India · Consumer-electronics ecommerce
An Indian consumer-electronics retailer came to us with Google Ads reporting 1.52× platform ROAS. Purchase-only value/cost was just 0.25× because the account counted the wrong commercial signals. We repaired measurement, rebuilt campaign allocation, scaled beyond 40× platform ROAS, and then made the result answer to Shopify.
Where our contribution begins: the customer confirms that we began the tracking repair and performance work in August 2024 at 1.52× platform ROAS. The signed SOW formalized the relationship on 2 December; it was not the operational start.
01 · The broken signal
The 1.52× headline hid a weaker commercial reality. Purchase value alone returned only 0.25× because checkout value supplied most of the platform total while another purchase action counted conversions at zero value.
We separated purchase value from activity, repaired the measurement basis, connected GA4, and rebuilt the acquisition structure around products and demand the customer could actually sell.
Repairing the signal made the next question possible: could the new account structure hold stronger return as spend increased?
INR 10.7K platform value from INR 7.0K spend
INR 1.7K purchase value from the same spend
We stopped checkout and zero-value actions from carrying the commercial story.
We used Shopping and selected-product Performance Max around observed product demand.
We kept weak months visible, reallocated budget, and checked every headline against the store.
02 · The rebuild
After tracking repair began, September reached 12.42× and November reached 20.02×. January 2025 closed at 34.32×. We nearly doubled monthly spend from INR 54.4K in June to INR 102.9K in August while retaining 27.58× platform ROAS.
Scale did not rise in a straight line. September 2025 fell to 17.32×. We kept that regression in the record, diagnosed allocation again, and crossed 40× in January 2026.
The platform return was now unmistakably stronger. But a high Ads number still had to survive a store-level reality check.
| Month | Platform ROAS | What it meant |
|---|---|---|
| Aug ’24 | 1.52× | We entered; purchase-only value/cost was 0.25× |
| Sep | 12.42× | Tracking-repair phase |
| Oct | 20.60× | Rebuild in progress |
| Nov | 20.02× | Growth under our management |
| Dec | 25.12× | SOW formalized 2 December |
| Jan ’25 | 34.32× | Scale and governance |
| Feb | 24.07× | Selected-product PMax entered late month |
| Mar | 29.20× | Scale and governance |
| Apr | 21.98× | Regression kept visible |
| May | 23.95× | Allocation review |
| Jun | 31.40× | INR 54.4K spend |
| Jul | 23.77× | Controlled scale |
| Aug | 27.58× | INR 102.9K spend |
| Sep | 17.32× | Regression kept visible |
| Oct | 18.95× | Allocation review |
| Nov | 36.23× | Scale and governance |
| Dec | 33.13× | Scale and governance |
| Jan ’26 | 43.49× | First 40×+ month |
| Feb | 34.50× | Scale and governance |
| Mar | 30.71× | Q1 closed at 36.23× |
| Apr | 31.06× | New PMax entered mid-month |
| May | 54.48× | 40×+ scale |
| Jun | 59.39× | Q2 closed at 48.40× |
03 · The platform-store conflict
Across Q1 2026, Google Ads attributed INR 9.91M in conversion value to INR 273.5K in spend: 36.23× platform ROAS. Shopify recorded INR 3.89M in total sales—9.1% below the complete Q4 2025 total.
We did not scale the largest number blindly. We treated the disagreement as the next constraint and made Google Ads, GA4, and Shopify answer separate parts of the same budget decision.
INR 273.5K spend
All-channel total sales
The available evidence cannot normalize Q4 seasonality, promotions, pricing, or inventory. We use the 9.1% decline as the decision tension—not as a seasonality-adjusted verdict.
The measurement system
Google Ads steered bids and campaign allocation. GA4 checked measured user and revenue direction. Shopify judged the all-channel store outcome. We connected those sources without collapsing them into one invented ROAS.
Platform-attributed conversion value and cost
Measured ecommerce revenue and transactions
All-channel sales, orders, fulfilment, and reversals
1,193 transactions
04 · The business validation
We held Ads spend close to the Q1 run rate while a new Performance Max structure entered in April and became a major attributed-value contributor in May and June. Google Ads closed Q2 at 48.40× platform ROAS. Shopify total sales rose from INR 3.89M to INR 6.77M.
INR 273.5K → INR 278.6K
Q2 2026
INR 3.89M → INR 6.77M
INR 278.6K spend
Exact Q1 → Q2: +74.1%
| Shopify metric | Q1 2026 | Q2 2026 | Change |
|---|---|---|---|
| Total sales | INR 3.89M | INR 6.77M | +74.1% |
| Net sales | INR 3.88M | INR 6.76M | +74.4% |
| Orders | 913 | 1,042 | +14.1% |
| Fulfilled orders | 683 | 904 | +32.4% |
| Dashboard-reported AOV¹ | INR 5,744.56 | INR 7,558.98 | +31.6% |
| Sales-reversal value | INR 1.37M | INR 1.18M | −13.4% |
¹ Shopify displays the AOV figures shown, but the supplied exports do not expose the widget’s exact denominator. Shopify is all-channel. The evidence shows co-movement; it does not isolate how much of the store increase paid media caused.
What a similar buyer should take away
The headline is not simply 1.52× to 48.40×. We first made the signal trustworthy, then rebuilt acquisition, governed the weak months, and required Ads reporting to answer to analytics and store value before the next budget decision.
Questions a careful buyer should ask
No. It is Google Ads conversion value divided by Google Ads cost. Shopify sales and profit are separate business measures.
The platform calculation is verified, and the customer confirms that our operational tracking and performance work began in that month. The signed SOW formalized the relationship later.
No such claim is made. Repairing tracking changed what the account counted; the later campaign rebuild and allocation record show the separate performance progression.
The outcomes moved together, but the evidence does not isolate that counterfactual. We report the Shopify increase as an observed all-channel customer result.
Ecommerce growth diagnostic
Bring us your Google Ads, GA4, and Shopify data. We will identify what the platform reports, what the store retains, and which constraint must be fixed before the next budget increase.
