Cookieless Attribution for SaaS: Measuring Long Sales Cycles Without Cookies
You absolutely can achieve SaaS attribution without cookies. Stop relying on broken attribution models and embrace causal inference.
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By Joris van Huët, Founder & CEOUpdated 2 min read
For SaaS businesses with long sales cycles, traditional cookie-based tracking is a disaster.
The Cookiepocalypse Cometh for SaaS
Cookies are crumbling, and SaaS marketers are scrambling. The deprecation of third-party cookies isn't some distant threat; it's reality. Apple's ITP, Firefox's ETP, and Google's Privacy Sandbox are all dismantling the old way of tracking. This hits SaaS companies especially hard because:
- Long Sales Cycles: B2B SaaS sales often take weeks or months. Cookies expire long before a deal closes.
- First-touch or last-touch attribution is laughably inaccurate.
- Offline Conversions: A significant portion of SaaS conversions happen offline via demos, calls, and meetings. Cookies can't track these interactions.
Traditional attribution vendors offer band-aid solutions: probabilistic modeling (guessing), data clean rooms (expensive data silos), and server-side tracking (complex and fragile). These approaches fail because they still rely on the flawed premise of associating clicks with outcomes rather than understanding why those outcomes happened.
Why Traditional Attribution Fails SaaS
Attribution models, by their very nature, are flawed. They attempt to assign credit to specific touchpoints based on arbitrary rules. This approach fundamentally misunderstands the complexity of human behavior. Consider these issues:
- Spurious Correlations: Just because someone clicked an ad before converting doesn't mean the ad caused the conversion. Correlation is not causation.
- Lack of Incrementality: Traditional attribution can't tell you whether a conversion would have happened anyway, even without the touchpoint being "attributed".
- Channel Silos: Attribution models typically operate within channel silos, ignoring the cross-channel effects that are important in SaaS.
For SaaS, where sales cycles stretch across weeks or months and involve multiple decision-makers, these flaws are amplified.
How Does Cookieless Attribution Work for SaaS?
Causal inference offers a better way. Instead of assigning credit based on clicks, it focuses on understanding the causal impact of each marketing activity on incremental sales.
- Refinement: Armed with this knowledge, you can sharpen your marketing spend, improve your messaging, and personalize your customer experience to drive more sales.
Sources and Further Reading
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Go deeper: Incrementality testing, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Attribution ModelAn Attribution Model defines how credit for conversions is assigned to marketing touchpoints. It dictates how marketing channels receive credit for sales.
- Causal InferenceCausal inference is the set of methods for estimating how much an outcome changes because of a cause, rather than alongside it. It works by comparing what happened with an estimate of what would have happened without the cause.
- Customer ExperienceCustomer Experience is the overall perception customers form from all interactions with a company.
- IncrementalityIncrementality is the part of an outcome, such as orders or revenue, that a marketing activity caused: the extra results compared with what would have happened without it. It is a causal effect, not the number of conversions credited to a channel.
- Last-Touch AttributionLast-Touch Attribution: A single-touch attribution model that gives 100% of the credit for a conversion to the last marketing touchpoint a customer interacted with.
- Spurious CorrelationSpurious Correlation is a statistical relationship between variables that are not causally linked. It occurs due to coincidence or an unobserved third factor.
- Third-Party CookieThird-Party Cookie is a cookie set by a domain other than the one a user currently visits. These cookies track users across sites for advertising.