The impact of ad impressions in the app ecosystem remains largely as a blackbox subjecting advertisers to estimation and guesswork as to the results of their advertising budgets. The evolution of View-through Attribution (VTA) allows for a more equitable and representative credit-allocating system by more accurately assigning the ad impressions that drove users towards installs.
Every mobile marketer now knows that the funnel does not end at app install. Retention and continuous re-engagement are recognized as essential components of achieving high customer lifetime value (LTV). Beyond its ability to provide accurate data on the early stages of the customer journey, VTA is also proving itself to be an invaluable tool for tracking post-install events.
With a renewed focus on the seamless blending of user acquisition and re-engagement campaigns, VTA plays a crucial role in holistically interpreting the customer journey. And yet some negative assumptions about VTA, from cannibalization to double conversions, persist.
Read on to learn about the merit of those assumptions and how VTA is critical in understanding the user lifecycle from the very first interaction with an app to converting into a valuable customer.
View-through Attribution Versus Click-through Attribution
Click-through attribution (CTA) works as follows:
- User is shown an ad
- User clicks on the ad
- User makes a conversion within the conversion window (normally around 7 days)
View-through attribution works on a much narrower timeframe:
- User is shown an ad
- User makes a conversion within the conversion window (normally around one day)
While CTA focuses on clicks as the sole touch point, enabling VTA expands this into both impressions and clicks. This gives marketers added visibility and a holistic view of their marketing campaigns’ impact on users.
Installs Do Not Occur in a Vacuum
When running programmatic campaigns, VTA is an important metric. Without it, advertisers are overly reliant on CTA and (often falsely) assume that campaign sources with low click-through rate (CTR) are bad performers. With VTA enabled, marketers are one step closer to better understanding the ROAS of all campaign sources and optimise based on an additional user touch point towards real value.
VTA has the ability to show how impressions have contributed to a users’ conversion. Contemporary advertising campaigns have a variety of touchpoints that influence conversion; the ad a user clicks on is not deserving of all the credit. Solely crediting a single touchpoint like that not only results in unfair distribution of revenue but risks skewing optimization efforts or even blacklisting channels that successfully (albeit indirectly) bring conversions.
Combining CTA, VTA and Organics – Can Conversions Be Reported Twice?
The answer is no.
Any Mobile Measurement Partners (MMPs) worth their salt have deduplication features in place that will prevent the double attribution of a single conversion. These protective measures stop advertisers from paying twice for the same conversion.
Moreover, when it comes to attribution a click will always be stronger than an impression (even when taking VTA conversions into consideration). In other words, view-through conversions happen only when there is no click after viewing an ad.
A single conversion can only be allocated in one of the following three methods:
- CTA – A conversion attributed to click-through attribution
- VTA – A conversion attributed to view-through attribution
- Organic – A conversion attributed to unpaid marketing activity
- Partner A delivers an ad impression. Partner B delivers a subsequent ad impression. The user only clicks on Partner A’s ad. Then the user converts.
In this scenario, the conversion is attributed only to Partner A as CTA is based on the last click attribution model.
- Partner A delivers an ad impression. Partner B delivers a subsequent ad impression. The user only clicks on Partner B’s ad. Then the user converts.
In this scenario, the conversion is attributed only to Partner B as CTA.
- Partner A delivers an ad impression. Partner B delivers a subsequent ad impression. The user clicks on neither of their ads. The user converts anyway (within one day of viewing Partner B’s ad).
In this scenario, without VTA, the conversion would be evaluated as organic (in spite of any influence from the unclicked ads). With VTA, the conversion would be attributed to Partner B as their impression served as the last ad impression seen by the user before converting.
Does View-through Attribution Cannibalize Organic Conversions? Far From It
An organic user can be defined as a user who converted to a customer without being influenced by any marketing activities. While there is difference in opinion on the existence of organic users (fuelled by vague market definitions and a strong digital marketing presence of brands), it’s important for advertisers to understand that they don’t necessarily have to pay for every new user acquired. Controls and guidelines in terms of priority of attribution as well as lookback windows help determine paid vs organic users.
The most common concern about VTA is whether it ‘steals’ organic conversions. While there are different views on this topic, when applied correctly VTA can help advertisers understand that some of the conversions they used to see as organic are in fact not organic at all. When ads are shown to users, their effectiveness is calculated by the combination of timing, interaction and intent.
Lookback windows are intended to prevent the overestimation of the influence of an ad. If lookback windows for VTA are too long then they can indeed cannibalize organic conversions. This is why lookback windows should not be longer than 24 hours. For many ads, the lookback window should be even shorter – it depends on a variety of factors, including the client’s brand awareness and the type of creative. One of the first steps before launching a campaign involves working out the optimal lookback window.
An organic conversion cannot happen if a user has never seen or heard about an app. If VTA is not taken into consideration, then there will be a high number of conversions credited as organic that have actually been unknowingly influenced by paid campaigns. This can lead advertisers to blacklist effective channels and placements because they are not driving CTA conversions even though they are driving VTA conversions.
Discerning an accurate lookback window goes a long way to clearing up these blurred lines. Once done, VTA becomes an excellent means by which advertisers can allocate budgets more efficiently.
View-through Attribution and iOS 14
While there is a lot of uncertainty about running view-through attribution campaigns on iOS 14, Probabilistic attribution at an aggregated level may become a formidable alternative to the SKAdNetwork, provided Mobile Measurement Partners receive server-side impressions and clicks from ad networks. Apple is expected to further develop their SKAdNetwork solution and include VTA in the next version, so a more realistic solution can be on the horizon.
Learning Through View-through Attribution
The greatest advantage of view-through attribution is its utility in identifying valuable campaign information. Clicking on an ad is not necessarily the decisive ad interaction that users take before installing an ad or engaging with it post-install. View-through tracking reveals when users see ads and the actions they took afterwards; maximizing the efficiency of advertising efforts requires an understanding of these campaign aspects. Marketers in today’s advanced digital ecosystem should rely on multiple touchpoints and use all available data in order to ensure efficiencies of marketing spends.
VTA provides insights into the incremental impact of impressions, allowing advertisers to analyze the customer journey with a more holistic view. VTA is the first step in building multi-touch attribution models that allow for advanced targeting of users at different stages in the decision-making process (which as mentioned, includes the post-install stages).
Analysis of view-through attribution can result in a treasure trove of data that enables more informed decision making for marketing strategies, channel selection, and budget allocation. While it has the ability to blur the lines between organic and paid-for advertising, its added value at both ends of the customer journey vastly outweighs this lack of absolute clarity.
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