Growth Hacking - AI Powered PPC



Subject:Growth Hacking - AI Powered PPC
Industry:FinTech - Finance
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Key Figures

  • $1.32

    Average Cost per Lead

  • x50

    Better than Industry Average

01 The Challenge

Launching a FinTech is highly challenging.

First, because of the complexity of the legal and compliant environment. Second, because of the tremendous User Acquisition Cost (CAC) you have to fight against – Average CAC in FinTech $550, Average Cost per Lead $65. Third, simply because we are targeting the most sensitive subject for a majority of people: money!

Among the numerous challenges we faced, we’ll focus this use case on growth acquisition and CAC.

02 The Results

The Results
After the first sprint, we had clear answers about core audiences to target first and the affecting triggers. Our Cost per Lead reached $0.78 with an average Cost per Lead at $1.32.

Having a clear understanding of our audience’s concerns provided us with:

  • Valuable information regarding the features we should implement first, allowing us to improve our MVP and adjust our Product Road Map.
  • New user acquisition opportunities and therefore, with a new growth window.

03 The Targeting

Bringing a new technology such as AI to a market, where your target’s financial wealth will be one of the main components of your revenue, requires a deep understanding of your audience and very precise targeting. First, we defined personas we believed were the primary audience based on age, industry, technological and digital preference, and of course, wealth. The personas developed were centered on our Vision and Market: savings, investment, digital, artificial intelligence, news, behavior and trust evolution and generation.

04 The Messages

Before going straight to message conception, we opted for a customised methodology. For your project to be a success with rapid growth, it has to solve a problem. Therefore, we listed all the pain points, barriers and constraints that our targets might experience. We also listed all the solutions we could provide, which brought us to 100+ paint points and insights to test. To improve the relevance of the data to be collected, we classified all insights into themes such Technology, Finance, Complexity, Knowledge, Performance, Personalization and more.

For each insight, we crafted a message, key visual and headline, in addition to a Landing Page with a claim, description and three key benefits to present the product.

05 Kill and Learn

Between each Sprint, we monitored all active campaigns. This was done not only to kill the lowest performing campaigns, but also to learn important information about our users. The campaigns revealed that some of our insights and assumptions were wrong and therefore didn’t drive the desired user results. This monumental discovery revealed that all messaging and directions employed by our competitors on the market were performing with absolutely no results at all. On the other hand, we discovered that three main topics were capturing all our audiences’ interest respectively at a $0.98, $0.92 and even a $0.78 Cost per Lead.

With these results, we performed an in depth exploration of these results in Sprint three and four to search for new insights and test new triggers and messages. These additional sprints allowed our team to bring down the Cost per lead from $0.78 to $0.48 and clearly identify core targets.

06 Accelerate

Now that we have identified our best performing target, the objective is to increase traction by increasing our Ad Spent volume. It may be considered that the hardest part is behind us, although it’s quite the opposite since there is no proof of market depth. In this case, increasing the ad spend budget might result in a soaring CAC due to an insufficient volume of users.

The acceleration phase forced us to enlarge our target while keeping the same insights and triggers, to bring us to an average cost per lead of $1.32 compared to the average industry cost per lead of $65.

Key Figures

  • $1.32

    Average Cost per Lead

  • x50

    Better than Industry Average