The surprising effects of paid marketing on organic installs
Paid online advertising campaigns account for 30% of total installs, according to Adjust figures. However, modern marketers dedicate 100% of their time, and headspace, to figuring out how to pick up more paid traffic. Instead, Moshi Blum, GM of Adjust’s Israeli office, suggests, marketers should think more about the relationship organic app installs have to paid marketing and the importance of organics overall.
“Sometimes, as a UA manager, you're only focused on paid marketing. This doesn’t make sense because you're not considering the organic impact your paid campaigns have,” Moshi says. To remedy this, Moshi highlights three factors that marketers need to consider as they seek to understand (and calculate) how campaigns impact organic results. As Moshi points out, knowing the real effects that paid advertising campaigns have on organic app installs can help marketers take their performance much further.
In this article you’ll learn about K-Factor, how your paid campaigns can boost app store optimization, and the role multi-touch attribution plays in understanding how all of these ideas come together.
Seeing the positives
In a competitive space brimming with apps, marketers can’t leave success to chance. It’s possible in rare cases to make your mark without paid promotion, but you don’t want to bet your business on it. Outliers exist but, for the most part, it’s a pay-to-play market, and “marketers have to perform paid activities,” Moshi says. The situation is harder for newcomers without a solid brand in a market where users increasingly search for what they want, and not to browse. To raise visibility and build a brand in 2020, marketers need to conduct paid campaigns.
Paid campaigns are built by maximizing lifetime value (LTV) against customer acquisition cost (CAC). “That's the essential marketing calculation, and the most important factor,” Moshi says, “but it takes time to get to a ROAS positive campaign.” Because of this, he adds, key stakeholders could begin to challenge the value of paid campaigns.
However, once campaigns start, they drive an uptick in organic which leads to other benefits and bonuses. In fact, paid activity is proven to provide an uptick in organic performance and influences app store rankings. Let’s understand how paid online advertising can increase organic before covering two ways to maximize organic reach.
Quantify paid influence with organic uplift
Paid campaigns undoubtedly affect organic installs, but many don’t take into account their influence. But it is possible to quantify how influential your paid campaigns are on organic uplift, thanks to an equation known as K-Factor. The K-Factor, you can calculate your campaign effects on users who don’t download via advertising, assessing whether your creatives push users onto the store without any direct action from advertisers.
Adjust data shows that K-Factor affects one in three apps, though apps that do experience K-Factor received 45 organic installs for every 100 paid, on average. In one case, the rate was 227 organic installs for a single paid conversion.
Without taking K-Factor into consideration, app marketers could be ignoring the impact of this formula and underplaying its influence. To find out how to calculate K-Factor, read our blog here.
Boosting App Store optimization with paid marketing
Paid marketing is an App Store optimization (ASO) driver. Downloads are a known ranking factor — and the more traffic your listing gets, the higher the number of downloads. This creates a positive feedback loop: the higher you rank, the more likely you are to get visits that lead to conversions.
We spoke to James Bott, CEO & Co-founder of The ASO Co (Part of Jellyfish Group), to learn more. “We definitely see a direct link between paid media and both organic installs, and organic keyword rankings. Paid can have both a positive and negative effect on organic traffic, so it’s important that you deploy the correct strategy.”
Interestingly, one platform James sees both positive and negative effects on is Apple Search Ads. By aligning paid keyword bid strategies with organic metadata optimizations, he sees two things happen consistently:
- Organic installs go up as a whole, in some cases 20-30%
- Improved organic search ranks on high-volume keywords
Both instances can have a huge and positive impact on a business. However, the negative impact you may see is with organic cannibalization. He says, “As a paid ad takes up 55% of the screen and organic 45%, it's easy to buy traffic you may have otherwise already received.”
In addition to this, James adds that install trajectory as a ranking factor when trying to optimize your organic search position. “This correlation is very clear, but we also see negative impacts if the wrong type of media is being purchased and if fraud is prevalent.” In his view, fraud reduces organic traffic and generates negative reviews in the app stores. But that’s not all. “It can also create a major long term negative impact on your ability to rank for certain search terms and grow organically thanks to high uninstall rates,” he explains.
It is therefore imperative that you monitor both organic and paid installs when running any form of paid media.
Moving towards multi-touch
Understanding paid uplift requires marketers to get granular with their data, especially as the number of channels proliferates. Adjust allows you to see how users interact with your campaigns before the install. If you have a hunch that your campaigns lead to organic conversions, you can add specific parameters to your callbacks that reveal what the users did before the eventual install.
By combining this data with other information, such as geolocation, or carrier, you can pinpoint the areas where your campaigns overlap (such as out-of-home), and optimize your campaigns to produce more organic uplift over time, Moshi says. “This approach gives you much deeper insight and can lead to major returns for your time.”
Learn more about Multi-Touch Attribution, and get best practices to help move toward a more comprehensive view of user behavior, here.
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