How fintech companies can use product analytics to improve customer lifetime value
The banking and finance industries have seen a lot of disruption in the last 15 years that’s brought financial services even closer to consumers. While grappling with volatile interest rates and overall low credit growth, traditional banks have had to fend off increasing competition in retail from financial technology (fintech) and platform-based competitors, all of which threaten the profitability of traditional banks. We’ve seen more neo-banking, trading, and eWallet apps find their place in the average user’s smartphone, and it’s also common to have multiple companies in the peer lending, micro loans, and ledger book spaces vying to be the winner of their respective domains. It’s because of all of this that the market for business analytics in fintech was valued at $3.1 billion globally in 2021, and it’s projected to reach $22.9 billion by 2031, growing at a CAGR of 22.4% from 2022 to 2031.
As an industry in growth, some of the most valuable data pouring in that fintech companies can focus on comes from product usage. Product analytics makes it possible to identify trends and patterns in how users are engaging (or not) with their services, which can then be used to inform business decisions like adding or dropping product features or promoting sales and marketing strategies.
Modern fintech users demand more flexible journeys, with a survey finding that 71% of them now prefer multi-channel interactions. Moreover, 25% of financial technology customers now want a fully digital banking experience fueled by remote human assistance available when they need it. Companies can identify and target these needs by better understanding their customers using data.
The role of product analytics in fintech
It’s simple, really: When fintech companies can easily collect and analyze crucial information about their users’ banking activities, identify pain points, and target anomalies, they’re able to react accordingly to build better solutions. This behavioral analysis-led development style is what product analytics unlocks, and it inevitably result in a substantial increase in the quality of customer service and the improvement of tech-driven service channels such as live chats or even automated tellers and chatbots.
To make better sense of behavioral data, fintech companies need robust product analytics frameworks. While many frameworks vary to a certain degree, adoption, engagement, and retention remain as universal metrics. Mixpanel works with leading and innovative fintech companies globally to answer the most compelling questions pertaining to onboarding efficiency, personalization/user segmentation, and long-term user retention. Let’s delve into each of these elements in more detail.
1. Understanding user onboarding to improve key metrics
For fintech companies, onboarding is everything. Understanding where new users are coming from and how to acquire them is one part of the puzzle. The fairly linear process of getting users to successfully sign up and proceed to monetization, however, is more deceptive than you may imagine. When users do not complete all steps in a Know Your Customer (KYC) process, they are locked out of the full suite of offerings. This explains why fintech companies spend millions of dollars trying to simplify the process and help users complete it as quickly as possible.
KYC (Know Your Customer)
With KYC implemented as a mandate in fintech institutions, the most optimized and efficient KYC flow quickly establishes a foothold in the addressable user base. The degree to which products successfully do this directly influences how many users adopt, spend, and return to the app. Fintech institutions need to get to know their customers on a more profound level to understand each individual user’s needs better, target those needs, and identify their lifecycle to increase scalability, reach, and revenue.
As KYC regulations vary across countries and products, it is important to understand where users struggle and drop off in your product. You can experiment with different onboarding sequences, where you change up the order in which key information is submitted. Utilization of shortcut features to upload information—such as scanning a card to capture payment details—can also be scrutinized to find bottlenecks. The ultimate goal here is to ensure users pass through each step only once and in the shortest time possible.
Key adoption metrics include:
KYC conversion rates
- It is important to identify and resolve friction points, especially at the activation stage, to ensure maximum return on marketing efforts. Product managers want to know where users are giving up in the onboarding process and what their drop-off journeys look like. Time to convert and how frequently users re-enter the activation process are also top metrics.
- Understanding demographic information about users can lead to innovations in the KYC funnel, resulting in better conversion rates. For example, VIP users who transact in volumes at the 90th percentile might be in an age range with lower technological literacy. AI bots can be utilized and targeted at certain users to ease their onboarding process.
Best path to activation
- Modern fintech users demand more flexible journeys, with a survey finding that 71% of them now prefer multi-channel interactions. How else can companies identify and target these needs if not for customer segmentation? Segmentation is how Mixpanel customer ATB Financial reached a 5% improvement in conversion rate for its digital banking signups, while Brightside used Mixpanel to get to a 30% increase in conversion as well as a 55% reduction in user verification costs. If AB testing tools are utilized here, running comparison analysis between control groups and experiment variants can also have a huge impact on overall activation rates.
Targeting unactivated users
- A key group of users to monitor is unactivated users. These are users who have completed the KYC but have yet to experience an “aha” moment in the product and make a transaction. Identifying these unactivated users and converting them is crucial, as users who go on to discover value in a product (reach “aha”) tend to have higher retention rates. Many marketing teams devote resources in the form of retargeting campaigns and push notifications. A common process here is to review the most successful campaigns and top types of first-time transactions carried out by new users and use them in future campaigns to incentivize users towards transacting.
2. The need for personalization and user segmentation
User composition and lifecycle analysis are especially important for continued user engagement. Once users are acquired, fintech companies can pinpoint spending habits and correlate them to things like user age or location. Two key user segments are newly acquired users and newly onboarded users who have yet to make transactions. Personalization strategies are refined to better serve these users so that they receive value in their earliest interactions and eventually become high-value customers. Fintechs iterate and create highly specific user composition breakdowns, ensuring that their customers receive targeted promotions at the right time and have access to the most suitable payment technologies, credit card limits, and account capabilities.
User lifecycle analysis helps you break down your user base into core segments. On the broadest level, this includes newly acquired users, newly transacting users, active users, and churn risk users. Fintech metrics should be replicated per user segment so product teams can better track and monitor the health of their user base.
Key engagement metrics include:
Monthly active users
- In the constellation of metrics, MAUs plays a significant role. MAU is the foundation when calculating activation, engagement, and retention metrics. It provides the most empirical measure of a product’s success. This can be further explored in terms of weekly and daily active users and spikes or dips in this metric provide an opportunity to investigate and understand what makes users tick.
Growth of highly engaged users
- A common benchmark is to apply a 75/25 rule, where 75% of product revenue comes from 25% of users—known as highly engaged users. Spending habits like frequency of purchase, coupon usage, and average transaction values are often used to define such user segments. Product teams can explore if certain activities encourage these users to become highly engaged, such as creating a recurring transfer. Once identified, marketing and product teams utilize upsell and cross-sell opportunities to increase user lifetime values.
Transaction metrics
- Depending on the industry, the transaction could be in the form of a trade, payment, buy, or sell order. Two topmost metrics would be the frequency of such transactions and the average transaction value. Knowing the differences between transaction amounts at the 25th percentile against the 90th percentile, split across various user segments, provides powerful insights. Product teams, like those at Mixpanel customer Khatabook, monitor these metrics closely as a monthly trend. Marketing teams would be able to interpret this data to understand which users would benefit most from marketing spend.
- Usage of promotions in the form of coupons and cashback is also a big factor in engagement: Which promotions resulted in the most transactions, and how does this impact the average order value? In trading and crypto firms, teams can experiment with varying levels of cashback or waived transaction fees for a specific period of time to encourage higher trading volume.
By analyzing customer data, such as purchasing patterns, preferences, and demographics, fintechs can tailor their products and services to meet customer needs more effectively. This data-driven approach enables SMEs to deliver personalized experiences that enhance customer satisfaction and foster loyalty.
“Mixpanel’s top use case in BILL encompasses user funnel analysis, a breakdown of customer success resolution by error types, and an increasing emphasis on experimentation. By leveraging Mixpanel, we aim to optimize processes such as nudging Account Payable users to switch vendors to e-payment, thereby enhancing efficiency and cost-effectiveness.”
Qiaoran Abbate, Staff Software Engineer, Data in Fintech @ BILL
3. Retention
Financial services apps tend to take a longer view of what successful retention looks like. In our 2024 Mixpanel Benchmarks Report, we saw that retention over 52 weeks for fintech companies ranked better than any other industry: After one week, approximately 27% of users re-engaged with fintech platforms, and after 52 weeks, 15% of users were still coming back.
Key retention metrics include:
Average retention rate
- As a rule of thumb, day 30, day 60, and day 90 retention allow you to understand how successful your engagement and short-term retention strategies have been. Product teams also monitor retention for specific user segments, such as high-value users. When marketing campaigns are launched to acquire new users, their downstream impact can also be understood in these retention metrics.
Impact of referrals
- Apart from marketing campaigns, most fintech firms believe in the power of referrals for long-term retention and brand awareness. Continuous efforts to entice current users (even with rewards) to invite friends to the product should be maintained. Marketing and push tactics to bring in new users via referral programs, campaigns and vouchers should also be monitored, to verify if referrals really are bringing higher quality customers.
The above metrics are typically used within product management teams. When in place, product managers work cross-functionally with retention marketing teams. They use a joint mix of new feature launches, UX tweaks, marketing campaigns, and AB testing to boost these metrics.
Key takeaways and recommendations
The next big disruption in fintech is possibly just around the corner, and staying ahead of it—in terms of user acquisition, risk management during onboarding, and nurturing user retention—will be crucial for long-term success. The only constant remains the ever-increasing amount of data generated that will continue to drive the industry-defining products and the business decisions that will make them succeed.
Democratizing the access to this powerful data continues to be the main priority for the most agile companies in fintech today, and tools like Mixpanel make that process effortless—whether you’re a new-age scale-up or a large traditional bank looking to quickly keep pace.