You manage to acquire millions of users. Amazing.
999,999 of them don’t make it through the funnel or churn. Now that’s not so amazing.
That’s an extreme example but it shows why optimizing your growth funnel is crucial during the early stages. What does a general growth funnel look like? Although this will vary between startups, at the core, it consists of three major pillars: acquisition, activation, and retention. I won’t go through each of these pillars in depth (there are many columns on this); however, I will be going through some key optimization concepts.
It’s a dance when optimizing a growth funnel, but let’s dive into how to make it the most methodical and strategic dance.
As a startup matures and robust user-level data starts to flow in, understanding which acquisition sources yield the highest propensity for users should be a priority. A bonus would be to measure the most incremental sources as well.
There should be a defined cadence between cross-functional teams (i.e., product, growth, and data) to continuously question the best sources of traffic.
While leading fleet growth at Postmates, I quickly learned to become numb to remarkable upper-funnel metrics. Below is an example of how we prioritized budget allocation with down-funnel metrics:
Even though Indeed has the worst CPL of the channel grouping, it nets the highest revenue-producing fleet drivers who are the most active in Y1.
As traffic sources begin to increase and the spend scale rises, testing for incrementality is the next level up from solely measuring ROAS or LTV. In other words, understanding how many users would have been acquired had a specific traffic source been turned off. How incremental is Facebook or a particular lifecycle marketing campaign?
If there’s one takeaway, it’s to double down on the highest LTV and incremental segments as rapidly as possible.
While there are three major pillars in the growth funnel, hundreds of segments are potentially sitting in each bucket. In the acquisition pillar, users may be bucketed by the channels they came through, while in activation, users may be bucketed by the number of days they’ve been waiting to get started.
It’s imperative to slice (or cohort) users into their respective buckets because it opens the opportunity for unique targeting and messaging.
Below are just a few examples to get your mind thinking about user buckets for each pillar of the growth funnel:
After slicing users into their respective buckets, it’s time to start thinking about how to message each user. At the foundational level, varied messaging by user slice is the largest lever for moving users through a funnel. To put things into perspective, would you email a user who just came into the funnel the same as someone who has lapsed for 90 days? Probably not.
A few tactics for moving users through the funnel:
Of all the tactics above, nothing works better than continuous and well-crafted messaging to drive desired actions from your users. It often takes B2B sales teams multiple attempts at calling, texting, and follow-ups until a deal closes. The same holds true for B2C startups – i.e., create email drip campaigns and lean on the side of over-communication with your users.
Whether devising a strategy for your email campaigns or retargeting on Meta, always test various styles of messaging. Below is a great framework that I’ve used to define the messaging:
A perfect example of this is the fleet funnel we had at Postmates, which would require people to submit their driver’s license and SSN. We had dedicated email drip campaigns for the people who dropped off at the SSN step to alleviate their concerns of entering sensitive information.
There will always be low-hanging fruit, whether it’s changing a subject line or simply adding emojis to retargeting ad copy. It starts with the basics of acquiring the right users, bucketing them the right way, and pushing every step of the funnel. As test throughput increases, the level of detail on metrics should increase to continue moving the needle. Out of all the metrics, my favorite at Coinbase was the incremental lift for each campaign as it helped us accurately understand how many users acted because of a specific email.
Every successful startup that I have been at or advised has implemented B.I. (business intelligence) tools such as Amplitude or Mixpanel to find these low-hanging fruit or even the bigger swings. It empowers growth and product teams to create dashboards filled with cohorts to pinpoint and optimize funnel drop-off points.
With a possible recession on the horizon, it further highlights how an inefficient growth funnel can crush a business. You must optimize as if you need to squeeze every single user through the funnel because of a short runway, then you’ll be much further along in the competition.
How does a founder implement a growth framework to scale to their first million dollars in revenue?