Company Overview
A fintech company in the banking and payment sector aimed to launch a new mobile payment solution in an existing market. The market already had established competitors, and the company’s primary challenge was identifying whether there was sufficient demand for its innovative product and how to differentiate it.
Challenge
Entering an oversaturated market where customer trust in existing solutions was high posed a significant challenge. The company struggled to validate whether their product had a unique value proposition and if it could achieve product-market fit amidst heavy competition.
Solution: Schemata’s 4-Core Framework
- Data Collection
Schemata began by gathering comprehensive datasets, including transaction histories, customer feedback, and regulatory updates. These were obtained from surveys, financial databases, and social media platforms to give a holistic view of customer sentiment toward current payment solutions. - Real-Time Analysis
Using machine learning algorithms, Schemata processed this data in real time to reveal actionable insights. This helped identify specific pain points within the market, such as dissatisfaction with transaction fees or poor integration with e-wallets, thus highlighting areas for the company to focus on. - Competitor Pricing and Elasticity
A key part of the analysis focused on competitor pricing models and consumer elasticity. The data revealed that customers were highly price-sensitive, and a slight reduction in transaction fees could drive significant adoption. Additionally, competitors had no immediate plans to offer discounts, giving the fintech company an edge. - Economic Indicators
The fintech company used economic indicators such as income distribution and inflation rates to predict changes in consumer spending. Schemata identified that targeting middle-income users, who were disproportionately affected by fees, would lead to higher conversion rates.
Implementation
Based on Schemata’s analysis, the company:
- Reduced transaction fees slightly to appeal to price-sensitive users.
- Emphasized integration with e-wallets in its marketing strategy to address a gap in competitor offerings.
- Optimized the launch timing based on market data, aligning it with favorable economic conditions.
Results
With these insights, the fintech company achieved:
- A 25% increase in customer acquisition within the first three months.
- A 15% higher retention rate due to better alignment with customer needs.
- A 10% reduction in churn as the lower transaction fees and added integrations appealed directly to dissatisfied customers from competitors.
Conclusion/Extra Value Provided by Schemata Solutions
Schemata’s real-time data analysis and predictive capabilities helped the fintech company reduce its time to market by 20%, allowing them to respond faster to shifting market demands. Moreover, their pricing adjustments based on elasticity data led to a 15% cost savings, creating a product that not only fits the market but is also cost-effective to operate.
