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Linear ROAS Growth for a Pan-Indian EdTech Brand

Linear ROAS Growth for a Pan-Indian EdTech Brand


Brand – A leading ed-tech platform that helps in language learning through pre-recorded sessions, app-based learning and live sessions.

Problem – Unable to move past the 1.5X return on ad spend (ROAS) mark every month, despite increasing the spends by 30%

Ask –  Performance Marketing (Google Search Ads, Display Ads, Facebook, Instagram Ads) achieve a constant ROAS of 2X+ monthly at the current budget.

edtech-performance-marketing-case study

Snapshot of the performance before engaging First Launch


Goal – Achieve month-on-month (MoM) ROAS 2X for a quarter

The following are the steps taken to achieve a consistent 2X ROAS through Performance Marketing

Phase 1 – Current Performance Analysis & Benchmarking

Through this phase, we first identified the best-performing campaign & assets from the past 6 – 12 months of data to establish trends & insights to help us optimize the current campaigns and launch new campaigns.

The following factors were considered through this analysis phase –

  • Keywords & search term bifurcation based on performance metrics
  • Keyword bifurcation based on intent
  • Campaign-type performance bifurcation
  • Ad placements & distribution breakdown
  • Ad quality score & related performance metrics
  • Click-to-conversion rate and landing page quality analysis

We also cross-verified the Ads data against the data provided by the sales team from the CRM to attain insights on –

  • Best performing courses
  • High-ticket courses
  • Location-wise performance
  • Lead to customer conversion cycle & journey
  • Peak lead generation times
  • First touch-point TAT
  • Revenue distribution across acquisition channels

Phase 2 – Ad Campaign Strategy & Optimization

From the insights gathered from Phase 1, we derived a two-prong strategy to ensure a smooth transition at an account level to the new campaigns without any significant drop in campaign performance and overall brand revenues.

The idea was to keep the best-performing campaigns with minor optimizations and replace the non-performing campaigns with new ones, which we crafted based on the analysis & insights.

On the champion campaigns which we retained, we optimized mainly for –

  • Negative keywords
  • Keyword match types
  • Landing page content optimization

We stuck to the above handful of activities to ensure that the whole account doesn’t go into a learning phase, considering that we’re also parallelly launching new ad campaigns.

With the new campaigns also launched, we continued optimization sprints with the following factors –

  • Monitoring Google Search Partner vs Display Partner Network ad distribution
  • Experimenting with new offers & bundles
  • Regional language campaigns
  • Search trends & patterns

Phase 3 – Analysis

In addition to the regular Ad campaign performance analysis we monitored the campaigns continuously and had weekly sprints for –

  • Lead-quality analysis
  • Conversion ticket-size analysis
  • User journey optimization
  • Touch-point with the sales team for deeper understanding on the leads and enquiries
edtech performance marketing case study - google ads

Snapshot of the performance AFTER engaging First Launch

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