How We Got 5× ROAS for a Pune E-Commerce Brand in 90 Days

The Situation When We Took Over the Account

The client — a Pune-based home décor e-commerce brand (name withheld by request) — had been running Google Ads for 14 months with a previous agency. They were spending ₹1.2 lakh per month and generating approximately ₹1.3 lakh in revenue. A 1.1× ROAS that left virtually no profit after cost of goods.

When we audited the account, we found five critical problems:

• Broad match keywords eating the budget — 68% of the ad spend was going to irrelevant searches. "Home décor" was triggering ads for "home decor ideas" (informational searches with zero buying intent) and even "home décor Minecraft" (no comment).
• No negative keyword list — After 14 months, the account had fewer than 30 negative keywords. A properly managed account this size should have 500–1,000.
• All campaigns using maximise conversions without conversion data — Smart bidding requires at least 30–50 conversions per month per campaign to work. With an 0.8% conversion rate, most campaigns had fewer than 10 conversions per month.
• Landing pages not matching ad intent — Ads for "buy cushion covers online Pune" were sending users to the homepage, not the cushion covers category page. This alone was responsible for most of the conversion rate problem.
• No shopping campaigns — The brand had no Google Shopping (Performance Max) campaigns. For e-commerce in India, Shopping ads typically generate 60–70% of revenue at lower CPA than search ads.

Month 1: Fixing the Foundation (Days 1–30)

Month 1 result: ROAS went from 1.1× to 2.4×. Spend was reduced to ₹90,000 but revenue increased to ₹2.16 lakh. The client nearly doubled revenue while spending less.

Month 2: Scaling What Works (Days 31–60)

With clean data now flowing in, Month 2 was about understanding which products, audiences, and keywords drove the best margins — then doubling down on them.

Product-Level Analysis

We segmented the campaign performance by product category and found a pattern that is common in Indian e-commerce:

Product Category	Revenue %	ROAS	Decision
Cushion covers (₹299–₹499)	38%	4.8×	Scale aggressively
Wall art (₹599–₹1,499)	24%	3.9×	Scale moderately
Decorative vases (₹1,200–₹3,500)	12%	2.1×	Pause and test new creative
Curtains (₹800–₹2,500)	18%	1.4×	Reduce budget, fix landing page
Table runners (₹199–₹399)	8%	6.2×	Underinvested — scale hard

The table runners category was the biggest surprise. It had the highest ROAS (6.2×) but was receiving less than 8% of the budget. We immediately reallocated 20% of budget to table runners and cushion covers.

Audience Layering for Search Campaigns

We added In-Market audience layers to search campaigns — specifically "Home Décor Enthusiasts" and "Recently Moved" audiences. These people were already in the market to buy. Layering them over keyword targeting with a 20% bid adjustment increased conversion rate to 2.8%.

Month 2 result: ROAS hit 3.8× on ₹95,000 spend, generating ₹3.61 lakh in revenue. The client approved an increase to ₹1.2 lakh budget for Month 3.

Month 3: Full System Firing (Days 61–90)

Month 3 was about enabling Smart Bidding strategies now that we had enough conversion data. With 60+ conversions per month per campaign, we switched from Manual CPC to Target ROAS bidding — giving Google's algorithm a clear goal of 4× ROAS minimum.

• Performance Max expansion — Expanded PMax campaigns to include YouTube and Display placements with lifestyle creative. These generated 22% of conversions at 4.1× ROAS — largely from people who had previously visited the website.
• Seasonal push for Makar Sankranti — January is a high-purchase period for home décor in Maharashtra (pre-festival gifting). We created festival-specific ad copy and landing pages 10 days before. These campaigns ran at 7.2× ROAS during the 5-day peak window.
• Customer Match campaigns — Uploaded 3,200 past customer email/phone records to Google. Targeted them with loyalty offers. These campaigns ran at 9× ROAS — the highest of any campaign type, because we were targeting people who had already bought from the brand.
• Negative keyword expansion to 800+ — By Month 3, our negative keyword list had grown to 847 terms. This ensured virtually every rupee was spent on genuinely purchase-intent searches.

Month 3 result: 5.3× ROAS on ₹1.2 lakh spend. ₹6.4 lakh in revenue. Cost per purchase: ₹320 (down from ₹1,240 when we started).

The Framework You Can Copy for Your Business

Whether you're spending ₹20,000 or ₹2 lakh per month on Google Ads, the same framework applies:

1. Audit first — what is your current budget actually buying? Use the Search Terms report to see what searches are triggering your ads. You will almost always find large amounts of irrelevant traffic.
2. Fix landing pages before scaling — A 3% conversion rate means 3× more sales from the same traffic. Fixing your landing page is the highest-ROI thing you can do before increasing budget.
3. Build negative keyword lists ruthlessly — Review Search Terms weekly for the first three months. Add negatives constantly. Never stop.
4. Analyse at product/service level — Your average ROAS is meaningless. What matters is which products or services have profitable ROAS — scale those and pause everything else until fixed.
5. Add Shopping/PMax for e-commerce — If you sell physical products and don't have Shopping campaigns running, you are leaving significant revenue on the table.
6. Use Customer Match — Your existing customers are your best audience. Upload their data to Google. These campaigns will almost always give you the best ROAS.