How much AI shopping optimization costs in Romania

Ongoing optimization. Implementing the fixes and holding visibility as your catalogue and competition shift: filling missing attributes, writing descriptions in citable language, schema on new products, FAQs in Q&A format, monthly monitoring of your position in AI answers. Cost: 300 to 900 Euro per month (1,500 to 4,500 RON), depending on how many products are touched monthly.

Brand authority work. The slowest and most expensive component. AI assistants recommend brands that appear consistently in credible external sources: reviews, comparisons, editorial mentions, category directory listings. This is PR and content work, not feed work. Cost: 200 to 500 Euro per month on top of the technical optimization, and it shows in results only after 3 to 6 months. Most stores defer this component until the data is fixed.

The cost rule for AI shopping: technical data is cheap and fast, brand authority is expensive and slow. Spend first on what you can control, only then on what you have to earn.

Cost by catalogue scenario

The real cost moves first with the number of products, because every product has data to fill, schema to write and a description to rework. Three scenarios cover most Romanian stores.

Scenario	One-time audit	Monthly optimization	Time to results
Small catalogue (under 100 products)	600 Euro / 3,000 RON	300 to 450 Euro / 1,500 to 2,250 RON	1 to 2 months
Mid catalogue (100 to 1,000 products)	800 to 1,000 Euro / 4,000 to 5,000 RON	450 to 700 Euro / 2,250 to 3,500 RON	2 to 4 months
Large catalogue (over 1,000 products)	1,000 to 1,200 Euro / 5,000 to 6,000 RON	700 to 900 Euro / 3,500 to 4,500 RON	3 to 6 months

For large catalogues, optimization does not touch every product monthly. The work runs on priority categories, in order of margin and search volume, while the rest of the catalogue benefits from structure changes applied once.

In-house versus agency: the real cost

The sticker price is not the real cost. The real cost of the in-house route is the time you pull from somewhere else plus the learning curve.

Do-it-yourself. Visible cost: zero. Real cost: your team's time. An AEO audit done in-house by someone learning as they go takes 30 to 50 hours, plus 5 to 10 hours monthly for upkeep. If the hour of the person doing the work is valued at 100 RON, the in-house audit costs you 3,000 to 5,000 RON in time, with no guarantee the schema is implemented correctly. For a founder whose hour is worth far more elsewhere, the in-house route is rarely the cheapest, only the least visible on the invoice.

With an agency. Visible cost equals real cost: the audit plus the monthly retainer. The advantage is not just time saved, but that the schema, data structure and multi-assistant testing are done once, correctly, by someone who has seen the pattern on other catalogues. The downside: you pay from month one, before you see movement in results.

The practical threshold: under 100 products, with someone in-house who genuinely has the time, the DIY route can make sense for the audit. Above that, or if nobody has 40 free hours, a paid external audit pays back fast from the time it frees.

The payback maths

The difference from classic Google Shopping is that a spot in the AI recommendation has no cost per click. The assistant hands the buyer a short list, and you are either on it or not. Let us put numbers to it, as a model you can rerun with your own data.

Assume a Romanian store with a category that brings 200 buyers per month from clear commercial intent. Assume that when a buyer asks an AI assistant what to buy, they get a short list of four stores. If you are on that list and the four split attention roughly evenly, you capture around 25%, about 50 buyers per month, with no cost per click.

At an average order value of 250 RON, that is around 12,500 RON in monthly revenue from the AI channel, with zero click cost. Against monthly optimization of 2,250 to 3,500 RON for a mid catalogue, the payback is fast even if the assumptions are half optimistic, that is 25 buyers instead of 50.

The figures above are an illustrative assumption, not a promise. The number of stores on the AI list, your share and the order value vary by category. What matters is the mechanism: if you are not on the list, your share is zero, no matter how good the product is.

A signal the direction is real

Adobe Analytics reported that in the first quarter of 2026, traffic from AI sources to retail sites in the United States grew 393% year over year, and visitors arriving from AI assistants converted roughly 31% better than those from other sources. This is US market data, not Romanian, but it shows the direction: buyers who arrive via AI buy more often. Romania is a few quarters behind, which means the window to get on the list before it gets crowded is still open.

When it is NOT worth it yet

There are two situations where AI shopping optimization is premature spend, however fashionable the topic.

Very small catalogue, under a few dozen products. The fixed cost of the audit and the structure changes does not amortise over so few products. With a small catalogue, the effort is better spent on feed data for Google Shopping, where the result is measurable sooner.

No competitor visible in AI for your category. Run the test: ask ChatGPT, Perplexity and Google AI Overviews what to buy in your category. If the assistants recommend no one, not even competitors, it means AI does not yet treat that category as a buying one. Do not pay to be first in an empty room. Repeat the test every two to three months, and when competitors appear, that is the moment.

The difference between these two scenarios and the rest is the test. You do not decide on press headlines, you decide on what you see in the assistants for your concrete category.

The concrete action

Before you allocate budget, run the manual test described above for your three most important categories. Note whether competitors show up and who. If they do, move to a structured assessment. If not, set a reminder for three months and focus on the channels that convert today.

If the test shows competitors already recommended and you missing, the cheapest way to know exactly what keeps you off the list, before committing monthly budget, is the AI-Ready Catalog Audit. In five days it maps schema, data structure and brand authority on your catalogue, manually tests five categories and delivers the order of fixes by economic impact. It is the lowest-commitment step: you learn what optimization would actually cost in your case before committing to a retainer.