App marketers are at a critical crossroad in how they grow their business and reach their targets. They can either pay higher prices to acquire app users or they can invest more effort in retaining high-value customers. It’s a massive shift to the latter as more app marketers harness data-informed approaches that emphasize “quality over quantity.” Paying higher CPIs is no longer off-limits if the data powering predictive models can prove the results will be off the charts.
Predicting the *true* value of users turns up the pressure on app marketers to double-down on data-informed approaches, such as look-alike targeting, to make sure they bid successfully for the audiences that will convert at the highest levels. Brand marketers have a slightly different (and less ambitious) agenda. As brand marketers don’t seek to drive in-app purchases or monetize players through reward video they don’t have to fish for ‘whales.’ But they do have to net audiences of individuals that are aligned with their target demographic.
In both cases, marketers need data to determine the value of the audience and transparency to place their bid. “Performance marketers who cut their teeth marketing mobile apps and games are smart about data and how to predict the value of their users. On the other hand, brand marketers, especially consumer brands, are just beginning to grasp the ‘how’ and ‘why’ of in-app engagement,” observes Pepe Agell, Chief Strategy Officer at Chartboost, leading in-app growth and ad monetization platform. He gives the inside track on both as he maps out the capabilities you need in your growth stack to seize opportunities and drive action.
Amplify impact and audience through programmatic
In-app advertising is just ‘business as usual’ for data-savvy gaming app marketers, who wrote the book on targeting and activating audiences sure to make purchases or give attention to gain rewards. Brand marketers are advancing up to the plate, but “many still don’t get what in-app advertising means or can deliver,” Pepe says. It’s the quiet before the storm, but all that will change as a ‘perfect storm’ of conditions come together to blow in-app out of the park. In fact, the latest research puts in-app marketing on a massive growth trajectory—pegged to grow at a CAGR of +40% by 2023.
For many marketers—across a broad range of app categories and consumer brands—the focus on activating (not just acquiring) audiences takes data-driven marketing into new territory. To help marketers navigate this new terrain, Chartboost has likewise expanded its horizons, striking out in new directions to help advertisers reach highly valuable and highly engaged audiences at scale, Pepe explains. Those services include a marketplace for mobile games companies to find players (which got a boost when Chartboost acquired capabilities to connect mobile games influencers with mobile game developers) and a programmatic offering that will let brands into ads across the 300,000+ titles it works with.
“It’s all coming together, and this is where we get excited,” Pepe says. At one level, the programmatic exchange continues to grow through partnerships with DSPs, allowing Chartboost to expand and diversify the kinds of advertisers it works with to monetize mobile games and apps. At the other spectrum, it’s all about tapping into brands. “Brands know they are still spending too much money on offline channels, channels where they are aren’t able to measure and estimate the real impact of their campaigns and spend,” he explains. That’s what marketers can achieve on mobile—provided they have the right mindset and models.
3 Data-Driven Strategies to Boost Audience Engagement
#1 Go beyond install and click-through rates
In a crowded app market, compelling creatives are key to amplify brand voice and boost performance. But what has been a design-driven approach has to become a data-driven discipline—and fast. “App marketers have to start perceiving ad creatives as a means to achieve a goal, namely a tool to grab the attention of the valuable user and very quickly convert that user into taking an action—booking a trip, buying an item or purchasing in-app.” Data about creatives—how they perform in your campaign and in other similar campaigns is pure gold. It starts with the click-through rate and the install rate. “But smart app marketers harness data, in the form of BI and tools, to see how the competition is conveying its message and—even better—how and where they are spending to get it in front of users.”
#2 Enrich your data to make quick predictions
Performance marketers are all about the return. The end-game is all about how much value players bring and the purchases they make. Here, Pepe says, it’s about having data—in the form of second-party and third-party data—to predict with high confidence the likelihood that a user will become a paying user. “Performance marketers have to be fast—and accurate—at predicting because users are coming in and they need to assign a CPI that will allow them to plan and profit.” Brand marketers look at their audiences differently. It’s not about converting; it’s about consumer connection and getting the message to the audience that will genuinely appreciate it. For both marketers, it’s down to data. “You have milliseconds to make a call on the value of a user and the value you’re going to assign that user.”
In practice, the bidder has to make a decision based on a device ID. “This requires strong models that do look-alikes quickly because, if you’ve seen that device before, then you have a much better idea of just how valuable that user is,” Pepe explains. Put another way, marketers across all categories need built-in prediction models powered by data. More is better, he continues, and it pays to buy data from second- and third-party providers.
#3 Treasure your first party data and don’t be a big spender… unless it pays
Your first-party data is the prize that will tell you more about the users who convert at a certain level. But who is your audience really? What devices do they use? Where and how are they converting? “Everything and every data point that allows you to target with granularity will also allow you to bid more accurately,” Pepe explains. “If you have a transportation app, for example, you want to target the user who converts quickly to take the first ride. You want data that will nurture your prediction model to be able to determine the likelihood that a user with a device ID you don’t recognize will convert at a level that justifies a $20 bid over, say, $10.”
Put simply, marketers don’t just need a firm grasp of all the data that will give them deeper insights into their most valuable users – they need clear visibility into the data around the bids. “So, you have to understand the user first and you have to know when you price that user, what your competition is bidding,” Pepe says. Unfortunately, it’s not so straightforward.
Looking towards the future: mediation and the need for bid-level data
For performance and brand marketers alike, there’s no shortage of pressure to double down on data-informed approaches — whether the end goal is to drive a lower CPI, retain the most profitable users, or get the brand in front of the right audiences.
The challenge, according to Pepe, is that “the element of mediation in the monetization stack” can muddy the waters. “The days of mediation layers or in-house mediation are gone, and there is a conflict of interest that takes the transparency and the control from the publisher.” It’s why Chartboost is “actively building a unified, fair and transparent auction through our SDK so that you don’t need a waterfall allocation for your demand partners,” Pepe explains. “Stay tuned…”