# AI-referral personalization for a long B2B sales cycle. - working worksheet

Reviewed alongside the Eli guide: https://hireeli.io/resources/ai-referral-personalization-long-sales-cycle

## Decision to make

Keep the buyer's decision context useful across a long sales journey

Owner: ____________________
Review date: ____________________
Canonical page or destination: ____________________

## Buyer questions

- [ ] Keep the buyer's decision context useful across a long sales journey
- [ ] Which evidence should a b2b company with a multi-stakeholder sales cycle preserve?
- [ ] What should be measured after the website change goes live?

## Evidence-led work plan

### 1. The obstacle for a b2b company with a multi-stakeholder sales cycle

One visitor may research fit, security, implementation and pricing across several sessions.

Evidence or artifact: ____________________
Status: [ ] not started  [ ] working  [ ] verified  [ ] blocked

### 2. Use confirmed question or intent context only before you show the relevant proof while preserving the canonical page

Use confirmed question or intent context only.

Evidence or artifact: ____________________
Status: [ ] not started  [ ] working  [ ] verified  [ ] blocked

### 3. Keep consent and identity state

Consent and identity state.

Evidence or artifact: ____________________
Status: [ ] not started  [ ] working  [ ] verified  [ ] blocked

### 4. The limit on the claim: personalization should reduce navigation work

Personalization should reduce navigation work, not manipulate or invent facts.

Evidence or artifact: ____________________
Status: [ ] not started  [ ] working  [ ] verified  [ ] blocked

## Source ledger

- [ ] Google Search Central: AI features and your website: https://developers.google.com/search/docs/appearance/ai-features
- [ ] Google Search Central: guidance on generative AI content: https://developers.google.com/search/docs/fundamentals/using-gen-ai-content
- [ ] OpenAI: publishers and developers FAQ: https://help.openai.com/en/articles/12627856-publishers-and-developers-faq
- [ ] Eli AI Visibility Index methodology: https://hireeli.io/ai-visibility-index/methodology

## Measurement boundary

Baseline date and exact context: ____________________
7-day observation: ____________________
14-day observation: ____________________
30-day observation: ____________________
Known limitations: ____________________

Keep technical eligibility, citations, recommendations, visits, leads and revenue as separate evidence. This worksheet does not guarantee an external ranking or commercial result.