How Kato helped Jugnoo in improving
the way they handled business

The Story

Autos | Fatafat | Food Delivery
Marketplace | Meals | Deliveries

Jugnoo is a hyperlocal marketplace present in 45 cities in India that caters to the on-demand needs of customers. Customers book auto-rides, order Food, Fresh Fruits, Vegetables and Groceries through Jugnoo mobile app.

Jugnoo being one of the fastest growing hyperlocal startups in India was facing a major challenges in detecting fake transactions, surge pricing, real time monitoring and biggest of all; demand-supply mismatch. Kato Business Intelligence Dashboard helped Jugnoo to solve these problem by using advanced Big Data Techniques and Predictive Analytics.

Demand - Supply Mismatch

Jugnoo Knows Balancing supply and demand is critical to business profitability. But with unpredictable consumer demand, striking the right balance is tricky. And wading through rows and rows of numbers in spreadsheets doesn’t make it easy to adjust supply accordingly. Kato’s robust business intelligence solution provide ready to use visual analytics to balance supply with demand and forecast demand more accurately. And helped jugnoo to increase fulfilment to 70%.

Real Time Business KPI Dashboard

Jugnoo has presence across 38 cities and each city is led by a city manager. They wanted to empower their city teams with real time data analytics related to their city. Kato provided a real time KPI dashboard and detailed visual reporting that empowered city operation team to take control of daily Jugnoo operations and take proactive decisions quickly and efficiently.

Fake Transactions

Jugnoo runs a lot of discount campaigns for its customers and thus burns a lot of money. One of the challenge that came with it was that drivers started misusing the system by booking fake rides and started fooling their system. Kato uses advanced pattern recognition algorithms to identify these cases and has saved $100,000 on these cheating cases uptil now.

Surge Pricing

Jugnoo was using surge pricing to match demand with supply. However a challenge that they faced was they couldn’t control the pricing by area or have a differential surge pricing for different regions neither was it dynamic so as to automatically adjust once the demand supply mismatch is covered. Kato helped provide an algorithm to provide automated differential pricing and control by region, leading to increase in revenue by 36%.