Advertising on Facebook and Instagram for an online store

At least three or four different ideas, not three colors of the same banner. The algorithm quickly determines what works and shows the rest less often - but for this it needs to choose from. And separately for formats: a horizontal frame stretched on a vertical placement cuts off the product, and this is visible in the breakdown by placements. The main problem of the channel is not in the settings, but in the fact that the materials are running out: what worked well for three weeks stops working, and there is nothing to replace it.

According to the increase in the cost of impressions for the same audience with an unchanged budget and a drop in the share of interactions. This is visible a few days before the order sinks. We watch every week and change materials according to the signs, not according to the calendar. Replacing a working creative "because a month has passed" is the same mistake as showing a burned-out one: you yourself remove from circulation something that brings money.

Because some of the browser events do not reach: blockers, privacy settings, interrupted sessions on mobile. The server channel is reporting the same event on your end, and together they give a more complete picture - provided you match up correctly, otherwise there will be double counting and you'll see twice as many sales as you had. This is a separate job with a separate risk, so we put it in a separate service so that the scope is visible. First, we still check the basics: in the store of self-defense equipment from our dimension, there is a Pixel, but there is no Google analytics at all - and this can be seen from the outside in five minutes.

Depends on how many events you give the system. On a store with dozens of orders per month, narrow audiences leave the algorithm without a signal, and broad targeting with good materials often results in a cheaper order. On small budgets and in a narrow niche, the opposite happens. We don't stick to one scheme: we check both on your data and keep the one that won. We show the comparison in the report by numbers, not by description.

Because these are different ways of counting. Meta counts the impression or click conversion in its attribution window, GA4 counts by the last source of the conversion. A discrepancy of one and a half to two times is a common thing and does not mean that someone is cheating. Therefore, in the report we show three numbers separately: the office, GA4 and your accounting system. The main one is accounting, because only it shows paid and unpurchased orders. We will not combine the first two into one figure, it would be fiction.

We do not name the sums on the page, but the arithmetic is simple and does not depend on us. A campaign needs a certain number of purchase events per week to unlearn. Divide this number by your conversion - you will get the number of clicks you need, multiply by the actual cost of a click in your niche. If the result is more than the amount you are willing to spend every month, the channel is not for you yet, and it is fairer to say so before the start. We do this calculation together with you during the free check.

The first sales are possible in the first week, but they do not prove anything yet. Meaningful conclusions — after the campaign exits the learning period and accumulates enough events; in practice it is two or three weeks. We openly call the first month a test period: we test audiences, formats and offers, and scale what survives. If you turn the settings every day this month, training is reset and two or three weeks turn into infinity.

No, this is a normal distribution. We need advertising rights, not publishing rights. But it is worth harmonizing: if there is one promotion in the tape, and another in the advertisement, a person sees the contradiction and does not buy either there or there. We agree on the promotion plan in advance and adjust the campaigns to it, not the other way around.

It also affects paid traffic more strongly than organic traffic: here, everyone who went to the first screen has already been paid. In our measurement on 07/31/2026 on one platform, the first server response went from 126.3ms to 1544.6ms, a twelvefold difference, and this is a matter of store-specific engineering, not engine. The second thing, more expensive than speed, is where the link leads: In a lingerie store, a third of the product addresses checked returned a 301 to another position. A fair line here is this: a fast page does not make an offer attractive. If the price is higher than the market, the store in 200 ms will simply give the person a reason to leave faster.