Unlike a weak phone signal that only causes a grainy sound, in growth marketing, it can mean the difference between a successful program or a massive cash bleed. As we move into an increasingly privacy-centric world, it’s even more necessary for businesses to nail the signal early on.
So what exactly is the “signal” in growth marketing? It can have many different meanings, but holistically speaking, it is the event data in our arsenal to help guide decisions. When it comes to paid acquisition, it is vital to optimize and return the correct event data to the payment channels. This is so that the targeting and bidding algorithms have the richest data to use.
I’ve seen startups spend thousands of dollars inefficiently as a result of not having an optimal signal in their paid acquisition campaigns. I have also spent millions on companies like Postmates refining our signal to the best possible state. I’d like every startup to avoid the painful mistake of not having this set up correctly, instead of making the most of every major ad dollar.
The selection
When starting out, it may seem obvious to optimize towards a north star metric, such as a purchase. If the spend is very minimal, that could mean that the conversion volume will be low in all campaigns. On the other hand, if the optimization event is set to a top of the funnel event, such as a landing page view, the signal strength can be very weak. The reason the force may be weak is due to the return of a low intention event as successful to the paid channels. By marking a landing page view as successful, payment channels like Facebook will continue to find users who are similar to these lower-propensity users who are converting.
Let’s take an example of a health and wellness app with the goal of boosting memberships to your training program. They are just beginning to explore paid acquisition and spending $ 5,000 per week on Facebook. Here’s a look at your events in the funnel, weekly volume, and cost per event:
In the example above, we can see that there is a significant volume of visits to the landing page. As we go down the streamlined flow, there is less volume as users leave the funnel. Almost everyone’s instinct would be to optimize for the landing page view, because there is so much data, or the sign-up event, because it is the strongest. I would say (after extensive testing on multiple ad accounts) that neither of these events would be the right choice. With landing page views as an optimization event, users have an outrageously low propensity as the conversion rate from landing page view to subscription is 0.61%.
The correct event to optimize here would be to sign up or start the test because they have enough volume and are strong signals of a user converting to the north star (subscription) metric. Looking at the conversion rate between signup and signup, it’s a much healthier 10.21%, compared to 0.61% for the landing page view.
I am always a huge advocate of trying all events as there can definitely be big surprises in what may work best for you. When testing events, make sure there is a baseline of statistics being followed for decision making. Also, I think it’s great practice to regularly test events early on because conversion rates can change as other channel variables are adjusted.
Flow settings
In certain cases, the current events that are set up are not optimal for paid acquisition campaigns. I’ve seen this happen frequently with startups that have long time windows between conversion events. Take a startup like Thumbtack, which provides a marketplace for vendors that can help with home repairs. After someone signs up for your app, the user can apply but not hire someone for a few weeks. In this case, making stream adjustments could improve the signal and the data it collects from users.
One solution Thumbtack could implement to gather a stronger signal would be to add another step between applying and hiring someone. This could potentially be a survey with propensity check questions that could ask how soon the user needs help or how important their project is from a 1 to 10.
After accumulating the data, if there is a high correlation between the survey responses and someone starting their project, we can begin to explore optimization for that event.
In the example above, we see that users who responded with “9” have a conversion probability of 7.66%. So this should be the event we optimize for. Artificially adding steps that qualify users in a longer flow can help steer optimization in the right direction.
Signal enhancement
Let’s imagine you have the most ideal stream that captures large volumes of event signal without much delay in your optimization event. That is still far from perfect. There are countless solutions that can be implemented to further improve the signal.
For Facebook specifically, there are connections like CAPI that can be integrated to return data in a more accurate way. CAPI is a method of returning web events from server to server instead of relying on cookies and the Facebook pixel. This helps mitigate browsers blocking cookies or users who can delete their web history. This is just one example. I’m not going to go through all the channels, but each one has its own solution to help improve the signal of the event that is returned to it.
IOS 14 signal
This wouldn’t be a column written in 2021 without mentioning iOS 14 and the strategies that can be leveraged for this growing segment of users. I’ve written another article on specific iOS-14 tactics, but I’ll cover it here on a broad level. If the north star metric event (i.e. purchase) can be triggered within 24 hours of the initial app launch, then that’s golden.
This would bring in large volumes of high intent data that would not be at the mercy of the 24 hour SKAD event timer. For most companies this may sound like a lofty goal, so the goal should be to have an event fire within 24 hours which is an indicator of high probability that someone will complete their pole star metric. Think about what events happen in the flow that eventually lead someone to buy. Maybe someone adding a payment method happens within 24 hours and historically has a 90% conversion rate for someone who buys. An “add payment information” event would be a great conversion event to use in this case. The landscape of iOS 14 is constantly changing, but this should apply for the immediate future.
Incrementality and stay ahead
As a general rule of thumb, incrementality checks should be performed consistently in growth marketing. It gives an important read on whether ad dollars are attracting users who would not have converted if they hadn’t seen an ad.
When comparing optimization events, this rule still applies. Make sure that costs per action is not the only metric used as a measure of success, but rather that you use the incremental increase on each conversion event as the ultimate KPI. In this piece, I detail how to run lean incrementality tests without swarms of data scientists.
So how do you stay ahead and continue to move the needle in your growth marketing campaigns? First of all, constantly question the events you are optimizing for. And second, leave no stone unturned.
If you are using the same optimization event forever, it will be a disservice to your campaign’s performance potential. By experimenting with flow changes and running tests on new events, you will be well ahead of the curve. As you iterate through the flow, think about user behavior and events from the user’s perspective. What flow events, if aggregated, would correlate to a high-propensity conversion segment?
