AI Sales Personalizer

Drop in a list of company URLs. Get back a personalized cold email opener, company summary, pain points, fit score, and an evidence quote that grounds every claim in the homepage content.

Powered by Claude Sonnet 4.6 (Standard) or Opus 4.7 (Premium). Pay only per result. No subscription.

Try it free first

Set mode to preview and run 1 URL. You see the full output (opener, evidence quote, fit score, confidence score) before spending a cent. Switch to standard once you've seen what you're paying for.

What you get back per URL

Field	Description
company_name	Pulled from the homepage
summary	1 to 2 sentences describing what they do
pain_points	3 plausible pain points your product solves
opener	2 sentences max, ready to paste into email or LinkedIn
opener_draft	The model's first attempt before self-critique
opener_critique	What the model thought was weak about the draft
evidence_quote	The exact substring from the homepage that the opener references
evidence_present	True if that quote actually appears in the page (post-hoc verification)
confidence_score	0 to 100, how confident the model is in this result
fit_score	0 to 100, how well this lead fits your offer
channel	Best outreach channel: email, linkedin, or phone
reasoning	Why the fit score is what it is
_meta	Mode, model, processing_ms, from_cache flag

Why this beats Clay / Smartlead / Instantly for personalization

	This actor	Clay	Smartlead
Pricing	Pay per result, $0.15 each (Standard) or $0.25 (Premium)	$149+/mo subscription	$97+/mo subscription
Commitment	None, run when you need it	Annual contract	Monthly minimum
Free preview	1 URL, full output, no charge	Trial only	None
LLM	Claude Sonnet 4.6 or Opus 4.7	OpenAI default	OpenAI default
Anti-hallucination	Self-critique + evidence quoting + post-hoc verification	None published	None published
Caching (no double-charge on re-runs)	30-day cache, same URL + pitch = free	No	No
Setup time	30 seconds	30 minutes	20 minutes

If you only need to personalize 50 leads this week, you pay $7.50, not $149.

Why this output is more trustworthy than typical AI tools

Three structural anti-hallucination guards run on every result:

1. Self-critique inside the model. The model produces a draft opener, critiques its own work (specificity, tone, grounding), and rewrites if its self-assessed score is below threshold. You see both versions plus the critique.
2. Evidence quoting. Every opener must include a specific, observable detail from the homepage. The evidence_quote field shows the exact substring the opener references.
3. Post-hoc verification. After the model returns, we check that the evidence_quote actually appears in the page text. If it does not, evidence_present is false and confidence_score drops.

Sort your dataset by evidence_present desc, confidence_score desc and you have a high-trust pipeline.

Example output

{
  "input_url": "https://www.notion.so",
  "company_name": "Notion",
  "summary": "Notion is a connected workspace combining docs, wikis, projects, and AI for teams that want one tool instead of ten.",
  "pain_points": [
    "Sales teams burning hours on manual research before each outreach",
    "Personalization quality dropping when SDRs scale outreach volume",
    "Marketing and sales data fragmented across separate platforms"
  ],
  "opener_draft": "Saw Notion is positioning as the connected workspace for AI-augmented teams. Curious how SDRs at your scale personalize outbound without burning their week.",
  "opener_critique": "Draft is decent but generic - 'AI-augmented teams' is filler. Tighten the observable detail.",
  "critique_score": 68,
  "final_opener": "Saw Notion's new 'AI Connectors' tier pitches itself at sales and revops teams. Curious how your own SDRs personalize outbound at scale without burning a week of research.",
  "evidence_quote": "AI Connectors for sales and revops teams",
  "evidence_present": true,
  "confidence_score": 84,
  "fit_score": 72,
  "channel": "linkedin",
  "reasoning": "Notion sells horizontally to ops and growth teams, which is exactly the buyer for AI personalization tooling."
}

Pricing

Pay per personalized opener generated:

• Preview: $0 (1 URL only, see output before paying)
• Standard: $0.15 per result (Claude Sonnet 4.6 with self-critique)
• Premium: $0.25 per result (Claude Opus 4.7 with deeper critique, recommended for high-value enterprise lists)

You only pay for successful, charged results. Failed URLs and preview runs are free. Cached re-runs (same URL + pitch within 30 days) are free.

Typical campaigns (Standard):

• 100 prospects: $15
• 500 prospects: $75
• 2,000 prospects: $300

Compare to Clay's $149+/mo minimum or hiring an SDR at $4,500/mo.

How to use it

1. Click Try for free at the top of this page.
2. Set mode to preview. Paste 1 URL into urls. Hit Start. Free.
3. Read the output. Check the evidence_quote matches what you'd expect. Confirm the tone is right.
4. Switch mode to standard. Paste your real list of URLs. Hit Start.
5. Results stream into the dataset as each URL finishes.
6. Export results as CSV, JSON, Excel, or push to Google Sheets via the Apify integration.
7. Sort by evidence_present desc, confidence_score desc to send the strongest openers first.

Caching: never double-charged

Hashed by URL + pitch + tone + mode. If you re-run the exact same combination within 30 days, the cached result is returned and you are not charged. Toggle use_cache off if you want fresh runs every time.

Use cases

• SDR teams: Pre-research the next 200 accounts before Monday morning.
• Founders doing outbound: Replace your "spray and pray" sequences with one tailored message per company.
• Agencies: Add personalization to client outreach without buying another SaaS seat.
• List vendors: Enrich the lists you sell with AI-generated openers as a premium tier.
• Investors: Personalize first-touch messages to founders based on what their company actually does.

What this actor does NOT do

• It does not find email addresses. Use Apollo, Clearbit, or Hunter for that.
• It does not send messages. Use Smartlead, Lemlist, or your own SMTP for sending.
• It does not scrape behind login walls. Public homepages only.
• It does not crawl deep into a site. It uses homepage signals (title, OG tags, H1, H2, body text), where the signal is densest.

Tips for better openers

1. Write your your_product_pitch like you would describe your product to a smart friend. Concrete > vague. "We cut SaaS waste 30 to 45%" beats "we help with cost optimization."
2. Use Preview mode on your first 1 to 3 URLs to calibrate the tone before running a big list.
3. Use the consultative tone if you are not sure. It is the highest converting default in cold outreach research.
4. Run the same list with different tones and A/B test which converts. The cost difference is trivial.
5. For enterprise targets ($50k+ ACV), use Premium mode. Opus 4.7 makes deeper observations and the deeper critique pass catches generic openers.
6. Pair this with Apify's Apollo or LinkedIn Search Scrapers to build the URL list, then enrich here.

FAQ

Q: How do I know the openers reference real facts? Every opener ships with an evidence_quote (the exact homepage substring it references) and an evidence_present boolean (our post-hoc check that the quote actually appears). Filter on evidence_present == true for the strongest results.

Q: Which LLM is this using? Claude Sonnet 4.6 in Standard mode, Claude Opus 4.7 in Premium mode (Anthropic). Both are state-of-the-art for nuanced writing as of mid-2026.

Q: How fast is it? About 4 to 8 seconds per URL on Standard, 6 to 12 seconds on Premium, running 5 in parallel by default. 100 URLs takes roughly 90 seconds to 2 minutes on Standard.

Q: Can I trust the openers? The prompt forbids inventing facts. The model self-critiques. We post-hoc verify the evidence quote. That said, always skim a sample before sending at scale.

Q: Does it handle non-English sites? Yes. Claude is multilingual. The opener will be written in the same language as the input pitch.

Q: Can I get the raw scraped content too? The _meta block includes processing details but not raw HTML. Use Apify's "Website Content Crawler" if you need raw scrapes, then pipe URLs here.

Q: What if I re-run the same URL? Within 30 days, with the same pitch and tone, you get the cached result for free. Toggle use_cache: false to force a fresh run.

Q: Refund policy? Apify's standard refund policy applies. Failed URLs and preview runs are never charged. Contact actor owner for any issues.

Companion actors

• Cold Email Rewriter ($0.10/rewrite). Paste a draft email, get a predicted reply rate + 3 stronger variants. Pair with this actor when you already have a draft you want to A/B.
• SEO Competitor Gap ($0.50/competitor). Find content gaps between your site and competitors. Use when prospecting at larger accounts where decision-makers research before reply.
• LinkedIn Post Personalizer ($0.10/opener). Same value-prop on LinkedIn DMs. Paste their post, get a personalized opener + connection note. No LinkedIn scraping.

Run all four on the same Apify wallet to cover homepages, LinkedIn, cold-email A/B, and SEO competitive intel for the cost of one $99/mo Clay seat.

The B2B Sales Intelligence Suite

This actor is part of a 4-actor suite by Emily Ward that turns a raw TAM list into a ranked, personalised outreach queue:

1. Hiring Signal Detector: who's expanding?
2. Funding Round Tracker: who has fresh capital?
3. SaaS Spend Scanner: what do they pay for?
4. AI Sales Personalizer (you are here): write the opener.

Used together, they 3x outbound conversion vs working from a raw TAM list. What used to take a 5-person SDR team a week takes 1 person 2 hours and ~$95 AUD in Apify credits.

---

Tags: ai sales cold-email personalization outreach sdr b2b claude lead-generation enrichment

Made by Emily Ward, Founder of Cancel Costs. Questions: emily@cancelcosts.com

Pairs well with

• email-finder-verifier: Resolve the named-contact email this opener will be sent to. $0.02 per resolved email.
• contact-details-extractor: Pull every email and social handle from the company contact page. $0.01 per site.
• shopify-store-detector: Qualify the lead's Shopify stack before personalising. $0.03 per store.
• dns-email-footprint: Reference the lead's actual SaaS vendor stack in the opener. $0.01 per domain.
• hiring-signal-detector: Layer in buying-signal hires for a multi-trigger opener. $0.01 to $0.03 per company.

Integrations

This actor works out of the box with every Apify-supported integration:

• API: call via Apify API or any official SDK (Python, JavaScript, PHP, .NET). Returns a clean dataset URL.
• Schedule: set a daily, weekly, or custom cron cadence in Apify Console. Combine with notification for fresh feeds.
• Webhooks: wire ACTOR.RUN.SUCCEEDED to Slack, Discord, Zapier, Make, n8n, Pipedream, or any HTTPS endpoint.
• MCP: this actor is discoverable through Apify's hosted MCP server at mcp.apify.com for Claude, Cursor, Cline, Windsurf, and other MCP clients.
• n8n / Make / Zapier: native HTTP-Request integration. Trigger the actor on schedule, pipe results to Google Sheets, Airtable, your CRM, or any database.

Try it free

Every Apify user gets $5/month in free platform credits (around 250 events at this actor's per-event price). Run preview mode first to confirm output shape before scaling.

New to Apify? Sign up here to get free credits on signup.

What's New

• 2026-06-03: Metadata, categories, and SEO refreshed. Latest version live on Apify Store.

Last Updated

2026-06-03