Digital ProductGrowth Marketing

ArturGrowth Hacking | User Acquisition

Reduced Costs Per Lead from $65 to $1.32 through Paid Social

Subject:User Acquisition
Client:Artur
Industry:FinTech
Service:Growth Lab
  • $1.32

    Cost per Leads

  • $65

    CAC

Challenge

Launching in FinTech is highly challenging.

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

Objectives

There are two defined objectives.

The first is to analyze the target market and get valuable data by identifying which triggers and audiences have the highest conversion rates. This is the best way to achieve Product-Market Fit minus the User Acquisition Cost.

The second objective is to onboard and convert as many users as possible in order to catalyze growth.

Targeting

Targeting

Bringing new technology to market, such as AI, requires a deep understanding of your audience and very precise targeting as timing and adoption are key.

First, we defined our personas based on our product’s unique selling proposition and user appetence, following criteria such as age, industry, job position, technological and digital preference, and of course, wealth.

The personas developed were centered around interest based on our Vision and Market: saving, investment, security, trust, mobility, performance, technology/artificial intelligence, news, mobility, behavior, and trust.

As a result, we defined 12 personas.

Messaging

For the mission to rapidly develop substantial growth, it had to solve a problem and present a clear solution.

We also listed all the solutions we could provide and even created a backlog that listed potential new features to integrate if our audiences were developing strong interest. This methodology brought us to identify 100+ pain points and therefore triggers to test.

To improve the relevance of the data collected, we classified all the campaigns into themes and triggers such as Technology, Finance, Financial World Complexity, Knowledge, Performance, Personalization, Simplicity, and more.

For each trigger, we crafted a specific campaign that directed users to a dedicated landing page with additional information about the product.

As a result, we launched more than 300 campaigns and 100 landing pages.

Management: Kill, Learn and Accelerate

Our first sprint consisted of testing all campaigns with a very low daily ad spend in order to quickly and efficiently understand which triggers and campaigns were performing the best. This step allowed us to learn important information about our users and to kill the lowest-performing campaigns. Following in-depth exploration and data analysis of the results, the following sprints focused on killing and improving campaigns, identifying new triggers and opportunities, and increasing the ad spend on the best campaigns.

At this point, market depth becomes a key focal point as we identify specific parameters to focus on to ensure the onboarding process will always be followed.