Every brand running wholesale in gift and lifestyle is making the same set of decisions with the same absence of structure: which stores to approach, what to show them, and how to frame it. The answer is always some combination of instinct, habit, and whoever happened to mention a store name at the right moment.
P23 replaces that process with a decision engine. A structural layer built on a 100-point fit scoring system, a controlled vocabulary of 128 theme IDs, 100 store types, and 217 product category classifications — all drawn from real wholesale data across nearly 3,000 accounts, scaling to 30,000 retailers and 500 brands by summer 2026. It answers three questions with precision, and gets more accurate with every outcome it records.
Wholesale in gift and lifestyle runs on instinct. Ask any brand how they decide which stores to pitch and they will describe trade shows, Faire, word of mouth, cold emails to accounts that looked right. Not a system. A feeling — repeated across hundreds of accounts by people who are often very good at their jobs but are still, fundamentally, guessing.
That guess is expensive.
Wrong stores get pitched. The wrong product leads the conversation. Outreach reads like a template because it is one. Reorders get missed because nobody tracked when the first shipment sold through. The cycle repeats next season, starting from the same place, having learned nothing.
This is not random.
Every wholesale account that became a long-term relationship followed the same sequence: right store, right product on the first order, sell-through, reorder, line expansion. Every account that went nowhere failed at a specific point in that sequence, for a specific reason.
Wrong price band. Aesthetic mismatch. Wrong entry SKU for this buyer type. Category already saturated. None of that is guesswork in hindsight. It is predictable — from signals that exist before a single email gets sent.
The fit between a product and a store is not a matter of taste. It is a measurable overlap across price architecture, thematic identity, aesthetic compatibility, brand adjacency, and buyer psychology.
This pattern scaled Piecework to nearly 3,000 stockists worldwide · Rewined from zero to 32 markets · P23 targets 30,000 retailers and 500 brands by summer 2026
P23 is a wholesale intelligence system. A decision engine. A structural layer that sits underneath the entire outreach process and answers three questions with precision.
It is not a CRM. It does not send emails or manage pipelines. It makes the decisions that determine whether those activities produce results.
Every store is profiled across six dimensions using a locked vocabulary — controlled values, not free text. The same store classified on two different days produces identical output. The pipeline runs in seven defined steps.
Click any step to expand.
The agent ingests every available signal: website, Instagram, Faire profile, brand handles, known stockists. Raw data with no interpretation yet. The more that gets captured here, the more accurate everything downstream becomes.
Store URLsInstagramFaireBrand handlesVisual style is extracted from photographs — not from a text description, but from actual images. Product photos, store photography, Instagram grid, brand imagery. This feeds the aesthetic dimension of the fit score directly.
Visual style from photos32 aesthetic valuesCompatibility matrix inputTwo parallel tagging agents run simultaneously. The Store Tagger classifies 97 fields — 36 CORE and required for routing. The Product Tagger classifies 58 fields — 31 CORE. Every field is a locked vocabulary value. No free text at any point.
97 store fields · 36 CORE58 product fields · 31 CORE128 controlled theme IDs100 store type valuesTag Governance Validator checks every enum value, null rule, and confidence threshold. Then the Fit Score Calculator runs across six weighted dimensions producing a 100-point score. The Hard Block Gate runs first — no exceptions.
Hard Block · runs first, alwaysFit Score · 100pt · 5 tiersExecution Score · sequencing onlyTwelve sequential rules determine the optimal entry product for this specific store. Returns Top 3 qualified products with per-dimension rationale. Never defaults to the bestseller. Category saturation, price gate, buyer risk modifier, and aesthetic boost all factor in.
12 selection rulesTop-3 with rationaleCategory saturation checkA confidence formula — 60% coverage ratio, 40% confidence mean — routes each record to one of five handling outcomes. High-confidence Tier 1 matches can dispatch automatically. Lower confidence routes to human review. Any human correction triggers immediate recalculation.
RT-1 Auto · Fit≥85 · conf≥0.85RT-2 Quick · 2hr SLART-3 Full · 1 day SLAThe profile of Tier 1 stores is used to actively search for stores the brand doesn't know yet. Common profile attributes become the search template. New qualifying stores are added with full tags and scores applied immediately.
Tier 1 profile → new store searchFull pipeline on new storesA human reviews every recommendation before anything sends. Every outcome writes back with specific field updates. Nothing resets. Everything accumulates.
Other tools make execution faster within an existing process. P23 replaces the process with one that learns.
No other platform, product, or service in gift and lifestyle wholesale does this.
Fit is a structured overlap across six measurable dimensions. The total produces a Fit Score out of 100 and places the store in one of five tiers. Score high enough and a store becomes Tier 1 — eligible for automatic dispatch.
Adjust each dimension below to see the Fit Score and tier change in real time.
Woods Grove — Brooklyn — Independent, multiple locations.
They carry BAGGU, Brooklyn Candle Studio, DOIY, Chunks. Price band $18–$70, volume in the $25–$50 range. Visual identity: playful, graphic, colorful. Buyer: trend-aware but not risky.
Scores high on aesthetic match, price alignment, brand adjacency, and giftability. Tier 1 fit — 88 points. Tier 1 does not mean send the bestseller. It means the system has enough signal to make a precise decision about what to send first.
Not "this is our best seller." References their mix of playful accessories and home objects. Positions the SKU between categories — shelf presence and giftability in one. It reads like someone walked the store.
The system does not lead with a core puzzle. It selects a visually strong, theme-forward object with immediate shelf presence in the $30–$45 range. They already carry puzzles — category saturation is flagged. The right SKU must feel like an impulse gift.
First order converts. Fast sell-through. Reorder window opens. The account becomes expandable into adjacent categories and higher price tiers.
The system does not log "failed" and move on. Category saturation for this store type is flagged as high. Puzzle entry is deprioritised across stores with this profile. The next recommendation shifts to an adjacent category.
Every store in the database that shares Woods Grove's structural profile is now smarter on the next pass. A single failed pitch produces usable intelligence across dozens of future decisions.
The vocabulary is the hard part. 128 controlled theme IDs. 100 store type values across 14 clusters and a 3-level hierarchy. 32 store visual style values. 25 product visual style values. A 32×25 compatibility matrix. Not free text — a structured table with defined levels that feed directly into scoring.
It took months to build. From real accounts — not scraped data, not a generated taxonomy. Built backwards from what actually converted and what didn't.
Every field is a locked value. No free text. The same store classified on two different days produces the same output. Reproducing this vocabulary alone would take most operators six to twelve months.
Every outcome writes back with specific field updates. First order, reorder, rejection, wrong SKU — each adjusts the model in a defined way. Two years of that cannot be caught up quickly. The system does not plateau. It compounds.
Each brand contributes to a shared retailer base. Response patterns, category saturation, theme conversion data — anonymised but real. Multi-brand operation is where the intelligence advantage becomes structural.
The scoring logic, buyer psychology fields, SKU selection rules — not generic B2B logic. Built for gift and lifestyle wholesale by operators who have run it for twenty years. That specificity cannot be replicated with a generic tool.
P23 was not designed as a product. It was extracted from a method that ran across nearly 3,000 accounts and 32 markets before anyone thought to turn it into a system. It now targets 30,000 retailers and 500 brands by summer 2026.
The entry SKU was selected for this store from twelve sequential selection rules applied to this store's specific profile. Not defaulted from a catalog.
Structural mismatches are caught before outreach begins. Tier 5 stores are identified and removed before any human time is spent on them.
The angle is built from store-specific signal. It reads like someone walked the store, because the system effectively did.
The right product in the right store converts and reorders. The wrong product — even in a high-fit store — stalls the relationship before it starts.
Display longevity data and reorder tracking means follow-up happens before the window closes — not after the buyer has moved to the next brand.
Every outcome makes the next decision more accurate. Year two is structurally better than year one. That gap is not closable from the outside.
Put two brands side by side. Same size, same category, same account list. One is operating inside P23. One is not. On day one the difference is invisible.
The gap opens quietly.
By year two the gap is structural. The brand without the system cannot close that distance by working harder.
The gap does not stabilise. It widens.
The fastest entry point is the Retailer Audit. Provide your existing wholesale account list and receive full scoring, profiling, and priority ranking across every store — with recommended actions per account. Delivered in 7–10 working days.