How operates the most invisible department in Mercuryo?
Data makes the digital world go round, and the work of the analytics department becomes as relevant as it can be. Whether you’re having issues with your customer flow or want to improve products and services without burdening development, enhancing the analytics team will be your best bet.
Mercuryo’s data analytics team consists of six members: product analysts focused on the company’s key services, data warehouse developer who collects data from internal and external resources, and data analytics lead. Although their work might not be on display, compared to other departments, the improvements they introduce are unchallenged.
How It Works
Data logging is the practice of collecting and storing data to analyse and record specific data-driven events. However, our service is not designed for data logging, and we try to collect a lot of WIM (weigh-in-motion) from other platforms we work with, like KYC providers, IP services, and others. And the primary goal of the Mercuryo analytics team is to collect data independently without any other department.
However, many services store data in a separate database, and we need to spend a lot of time trying to retrieve it. The automatisation of this process is impossible without DevOps’ help, and they’re currently assisting the analytics team.
The aim is to abandon Amazon DMS whatsoever and provide a fast and stable data collection flow using only our own resources. We recently started working with custom replication which allows us to collect data efficiently and quickly.
The Art of Research
According to analytics departments themselves, their main goal is to increase the company’s profit without development. There are a few ways to achieve it, including the ones below:
- Analysing user’s funnel and conversions
- Analysing incoming traffic
- Segmenting traffic and working with each segment (which basically means dividing users according to their behaviour, frequency, average bill, and more)
- Analysing customer experience (problems with KYC, transactions, cards, etc.)
“Many people do not realise it, but it is not only the customer service team that works with users’ feedback; the analytics team has a lot to do with it too,” – says Philipp Chistyakov, Mercuryo’s data analytics lead. “We treat every call to support with utmost care as each of them affects retention and average bill. When handled as a top priority, streamlined customer experience improves users’ wellness and, consequently, a company’s profit.”
As for the conversions’ analysis, the process starts when a customer sees the widget screen or downloads the app and ends with their last purchase. We monitor it daily to spot the issues and constantly make important discoveries.
For example, we noticed some troubles with our external verification process. After looking into the operation specifics of various browsers, we realised that some of the browsers demonstrated a very low conversion rate when adding KYC documents. A quick fix of the issue helped eliminate the problem entirely.
That wasn’t the only time the analytics department helped prevent a mounting problem. At one point, we elicited an issue with Mercuryo’s traffic in Nigeria – more specifically, it was not as great as we hoped it would be. Immediately, the team started researching the ways to improve it. In the meantime, our long-term partners, a leading KYC provider, suggested trying out a new document verification system developed specifically for Nigeria. After the integration, we checked the data and saw an impressive surge in verified users’ cases.
There’s no lack of curious data cases we still need to investigate. For instance, we’ve discovered that the US user funnel conversion is lower than in other regions, and the team is currently checking various hypotheses on this matter.
The work of the data analytics department is not as invisible as it may look at first sight. The Mercuryo team members can request access to the key data researches and use this data to improve the workflow of other departments, be it sales, product, or marketing.
Data analysis is the surefire way to make essential business decisions. For instance, how will the No KYC under €300 purchases policy affect conversions in different regions? Can we raise this amount, or should we turn down the initiative due to the increased fraud attempts? In-depth research will give you the answers.