By Will Burghes, Head of Professional Services, DV Rockerbox
When you see a conversion in a report, you might think: My customer clicked on this ad and then immediately purchased my product or joined my list.
Sometimes this is true, and sometimes it isn't. In advertising, account for two types of conversions: post-click and post-view.
Post-click conversions occur when a user is served an ad, clicks it and then converts on your site within a set period. This period is usually called a lookback window (30 days is the most common, but it varies by channel and publisher).
Post-view conversions occur when a user is served an ad and doesn't click it. They later return to your site (via some other path) and convert within a set period.
To add more color here, let's use car shopping as an analogy.
Scenario One: You visit a car dealership without researching which car is best for you. So, you chat with a salesperson about your options and then make your purchase. Chatting with the salesperson leads to your purchase, not anything that came before it. This is similar to a post-click conversion, where your click is considered the main driver of your conversion.
Scenario Two: You research cars online for weeks. You then visit a car dealership, bypass talking to a salesperson (because you already know what you want) and make your purchase. This is similar to a post-view conversion, where prior exposure to a brand drives conversion.
Post-click measurement is more historically rooted in digital paid advertising because it was the first measurement people used for pay-per-click channels.
Also, post-click has been considered more valuable because a click is a clearer indicator of someone's interest. A customer had a question or wanted something, saw your ad and determined that your offering might be right for them. It's a straightforward conversion path that gives advertisers simple insight into what's working and what isn't, similar to last-touch attribution.
Lastly, it's easier to measure because it relies less on cookies and doesn't depend on an identity graph or other cross-device tracking.
Post-click appeals more to bottom-of-funnel search channel managers or direct-response advertisers. It doesn't account for top- or mid-funnel marketing efforts that promote brand awareness.
Also, as everyone has heard by now, "people don't click on ads." Industry reports indicate that less than 1% of the Internet population is even classified as "clickers." This implies that 99% of consumers don't click on ads at all.
Post-view conversions often give you a more complete picture of your marketing funnel.
Think about ads on the subway. No one can click on these; that doesn't mean they have no impact. Similarly, users who see an online ad may not click it because they don't immediately need your product or solution. This doesn't mean they won't remember your brand later, when they're in a better position to convert.
Determining how to value view-through conversions definitely isn't simple. Consider the following scenarios:
You can see now that post-view conversion attribution gets complicated and fuzzy pretty quickly, and that is a big reason machine learning multi-touch attribution (MTA) models are so valuable. When you can turn post-view conversion tracking from a "soft methodology" into something more concrete, you can assign value to your marketing touchpoints more accurately.
Accurate post-view conversions depend on the quality of the data feeding your measurement, which is why view-through integrations in DV Rockerbox™ with platforms like TikTok, Meta, Reddit, and Snapchat matter. These integrations let DV Rockerbox capture impression-level exposure data directly from the platforms themselves, rather than relying on modeled or estimated view-through figures. That means when someone sees an ad on one of these channels and later converts without clicking, Rockerbox can tie that conversion back to the correct exposure with far more precision.
This matters most for channels like TikTok, Reddit and Snapchat, where scroll-based, low-click-through browsing means a huge share of impact would otherwise be invisible in a post-click-only view. With direct view-through integrations, DV Rockerbox can fold this data into its MTA and marketing mix models (MMM), giving you a more complete and accurate picture of how these platforms contribute to your funnel, not just what a last-click report suggests.
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