Intent Data 2 min read
Product reviews aren't just social proof. They're the richest intent signal on the public web - declared pain points, switching triggers, feature gaps. The job: find the right reviews, fast, on the right prospects.
Here's how to build a product review finder workflow that scales in B2B prospecting.
Why product reviews beat traditional intent
Traditional intent providers (Bombora, G2 Track) tell you "company X is researching CRM topics." Useful, but vague.
A product review is 10x richer:
- Named buyer: review byline = decision-maker or evaluator
- Exact pain point: "Tool struggles with X feature" = your opening line
- Stage signal: "Considering alternatives" vs "Just switched" tells you timing
- Tech stack context: reviews list integrations, complements, replaced tools
The review sources you should track
Tier 1 (must-track)
- G2 - B2B SaaS dominant, 2M+ reviews
- Capterra - broader category coverage (vertical SaaS too)
- TrustRadius - long-form reviews, deeper insights
Tier 2 (depending on your ICP)
- Product Hunt - early-stage tools, startup buyer signal
- AppSumo - SMB tool-stack indicator
- Reddit (r/sales, r/SaaS, vertical subreddits) - unstructured but high-quality intent
Tier 3 (niche)
- Gartner Peer Insights - enterprise procurement signal
- Glassdoor (work tools mentioned in reviews) - operational pain
The finder workflow
Step 1: Define your trigger queries
For each competitor or adjacent tool, build query templates:
- "switched from [your tool]" - churn risk for you
- "switched from [competitor]" - opportunity
- "missing feature [your differentiator]" - fit signal
- "can't [job to be done]" - pain you solve
Step 2: Automate the scrape
Options ordered by cost:
- Free: Google Sheets + IMPORTXML on review URLs (low volume)
- Cheap: Apify / Bright Data scrapers ($50-200/month)
- Enterprise: G2 API + Capterra partnership ($1k+/month)
Step 3: Enrich + score
For each review found, append:
- Reviewer LinkedIn (Derrick enrich profile)
- Company firmographics (size, industry, region)
- Reviewer's decision-maker score (job title parser)
- Pain-point classification (LLM tag)
Step 4: Route to outreach
Push to your sequence tool (Outreach, Salesloft, LGM) with merge fields containing the actual review snippet - your AE personalizes from real declared pain, not guesses.
Key takeaways
- Product reviews are 10x richer than topic-level intent - they name the buyer, name the pain, signal the stage.
- Cover at least 3 sources (G2, Capterra, TrustRadius). Add Reddit if your ICP includes technical buyers.
- 4-step workflow: query templates → automated scrape → enrich + score → push to sequence with review snippet as personalization input.
- Cost scales from free (Sheets + IMPORTXML, low volume) to $1k+/month (enterprise APIs). Start cheap, scale when ROI is proven.
- Personalization win: an email opening with the prospect's actual review quote converts 3-5x better than generic outreach.
Frequently asked questions
Les product reviews G2 sont-ils accessibles pour toutes les entreprises ?
Yes, G2 reviews are public web data that anyone can browse for free. The real question is volume: manual checking works for a handful of accounts, low-volume automation is free with Google Sheets and IMPORTXML, scrapers like Apify or Bright Data run $50-200/month, and enterprise options like the G2 API start at $1k+/month. Start cheap and scale once the ROI is proven.
Combien de crédits Derrick faut-il pour enrichir une liste de 500 prospects avec leurs product reviews ?
In Derrick, one enrichment consumes one credit per row, so enriching 500 reviewers with their LinkedIn profile data uses about 500 credits, and each extra enrichment pass (firmographics, for example) adds one more credit per prospect. The free plan includes 100 credits/month, so a list of that size means either spreading the work over time or moving to a paid plan.
Peut-on trouver les product reviews d'une personne spécifique et pas seulement d'une entreprise ?
Partially. Many reviews carry a byline, so the reliable path is review-first: find the reviews that match your trigger queries, then identify the reviewer and enrich their profile (LinkedIn, job title, company) to confirm they are a decision-maker. Review platforms organize content by product rather than by person, so you work back from the review to the individual instead of searching by name.
Quelle est la différence entre product review et product rating dans l'enrichissement Derrick ?
A product rating is the numeric score (typically 1-5 stars) a reviewer gave a tool - quick to collect and ideal for scoring and segmenting accounts. A product review is the full written feedback, which names the exact pain points, switching triggers, and feature gaps. Ratings tell you how satisfied an account is; reviews tell you why, and that why is what feeds personalized outreach.
Les product reviews peuvent-ils être utilisés pour du cold emailing en respectant le RGPD ?
Yes, with standard B2B guardrails. Reviews are public data published voluntarily, and using them as research input for relevant, professional outreach generally falls under legitimate interest in a B2B context. Keep the message tied to the business pain the review describes, avoid building mass lists from reviewer names, and always honor opt-outs and platform terms of service.
Combien de temps les données de product reviews restent-elles pertinentes pour la prospection ?
The fresher, the better. A recent review reflects a live frustration or an active evaluation, which is exactly the intent you want to act on, while an old review may describe a stack the company has already replaced. As a rule of thumb, prioritize reviews from the last 6 months and treat anything older than 12 months as background context rather than a trigger.
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