CASE STUDY

sulekha

How we helped   to increase data collection accuracy & speed by 30%

client background
Client Background

Sulekha’s business model is to provide a platform to the users looking for services in 200+ different categories (including home/office services, coaching/training, lifestyle & property/rentals, etc.) and to businesses which offer these services to the end users. Apart from India, where Sulekha is a strong leader in services, it also operates in USA, Canada, UK and UAE markets to serve Non-resident Indians.

problem
Problem

Data accuracy and faster implementation were key challenges in Sulekha’s analytics project due to its wide range of services to different markets spread across 7-8 digital properties. And another challenge was that it required close communication between teams for implementation status.

approach to solution _ hypothesis
Approach to Solution

Development of Data Layer Tool

The DataLayer Tool is designed in PHP & MySQL and it utilizes Google Analytics 360 Management API & Google Tag Manager 360 API to interact with clients’ GA & GTM Account. By this it performs different operations automatically such as creating variables, triggers, tags & various GA configurations. Additionally, it keeps a track of each dataLayer status as Created, Implemented, Tested and Tags Created. DLT has an inherent capability of connecting DataLayer variables with GTM variables, and GTM variables with Google Analytics Dimensions & Metrics. The DataLayer screen contains page-wise dataLayer to be implemented by the developer and a ready-made snippet to be pushed in to the code. DLT has been integrated with Mandrill API to send out status or snippet emails to the relevant stakeholders.

Results
Results

Accuracy in data collection while saving team’s time

DataLayer Automation Tool addressed their team’s issues almost immediately. The DataLayer Automation Tool made it simpler for all the different stakeholders in their organization like Analytics team, developers, testers and admins to co-ordinate various implementation-related activities.

What DLAT delivered was an easy way to create a tracking requirement for managers. It provided exact snippets to our respective developers through email so that they can push it on the web or app accordingly. This resulted in a visible change in the accuracy of the data they were collecting while also saving their time.

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