> ## Documentation Index
> Fetch the complete documentation index at: https://docs.influship.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Campaign Fit & Evidence
> Understand the AI explanations returned by search, lookalike, and match endpoints
Scored results include reasons you can use to review matches, explain rankings to your users, and refine queries.
## Where Reasons Appear
| Endpoint | Field | What it explains |
| - | - | - |
| `POST /v1/search` | `data[].match.reasons` | Why the creator matches your query |
| `POST /v1/creators/lookalike` | `data[].similarity.shared_traits` | Why the creator is similar to the seed |
| `POST /v1/creators/match` | `data[].match.reasons` | Why the creator is a good, neutral, or poor fit for the campaign |
## Search Reasons
Search results include a score, a plain-text `reasons` list, and a structured `evidence` array that grounds each reason, plus a `confidence` value and a `low_confidence` marker:
```json theme={null}
{
"data": [
{
"creator": {
"id": "a3f1b9c2-d4e5-6f7a-8b9c-0d1e2f3a4b5c",
"name": "Nadia Kaur"
},
"match": {
"score": 0.92,
"confidence": 0.92,
"low_confidence": false,
"reasons": [
"Publishes ingredient-education Reels on sensitive-skin routines",
"High engagement rate suggests an active audience"
],
"evidence": [
{
"text": "Publishes ingredient-education Reels on sensitive-skin routines",
"provenance": "post_evidence",
"fact_id": "b7c1f0a2-3d4e-5f60-8a9b-0c1d2e3f4a5b",
"source_post_id": "23256c2e-51fa-4389-a4a1-945e461e951b",
"evidence_quote": "Today we break down why fragrance wrecks a sensitive-skin barrier…"
},
{
"text": "High engagement rate suggests an active audience",
"provenance": "inferred",
"fact_id": null,
"source_post_id": null,
"evidence_quote": null
}
]
}
}
]
}
```
Use `reasons` for plain-text explanations and `evidence` for the same reasons with source details you can display alongside each match.
### Provenance
Every entry in `evidence` carries a `provenance` label so you can tell a grounded claim from an inference. Strongest first:
| `provenance` | Meaning | What you get |
| - | - | - |
| `post_evidence` | Backed by a specific source post | `source_post_id` identifies the source; `evidence_quote` contains supporting text when available |
| `profile_fact` | Backed by a profile fact | `fact_id`, no `source_post_id` |
| `inferred` | Inferred from profile information, without direct post evidence | `text` only |
An `evidence_quote` contains supporting text copied verbatim from a source post. It is `null` when a supporting quote is unavailable; `source_post_id` is still returned when available. Display the quote and provenance together so users can distinguish post evidence, profile facts, and inferred reasons. Source IDs are identifiers, not public post URLs; do not construct a link from the ID.
### Review lower-confidence matches
`confidence` mirrors `score` (0–1). Use `match.ranking_source` to interpret it: `reranked` indicates AI relevance scoring, while `retrieval_fallback` indicates discovery ranking. See [search quality](/concepts/semantic-search#search-quality). When `low_confidence` is `true`, group the result under a label such as "Additional candidates to review." This flag labels results without changing which creators are returned.
## Lookalike Reasons
Lookalike results explain shared traits between the seed creator and the match:
```json theme={null}
{
"data": [
{
"creator": {
"id": "e8d7c6b5-a4f3-2e1d-0c9b-8a7f6e5d4c3b",
"name": "Marcus Rivera"
},
"similarity": {
"score": 0.87,
"shared_traits": [
"Both focus on fitness and wellness content",
"Similar step-by-step presentation style",
"Comparable engagement patterns on workout videos"
]
}
}
]
}
```
Shared traits describe content topics, presentation style, and posting or engagement patterns.
## Campaign Match Reasons
`POST /v1/creators/match` returns structured campaign-fit output with a decision and supporting reasons:
```json theme={null}
{
"data": [
{
"creator": {
"id": "f9e8d7c6-b5a4-3f2e-1d0c-9b8a7f6e5d4c"
},
"match": {
"score": 0.88,
"decision": "good",
"reasons": [
{
"text": "Reviews protein bars and macro-friendly snacks in weekly Reels",
"provenance": "post_evidence",
"fact_id": "fact_abc123",
"source_post_id": "9b8a7f6e-5d4c-3b2a-1f0e-9d8c7b6a5f4e",
"evidence_quote": "This bar packs 20g of protein and actually tastes like dessert…"
}
]
}
}
]
}
```
| Decision | Meaning |
| - | - |
| `good` | Strong fit for the campaign |
| `neutral` | Could work — review manually |
| `avoid` | Weak fit against the campaign brief |
Campaign-match reasons carry the same `provenance` label as search evidence (`post_evidence`, `profile_fact`, `inferred`). When present, `source_post_id` identifies the source post and `evidence_quote` contains a verbatim snippet. Show the quote and provenance to your users. Neither `source_post_id` nor `fact_id` is a public URL.
## How to Use Reasons
* **Display reasons alongside scores.** A reason such as "Publishes sustainable fashion content" gives users a concrete detail to review.
* **Validate your queries.** If the reasons don't match your intent, the query needs refining — tighten the language or add filters.
* **Compare across results.** Reasons help you understand why one creator ranked higher than another, beyond just the numeric score.
* **Debug broad searches.** When results feel off, the reasons usually reveal whether the query was too vague or the filters too loose.
## Scores vs Reasons
Treat the score as the summary and the reasons as the explanation. A high score with reasons that don't match your intent is a signal to refine the query, not to trust the number.
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