👇 Heartcore Consumer Insights
Welcome to the 95th edition of Heartcore Consumer Insights. Curated with 🖤 every two weeks by the Heartcore Team.
If you missed the past newsletters, you can catch up here. Now, let’s dive in!
It's no secret that investors - public or private - are no longer rewarding growth at all costs. In public markets, the index of unprofitable tech companies has fallen twice as much as Nasdaq. Now CAC, burn multiple and profitability are king.
For a decade we've built ad-centric growth engines that wasted $19 out of every $20. You can't just take out a scissor and cut your way to profitable growth.
Growing at all costs is fundamentally different than growing efficiently. Companies need to change 4 things:
Shift to program-level CAC: to drive profitability, you have to understand CAC at the program level, not overall. Build real-time infrastructure to see conversion and CAC for expensive programs like ads. Calculate CAC quarterly for smaller programs. Cut/optimize constantly. You can have a finite number of "influencer" programs that accelerate (but don't generate) revenue. e.g. content that nurtures deals. Use a revenue attribution model for these programs since program-level CAC won't give the full picture. Fold the cost into the overall CAC.
Invest in conversion, not just demand: there are 2 growth levers. Demand helps you get in front of the right buyers. CPC = $$$. Conversion gets them to buy your product. CPC = 0. At Gusto's marketing, ~100% of spending went into generating demand (ads, content, PR). CAC >20 months. Gusto redirected ~50% of the budget to conversion and analytics. CAC <12 months & ARR grew way faster. Don't just cut. Reallocate budget to efficiency drivers.
Launch new programs iteratively: all new programs require optimization to become profitable. Most never do. Fund experimentation liberally, but in small amounts. Define a gate to get additional funding in 3 months. Cut programs that don't hit the target.
Design an operating cadence: create quarterly goals across GTM teams, and turn those goals into weekly targets. Design a system of weekly and quarterly meetings and dashboards to track progress and course correct. Bring finance, sales, and marketing leaders together weekly. CFOs & CEOs should partner with the CMO to understand their growth levers, cash guzzlers & efficiency drivers.
Many product managers & founders are intimidated by retention. The graphs can be difficult to read, the definitions vary for each product and business type, and the SQL is complex. At the same time, retention is both the most important and the least understood metric at most companies.
A short guide on how to measure retention:
Step 1: define “active”: a fundamental variable in calculating retention for most products is “active users.” But it’s not obvious what “active” means. Below are the most common events used to define “active” across companies. (a) visit (you will overcount users, most likely having a challenge with unauthenticated and not registered users), (b) session starts (you’ll possibly overcount users by pulling in unauthenticated IDs), (c) Login/app opens (you will need a way to exclude new users with their first app open event for cohorted retention), (d) Web page or screen views (most likely will pull in all user types - dormant, lapsers, new users - into one bucket and over-report both DAU and retention), (e) Main user action (e.g. item view, search, log an exercise, transaction, etc - easy to miss active users who don’t do the main activity you expect but keep using the app cf adjacent users case).
Most companies use logins or app opens as main events for the “active users” definition. Using main user action as the activity event is recommended.
Step 2: pick your retention type: the next step in calculating retention is setting your timeline. The method you choose will significantly affect your results.
(a) X-day retention: X-day (also known as N-day or bounded) tells you the percentage of users who come back on a specific day. For example, for all users who join, what percentage return to your app on exactly day 14:
(b) Unbounded retention: Unbounded retention tells you how many of your users got back on a specific day or later. For example, for all new users who joined on a specific day, what percentage of users are using the product after 14 days (and not necessarily on day 14). If your goal is to match retention with your user churn, this is the way to go.
So which approach should you use? Both are correct, yet both will return completely different retention data:
Overall, a rule of thumb in analytics is that if your product is SaaS, you are likely to be tied to a specific time-bound (paid subscription length, trial length, etc.). Because of that, it’s recommended to follow X-day retention. If you are not in SaaS but in a B2C or consumer transactional or social business, then you can be more flexible and adopt unbounded retention.
The full post contains a very useful guide & practical on how to report retention (from BI applications vs. SQL) - check it out if interested!
Last thing to keep in mind: given that retention includes so many elements of activity, it’s not the right metric to use for weekly reporting or as a baseline for an A/B test. Too often product analytics teams evaluate experimentation against retention and wonder why the increase in user activity doesn’t lead to a change in retention. Because the activity is only one of the components of retention. Retention (like revenue) is the output metric. You should monitor it but not strictly utilize it as a goal for testing or campaigning.
How Monzo grew to 1 million customers with ~zero marketing budget
Teens, Social Media, and Technology 2022 Report
Virtual reality - coming soon?
What’s a good monthly renewal rate for in-app subscriptions?
The Importance of Whale Watching
The three types of “good” onboarding friction
🇪🇺 Notable European early-stage Consumer rounds
🇺🇸 Notable US early-stage Consumer rounds
🔭 Notable later stage Consumer rounds
🍭 Notable Consumer Exits
Heartcore Consumer Insights is a weekly newsletter covering notable consumer rounds and exits and top content in the B2C space.