Does growth hacking apply to fintech? Can the fintech industry actually implement growth methodology and active experimentation framework?

Growth hacking is a relatively new focus in the marketing field, which focuses on company growth, fintech startups, established companies and others. The goal of its extremely effective methodology is to quickly test ideas that can improve the customer experience before investing a lot of resources, copy and expand ideas that can work, and modify or abandon those that don’t work.

First, we start with metrics to measure growth of our fintech corporation. The key metrics should always be the ones that best deliver growth to your industry, like the number of potential clients, qualified lead generation, MRR, increased channel sales revenue or SaaS upselling. Once we know which metrics are the most important ones, it is time to set goals. Goals should be SMART, and these are specific, measurable, achievable, relevant and timely. A good SMART goal would be to go from 50 to 80 sales qualified leads delivered every fortnight to the inside sales team. After we set up our goals, we ideate new or existing growth drivers.

Growth levers, or drivers, are hypothetical ways to achieve goals, and now if our ideas are worth it without unnecessary risk. In fintech, as in finance itself, it is all about trust, trust and being able to attract the right potential customers with our value proposition. The content we produce should always be excellent, top quality and, if we are in B2B fintech, we could test a driver of Account Based Marketing and try different tactics depending on the Target Accounts. First of all we have to be thinking outside the keyword search box, as you may already know, keyword research forms the foundation of all fintech inbound marketing. This means that our content will be presented at the right time and in front of the right people, and if you do it right, you can turn them into potential customers.

• But what happens when no one is looking for your product?
• If people don´t know they need help in their lives and businesses, how can you increase your influence?

In short, thinking outside the keyword search box could be a door to open in order to get more income, and get to these specific terms that respond to hidden needs that no one is catering for, but which are golden opportunities to test our inbound strategy. On the other side in the 21st century, everything is mobile. If you don’t carry out marketing activities based on these precious handheld devices, you will miss one of the most effective ways to connect with consumers. So why do we want to make experiments based on mobile devices? Recent research shows that we spend 5 hours a day on mobile devices, and the time spent on mobile apps has soared by 69% compared to 2016. Many fintech companies will be surprised to see that now, over 80% of their traffic is mobile.

• So how can fintech companies target mobile users to get the most benefits?
• Could it help us to have a more responsive mobile website?

These are additional hypotheses to test by turning them into specific growth drivers. Apart from this we have to know what is the content that our users are looking for taking advantage of visual marketing tactics. Asking ourselves:

• is this digital content useful to attract potential customers to purchase our product?
• Should we invest in digital content to seek to attract investment from our public?
• Are they interested in short or long videos?
• Is it important if the video has a good sound quality or the viewer prefers just to read a text?
• Where should we implement these videos?

All these and more questions are what we have to answer to find the right growth drivers, and then use experiment to test these drivers and learn from them. Learnings are crucial in growth methodology. Learnings are essential to document in order to know what worked in the past and what to avoid repeating. You should have a regular feedback cycle and track your learnings consistently and have general learnings available for the team as well as specific learnings applied to every single experiment.

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