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Default search vs. AI search: when the switch pays off

An honest decision aid

Eywora Editorial · May 2, 2026 · 8 min read
Standard search
  • 200–400 ms response time
  • ~12% hit rate on B2B queries
  • Manual maintenance required
  • Black-box ranking
vs.
Eywora
  • 47 ms response time
  • 90%+ result match
  • Self-learning from conversion
  • Explainable per result

Not every shop needs AI search. We give you an honest decision aid, even when the answer sometimes means: stay with your standard search.

When standard search is enough

Standard shop searches (Shopware-native, simple Elasticsearch setups) are not bad tools. They are enough if:

  • Your assortment has fewer than 5,000 products
  • Products have simple, linguistically clear names
  • There are no industry synonyms or norm codes
  • Search is not conversion-critical (e.g. most customers buy via category navigation)
  • You don’t have an internal search team and don’t want to build one

If that fits you: stay with the standard search. AI search would not deliver measurable ROI, only cost and complexity.

When AI search is the better match

AI-based search (semantic search, embeddings, re-ranking) is worth it when:

  • Your assortment covers 10,000 to 500,000 products
  • You have technical attributes, norms, material codes or variants
  • Search is a daily conversion driver (search share above 25%)
  • You have GDPR requirements that get tricky with US cloud vendors
  • You want control instead of black box
  • You want a fast setup (days, not weeks)

Three hard comparison points

1. Response time

Standard searches often sit at 200–400 ms. AI searches can be at 47–80 ms when the index setup is right. Every 100 ms delay costs 1–3% conversion.

2. Result quality on complex queries

With a standard search and a query like “stainless steel m12 cap nut set 50pcs”, the hit probability is around 12–18% (all four filters must be maintained explicitly as attributes). With AI search: 90%+.

3. Maintenance effort

Standard search requires manual synonym maintenance, boost rules and re-ranking adjustments for every new category. AI search learns this automatically from conversion signals, which reduces maintenance effort by 60–80%.

faster response time
90%+ result quality on B2B queries
−70% maintenance effort
Three measurable differences between standard and AI search in B2B operations.

The honest ROI calculation

In mid-market manufacturing and wholesale shops, we see for comparable setups:

  • Eywora license: ~€4,800–20,000 per year (depending on assortment tier)
  • Implementation: 0€ internal hours with direct setup (24h standard) or a few days of agency time for custom integration
  • Additional revenue per year: typically €200,000 to €5,000,000, depending on daily revenue
  • Payback: under 14 days for most setups

If you want it exact for your shop: the ROI calculator gives a first estimate, the fit check delivers a defensible number for your shop.

~€12K Eywora license per year €200K+ additional revenue per year
Typical mid-market case. Payback under 14 days in most setups.

What’s not in the pitch-deck logic

A point we emphasize with customers more often than we sell it: AI search is not autopilot. For it to work, you need:

  • Assortment data that is at least minimally maintained (Health Score surfaces this)
  • A clear idea of what search should achieve (optimize margins? avoid out-of-stock? cross-sell?)
  • Willingness to tune ranking logic in the first week, not just observe

Whoever brings that benefits immediately. Whoever is just looking for a magic tool that solves everything alone will be disappointed, with AI too.

Methodology & sources

The figures cited are based on an analysis of search logs from 50+ B2B shops in manufacturing, wholesale and spare parts (Eywora projects and prior projects of signundsinn GmbH, 2023-2026). Conversion-uplift values are averaged across Eywora customers after at least 90 days of live operation. Response times are measured as the P50 median. Results in an individual shop may differ depending on assortment, data quality and search share.

Published May 2, 2026 · Author: Eywora Editorial

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