Mobile Responsive Transport Networking Web Application

The project was kick-started with market research and competitor analysis; based on the finalized modules and features VSH decided to leverage its Marketplace platform for the development of this product and employ its inbuilt modules to reduce the overall development costs and minimize the time to market.

Modules

Development of the Product has three important components:

Google map service was integrated in the application and it was pivotal in the selection of the routes and providing directions to reach the commuters’ destination. But to improve the overall user experience and take the product offerings to next level, machine learning algorithms were developed for route selection, route calculation, and route optimization which were based on the number of variable factors like real-time traffic, driver’s current location, their preferred coverage areas and most suitable driver to complete a particular ride.

Based on the average of the rates proposed by the partners, an algorithm was developed to calculate the mutually profitable rate for the users as well as for the partners. In the later phase, the strategy was fine-tuned to remove the anomalies arising from unusually high and low prices proposed by the partners.

A unique module was developed to display all the unclaimed bookings which were initially offered to the nearest or suitable drivers selected by the algorithm. This feature allowed drivers from other locations to claim the ride which was otherwise going to be cancelled; making the engagement more beneficial for users as well as partners.

Integrated with payment API’s to complete the two way payment processing i.e. for user and for partners. Automatic backend system was developed for this application to: refund the amount for cancelled rides, automatic invoice generation, settlement of the partner account after every seven days, calculation of penalties and the government taxes and transfer of the money directly to partner accounts.

Disconnected user experience was one of the early challenge faced by the management. To overcome the same multiple UX iterations were done and Google API’s were integrated to show the relevant auto fills, nearest location suggestions along with the ability to fine-tune the search functionality with the help of integrated map.

Partner/driver on-boarding was challenging and the involved technicalities were bothersome to some of the partners and drivers. Process simplification was done by developing a standard profile forms and by designing easily understandable training collaterals for partners.

Price for a particular ride was calculated with the help of an average price algorithm, but in case of unusual low and high prices proposed by the partners it used to show aberrancy in the average ride price leading to erroneous calculations. The issue was subdued by developing a separate algorithm to eliminate the outlier values.

AdWords cost optimization was a challenge during the marketing phase and absence of relevant keywords on site was the reason behind it. In order to include these keywords and names of popular tourists’ locations and places; a system was developed to create dynamic web content.

In case of aggregator portals serving large number of users, verification of various involved entities is crucial.

Development of mutually beneficial pricing strategy, then analysing and overhauling the strategy by eliminating the anomalies was insightful