> ## Documentation Index
> Fetch the complete documentation index at: https://hc.pillargtm.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Product Affinity

> Co-adoption analysis, product affinity scoring, whitespace identification, and prioritized expansion signals

# Product Affinity

The Product Affinity engine analyzes co-adoption patterns across your account base to identify which products are most commonly purchased together, how long cross-sell cycles typically take, and which accounts have the highest-value expansion opportunities. It generates prioritized expansion signals that feed into the [Expansion Pipeline](/data/expansion-pipeline).

<Note>
  Product Affinity is a companion to the Expansion Pipeline dashboard. The Expansion Pipeline shows account-level whitespace and propensity; Product Affinity adds the **product-pair intelligence** layer -- which products lead to which, at what rate, and with what ARR uplift.
</Note>

## How It Works

```
Account product ownership data
  → Co-adoption matrix (product A → product B frequency)
  → Segment-level affinity (Enterprise vs Mid-Market vs SMB patterns)
  → Whitespace identification (missing products per account)
  → Expansion scoring (affinity + readiness + health + propensity)
  → Prioritized expansion signals (ranked by score and estimated ARR)
```

## Affinity Matrix

For every ordered product pair (A, B), the engine computes:

| Metric                     | Description                                                      |
| -------------------------- | ---------------------------------------------------------------- |
| **Co-Adoption Count**      | Number of accounts that own both product A and product B         |
| **Co-Adoption Rate**       | Co-adoption count / total accounts owning product A (percentage) |
| **Avg Time to Cross-Sell** | Average days between start\_date of product A and product B      |
| **Avg ARR Uplift**         | Average contracted ARR of product B for accounts that also own A |

The matrix is computed both at the portfolio level (`segment: "all"`) and per segment (Enterprise, Mid-Market, SMB) to surface segment-specific patterns.

## Confidence Levels

Affinity data quality is scored by sample size:

| Level      | Interpretation                            |
| ---------- | ----------------------------------------- |
| **high**   | Reliable pattern based on sufficient data |
| **medium** | Directional signal with moderate data     |
| **low**    | Insufficient data -- treat as hypothesis  |

## Expansion Scoring

Each whitespace opportunity (account + missing product) receives a composite score from 0 to 1, computed from multiple weighted components:

* **Affinity** -- Co-adoption rate from owned products to the target product
* **Adoption Readiness** -- How well the account uses its current products
* **Account Health** -- Overall account health score
* **Expansion Propensity** -- Account-level expansion propensity from the scoring engine

> Exact component weights are configurable per organization. Default weights are available in the PILLAR Implementation Guide provided to active customers.

## Priority Levels

Expansion signals are assigned a priority from 1 (highest) to 5 (lowest) based on the composite score. Higher scores indicate stronger expansion opportunities deserving immediate attention, while lower scores are monitored over time.

## ARR Estimation

Expansion ARR is estimated using available pricing data, adjusted for account size and segment characteristics.

## Signal Lifecycle

Expansion signals follow a four-state lifecycle:

| Status      | Description                                             |
| ----------- | ------------------------------------------------------- |
| `pending`   | Signal generated, not yet acted on                      |
| `pitched`   | Expansion opportunity has been presented to the account |
| `won`       | Cross-sell completed                                    |
| `dismissed` | Signal dismissed (not applicable)                       |

Pending signals are regenerated on each computation cycle. Signals in `pitched`, `won`, or `dismissed` status are preserved across recomputations.

## Data Model

PILLAR stores product affinity matrices (co-adoption metrics per product pair) and prioritized expansion signals (per-account expansion opportunities with scoring, priority, and lifecycle status). Both are scoped by organization and recomputed on each computation cycle.

> Detailed data model schemas are available in the PILLAR Implementation Guide provided to active customers.

## API Endpoints

```
GET  /api/expansion/affinity
POST /api/expansion/affinity
GET  /api/expansion/signals
POST /api/expansion/signals
PATCH /api/expansion/signals
```

See the [Expansion Intelligence API](/api/expansion-intelligence) reference for full endpoint documentation.

## Access

Available to: CRO/CEO, VP Sales, VP CS, RevOps