Lead generation overhaul
The release of iOS14 back in 2020 was a turning point for Airofit’s aggressive paid social media strategy. The sudden loss of user tracking data across Facebook and Google platforms made the conversion costs skyrocket.
Here’s how we turned it around, lowered our acquisition costs, decreased the purchase decision-making time and skyrocketed the number of warm leads instead.
The premise
Facebook (Meta) used to be very good at finding the right audience for your communication. If you made a creative for a specific audience, their algorithm found the people who were the most likely to convert through the particular ad.
You could run one main campaign with many ad sets and Facebook would assign the budget within the campaign accordingly, pointing out the winners. You knew what to replicate and acquisition costs remained low. That changed.
By losing the tracking data on most iOS users, Facebook could no longer distinguish between people’s preferences and interests. Rudimentary demographics was what audiences were built around. However, if you compare two 30-year-olds in Texas, their behavioral profiles could be vastly different.
We figured out a campaign structure that allowed for simplified architecture. We didn’t want to compromise Facebook’s already compromised algorithms. This meant we had to simplify our ad messaging to hit wider audiences and continue driving considerable traffic to the website
While we managed to do it, the conversion rates on the website plummeted - people clicked on the ad could not find themselves in the homepage as we were shooting wide.
We decided to implement a quiz on the website that would become the main CTA button. We wanted to allow people to tell us why they’re here and from there tailor our communication to the potential customer’s needs.
Step 1:
Mapping out the quiz logic
I decided to split the quiz into two parts not to overwhelm the customer. First part would focus on their general demographics and preferences, while the second dug deeper into their breathing habits and current data.
Step 2:
Connecting to CRM
The more challenging task was connecting the gathered data from Typeform to ActiveCampaign. I made sure every customer was logged into our CRM system. Based on their answers, they would receive tailored emails on how breath training could affect their daily lives, sports performance, etc. This meant we needed to tag each potential customer with all relevant information - also for future communications.
Step 3:
Building emails
Once I sure sure that we’re capturing our users’ inputs correctly, I built out the email communication using condition-based content. People only received content that was tailored based on their answers.
Depending on the selected focus area, the email header would be tailored to best represent the potential customer.
This graph displays the difference in lung capacity based on Airofit’s user data - before training compared with 4 weeks of training.
Based on the age group you selected in the quiz, you would receive a visual representation of your potential gains.
As the potential customer shares in-depth information about their training motivations, we can find 100% relevant examples of other users who have publically shared their information.
This significantly reduces the decision-making time frame as they can see how the implementation of the product can benefit their specific situation.