How We Helped a D2C Brand Triple Their Revenue in 6 Months

In October 2025, a D2C health supplements brand came to us doing ₹80L/month in revenue. They had been stuck at that number for four months despite increasing their ad spend. By April 2026, they were at ₹2.4Cr/month. This is the full story — what we found, what we built, what worked, and what didn't. We're sharing it because the problems they had are the same problems we see in almost every D2C audit we run.

What the initial audit uncovered

Before touching any campaigns, we spent two weeks doing a full audit across their ads, attribution, creative, CRM, and Shopify data. Here is what we found:

Broken attribution They were reporting a 4.8x ROAS on Meta. Blended ROAS calculated from Shopify revenue vs. total ad spend was 1.9x. The gap: iOS signal loss plus view-through attribution inflating Meta numbers. Every budget decision was made on misleading data.

Zero creative testing infrastructure The account had been running 3 ad creatives for 90 days. No new creative had been introduced, no structured A/B tests had been run, and the team had no framework for evaluating what worked. Ad fatigue had set in — CTRs had dropped 40% over the previous 8 weeks.

No retention programme Despite having 12,000 email subscribers and 4,500 past customers, they had no Klaviyo automation beyond a single 3-email welcome sequence. No abandoned cart flow. No post-purchase upsell. No win-back sequence. They were leaving an enormous amount of repeat revenue on the table.

Chaotic Google Shopping structure Their Google Shopping campaigns had no product segmentation. High-margin products and low-margin products competed for budget inside the same campaign with identical target ROAS targets. Predictably, budget flowed to the cheapest products with lowest AOV.

No data pipeline Revenue, ad spend, and customer data lived in three separate places — Shopify, Meta Ads Manager, and a spreadsheet that was updated manually every week. There was no way to see a complete picture of business performance without significant manual work.

The strategy we deployed

We prioritised four parallel workstreams, sequenced so that each one compounded the impact of the others.

Data pipeline and measurement fix

We connected Shopify, Meta, Google, and TikTok to BigQuery via Fivetran. Built a dbt model that calculated daily blended ROAS, new customer acquisition cost, and contribution margin after ad spend. This gave us a single source of truth for all budget decisions within 3 weeks of onboarding. Every optimisation decision from this point was made on real numbers.

Creative testing framework

We introduced a weekly creative testing cadence: 3 new concepts launched every Monday, evaluated on hook rate (3-second view rate) and link CTR at 72 hours, scaled if metrics exceeded account average, cut if they didn't. Over 6 months, we tested 94 creative variants and identified 8 that drove the majority of revenue. These became our control creatives while testing continued.

Klaviyo flows built from scratch

We built out 7 automated flows in Klaviyo: welcome series (5 emails), abandoned browse, abandoned cart (3 emails + 1 SMS), post-purchase upsell, 30-day replenishment reminder, 60-day win-back, and VIP customer early access. Within 90 days, email and SMS accounted for 22% of total revenue — revenue that cost nearly nothing to generate.

Google Shopping restructure

We segmented the Shopping campaigns by product margin tier: high-margin SKUs in one campaign with a target ROAS of 3.5x, lower-margin SKUs in a separate campaign with a target ROAS of 5x to protect profitability. We layered in a Performance Max campaign for prospecting on top, with brand exclusions applied. Google revenue grew 180% within the first 60 days of restructure.

Month-by-month results

Growth was not linear — the first two months were largely groundwork. The compounding kicked in at month three once all workstreams were running simultaneously.

Month 1 (Oct 2025) — ₹88L Slight increase. Data pipeline live, Klaviyo flows launched. Creative testing begun. No major scaling yet.

Month 2 (Nov 2025) — ₹1.1Cr Google Shopping restructure delivered first significant lift. Email flows contributing 8% of revenue. Attribution now accurate — real blended ROAS: 2.4x.

Month 3 (Dec 2025) — ₹1.5Cr Seasonal boost + first high-performing creative set identified and scaled. PMax launched. Email up to 16% of revenue.

Month 4 (Jan 2026) — ₹1.7Cr Post-holiday normalization. Held revenue gains from Dec. Second creative batch identified. Klaviyo flows fully optimised.

Month 5 (Feb 2026) — ₹2.0Cr Full-funnel paid social structure in place. TOFU video campaign building audience for MOFU retargeting. Email/SMS at 22% of revenue.

Month 6 (Mar 2026) — ₹2.4Cr Full compounding effect. Three revenue streams (Meta, Google, CRM) all operating at scale simultaneously. Blended ROAS: 2.9x.

What didn't work — the honest part

No growth story is complete without the failures. Here are the things that didn't go as planned:

TikTok Ads underperformed for this category We launched a TikTok campaign in Month 2 expecting it to be a strong acquisition channel for their 25–35 demographic. CPAs were 2.3x higher than Meta for the same audience. We cut TikTok spend by Month 3 and reallocated to Meta prospecting. Health supplements with longer consideration cycles don't align well with TikTok's impulse-purchase user behaviour.

Early Performance Max cannibalised Shopping We launched PMax too aggressively in Month 2 without proper brand exclusions. Standard Shopping spend dropped 50% in two weeks and total Google revenue was flat despite higher reported PMax ROAS. We rebuilt the structure with brand exclusions, segmented asset groups, and a controlled PMax budget. Lesson: PMax should be introduced gradually, not as a direct replacement.

Influencer campaign did not convert to sales The brand invested ₹4L in a single macro influencer post in Month 3. Traffic spiked but conversion rate was 0.3% — well below site average of 2.1%. The influencer's audience didn't match the brand's buyer profile. We moved to a micro-creator affiliate model in subsequent months with significantly better results.

The key learnings that apply to any D2C brand

Looking back at the full six months, these are the patterns that determined the outcome:

• Fix measurement before scaling. Every week you scale on bad data is wasted budget. The 3-week delay to build the data pipeline was the highest-ROI work we did.
• CRM is the highest-margin growth lever. Email and SMS went from 0% to 22% of revenue in 90 days without any incremental ad spend. For a brand that already has customers and subscribers, this is almost always the fastest path to revenue.
• Creative velocity beats creative quality. Launching 3 concepts per week and ruthlessly cutting what doesn't work outperforms spending 3 weeks producing a polished video. Volume and iteration win.
• Channels have category fit. TikTok is not the answer for every D2C product. Match your channel mix to your buyer's decision-making behaviour — not to what's trending in marketing Twitter.
• Revenue growth compounds when multiple channels run well simultaneously. Single-channel excellence has a ceiling. The jump from ₹1.5Cr to ₹2.4Cr happened because Meta, Google, and CRM were all optimised and scaling in the same window.

What this looks like for your brand

The brand in this case study was not exceptional. Their product was good, their brand was solid, and their team was capable — but they had the same structural problems we find in 80% of D2C audits. Broken attribution, stale creative, untouched CRM, and fragmented Google campaigns. These are solvable problems.

The three-times revenue growth was not the result of finding some secret tactic or unlocking a new channel. It came from fixing the fundamentals and running them well simultaneously. That's the work.