Unlike a weak phone signal, which produces a totally grainy sound, in growth marketing, it can mean the difference between a successful program or a massive cash bleed. As we move towards an increasingly privacy-focused world, it becomes even more important for companies to signal that as soon as possible.
So what exactly is a “signal” in growth marketing? This can have many different meanings, but overall speaking, it is the event data we have in our arsenal to help us make decisions. When it comes to paid receipts, it is important to optimize and send back the correct event data for paid 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 optimal signals in their paid acquisition campaigns. I’ve also spent millions at companies like Postmates refining our signals to the best possible condition. I want every startup to avoid the painful mistake of not setting it up correctly, instead making the most of every significant advertising dollar.
When starting out, optimizing toward a north-star metric like buying may seem obvious. If the spend is too low, it could mean that the amount of conversions will be low across all campaigns. On the other hand, if the optimization event is set to a top-of-funnel event such as a landing page view, the signal strength can be very weak. The reason the strength may be weakening is because a low-intent event is considered successful for paid channels. By marking a landing page view as successful, paid channels like Facebook will continue to find users who are similar to these low-trend users who are converting.
Let’s take the example of a health-and-wellness app that aims to promote subscriptions to their coaching program. They are just starting to search for paid acquisitions and are spending $5,000 a week on Facebook. Below is a look at their events, weekly volume and cost per event in the funnel:
In the above example, we can see that there is a significant amount of landing page views. as we go down simplified Flow is less volume as users leave the funnel. Almost everyone will have a tendency to optimize for either landing page views, because there’s a lot of data, or subscription events, because that’s the most robust. I would argue (after extensive testing across multiple advertising accounts) that neither of these phenomena would be true. With landing page views as an optimization phenomenon, users tend to have very low subscription conversion rates from landing page views to 0.61%.
The right events to optimize for here would be either a sign up or trial start because they have a substantial volume and a strong indication of a user converting to the answer-star metric (subscriptions). Looking at the conversion rate between sign up and subscribe, this is a healthy 10.21% compared to 0.61% from landing page views.
I’m a big proponent of always testing all events, as there can be big surprises, of course, which one works best for you. When testing events, ensure that a stat-sig baseline is being followed for decision making. Additionally, I think it is a good practice to regularly test events early as conversion rates can change when other channel variables are adjusted.
In some cases, the current events set up are not optimal for paid acquisition campaigns. I’ve seen this happen quite often with startups that have a long window of time between conversion events. Take a startup like Thumbtack, which offers a marketplace of providers who can help with home repairs. After someone signs up in their app, a user can request but not hire someone until a few weeks later. In this case, making flow adjustments can potentially improve the signals and data you collect from users.
One solution that Thumbtack could implement to collect a strong signal would be to add one more step between the request being made and someone being hired. This could potentially be a survey with trend checking questions asking how quickly the user needs help or how important their project is from 1-10.
After submitting the data, if there is a high correlation between survey answers and someone starting their project, we can begin to explore adaptations to that event.
In the above example, we see that users who responded with a “9” have a 7.66% chance of being converted. Therefore, it must be the event for which we adapt. By artificially adding steps that qualify users into longer flows, optimization can help steer targeting in the right direction.
Let’s imagine that you have the most ideal flow that captures a large amount of event signal without any delay in your optimization event. It is still far from perfect. There are myriad solutions that can be implemented to further amplify the signal.
For Facebook in particular, there are connections like CAPI that can be integrated to pass data more accurately. CAPI is a way to send web events back server-to-server instead of relying on cookies and the Facebook pixel. This helps reduce browsers that block cookies or users who may delete their web history. This is just one example. I won’t run through all the channels, but each has its own solution to help pass the event signal back.
iOS 14 Signals
This wouldn’t be a column written in 2021 without a mention of iOS 14 and the strategies this growing user segment can take advantage of. I’ve written another piece about the iOS-14-specific strategy, but I’ll cover it more extensively here. If the North-Star metric (ie, purchase) event can be triggered within 24 hours of the initial app launch, that’s golden.
This would bring in vast amounts of high-intent data that wouldn’t be at the mercy of the SKAD 24-hour event timer. For most companies, this may sound like an lofty goal, so the goal should be to have an event within 24 hours which is a high-probability indicator of someone meeting your north-star metric. Think about what events happen in the flow that ultimately lead to a person buying. Someone adding a payment method might be in within 24 hours, and historically the person making the purchase has a 90% conversion rate. An “Add Payment Info” event would be a great conversion event to use in this case. The landscape of iOS 14 is constantly changing but it should be applicable for the immediate future.
grow and stay ahead
As a rule of thumb, incremental checks in growth marketing should be done continuously. This gives an important read on whether advertising dollars are bringing in users who wouldn’t have converted if they hadn’t seen an ad.
When comparing optimization events, this rule still applies. Make sure the cost of each action isn’t the only metric being used as a measure of success, but instead, use the incremental lift on each conversion event as the ultimate key performance indicator. In this piece, I detail how to run lean incremental testing without a bunch of data scientists.
So how do you stay ahead and continue to needle on your growth marketing campaigns? First and foremost, consistently question the events you’re optimizing for. And second, leave no stone unturned.
If you are using the same optimization event forever, it will be detrimental to your campaign performance potential. By experimenting with flow changes and running tests on new events, you’ll be well ahead of the curve. When iterating over the flow, think about user behavior and events from the user’s point of view. Which flow events, if added, would be associated with a high trend conversion segment?