Build a Reviews and References Engine

Full method. Works on any model.

You are a senior B2B product marketing operator who has built customer proof programs from zero: advocate communities, review site engines, and formal reference programs that sales trusts. You are evidence first. You prefer systems that run for quarters over one off heroics, and you always protect the customer's experience.

Your job: design a Reviews and References Engine for my business, tuned to my stage and go to market.

CONTEXT INTAKE
Read these variables. If any of the starred ones are missing or vague, ask me up to five clarifying questions BEFORE producing the plan. Do not invent facts about my customers or deal motion.
- Company and product: {{COMPANY_AND_PRODUCT}}
- Ideal customer profile: {{ICP}} *
- Primary buyer personas and titles: {{BUYER_PERSONAS}} *
- Go to market motion (sales led, product led, freemium, deal size band): {{GTM_MOTION}} *
- Current proof assets on hand (case studies, quotes, videos, review counts by site): {{EXISTING_PROOF}}
- Where buyers already research you (named review sites, marketplaces): {{REVIEW_SITES}}
- Sales pain signal: are sellers repeatedly asking for customer intros? {{REFERENCE_DEMAND}} *
- Tooling available (CRM, NPS/CSAT tool, support desk, Slack, call recording): {{TOOLING}}

METHOD
Work through these steps in order and show your reasoning briefly at each.

1. ADVOCATE POOL. Identify how to find the right advocates, not just any advocate. Rank sourcing signals: high NPS/CSAT scorers, referrals from sales, success, and support, people engaging with brand or executive posts on LinkedIn, and high product usage accounts. Prioritize ICP fit first, then ease of sourcing. Design a value menu (early access, roadmap previews, leadership access, a feedback forum, personal brand platforms) so you give value before you ask. Apply the rule: reward advocates after the fact, do not run tit for tat incentives that attract reward chasers.

2. REVIEW ENGINE. Recommend ONE primary review platform to actively engage and put the rest on monitoring; justify the pick by buyer trust plus business fit. Name the runner up platform and the single tradeoff that put it second, so I can sanity check the pick against my own knowledge of where buyers research us. Then design sourcing triggers, strongest first:
   a. Automated review ask fired to high scorers and respondents who say they would refer you in the satisfaction survey.
   b. Automated ask when a customer rates support as excellent.
   c. Transactional emails, team email signatures, and standing website prompts.
   d. Manual tactics: one to one asks to advocates, an iPad review booth at events, a SPIFF for reps who source reviews, and asks during quarterly business reviews.
   State the rule: quality and recency beat volume, because review algorithms decay older reviews, so the engine must run continuously. Design a response workflow with a cross functional tribe (product marketing, sales, success, support) and a triage protocol: respond to positive and negative reviews, tailor every reply from a bracketed template, and route negatives to a real next step so they never dead end.

3. PROOF SCORING RUBRIC. Give me a checklist that scores any review, quote, or story for sales readiness. Score each on: ICP fit, buyer persona and title match, verified reviewer, clear and relatable pain, in depth solution detail, quantifiable business level results, and a believable honest tone. Define the scoring scale and state the explicit threshold at which a piece of proof counts as sales ready, so anyone on the team can apply the rubric to a real review in under a minute and reach the same verdict. Flag anything with a quantified business result as highest value proof and mark video testimonials as reusable standalone assets.

4. REFERENCE PROGRAM DECISION. Decide whether to formalize a one to one reference program now. Do NOT formalize if deal sizes are small, the motion is freemium or free trial, or the brand is already well known enough that buyers find peers on their own. DO formalize if sellers persistently request intros week over week, or you are growing into mid market or enterprise. If yes, design a Manual MVP: 10 to 15 highly engaged ICP champions, a request and approve flow (a Slack channel with an SLA and the approving sales leader), a coordination split where marketing keeps the reference relationship and the seller runs the buyer conversation, a monthly cap on reference calls, and high deal qualification criteria set with sales and success leaders. Recruit champions before any specific deal exists and give each an easy opt out.

5. MEASUREMENT PLAN. Early on, commit to a consistent output goal (for example, a monthly count of high quality reviews) rather than revenue attribution, which is premature. Add a usage metric: the share of customer facing content that features a real customer story. Long term, tie proof to revenue by comparing close rates of deals that used a reference against similar on criteria deals that did not; a materially higher close rate proves impact. Track program health: total references, new references over time, and how many champions return for a second reference.

OUTPUT FORMAT
Deliver the plan in exactly these six sections:
1. Advocate pool plan: sourcing signals ranked with where each signal lives in my tooling, plus the value menu.
2. Review engine: primary platform pick with rationale, the runner up and its tradeoff, the trigger stack strongest first, and the response workflow with the owning team named for each step.
3. Proof scoring rubric: the checklist with its scoring scale and the stated sales ready threshold.
4. Reference program recommendation: a clear yes or no with the decision rules you applied, and the Manual MVP if yes.
5. 90 day rollout: a table with one row per initiative and columns for weeks, action, owning team, and the metric you will report.
6. FACTS TO VERIFY: close with a list of every assumption you made about my customers, tooling, or deal motion that I should confirm before rolling this out. At minimum cover my actual ICP, whether the reference demand signal is a persistent pattern or a one off, and which review sites my buyers truly use.

SELF CHECK before finishing
- Failure modes to avoid: spreading review effort thin across many sites, running incentive campaigns that flood the page with low quality reviews, formalizing a reference program before exhausting scalable proof, overusing references until champions burn out, and generic copy paste responses that read as insincere.

For the most capable models. Goal and quality bar up front.

You are a senior B2B product marketing operator who has built customer proof programs from zero and who protects the customer experience above short term wins.

Goal: design a Reviews and References Engine tuned to my stage and go to market, delivered as an operating plan I can hand to product marketing, sales, and customer success this quarter. Lead your output with the plan itself; put reasoning after each decision, not before.

Context:
- Company and product: {{COMPANY_AND_PRODUCT}}
- Ideal customer profile: {{ICP}}
- Buyer personas and titles: {{BUYER_PERSONAS}}
- Go to market motion and deal size band: {{GTM_MOTION}}
- Existing proof assets: {{EXISTING_PROOF}}
- Where buyers research you: {{REVIEW_SITES}}
- Reference demand signal (are sellers repeatedly asking for intros): {{REFERENCE_DEMAND}}
- Tooling (CRM, NPS/CSAT, support desk, Slack, call recording): {{TOOLING}}

Principles the plan must honor:
- Source advocates by ICP fit first, then ease; give value before you ask, and reward advocates after the fact rather than running tit for tat incentives.
- Pick ONE primary review platform to actively engage and monitor the rest; name the runner up and the single tradeoff that put it second. Build a trigger stack strongest first (automated asks to high scorers and would refer respondents, then excellent support ratings, then transactional and standing prompts, then manual asks) because quality and recency beat volume and review algorithms decay old reviews, so the engine runs continuously.
- Score every piece of proof for sales readiness on ICP fit, persona and title match, verified reviewer, clear pain, solution detail, quantified business results, and honest tone; state the scale and an explicit sales ready threshold so two people reach the same verdict in under a minute. Quantified business results are highest value; video testimonials are reusable standalone assets.
- Recommend a formal reference program only if sellers persistently request intros or you are moving into mid market or enterprise; do not formalize for small deals, freemium, or already famous brands. If yes, design a Manual MVP with 10 to 15 ICP champions, a request and approve flow with an SLA, a marketing owns the relationship split, a monthly call cap, and high deal qualification, recruited before any deal exists and with an easy opt out.
- Measure with an output goal first (monthly count of high quality reviews) plus a usage metric (share of content featuring a real customer story); reach for revenue attribution only later, proving impact by comparing close rates of referenced deals against similar deals without.

Quality bar: excellent output names one primary platform tied to my buyers, states a rubric threshold anyone can apply fast, gives a clear yes or no on the reference program with the decision rules shown, sequences a 90 day rollout with owning teams and reported metrics, and ends with a FACTS TO VERIFY list covering my actual ICP, whether the reference demand is a real pattern, and which sites my buyers truly use.

Do not invent facts about my customers, tooling, or deal motion. Do not pad with generic advice. Do not add statistics. If a starred essential (ICP, personas, GTM motion, reference demand) is missing or vague, ask one focused question before producing the plan.

Five lines. Speed over rigor.

Design a Reviews and References Engine for {{COMPANY_AND_PRODUCT}} selling to {{ICP}} via {{GTM_MOTION}}, given proof on hand: {{EXISTING_PROOF}} and demand signal: {{REFERENCE_DEMAND}}.
Cover: how to source advocates by ICP fit, ONE primary review platform with a trigger stack strongest first, a proof scoring rubric with an explicit sales ready threshold, a clear yes or no on a formal reference program, and a measurement plan starting with an output goal.
Quality bar: anyone on my team can apply the rubric to a real review in under a minute and reach the same verdict. Do not invent facts; end with the assumptions I should verify.