An Ecommerce Ad Agency That Sells Products,
Not Just Clicks,
For Nepali Online Stores.

As an ecommerce ad agency, the first thing we tell Nepali store owners is that standard search advertising is built around keywords you choose. Ecommerce advertising, Google Shopping, Performance Max for retail, and Meta catalogue ads, is built primarily around your product feed, the structured file listing every product’s title, price, category, image and availability. Get the feed wrong, and no amount of bid management fixes it, because the platform is showing your product for whatever it thinks that feed data describes, accurately or not.

We manage ecommerce advertising for Nepali online stores starting with the feed itself, then layer campaign strategy, bidding and creative on top of a foundation that is actually accurate.

A product feed submitted to Google Merchant Center or Meta Commerce Manager needs specific, structured fields done properly: a title that actually matches how people search (not just the internal SKU name), the correct product category, accurate price and availability kept in sync with your actual inventory, and a GTIN or brand identifier where applicable, since Google increasingly deprioritises or disapproves listings missing this data.

We regularly find feeds with vague titles copied straight from a supplier catalogue, categories left as the platform’s generic default, and price or stock data that has drifted out of sync with the actual store, sometimes advertising a product that sold out weeks earlier. Each of these individually caps performance. Together, they explain a large share of the underperforming Shopping and catalogue campaigns we audit.

Return on ad spend, ROAS, revenue generated per rupee of ad spend, is the headline metric most ecommerce ad platforms report, and it can still mislead if margin is not part of the equation. A product with thin margins needs a meaningfully higher ROAS to be genuinely profitable than a high-margin item does, and a campaign optimising purely toward revenue, without margin data, can happily scale spend on low-margin products that generate impressive top-line numbers while barely breaking even, or losing money, once real costs are factored in.

We set target ROAS per product category based on actual margin, not a single blanket target across the whole catalogue, so the campaign’s own optimisation is working toward genuine profitability, not just a bigger revenue number.

Google Shopping captures active search intent, someone typing a product name or category directly. Meta catalogue ads work more on discovery and retargeting, showing products to people based on browsing behaviour and past site visits rather than an active search. Running both from the same underlying feed data, rather than treating them as two separate, disconnected campaigns, keeps messaging and pricing consistent and lets each platform reinforce the other across a buyer’s full path to purchase.

A meaningful share of online shoppers add a product to cart and leave without completing checkout, price hesitation, a distraction, an unexpected shipping cost revealed too late in the process. Dynamic retargeting ads showing that exact abandoned product, sometimes alongside a gentle nudge like a limited-time offer, recover a genuine share of these near-misses at a lower cost per result than acquiring a completely new customer. We set this up as a standard campaign type on every ecommerce ads engagement with sufficient traffic to support it.

Google’s Performance Max for retail campaigns rely almost entirely on feed signals, historical performance data and audience signals to automate targeting across Search, Shopping, Display and YouTube simultaneously. This works well once a feed is clean and there is enough conversion history to inform it, and performs poorly, sometimes wastefully, on a messy feed or a brand-new account with no data yet. We sequence this correctly: feed and tracking fixed first, standard Shopping campaigns establishing a data baseline, then Performance Max layered on once the foundation actually supports it.

In Shopping and catalogue ads, the product image is doing most of the persuasive work an ad headline would do in a standard search ad, since the format is built around showing the product directly. A low-resolution, poorly lit or cluttered product photo consistently underperforms a clean, well-lit image on a neutral background, even when everything else about the listing is identical. We review and, where needed, recommend or coordinate image improvements as part of feed optimisation, since this is genuinely one of the higher-leverage, lower-cost fixes available.

A shopper who clicks a Shopping ad, lands on a fast product page, adds to cart, and then hits a slow, clunky checkout process abandons at a genuinely higher rate than one who sails through cleanly, and this loss happens entirely after the ad has already done its job and been paid for. Checkout page speed, payment gateway reliability and how smoothly the cart syncs with your inventory in real time all sit downstream of hosting infrastructure most ad managers never look at, because it is simply not their part of the stack.

This gap between “the ad account looks healthy” and “the store actually converts” is exactly where a lot of Nepali ecommerce ad spend quietly underperforms, not because the campaigns are wrong, but because the technical foundation underneath them is not built to convert the traffic they are successfully generating.

We check checkout and site speed as part of every ecommerce ads engagement, coordinated with our broader ecommerce SEO work. Where your hosting and platform setup is a good fit, we can bring server and infrastructure management under our own service directly so speed and reliability are actively maintained, not just checked once. Where it is not a fit for what we offer, we will say so and point you toward hosting genuinely suited to a high-traffic checkout flow.

Beyond the budget increases most stores already plan for Dashain, Tihar and New Year, seasonal success in feed-driven advertising depends heavily on preparation done weeks in advance: seasonal collections built and submitted to the feed early enough to be indexed and trusted by the algorithm before the actual demand spike, promotional pricing and sale badges reflected accurately in the feed itself, not just on the site, and stock levels realistic enough to avoid advertising products that sell out on day one of the sale. We plan feed and campaign preparation on Nepal’s own seasonal calendar specifically.

A feed that updates stock status once a day, or worse, manually and irregularly, can keep advertising a sold-out product for hours after it actually ran out, generating clicks and cost with no possibility of a sale, and creating a frustrating experience for the customer who clicked expecting to buy. We set up real-time or near-real-time inventory sync wherever the platform supports it, so the feed reflects what is actually available, not what was available when someone last manually updated it.

Many Nepali sellers run both a Daraz storefront and their own site, and the advertising question that follows is where to put budget. Daraz’s own internal advertising tools promote listings within the marketplace itself, competing directly against other Daraz sellers, including sometimes cheaper competitors selling the identical product. Google Shopping and Meta catalogue ads for your own store build a customer relationship and brand presence you own outright, without a marketplace commission on every resulting sale. We help think through this allocation based on your actual margins and growth goals, rather than defaulting to whichever channel is easiest to set up.

A brand-new product has no purchase or click history for the algorithm to learn from, which means it competes at a real disadvantage against established products in the same automated campaigns until it accumulates enough data. We often run new product launches in a dedicated campaign with a temporarily adjusted ROAS target, deliberately accepting a lower efficiency for a few weeks to build the performance data the product needs before folding it into standard automated bidding.

Ecommerce campaigns are not immune to click fraud, and in competitive product categories we occasionally see patterns consistent with a competitor repeatedly clicking ads purely to drain a rival’s daily budget. We monitor click patterns for anomalies and file invalid click claims where the evidence supports it, alongside general account health monitoring.

We report ROAS, revenue and margin-adjusted performance broken down by product category, not one blended account-wide number, so you can see clearly which parts of your catalogue are genuinely profitable in ads and which need a different approach entirely.

Ecommerce advertising is genuinely ongoing work, feeds need maintaining as your catalogue changes, seasonal campaigns need planning ahead of demand spikes, and ROAS targets need periodic review as margins shift. We price it as a monthly management fee, scaled primarily by catalogue size since that most directly drives the volume of feed and campaign work involved, and as with all our PPC work, this is a flat fee, never a percentage of your ad spend.

Most ecommerce ad management in Nepal treats Shopping and catalogue campaigns like any other PPC account, adjusting bids without ever touching the underlying feed that actually determines what gets shown and to whom. We start with the feed on every engagement, since no amount of bid or budget management fixes a fundamentally broken product data source.

We report ROAS, revenue and margin-adjusted profitability by product category, alongside feed health, so you can see exactly which parts of your catalogue are earning their ad spend.

We manage ecommerce advertising for online stores across fashion, electronics, home goods and specialty retail in Nepal, alongside platform and marketplace partnerships that keep us current on how Google Shopping and Meta catalogue ads actually behave in 2026.

Nobody gets excited about product titles and category mapping, and that is exactly why it stays broken on so many accounts. The stores that consistently win in Shopping and catalogue ads are rarely the ones with the cleverest bidding strategy, they are the ones whose product data was actually correct in the first place.