An AI-built Google Ads search campaign for an online store: four steps

Tell an assistant “build me a campaign for a shoe store” and you get a generic plan. In Tecrube, however, the assistant can read your account and Keyword Planner. So your first sentence should be a research instruction: “Audit my account first, then pull real search volumes for this product category, and only then propose a campaign.”

Our example is an Istanbul-based sneaker store shipping across Turkey. The range covers running, training and everyday shoes; the goal is purchases on the site.

The audit answers three things: is the purchase conversion tracked correctly, is conversion value (basket total) coming through, and where are existing campaigns spending? In chat, ask to “list conversion actions and their status over the last 30 days”.

If the purchase conversion exists but the value column is empty, strategies like target ROAS cannot work; the tag gets fixed first. If the conversion is missing, adding it through Tag Manager can be done in the same Tecrube chat with a preview and approval.

Start with seed terms such as “running shoes, men's running shoes, lightweight running shoes, training shoes”; the assistant pulls monthly volume, competition and bid range from Keyword Planner. Have the output grouped by intent: product-led, brand-led, problem-led (“flat feet running shoes”).

This is where budget reality surfaces. High-volume terms with a bid range above $10 do not belong in a first campaign if product margin is thin. The model cannot make that call; it gives you the table and you decide.

Start the daily budget cautiously: at least ten times the average cost per click, held steady for two weeks. Geography should cover everywhere you ship, though limiting the first week to major cities gathers data faster. Language set to your market, device targeting left open at the start.

The bidding sequence: maximise clicks or enhanced CPC while conversion data is thin; maximise conversions once at least thirty conversions a month have accumulated; target ROAS once value data flows as well. Each transition is made in chat with a preview you approve.

Each ad group carries one intent: “Running shoes”, “Men's running shoes”, “Training shoes”. Match types start with phrase and exact; broad match is opened only once conversion data has settled. The negative list is attached from day one: “used”, “cheap”, “repair”, competitor marketplace names.

At least two responsive search ads per group: one focused on product features, the other on offer and trust (free shipping, easy returns). Sitelink, callout and price extensions enlarge the clickable area. Tecrube shows the whole structure in one preview; the campaign is created paused, you review and enable it.

For the first three days after launch, touch nothing; only read the search terms. From day four, move non-converting and expensive terms into the negative list, read the preview and approve. At the end of week one compare click-through rates across ad groups; refresh the headlines in groups below two or three percent.

Week two brings the budget decision: shift budget toward converting groups, and narrow match types in the others rather than pausing them. Because a budget increase cannot exceed fifty percent in one step, plan growth in stages. Every decision is made in the same chat, looking at the previous week's data.

Every write follows preview → approve → apply; a budget cannot be raised more than fifty percent in one step; every change is logged. For a store owner just starting out, that removes the fear of burning budget on a wrong setting.

A starter prompt you can use: “Audit my Google Ads account and report conversion tracking status. Then pull real volume and bid range for 20 keywords around 'running shoes' and group them by intent. Finally prepare a preview of a paused search campaign with a $30 daily budget targeting Turkey.” The 75 free credits cover the whole flow.