to further exacerbate the measurement gap. As AI assistants become more prevalent, buyers will be able to research and evaluate vendors without ever interacting with ad tech. This will make it even more difficult for the industry to measure the impact of marketing activity.
To address this challenge, the industry needs to develop a new measurement paradigm that focuses on decisions rather than impressions. This could involve using self-reported attribution, incrementality testing, and pipeline and revenue metrics to get a more complete picture of the buyer's journey.
Ultimately, the industry needs to prioritize solving the problem of measuring decisions, rather than just impressions. This will require a fundamental shift in how the industry approaches measurement, but it is necessary to ensure that marketing activity is effective and accountable. This article is based on reporting by AdExchanger.
Questions and answers
What is the main challenge facing the ad tech industry's measurement infrastructure?
The main challenge is that B2B buyers are increasingly using channels that are not visible to ad tech, making it difficult to measure the impact of marketing activity.
What is incrementality testing and how can it help address the measurement gap?
Incrementality testing measures the actual impact of marketing activity on behavior, by asking whether the activity changed behavior that would not have happened otherwise.
How can the industry develop a new measurement paradigm that focuses on decisions rather than impressions?
The industry can use self-reported attribution, incrementality testing, and pipeline and revenue metrics to get a more complete picture of the buyer's journey, and prioritize solving the problem of measuring decisions.
