Prepare Shopify for AI purchasing agents.

We make Shopify feeds, products and buying arguments usable for AI purchasing agents.

Companies already recommended by LLMs through getSichtbar

AGS IT-ServiceAGS IT-ServiceHealthcare IT services
William WalkerWilliam WalkerPremium dog accessories
VOLTH MaterialsVOLTH MaterialsIndustrial insulation & aerogel
voids.aivoids.aiSupply-chain SaaS
SeedwiseSeedwiseGrant consulting
Campus FiveCampus FiveAI consulting & automation
NiccosNiccosShopify & e-commerce
RAY AIRAY AIExecutive assistant service
NEONANEONADesigner lighting & e-commerce
MAYKS FahrschulenMAYKS FahrschulenDriving school group
Agentur AusdruckslosAgentur AusdruckslosPerformance marketing agency
Senseven GmbHSenseven GmbHIndustrial AI & predictive maintenance
SPIELMANN Steuerberatung GmbHSPIELMANN Steuerberatung GmbHTax consulting
Zahnzentrum St. GeorgZahnzentrum St. GeorgDental practice
Ad SpecialistAd SpecialistPerformance marketing agency
PUNKT PRPUNKT PRPR agency

What we do.

Shopify Agentic Purchase means preparing product data, feeds, categories and buying arguments so AI purchasing agents can understand, compare and recommend your products.

SHOPIFY AGENTICFeedVariantsAgentPICKSBuyFeed and product logic become agent-readable.

01

Buyer questions

Can an agent compare our products correctly?
Which product attributes decide the purchase?
Which feed fields or buying arguments are missing?

02

Evidence

Feed and attribute audit
Structured buying criteria
Agent test for product recommendations

03

Outcome

Your Shopify products become easier for purchasing agents to understand and compare.

Why it matters

A good-looking shop is not enough for agents. Agents need structured product data and clear buying logic.

0% vs 4%

UCP against ACP

Merchant fee under UCP (Google and Shopify, since January 2026) compared with ACP (OpenAI and Stripe).

68%

trust AI advice

Share of consumers who trust AI recommendations when buying (HubSpot State of AI 2025).

3

signals

Product data, content and buying arguments have to tell the same story.

0

guessing

We test with real agent questions instead of assumptions about agent behaviour.

A nice shop is not enough for agents.

Agents need data, criteria and rules. If that is missing, your product can be skipped or misunderstood.

Required feed fields exist, but buying criteria are weak.
Variants and attributes are inconsistent.
Product text does not explain fit or exclusion.
Agents cannot rank products against alternatives.

The shop becomes a data source for buying agents.

We make product facts, criteria and arguments explicit.

Result

AI should not just find your company. AI should understand when your offer fits.

From product data to clear recommendation.

We check the feed, define buying criteria, improve content and test agent questions.

01

Check feed

Attributes, variants, prices, availability and errors.

02

Build criteria

Which properties decide the purchase?

03

Add content

Product and category texts answer agent questions.

04

Test

We check how AI agents classify the range.

What we actually do.

Shopify feed audit
Attribute and variant cleanup
Buying criteria and product arguments
Product and category content
Agentic product test

What you get.

Feed gap list
Attribute and criteria plan
Product data improvements
Agent-ready buying arguments
Agent test result

Good fit if you want implementation.

You run Shopify and have product data to improve.
Your products are compared by criteria.
You want product data and content to work together.

Not a fit if you only want a report.

You only want a report and no implementation.
You expect a guaranteed mention in one exact AI answer.
Your offer is not clear enough to recommend yet.

When this service is especially useful.

You sell many variants or products with clear criteria.
Your product feed is basic or inconsistent.
You want to prepare for AI shopping agents.

What this should not be confused with.

Shopify GEO

Shopify GEO improves visibility. Agentic Purchase prepares data for buying agents.

Feed tool

A tool distributes data. We check whether the data supports buying decisions.

Product text

Agents need structured criteria, not only nice descriptions.

What it needs.

Audit feed, attributes and product pages.
Improve buying criteria and product facts.
Test how agents understand the catalog.

Clear answers.

Is this only feed cleanup?

No. The feed is one part. Categories, product pages, attributes and buying arguments belong together. A clean feed pointing at thin product pages helps an agent compare about as much as no feed at all.

Is this urgent or can it wait?

For stores with explanation-heavy or variant-rich products it is already relevant. The ChatGPT Atlas browser has been able to complete transactions since October 2025, and UCP from Google and Shopify launched fee-free in January 2026.

What is the difference between ACP and UCP?

Two agentic-commerce protocols. ACP from OpenAI and Stripe charges merchants roughly 4%. UCP from Google and Shopify launched in January 2026 with no fee. For Shopify merchants UCP is the natural fit, ACP opens the ChatGPT channel.

Does this replace Shopify GEO?

No, it complements it. Shopify GEO works on how humans and AI answers find and understand your store. This work makes the underlying product data usable for agents that compare and buy automatically.

How do we know whether an agent understands our store?

We put real buying questions from your category to an agent and record whether your products appear, are described correctly and get compared sensibly. The result is a concrete gap list per attribute, not an assessment.

Is it worth it when AI channels drive little revenue yet?

The channel is small today but growing fast — BrightEdge measures AI-generated traffic rising roughly 25% per quarter. Work on product data also pays into Google Shopping and your own store search, so it is not a single-channel bet.

Let us check whether this service should come first.

One call is enough to see the rough direction: website, content, sources, product data or measurement.