Customer journey analysis:
What customers ask before they search for your product.

An AI persona is a simulated model of a typical customer situation. It puts itself in your customer's shoes: what problem do they have, what questions do they ask, what do they doubt, and what convinces them in the end? This quickly reveals questions and decision hurdles that never show up in a keyword list.

Important for your decision: an AI persona delivers hypotheses, not customer truth. That's why every insight carries one of three labels:

• Observed signal:

  • Backed by your data, for example by search queries, reviews or questions to customer service.

• Plausible hypothesis:

  • Consistently derived, but not yet confirmed in your data.

• Test before implementing:

  • Check it on a small scale first, before budget goes into implementation.

But the result only becomes reliable once it is matched against your data.

A target group analysis describes who your customers are. The sprint shows what these people want to know before they buy. Industry, age, purchasing power and channels help with targeting. But they don't explain why a visitor leaves your store again or buys from a competitor.

The difference at a glance:

• Target group analysis:

  • Who buys? Demographics, industry and channels. The result is a profile.

• Customer Insight Sprint:

  • What does this person ask, when do they doubt, and where does your Shopware or Shopify store have no answer? The result is ten prioritised measures.

An existing target group analysis is therefore not a substitute but a good starting point. It feeds into the kick-off and makes the sprint even more accurate.

No. The customer journey analysis is a short, structured analysis and strategy process, not a representative study. Classic market research with surveys or in-depth interviews often takes months and costs many times as much. For small and mid-sized stores, that is rarely economical for every single product range.

The sprint takes a more pragmatic route:

• Use what is already there:

  • Search data, reviews and questions to customer service already exist in most stores but are hardly ever analysed.

• Get clarity fast:

  • After two to three weeks, you know where the biggest gaps are and what to do first.

• Go deeper where it matters:

  • If questions arise that only a real survey can answer, that goes into the roadmap, together with the questions you should then ask.

That way you only invest in market research once it is clear what for.

Four things are enough to get started: the product range, your target group, the store URL and a date for the kick-off. The more real signals are added, the more reliable the result becomes.

Helpful for the matching are, for example:

• Search data:

  • Google Search Console or queries from your store search show what your customers actually search for.

• The voice of your customers:

  • Reviews, product ratings and anonymised topics from customer service show what customers have doubts about.

• Behaviour in the store:

  • Entry pages, drop-offs and cart data show where customers get stuck.

The fixed price includes matching with up to two data sources. Which ones is agreed together in advance, and only what you release is used.

Yes. In that case, the customer journey analysis works on the basis of assumptions and publicly available signals. These include, for example, questions in forums and advice portals, answers from AI assistants such as ChatGPT, Claude or Gemini, reviews on marketplaces, and the content of your store and your competitors.

The result clearly labels which assumptions could not be checked against internal data. So you know exactly what you can build on right away and what you should test first.

It often also becomes clear which data you are missing and how you can collect it in future with little effort.

The sprint pays off wherever customers think, compare or hesitate before buying. That applies equally to B2B and B2C stores.

Typical signs that the sprint is worthwhile for your store:

• Products that need explaining:

  • Your customers need advice before they buy, for example on technology, material or application.

• A large range:

  • Many similar products make the decision difficult, and customers don't find the right one.

• Decent traffic, weak conversion:

  • Visitors come, but too few buy, and nobody knows exactly why.

• Long decision paths:

  • There are several steps and many questions between the first problem and the purchase.

The approach works regardless of platform. arboro has the most project experience with Shopware and Shopify, so the measures for these systems are correspondingly concrete.

You don't get a presentation for the drawer, but a roadmap your team or a service provider can work with immediately.

The result at a glance:

• Two AI personas:

  • With situation, motives, questions and doubts, tailored to your product range.

• Customer journey map:

  • All stages from the first problem to the purchase, with the questions and hurdles at every step.

• Gap analysis:

  • Where your store currently has no answer in search, content, navigation and conversion.

• Roadmap with ten measures:

  • Prioritised by impact, effort and urgency, each measure labelled as signal, hypothesis or test.

• Final workshop:

  • 90 minutes in which the results are assessed together and the next steps are agreed.

Afterwards, you know what your customers want to know before they buy, and which measures you should tackle first.

The fixed price of €4,900 excl. VAT includes the customer journey analysis and the roadmap, but not the implementation. That is deliberate: you decide freely who implements which measure.

You have three options:

• Implement in-house:

  • Every measure is described so that your own team can work with it directly.

• With your service provider:

  • The roadmap is also clear and actionable for existing agencies or freelancers.

• With arboro:

  • If you wish, arboro handles the implementation, from SEO, GEO and content through conversion optimisation to development in your Shopware or Shopify store.

A follow-on contract is not a condition. The sprint has to be worth it on its own.

Before the project starts, we agree together which sources are released and how they are used sparingly. Your data remains your data.

In concrete terms:

• Released sources only:

  • Only what you explicitly release is used.

• Patterns, not people:

  • Topics and patterns are enough for the analysis. Your customers' names or contact details are not needed.

• No unchecked route into AI tools:

  • Personal or sensitive information does not go into AI tools without an agreed procedure.

The details are agreed on a project basis.

The best fit is the product range where the most revenue is at stake or where customers hesitate most often. That is often not the largest category, but the one where advice, comparison or uncertainty shape the purchase decision.

Good candidates to start with:

• High share of revenue:

  • Every better answer has a direct effect on your revenue here.

• Many queries:

  • Where customer service answers the same questions again and again, the gap is out in the open.

• Strategically important:

  • A new or growing product range in which you want to beat your competitors.

In a free initial consultation, we clarify which product range suits your customer journey analysis and which data is available for it. And if the sprint isn't right for your store, we'll tell you.