Who WAIR sells to, and how big that market is
One shared definition of the exact accounts we target, scored from 0 to 100, and a defensible view of the market. Built to align in the session and to share with the team. The full ICP lives in the Ideal Customer Profile tab.
Fashion and footwear retailers and brands, value to premium, that own their sell-through across stores, omnichannel, VMI or concession.
Finite and mappable. Roughly 2,000 to 3,000 retailers in Europe with 15 or more stores. You can map all of it.
Agree one revenue band, one store gate and one segment list, so sales, marketing and the data pipeline target the same accounts.
The ICP in one line
Three decisions for today
- Store gate. 15 or 20 stores as the qualifying floor.
- Revenue band. Confirm €50M to €1B as the core, and re-band the scorer away from its current bias toward companies above €100M.
- Segments. Are the adjacents (home, kids, department stores) in or out.
Why it matters: the scorer ranks every company the pipeline finds. If it rewards above €100M while the brand promises €50M to €1B, the team chases bigger logos than the positioning supports, and the market math is built on the wrong base. One aligned definition fixes targeting, scoring and sizing in a single move.
Ideal Customer Profile
The precise account we target. One fit test, a firmographic definition, and the sweet spot we lead with.
The fit test: does the account control its sell-through?
Strong fit
Not a fit
The definition
| Industry | Apparel, footwear, sportswear and lifestyle (core). Home, kids and department stores are secondary. |
| Positioning | Value to premium. Not ultra-luxury, not wholesale only, not D2C only. |
| Revenue | €50M to €1B. Syrup's own published cutoff is "above $50M", which validates the floor. |
| Stores | 15 or more shop floors (the gate to set). Sweet spot 30 to 500. |
| Channels | Two or more: omnichannel, VMI, concession or shop-in-shop. |
| Complexity | Deep size and colour assortments, seasonal drops, inventory spread across locations. |
| Geography | Benelux, DACH, Nordics, Southern & Eastern Europe, UK & Ireland, ANZ. |
The sweet spot we lead with
Readiness signals (the buying window is open)
| Markdown spike | High or rising share of the catalogue on sale (our Markdown Pain Index reads this from the outside) |
| Excel bound | Planning still in spreadsheets, no modern tool |
| Hiring | Open planner, merchandiser or allocator roles |
| Champion move | A known merchandising leader joins a target account |
| Network change | Crossing the store-count gate, opening or consolidating stores |
Scoring, 0 to 100
Every company the pipeline finds gets one defensible number, and the same number means the same thing to everyone. This is how mature SaaS companies do it, and how WAIR's model maps onto that standard.
The standard: two axes, never one
Tools like HubSpot, Salesforce Einstein, Marketo, MadKudu and 6sense all separate these two axes. A single blended number hides whether an account is a bad fit that is busy, or a perfect fit that is quiet.
Fit times intent: what the two axes produce
WAIR's fit model: 100 points across 8 dimensions
| Dimension | What earns the top score | Weight | Share |
|---|---|---|---|
| Revenue | Above €100M (re-band to the €50M to €1B core) | 20 | |
| Industry fit | Apparel, footwear or sports core | 20 | |
| Stores | Above 100 stores (gate at 15) | 15 | |
| Sales channels | Two or more (omnichannel, VMI, concession) | 15 | |
| ERP system | SAP, Infor, Oracle, Microsoft | 10 | |
| Store complexity | Above 20 stores plus shop-in-shops | 10 | |
| Geographic fit | Primary target territory | 5 | |
| Data completeness | Above 80% of fields known | 5 |
Top priority, qualified
Qualified, work the list
Monitor and nurture
Suppress
How a SaaS company keeps the score honest
Market & TAM
Anchor the top on published figures, then narrow to the served market from the bottom up through the pipeline, because no one publishes a clean count of €50M to €1B fashion retailers. That bottom-up number is our most defensible figure.
From the whole market to the accounts we can win now
Why this segment, and why now
of retailers run merchandise planning in spreadsheets.4
lost to over and under stock each year, 6.5% of retail sales.1
typical mid-size Blue Yonder contract, plus 12 to 24 month rollouts.13
How the qualified market splits by territory
| Territory | Countries | Lead | Status |
|---|---|---|---|
| Benelux | NL, BE, LU | Rianne | Proving ground, first |
| DACH | DE, AT, CH | DACH team | Second, proof of repeatability |
| Nordics | SE, NO, DK, FI | WAIR Nordic | Later |
| Southern & Eastern Europe | ES, IT, PT, FR | Southern Europe | Later |
| ANZ | AU, NZ | ANZ | Later |
The largest pools sit in DACH and Benelux. We prove the full motion in Benelux, then clone it to DACH before scaling further.
Customers & rivals
Who already buys, the results they get, and why the white space is real. The ICP is sharp precisely because of where competitors are not.
Proof, and what it says about the best-fit customer
Retailers and brands WAIR works with
Documented case studies (Shoeby, Daka, OFM, Van Dal, Berden, Baukjen) plus retailers and brands named in WAIR's public materials. The mix already clusters in one place: multi-store fashion and footwear that owns its sell-through.
The white space
| Vendor | Who it targets | Relevance to our ICP |
|---|---|---|
| Syrup Tech | Fashion mid-market, above $50M | Closest match, now acquired by Anaplan (Sep 2025) and folded into an enterprise suite |
| Nextail, Toolio, Style Arcade | Fashion mid-market | Heavier, US or single-region, planning first rather than agentic |
| Increff, EDITED | Fashion, enterprise leaning | Heavy, or intelligence only, not in-season allocation |
| RELEX, o9, Blue Yonder | Large enterprise, cross-industry | Too heavy and too costly for the mid-market. This is our home turf. |
Decisions & next steps
Everything resolves to a short list of choices. Make these in the session and the pipeline, the scoring and the market sizing all snap into alignment.
Decide today
- Store-count gate. 15 or 20. Sets the qualified market and the scorer's hard floor.
- Revenue band. Confirm €50M to €1B as the core, and re-band the scorer away from its current bias above €100M.
- Segments. Core versus adjacent: are home, kids and department stores in or out.
- The single sweet-spot profile we lead positioning, content and outreach with.
- Primary persona. VP Planning or Chief Merchant as the economic buyer we anchor the message on.
- Exclusion list. Named accounts already in active conversation, so automated plays do not touch them.
Right after the session
Apply the agreed bands and gate to the 0 to 100 model, then re-rank the existing register.
Generate the defensible SAM and SOM count per territory under the new ICP.
Attach the signal engine so every account carries a fit grade plus a temperature.
How we measure
Sources
1 · IHL Group, Inventory Distortion, 2024. 4 · AbcSupplyChain S&OP survey. 12 · Eurostat via Statista, about 316,000 EU clothing and footwear stores, 2020. 13 · Public pricing and implementation analyses. Customer results from WAIR case studies (Shoeby, Daka) and 2025 press. The €50M to €1B segment count is derived bottom up from WAIR's own pipeline; market software figures vary by report, so cite the specific source before external use.