How We Set Up Ads for the Bottom of the Funnel for a US Digital Bank and Increased Bank Account Openings by 14x

A digital bank focused on business-to-business (B2B) services in the United States market.

We have been working with the client on an ongoing basis for several years.

At the very beginning of our work together, our key goal was to enter the market and achieve KPIs for top-level conversions: registration and onboarding.

At the next stage, the client set a new goal: to improve in-funnel conversion within the current traffic volume and increase the number of customers who do not just register and successfully onboard, but perform the bottom-of-the-funnel action (open a paid account). The client was actively working on this goal on the product side and improving the funnel. And we got a new goal for the advertising traffic: to increase conversion into paying customers

While solving the task of increasing the conversion rate at the bottom of the funnel, we tested different hypotheses:

1. We tried to increase CR through deeper and more precise work with keywords.
2. Together with the client we planned and tested new unique offers.
3. We optimized current campaign settings to the maximum, manually disabling everything that did not bring paying customers.

These actions were impacting conversion rates, bringing us closer to our goal, but the change wasn’t enough. Eventually, we found a solution that increased the number of paying customers by 14x.

The key solution that allowed us to achieve this success was shifting our ad campaigns to value-based auto-strategies, incorporating the entire depth of the funnel into conversion optimization. The framework itself for transitioning campaigns to the new settings also played a significant role in the success. It was important to smoothly retrain campaigns on the new settings in a way that would not damage the current results, but improve them.

What we did:

1. We set up offline conversions transfer to Google Ads via gclid. All key actions of the event funnel (4 stages) were transmitted.
2. We set a value for each conversion in the funnel. Calculated it based on the CPA for the final step (paying customer). Calculated the value of each previous step of the funnel by the conversion rate from step to step.
3. Took 6 weeks to accumulate data on conversions with value. During this time, the campaigns ran on current strategies that did not consider the value of conversions (max conversions or tCPA).
4. After 6 weeks, we switched a couple of key campaigns with the highest traffic and number of conversions to an auto strategy, taking into account the value of conversions. Immediately in the campaigns we set tROAS to the same level as it was actually in the campaign for the last 4 weeks.
5. Left the campaigns alone for 4 weeks. Gave them time to collect data and learn. During this time, only regular optimization work was performed.
6. After this stage, we left the campaigns alone for 2 more weeks to evaluate how well they performed in the new set-up after the learning phase.
   After we were sure that the campaigns had been trained and were showing positive dynamics, we started working with the tROAS value — we gradually increased it, closely monitoring the changes in the actual ROAS, as well as the number of conversions/clicks/shows. It was important that the increase in tROAS was not too sharp and that it did not differ too much from the actual value.

By switching campaigns to value-based auto-strategies with optimization for all conversions in the funnel, we managed to increase the number of users who made the final conversion by 14 times. At the same time, it is extremely important that the cost per conversion decreased by 4 times.

By training campaigns on value-based strategies, we influenced the quality of the traffic we attracted. Conversion Rate increased, which allowed us to get more conversions at a lower price.