Performance Marketing for Ecommerce & D2C Brands

That question comes before any campaign, and the answer is a number we work out with you. Take the selling price, subtract the cost of the product, packing, shipping, the payment fee, a realistic allowance for returns and any discount, and what remains is the contribution from that order. Advertising has to be paid from it.

From that we derive a break-even return on ad spend for each product or group of products, and a target above it. A product with a thin margin may never justify paid acquisition at all and is better used as a bundle component or left to organic traffic. A product with a generous margin and frequent reorders can justify paying more than the first order earns.

Repeat purchase changes the answer. If a good share of customers buy again within a few months, a first order at break-even is a sound investment. If almost none do, it is not. We ask what you know about repeat behaviour and, where you do not know, we measure it before settling the targets.

Because Google Shopping and similar placements are built from your product data, not from copy you write for an advert. Google decides which searches your products appear for largely from the titles, descriptions, categories and attributes in your feed, and a vague title wastes your budget on the wrong searches or none.

We review the feed in the Merchant Center, correct disapproved items and rewrite titles the way shoppers search, with brand, type and key attribute such as size, colour or material in the right order. We check prices and availability match the product page exactly, since mismatches lead to disapprovals, and we group products so that budget follows margin and not simply volume.

Our Google Shopping ads page describes the set-up. Where the same data also feeds a marketplace, we keep one clean source of truth, which is easier to maintain than several files.

Each does a different job, and mixing them up distorts the results. Search campaigns catch people typing a specific need. Shopping shows the product directly. Performance Max lets Google's automation spread your budget across its channels from your feed and creative, which can work well and can also quietly spend on brand searches that would have converted for nothing.

We therefore separate brand and non-brand reporting, so you can see what the automation really added. We feed Performance Max with strong product data, good creative and exclusions where they help, and we review its search terms and placements regularly. If it only recycles your existing customers, we say so and reduce its budget.

The method for each is on our Google Ads management and Performance Max pages. For a first-time advertiser, we usually begin with Shopping and a small set of high-intent Search campaigns before adding automation.

It starts with the creative, because on Facebook and Instagram the advert is the targeting. Meta's systems find buyers largely from how people react to the ad itself, so a handful of clear, distinct ideas tested honestly will beat endless tinkering with audiences.

We plan creative as a testing programme: several hooks for the first seconds of a video, different formats such as a short video, a carousel and a still image, and different offers, each given enough budget to read. We keep a record of what was learned, so that the next batch builds on it. Product catalogue campaigns show people the items they viewed, and we set them up with sensible exclusions, such as people who bought recently.

Our Meta Ads management page covers the approach, and the comparison of Google Ads and Meta Ads for Indian businesses helps decide where a first budget should go. Creative production for the ads is discussed on our social media marketing page for this industry.

Because each platform counts in its own way. Each credits itself for orders that followed a click or a view within its window, so the same order can be claimed by two platforms and by your email tool at once. Browser privacy settings and consent choices also hide some conversions from the tags altogether.

We handle this in layers. First we make the tracking itself sound, with the purchase event, value and currency sent correctly, and where useful with server-side sending. Then we compare, each month, the platforms' total claimed revenue with actual store revenue and ask a blunt question: did total sales rise in proportion to spend? That blended view, with new-customer share, tells you more than any single platform's return figure.

The set-up work is described on our analytics and CRO page for this industry. When a platform says one thing and your store says another, we trust the store.

A great deal, in India especially. Where cash on delivery is common, a share of the orders an advert generates are never accepted, so the platform reports a sale and the warehouse receives a parcel back, having paid shipping both ways. A campaign that looks efficient at order level can be unprofitable at delivery level.

We ask for your delivered-order and return data by product and, where possible, by campaign, and adjust targets to match. Often the fix lies outside advertising: a confirmation message before dispatch, a small prepaid incentive or a stricter rule on high-risk pin codes. We raise these with you and, for the confirmation step, connect them to the marketing automation work.

The United States has its own version, in return rates for categories such as clothing, where free returns are expected. The principle is the same: judge a campaign by what is kept, not what is ordered.

Demand in ecommerce is lumpy, and budgets should be too. In India the festival weeks around Diwali and the end-of-season sales move buying; in the United States the weeks around Thanksgiving carry the year. Our checklists for the Diwali sale and for Black Friday and Cyber Monday describe what the store must be ready for.

On the advertising side we plan the build-up: remarketing audiences grown beforehand, creative approved early, budgets raised in steps and not in one night, and stock levels checked, since an advert for a sold-out product wastes money. Afterwards we look at what the discounts did to the customers acquired: whether they came back at full price or waited for the next sale.

Outside peak weeks, the work is quieter and more valuable: cleaning the feed, learning from creative tests and strengthening the store's conversion rate, so that the next peak starts from a better place.

Only those you can support, and the ad platforms enforce their own policies on top. Categories such as health, supplements, cosmetics, children's products and weight loss are policed closely, and an account can be restricted for claims the platform judges unsupported. Whether a particular claim is permitted by law is a question for your legal or compliance adviser, and we write to the limits they give us.

Honest reviews matter too. In the United States, the Federal Trade Commission's rule on consumer reviews and testimonials, in effect since October 21, 2024, prohibits fake reviews and testimonials, so we never write them or ask others to, and we use only genuine customer content with permission.

We should also say what we have to show. We have not published ad results for a store, and the nearest related work we can point to, such as our Google Business Profile work for Shruti IT Service, is local-service marketing and not ecommerce. Our approach has to be judged on its method, which you can read here, and on a short audit before you commit.