How Tech Simplified A SaaS Startup's
Business Analytics Process

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Business analytics

Business Model –

The Client has a mobile and web app which is used by local and international business houses to optimize their business process.

Client’s Issue –

Client were unable to track user’s activity trace on their application. They wanted to know all about their users to improve their next iterations.

Client's Expectation–

The Client wanted a platform where they can observe every activity performed by users on their app.

They were looking for a detailed reports for every action performed by their users.

However, they did not want to change their existing code base as it would alter their performance matrix.

Our Solution–

We built a parallel web application specifically for their marketing team which would contain all the information and data points about their app users.

This was done in a very unorthodox manner. Our client’s app was using RDBMS and we were about to use No-SQL.

To counter that, we had to write a data migration module from SQL to No-SQL. This module would run in set time interval to update our DB with the latest changes from client’s app.

Using the sleek nature of MEAN stack we were able to deploy this on minimum server specifications.

CHALLENGES:–

  1. Data MigrationEntire data had to be migrated from SQL to No-SQL. To facilitate this, whole schema had to be redesigned.
  2. Time Interval for Data Migration ModuleWe could not overload client’s server with 100s of queries but we had to keep our DB as latest as possible.
  3. Creating new Data points using existing valuesKey Activities were not present in the current system and we had to apply sets of logic to generate crucial data points to be saved by our db.

Client’s Feedback:–

The most important part of marketing your solution online is following up with your clients. Earlier we used to fetch the raw data and monitor details on Excel sheets.

Although functional, but it was too time consuming. We had to go through the same exercise of setting up sheets every day. Getting a monthly overview was also a bit difficult as there were many copies and too many data points.

This led us to Roaring Studios who helped by creating a utility and solve this problem. Their app helped us in following manner –

  • After using the app, we get all the relevant data right on the dashboard which can be sorted and filtered in many combinations.
  • Getting an overview for longer durations is also very easy, since all the data points are included in the app.
  • This utility helps us with lead qualification and allows us to focus all our energies on following up with quality leads and thereby increasing our overall conversions.

Other Related Industries where predictive analysis can help -

  • E-Commerce
  • Manufacturing
  • Retail
  • Healthcare & Pharmaceuticals
  • Banking & Finance

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