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💎 Growth Gems #66 - Paid Acquisition, ASA and Retention
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This week I’m sharing gems on onboarding and retention experiments, Apple Search Ads Cannibalization and paid acquisition post-ATT for subscription apps. These insights come from Ally Tubis, Annie Kim, Josh Stephens, Simon Thillay, Thomas Petit and Lisa Kennelly.
🥇 TOP GEM OF THE WEEK
Retention/Onboarding: metrics, testing
App Growth Summit NYC was a few weeks ago, and it was great to catch up with folks in the industry!
But of course I took some time to mine some gems as well, and I’m sharing a few below.
💎 Figure out the “all star metrics” you can use as proxies for subscription health and your business goals.
💎 Often times when testing, what you think will happen doesn’t happen. It’s useful to have a framework to guide your decision once the test is over.
💎 Data is important but qualitative insights are important too. Always gather feedback from users on how they feel when going through your onboarding journey. At Stash, they’ve created a customer journey scorecard to keep track of this.
💎 You need to track cohorts all the way through. There’s always a tendency to call the test as soon as you have statistical significance. But sometimes this statistical significance is just based on the conversion metric, not on the quality of users or how users retain.
💎 “The onboarding funnel is a story”: you need to look beyond the drop and understand the full picture and the actual problem. What is the customer thinking?
⛏️ Going Deeper: Josh mentioned several times the importance of “Time to value” for their product, which is also about getting into the mindset of the customer.
💎 The onboarding experience starts with the ad impression/click. You need to build processes and rituals to connect the teams together so everyone collaborates on the entire funnel (a more holistic approach).
Paid Acquisition: ASA cannibalization, post-ATT approach
The ASO conference 2022 is around the corner!
Seeing the announcements reminded me of the method Simon Thillay (Head of ASO at AppTweak) shared last year in his session Measuring the Costs of Cannibalization in Apple Search Ads.
💎 The difference between cannibalized and protected lies in the question: “if an Apple Search Ads impression goes to a competitor rather than my app, which app does the user choose to download?”. It’s all about comparing conversion rates.
💎 The conversion rate of your competitors for your brand terms is most likely somewhere between your ASA conversion rate for your competitors’ keywords (e.g. 5.36%) and your ASA conversion rate for your brand terms (e.g. 16.27%). The closer your competitor is from you (look at your organic keyword ranking), the higher that conversion rate should be. Full example below.
💎 Deduce the cost per defended install by using the volume of impressions you are currently getting when bidding for your brand terms, the hypothetical competitor CVRs and your ad spend. See table below.
⛏️ Going Deeper: this clearly highlights the power of having a strong brand, as it will make it harder for your competitors to convert well on your brand terms.
💎 To define your bids when targeting competitors on their brand terms, revert the model assumptions to determine who might be the most vulnerable target (i.e. the apps you’re the closest to in terms of CVR).
Shamanth Rao (Founder at RocketShip HQ) put together a great cast to discuss Winning Strategies for Subscription Apps in 2022: Thomas Petit (Growth Consultant), Lisa Kennelly (CMO at Fishbrain), Carolin Rohte (Head of Performance Marketing at Yazio) and Hichem Belouizdad (Senior Account Executive at Liftoff/Vungle).
A few gems below on performance marketing, the main topic for this panel.
💎 The pre-ATT playbook was to have acquisition mainly driven by paid and to have aggressive monetization/paywalls. Now, more apps are questioning if there are other ways to do things (examples of apps “rebalancing” the model: AllTrails, Strava, Duolingo, etc.). Each app needs to find its own model.
⛏️ Going Deeper: Thomas also shared that you shouldn’t try to copy best practices from others, because the playbook is being rewritten and nobody really knows what works. Don’t assume anything, focus on what your customers want and test it for yourself.
Some inspiration can’t hurt however, and in Growth Gems #56 I included a few examples shared by Eric Crowley (Executive Director at GP Bullhound)👇
💎 Post-ATT, Fishbrain has been looking more at partnerships. They want to find who is upstream in the customer journey so that they can be early in the conversation.
💎 Flyers with QR Codes might be a better opportunity now. They’ve made a comeback and also make tracking easier.
💎 Two problems with SKAN postbacks:
It’s a sample, not the entirety since it’s only for iOS 15 users
You receive campaign ids that you can’t match specifically, especially with some networks like Facebook running sub campaigns in the background.
⛏️ Going Deeper: if you want to dive more into SKAN, I recommend reading the gems by Piyush Mishra (Growth Marketing Lead at Product Madness) from "SKAN: a playbook for today and the future” shared in Growth Gems #60.
💎 Media mix modeling and incrementality tools are a complement, and only advanced teams can afford to have this complement. If you’re operating at a low level of spend, don’t get into this rabbit hole for now.
💎 Having web acquisition allows for channel diversification. The users you are reaching might not be the same either.
💎 One approach for web campaigns is to remove all possible friction and focus on raising users’ intent before they get to the app store page, instead of trying to get them to sign up or pay directly on the web. It is challenging because the onboarding might need to be completely different depending on the app.
💎 Adding a free trial can be a way to get more signal (than with direct purchase) for acquisition.
⛏️ Going Deeper: in Growth Gems #52 I shared a gem by Andy where he explained how Phiture uses the AIC framework to help with “signal testing” (identifying the signals of conversion and optimizing for them)
💎 Pre-ATT, there were channels that were bringing a lot of “late converters''. Often, these late converters retained more, invited their friends more and in general had a higher value. These networks probably still bring the same conversions, but post-ATT, we have a blind spot when it comes to measuring these.
And before I leave, a quote from Mike Brooks on the evolution of their UA strategy post-ATT:
“Bigger bets, fewer partners” - Mike Brooks (SVP of Revenue at WeatherBug)
See you next time. Stay savvy!