For e-commerce agencies
Qualified shop leads. AI-analyzed. With revenue estimation and decision-maker contact — export-ready for your CRM.
Book a 15-min callYour challenge
The data reality
13M shops worldwide, 600k in DACH
Among them are your ideal customers — but also hundreds of thousands of hobby projects, dead domains and shops without budget. Searching manually burns time.
Today
Manual prospecting does not scale
Every prospect has to be researched individually: which shop system? what does the site look like? is it even worth pitching? Impossible at 600k shops.
No context
Cold outreach without substance
"We build shops" convinces no one. But: "Your shop does ~80k/month on a standard theme without email marketing — there is money on the table" absolutely does.
E-commerce market
Your best customers do not know they need you
Shops with solid revenue but mediocre design, missing tools and an unoptimized checkout — those are your ideal customers. The pipeline finds them automatically.
Already in use
Still under the radar — but not for long. Whoever joins now has the head start, before every agency prospects with this.
0
E-commerce agencies
actively use the pipeline for outbound
0M
Leads processed
across DACH — filtered, classified, scored
0
Qualified shops
with verified revenue potential ≥100k€/month
0
Relevant contacts
CEOs and decision-makers with verified email
Ahead of the wave — not behind it.
15 minutes to see if it fits.
The 7-stage pipeline
Conversion rates based on validated test runs with 2,200+ leads. Stages added or removed as needed.
Stage 0
CSV pre-filter
Remove duplicates, inactive domains and tiny shops. Only DACH with minimum traffic.
~250,000
€0
Stage 1
Shop validation
Is it an active shop? Platform, installed apps, payment, email tools, B2B/B2C classification.
~180,000
72% pass
Stage 2
Location filter
Imprint + address confirms physical DACH presence. Legal entity detection.
~140,000
78% pass
Stage 3
Traffic analysis
Monthly visitors, DACH share, growth trend. B2C: ≥10k, B2B: ≥5k visitors.
~51,000
36% pass
Stage 4
AI shop analysis
Screenshot + source code: design quality, UX flaws, conversion blockers, missing elements.
~45,000
89% pass
Stage 5
Revenue estimate
Traffic × avg. cart × conversion = estimated monthly revenue. Catalog depth, price level.
~11,000
24% ≥100k€/mo
Stage 6
Contact enrichment
Identify CEO/founder, LinkedIn profile + verified work email.
~9,500 ✓
85% hit rate
← Swipe to see all stages →
How it looks in your CRM
Every qualified shop lands as one row — enriched fields, buying signals, prioritization score, and ready-to-send LinkedIn and email copy.
← Swipe to see all columns →
Sample export rows — field mapping adapts to HubSpot, Pipedrive, Salesforce, or CSV.
What the pipeline detects per shop
Shop system & platform
Exact platform identification
Automatic detection from source code + metadata:
- Shopify, WooCommerce, Shopware, Magento, Wix, JTL, PrestaShop
- Theme/template detection (e.g. Dawn, Prestige, Impulse)
- Custom build vs. standard theme — at a glance
Tech stack & components
Installed tools & missing tools
Two detection layers — database + HTML scan:
- Email marketing: Klaviyo, Mailchimp, Brevo, Omnisend, Uptain & more
- Payment: Klarna, PayPal, Stripe, Mollie, Amazon Pay
- Tracking & analytics, reviews, chat, trust badges
- B2B/B2C classification from 35+ signals (DE + EN)
AI screenshot analysis
Visual quality & UX scoring
AI vision analyzes one or more screenshots:
- Design quality: professional, outdated or amateur
- Conversion elements: CTAs, trust badges, urgency, email popup
- Industry-specific: fashion needs premium design, B2B does not
- Concrete verdict: "qualified", "uncertain" or "rejected" with reasoning
Revenue, traffic & potential
Revenue estimate + growth trend
Automatic calculation from multiple signals:
- Monthly visitors × DACH share × conversion × AOV
- Growth trend: rising, stable or declining
- Catalog depth, product count, price level (low/medium/high)
- Missing tools = concrete upsell potential for you
How data turns into a perfect pitch
Example: a lead from the pipeline
Pipeline output
- Shopify · Dawn theme (standard)
- ~85,000 visitors/month, 92% DACH
- Est. revenue: ~€120k/month
- Email tools: none detected
- No urgency, weak CTAs, no popup
- Design: "functional but outdated"
- B2C, trend: stable, AOV: €85
- Contact: Max Mustermann, CEO, LinkedIn + email
Your outreach
Hi Max,
I had a look at modehaus-beispiel.de — you do solid revenue with ~85k monthly visitors, but your standard theme and missing email marketing are likely costing you 20–30% conversion.
We have helped similar shops add €40k/month with a custom theme + email flows. Worth a quick chat?
Context > cold calling
- You know the shop system — your pitch is instantly relevant
- You know the revenue — you can quantify the ROI
- You see missing tools — concrete improvement suggestion
- You have the screenshot — visual evidence for your thesis
- You reach the CEO directly — no gatekeeper
- You know B2B vs. B2C — pitch matches the audience
3 weeks to a finished lead engine
Example setup. Stages and timing are tailored to your requirements.
Week 1
Filter pipeline & requirements
- Nail conditions, data needs & pass criteria together
- Stages 0–3: CSV filter, shop validation, location, traffic
- Calibrate platform, tech & B2B/B2C detection
→ ~51k relevant shops filtered
Weeks 2 & 3
AI analysis, revenue & enrichment
- Stage 4: AI vision for screenshot analysis + quality scoring
- Stage 5: refine & validate revenue estimates
- Unlimited persona search with up to 3 best-in-class waterfalls
- Email + phone enrichment with up to 3 best-in-class waterfalls
- Test run with 1,000 shops — joint iteration on your ICP
- End-to-end integration test
→ Full pipeline live, calibrated to your ICP
Week 4
Production
- Production run on the full DACH dataset
- Result report with funnel statistics
- CSV export: import-ready for your CRM or outreach tool
→ ~9,500 qualified leads delivered ✓
What's the impact for you?
What you get
Complete pipeline. Your data. No lock-in.
- Lead pipeline with AI vision analysis — stages flexible
- DACH-wide shop dataset as foundation
- Platform, tech & B2B/B2C detection
- Revenue estimate + conversion insights per shop
- Unlimited persona search with up to 3 best-in-class waterfalls
- Email + phone enrichment with up to 3 best-in-class waterfalls
- Calibration to your ICP — iterated together
Stages can be added or removed as needed. One-time setup, ongoing API costs: cents per qualified lead. Setup typically pays for itself after a single customer.
Impact calculator
Set the values that match your business.
Investment on request · clarified in a 15 min call
Three honest questions
Could you use more sales?
Do you know that thousands of untapped leads are waiting for you online?
Would it be an edge to find them first — before everyone else does?
15 minutes. No pitch bingo. We check if it is a fit.