View-Through Conversion Tracking

There’s a commonly held belief among Meta advertisers that view-through conversions aren’t truly incremental to your business. However, you can’t click on a TV ad, and those conversions have proven impactful for businesses for over 70 years! By ignoring advertising viewers and focusing only on clickers, you might be missing out on a key demographic: younger users. These younger age groups convert more without clicking, leading to inaccurate attribution. It’s not a small difference. Click-based measurement undervalues younger age groups twice as much as other age groups. This is part of why Meta introduced a new engaged-view through attribution lookback. The other reason is the different user behavior with Reels ads compared to Feed ads. A recent Meta study of 15 A/B tests showed that advertisers who included Engaged-View in their attribution settings saw an average 3% lower cost-per-result compared to using Click-Through only or Click-Through + View-Through, with 95% confidence. Instead of assuming which efforts are incremental to your business, it's better to dispel long-held convictions through testing. Advertisers that ran 15 experiments in a year saw 30% higher ad performance.

Apple Search Ads Just Got More Powerful – But at What Cost? Apple is introducing view-through attribution (VTA) for Apple Search Ads. This means that even if a user doesn’t click on an ad but merely sees it and later downloads the app, the conversion can now be attributed to that ad. For premium brands in India that rely on iPhone-heavy, high-LTV audiences, this change could have major implications: 1. Inflated Attribution? With Apple already claiming a significant share of app marketers' budgets post-ATT, this shift may further consolidate ad dollars into the Apple ecosystem. 2. Higher CAC, Lower Incrementality? VTA tends to favor last-touch platforms, potentially making it harder to assess the true incrementality of installs. 3.More Budget for ASA? Brands that target affluent iPhone users—like fintech, luxury fashion, and premium subscriptions—may need to rethink their ASA strategy to leverage this change while ensuring measurement accuracy. Apple’s proprietary Ads Attribution API will be the measurement source—meaning limited transparency into cross-channel impact. The big question: Will brands see true value, or just a shift in how conversions are attributed? Would love to hear how fellow marketers are thinking about this! Will this change your Apple Search Ads budget in 2025? #AppleSearchAds #MobileMarketing #Growth #PerformanceMarketing #iOSMarketing

If you are running programmatic Ads for B2B - Read this My client was facing significant challenges with programmatic advertising for B2B services and software. Despite extensive use of digital channels like Google Display Network, Google Paid Search, LinkedIn, and Bing Paid Search—which show clear user engagement and click-through conversions—programmatic ads result in high bounce rates close to 99%, with little to no real user engagement or conversions. ➡️ Possible Causes: ◾ Bot Traffic: A high volume of traffic from identical IP addresses, with uniform engagement patterns, suggests bot activity. ◾ Ineffective Targeting: Cookie-based targeting in programmatic platforms may not accurately reach intended audiences. ◾ Misalignment of Metrics: Traditional engagement metrics (click-through rate, time on site, etc.) may not effectively measure the impact of programmatic ads, which some liken to billboard advertising. ➡️Solution: ✔️ Scroll Tracking: We use tools like Google Tag Manager (GTM) to implement scroll tracking, firing a pixel once a visitor scrolls through a significant portion of the page (e.g., 50%). This provides a better indicator of engagement beyond mere page views. ✔️View-Through Conversions: Shift focus to view-through conversions, which track if users who saw your ad but didn’t immediately click on it, convert later. This acknowledges the billboard-like nature of programmatic ads. (In this case, we can also consider metrics like brand recall and search lift, which reflect the indirect benefits of visibility and brand exposure.) ✔️Report Suspicions: Address the suspected bot activity by reporting it to your Demand-Side Platform (DSP) or Account-Based Marketing (ABM) platform provider. Request investigations and refunds for fraudulent activity. ✔️Use Advanced Filters: Implement IP blocking and more sophisticated fraud detection measures to improve the quality of traffic. ✔️Cross-Channel Retargeting: Use insights from more successful channels to retarget engaged users through programmatic ads. ✔️Unified Analytics: Analyze data across all platforms to better understand user paths and optimize ad strategies accordingly. ➡️ Results: ◾ Better Traffic Quality ◾ More Realistic Goals ◾ Higher ROI P.S. Programmatic ads are great for boosting brand awareness, even if they don't always get direct clicks. By adjusting your strategy and expectations, you can maximize their effectiveness and see better results.

Many marketers still avoid CTV. Too expensive. Attribution is messy. Here's why that's a mistake: The reality? View through conversions aren't a bug. They're a feature. I'll be honest. I used to hate view-through conversions. I was that marketer demanding click attribution for every dollar. If I couldn't trace it directly, it didn't count. I'd look at CTV campaigns and dismiss them because the attribution wasn't "clean enough." Then we actually started listening to students. They'd tell us about seeing our ads on Hulu while watching TV with their parents. Then they'd research us later on their phone. Apply days later on their laptop. That's when it clicked. I wasn't measuring wrong conversions. I was ignoring real ones. Students don't see your ad on their TV and immediately apply. They research. They compare. They talk to family. Then they convert days or weeks later. That's the actual student journey. But too many marketing leaders want perfect attribution. I was guilty of this. They want every dollar tracked to a click. So they stick with Google and Meta, ignoring where prospective students actually spend their time. Here's what we've learned running CTV campaigns: 1. Brand awareness compounds over time 2. View-through data tells the full story 3. Multi-touch attribution reveals true impact 4. Cost per completed application drops Stop demanding perfect attribution. Start meeting students where they are. Are you still avoiding CTV because attribution isn't clean?

A colleague of mine asked a great question recently: “Our display ads show solid view-through conversions, but how do I know if we’re spending too much or too little? Some of these conversions would happen anyway.” It’s a question I get a lot — and one that cuts right to the heart of modern measurement. Here’s what I told him: 1. View-through conversions ≠ incrementality. Just because someone saw your ad and later bought doesn’t mean the ad *caused* the sale. Many of those users might have converted anyway. So before increasing spend, it’s critical to know: *What’s the true lift?* 2. Incrementality testing is essential. The best marketers run geo holdouts, sophisticated A/B tests, or randomly selected matched market experiments. These give you a clean read on whether your display ads are actually *driving* results — or just taking credit. 3. Leading indicators matter too. One sophisticated client I have uses AI to track marketing metrics as leading indicators of effectiveness: increases in brand measures, branded search activity, CLV shifts among exposed audiences. These signals tell you if you’re moving in the right direction *before* the conversions show up. 4. Ask better questions, not just measure more. Don’t settle for surface-level metrics. Align your measurement to business impact. That means understanding how different channels contribute to awareness, consideration, and — most importantly — profitable growth. Efficiency metrics like CTR or ROAS don’t tell the whole story. The smartest brands go deeper. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

Seeing ROAS dip in your vCPM campaigns? Chances are, performance hasn’t actually changed. The measurement has. This was a big topic in our weekly account manager meeting yesterday as we are starting to see the shift across our accounts. Earlier this month, Amazon tightened how view-through conversions are credited for ads that appear in the Amazon Store. Fewer ads get credit for the same sale, attribution windows are shorter, and reporting is more conservative by default. So, Sponsored Brands, Sponsored Display (vCPM), and DSP store placements may suddenly look worse on paper, even though shopper behavior hasn’t shifted. I see this as Amazon dialing back cannibalization and over-crediting. For advertisers, re-baseline your metrics, focus on the full-funnel story, and leverage “all views” metrics for context. Smart teams will see this as an opportunity to optimize strategy, not chase upper funnel ROAS.

🤔 Are you attributing and measuring correctly? In the modern view-centric world, distributing conversions and budgets based on clicks is simply not enough! If we compare 18-24 age group vs. all, they are 2.4x more likely to purchase an advertised product without clicking after viewing the ad. Using click-based attribution and optimisation (optimise your delivery on after-click metrics) is efficiently steering your campaigns away from being delivered towards younger audiences. Not always your goal, when you try to tap into those younger demographics at social media. And at placements that are typically more view-through, where users spend the most time, actually. Don't you want to be where your potential customers are? Using click-based attribution and budget steering is also efficiently under-valuing the real impact of your investments, making it seem like you delivered much worse performance than what is the reality. How to solve this: - Move towards incrementality measurement and mindset, measure the true impact of your ads through experiments, holdout groups, conversion lift studies. - Use view-through for optimisation of your campaigns. - Add view-through reporting window to your overview to see the "bigger picture", even if you will not accept is as the source of truth. #socialmedia #paidsocial #marketing #advertising #attribution

Should you care about view-through conversions? There’s plenty of controversy within advertising circles about view-through conversions. Some advertisers embrace them and others ignore them. Meta’s default attribution setting is 7-day click and 1-day view. That means that unless you changed it, conversion reporting is based on anyone who clicked your ad and converted within seven days or viewed your ad without clicking and converted within a day. The stance against view-through is that it can inflate results. While in a perfect world, your ad may have contributed to someone coming to your website later that day and converting, it also includes people who may not have even seen your ad (though it was shown). My opinion: Embrace view-through conversions, but with context. They add to the overall picture of how your ads contributed to your results. If you run video ads, prioritize engaged-view over 1-day view. These can at least isolate higher-valued view-through conversions from people who watched at least 10 seconds of your video before converting later that day. This isn't a matter of believing that view-through conversions are the same as click-through conversions. They're not. But 1-day click isn’t the same as 7-day click or 28-day click either. Each is viewed differently. If all of your reported conversions are view-through, then yeah. That's a problem and you can basically ignore them. But otherwise, it’s okay to use view-through conversions as long as you don’t hide how they happened. Use that knowledge that these additional conversions, while they can't be verified via other tracking, may have contributed to your results. What are your thoughts on view-through conversions?