There are limitless opportunities and challenges that each product manager can encounter in their career as we attempt to transform raw data into actionable strategy.
It is even more obvious now that every click, swipe, and transaction generates data. A lot of product managers will agree that the difference between a product that does very well and one that just fails miserably often hinges on the ability to quickly and efficiently turn the immense raw data into insights capable of driving decisions
My role at Access Bank PlC where I was part of the team behind the rise of QuickBucks, a lending platform created for SMEs, showed me that tools like Power Bi and Tableau if used effectively can guide teams through the complexities of user behaviour, market dynamics, and operational efficiency.
I remember QuickBucks in particular as it was quite challenging. My team and I saw that the adoption rates were quite low despite the growing demand for SME loans and that was the unique challenge.
We could go the traditional route that suggested that we expand our marketing spend and do more advertising but we had a more radical solution because using Power BI we dissected the user journey and noticed that there was a drop-off rate mostly in a particular stage in the application process.
The team at Access Bank was so focused on getting some clarity in the process and utilized analytics in achieving this.
We used Tableau to understanding the creditworthiness of the SMEs that applied for loans. Traditional models worked by examining the financial transactions and histories of SMEs that applied for its loan facility and this shut down diverse businesses that should have tried if they had access to more capital.
However we used Tableau visualizations to explore alternative data such as social media engagement, supply chain partnerships and transaction frequency to build machine learning models that accessed risks holistically.
The impact was huge we were able to expand the reach of the QuickBucks application which meant we were able to grant loans to 12,000+ previously excluded SMEs.
The dashboards also empowered stakeholders: Executives tracked portfolio health in real-time, while compliance teams monitored fraud patterns.
Data wasn’t just a tool; it became a universal language aligning cross-functional teams around shared objectives.
The strategic alignment of data determines its actual value as an organizational asset. We employed Power BI to set KPIs for QuickBucks’ Instant Business Loan launch which directly supported the bank’s target of digital dominance in the Nigerian market.
Our ability to change the system repeatedly depended on real-time tracking of approval speed together with disbursement performance and customer satisfaction levels. When initial data showed a decline in repeat applications, user feedback analysis uncovered frustration with opaque repayment terms.
A solution to this issue was the integration of calculators with adaptable repayment solutions within the user interface framework.
The feature enhanced repeat engagement during its first six weeks while funding ₦2.8 billion in loans which translated into a growth in quarter-over-quarter revenue.
Actionable insights also demand foresight. Following our product release date we put predictive analytics methods into action to forecast market developments.
Tableau’s forecasting analysis demonstrated to us that agricultural SMEs request loans in seasons of increased activity.
We pre-approved credit limits to target our agricultural SME customers before planting seasons which resulted in acquiring 30% of this target segment during one year.
The analysis of user churn patterns let us identify users who were at risk so we could take preventive measures such as extending payment flexibility which cut down on defaults
Data-driven management instead enhances human intuition rather than eliminating it. The critical objective at Access Bank required organizations to implement analytics as a means to augment human decision-making capabilities.
Food processing startup models pointed to high risk because of unstable cash flow but customer interviews showed their customer loyalty together with their patented recipes.
The pilot loan we provided was repaid early by them in six months and evolved into an acclaimed success story. This synergy of data and empathy underscores a vital lesson: Numbers guide, but context decides.
Today, as AI and real-time analytics redefine possibilities, the next frontier is personalization. Imagine platforms that don’t just respond to user behaviour but anticipate needs—like offering microloans ahead of cash flow crunches or adjusting interest rates based on real-time market risks.
At QuickBucks, early experiments with AI-driven recommendations increased cross-sell rates, hinting at a future where products evolve with users.
For product managers, the mandate is clear: Harness analytics not as a rearview mirror, but as a headlight. Tools like Power BI and Tableau are more than visualization engines—they’re bridges connecting raw data to strategic action. In the hands of teams willing to ask the right questions, they transform uncertainty into opportunity, one insight at a time.
*Razzaq Onotu is a fintech product leader with a track record of leveraging data-driven strategies to scale digital solutions. His work at Access Bank PLC and Sendbox has driven over $150M in revenue impact, blending analytics with user-centric innovation.
