Michael
db5ec084da
Sweep follow-up to 93e43fc. Display labels now consistent across docs,
landing pages, CLI output, code comments, docstrings, and test prose.
Five parallel surfaces touched:
- docs (EN + ES): README, USER-GUIDE, CLI-REFERENCE, and 11 internal
design/planning docs
- landing pages: index + bookkeeper/revops/shopify-pet
- src: CLI module docstrings, _TOOL_DISPLAY dicts in cli_analyze.py
and gui/components/_legacy.py, core module headers, every tool
page's module docstring
- tests: class/method/module docstrings and section-header comments
- test-cases READMEs
Page slugs (1_Deduplicator etc.), tool_id strings (01_deduplicator
etc.), Python class names (TestDeduplicatorWorkflow, FeatureFlag.*),
URL paths, anchor IDs, CSS classes, and asset filenames were left
intact since they're code identifiers / structural references.
All 2033 tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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18 KiB
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353 lines
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<title>DataTools for RevOps — Dedupe Lead Lists Across HubSpot, LinkedIn, and Manual Scrapes · $49</title>
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<meta name="description" content="One tool to dedupe lead lists across HubSpot, LinkedIn, and manual scrapes. International phones (50+ country codes), per-row country normalization, fuzzy match across vendors, fully offline. $49 one-time." />
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<meta name="keywords" content="dedupe lead list, hubspot deduplicate, linkedin lead cleanup, marketing data cleaning, revops csv tool, multi-vendor lead unification, international phone normalization" />
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<link rel="canonical" href="https://datatools.app/revops/" />
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<link rel="stylesheet" href="../_shared/styles.css" />
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<!-- Persona accent: RevOps → vivid violet -->
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<style>
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:root {
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--accent: #c4b5fd;
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--accent-ink: #2e1065;
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}
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</style>
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<meta property="og:title" content="DataTools for RevOps — Dedupe Lead Lists Across HubSpot, LinkedIn, and Manual Scrapes" />
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<meta property="og:description" content="International phones, country normalization, fuzzy dedup with merge — one tool, no upload. $49 one-time." />
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<meta property="og:type" content="product" />
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<meta property="og:url" content="https://datatools.app/revops/" />
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<script type="application/ld+json">
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{
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"@context": "https://schema.org",
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"@type": "SoftwareApplication",
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"name": "DataTools for RevOps",
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"operatingSystem": "Windows, macOS, Linux",
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"applicationCategory": "BusinessApplication",
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"offers": {
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"@type": "Offer",
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"price": "49",
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"priceCurrency": "USD"
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},
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"description": "Dedupe and unify lead lists across CRM, scraping, and manual sources. International phone normalization, per-row country, fuzzy match with merge. Six-tool data-cleaning bundle for RevOps and marketing agencies.",
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"softwareVersion": "1.0"
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}
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</script>
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</head>
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<body>
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<div class="buybar">
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<div class="buybar-inner">
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<div class="brand"><span class="brand-mark">●</span> DataTools <span class="muted">/ for RevOps</span></div>
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<div>
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<span class="price-tag">$49 — one-time, no subscription</span>
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<a class="btn" href="https://gumroad.com/l/datatools?from=revops" rel="noopener">Get DataTools →</a>
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</div>
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</div>
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</div>
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<section class="hero">
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<div class="container">
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<div class="eyebrow">For RevOps · marketing ops · agency lead-gen · audience-builders</div>
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<h1>Dedupe lead lists across HubSpot, LinkedIn,<br /><strong>and manual scrapes — locally.</strong></h1>
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<p class="lead">
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The same prospect shows up as <code>alice@acme.com</code> in HubSpot,
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<code>Alice.Johnson@acme.com</code> in LinkedIn Sales Navigator, and
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<code>alice@acme.com</code> again from your VA's manual scrape. Their
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phone is <code>(415) 555-1234</code> in one source and
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<code>4155551234</code> in another. DataTools fuzzy-matches across
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sources, normalizes phones to E.164 with per-row country awareness,
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and produces one canonical lead per real person — without uploading
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a single contact to a third-party tool.
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</p>
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<div class="cta-row">
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<a class="btn btn-large" href="https://gumroad.com/l/datatools?from=revops" rel="noopener">Get DataTools — $49 →</a>
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<a class="btn btn-ghost btn-large" href="#demo">Try the live demo ↓</a>
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<span class="price-note">One-time payment · cross-platform · runs offline</span>
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</div>
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<div class="stats">
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<div class="stat"><div class="num">50+</div><div class="label">country codes</div></div>
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<div class="stat"><div class="num">3</div><div class="label">CRM sources unified</div></div>
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<div class="stat"><div class="num">0</div><div class="label">cloud uploads ever</div></div>
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</div>
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</div>
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</section>
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<!-- ============= Pain points ============= -->
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<section>
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<div class="container">
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<div class="eyebrow">If your last campaign launch was held up by data hygiene</div>
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<h2>Five pains DataTools fixes before you import to HubSpot</h2>
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<div class="grid">
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<div class="card">
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<span class="icon">💸</span>
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<h3>HubSpot / Marketo / Iterable bills you for every duplicate contact</h3>
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<p>10 k contacts → enterprise tier at $4–8 k/mo. 18 % cross-source duplicate rate from Apollo + ZoomInfo + LinkedIn means you're at 8.2 k unique people but paying for 10 k. Every month. Forever.</p>
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<p class="muted"><strong>What it costs:</strong> $200–$800 per 1 k duplicate contacts — recurring, every month.</p>
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</div>
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<div class="card">
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<span class="icon">🚫</span>
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<h3>Sender reputation tanks when you mail to invalid or duplicate addresses</h3>
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<p>One bad sending session — to addresses your team scraped or imported without hygiene — and your domain reputation takes weeks to recover. Your good campaigns sit in spam folders during the recovery.</p>
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<p class="muted"><strong>What it costs:</strong> catastrophic — entire email programme degraded for 2–6 weeks.</p>
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</div>
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<div class="card">
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<span class="icon">⚖️</span>
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<h3>GDPR makes uploading to a cloud cleaner a legal-review marathon</h3>
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<p>Every cloud-based lead-cleaner needs you to upload your prospect list. Your legal team needs 4–8 weeks to bless that. DataTools is desktop-only — no upload, no DPA, no review, no delay.</p>
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<p class="muted"><strong>What it costs:</strong> 4–8 weeks of legal-review delay per tool, every time.</p>
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||
</div>
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<div class="card">
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<span class="icon">🪢</span>
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<h3>Apollo + ZoomInfo + LinkedIn + manual scrapes all use different schemas</h3>
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<p>Each export has its own column names, scoring scale, country format. Unifying them by hand for one campaign costs 1–3 days. Doing it for every campaign is unsustainable.</p>
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<p class="muted"><strong>What it costs:</strong> 1–3 days per campaign of manual unification + judgement calls that drift across team members.</p>
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</div>
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<div class="card">
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<span class="icon">🛡️</span>
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<h3>Suppression lists across 5+ marketing platforms get out of sync</h3>
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<p>Each platform has its own suppression format. Out-of-sync lists let opted-out contacts slip through, triggering CAN-SPAM / GDPR exposure and the kind of "we got a complaint" email no one wants.</p>
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<p class="muted"><strong>What it costs:</strong> compliance risk + churn-back cost + stakeholder trust.</p>
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</div>
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<div class="card">
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<span class="icon">📞</span>
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<h3>International dialer fails because phone formats vary</h3>
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<p>Calling list to 15 countries with mixed formats means dialler rejects 8–15 % of numbers, your reps spend the day on "number invalid" tones instead of conversations.</p>
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<p class="muted"><strong>What it costs:</strong> rep productivity × failure rate × team size.</p>
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</div>
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</div>
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</div>
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</section>
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<section id="demo">
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<div class="container">
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<div class="eyebrow">Live demo · runs in your browser</div>
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<h2>Try it on a real-looking 3-vendor lead list</h2>
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<p>
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The demo below loads a 25-row lead worksheet combining HubSpot,
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LinkedIn Sales Navigator, and manual scraping — with the same prospect
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appearing in two or three sources, country names spelled three
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different ways (<code>USA</code>, <code>US</code>, <code>United
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States</code>), and 13 different international phone formats. Click
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<strong>Run pipeline</strong> and watch the 5-step pipeline (text
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clean → format → missing → column map → dedup) collapse 25 rows to 19
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with a single canonical record per prospect.
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</p>
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<div class="demo-frame">
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<iframe
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src="https://demo.datatools.app/?p=revops"
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loading="lazy"
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title="DataTools live demo — RevOps"
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sandbox="allow-scripts allow-same-origin allow-downloads allow-forms"></iframe>
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<div class="demo-caption">
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Demo runs on free hosting. Capped at 100 input rows · output
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watermarked. The paid product has no caps and runs entirely offline.
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</div>
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</div>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">Built for the agency RevOps day</div>
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<h2>Three workflows you do every campaign</h2>
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<div class="grid">
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<div class="card">
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<span class="icon">🪢</span>
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<h3>Email-list dedup across lead sources</h3>
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<p>HubSpot exports + LinkedIn Sales Navigator + the VA's spreadsheet, all merged. Fuzzy match across email + phone + name catches the cross-source duplicates that broke your last campaign send.</p>
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</div>
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<div class="card">
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<span class="icon">🌍</span>
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<h3>Multi-platform audience reconciliation</h3>
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<p>Build one canonical audience from Meta, Google Ads, LinkedIn, and your CRM. Each platform exports a different shape; Map Columns aligns them all, dedup merges the survivors with their most-complete fields.</p>
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</div>
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<div class="card">
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<span class="icon">🛡️</span>
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<h3>Suppression-list management</h3>
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<p>Suppression lists need to dedupe across email + phone + first-party identifiers. Add a row, dedupe, ship the canonical CSV to every platform — without uploading the suppression list to any of them.</p>
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</div>
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</div>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">If your campaigns target outside the US — almost everyone's do</div>
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<h2>50+ country codes. Per-row country awareness.</h2>
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<p>
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Your HubSpot list has <code>(415) 555-1234</code>. Your scraped
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list from the same prospect has <code>+1 415 555 1234</code>. Your
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Italian prospect entered <code>+39 06 6982</code>. Your Brazilian
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lead has <code>11 3071 0000</code>. Each comes from a row tagged
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with its country — DataTools reads that column per row and parses
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every phone correctly to E.164.
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</p>
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<ul class="bullets">
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<li><strong>Per-row country column</strong> drives the parser — no global default that bucks UK numbers as malformed US.</li>
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<li><strong>Country-name normalization</strong>: <code>USA</code> / <code>US</code> / <code>United States</code> all resolve to the same ISO-2 code.</li>
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<li><strong>50+ country support</strong> via Google's libphonenumber, including KR, CN, IN, MX, BR, IL, TR, PL, DK, SE.</li>
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<li><strong>Schema enforcement</strong> via Map Columns: project to your CRM's required shape, coerce score columns to integers, reorder fields to match the import contract.</li>
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</ul>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">For platforms that charge per contact</div>
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<h2>Every duplicate you don't catch costs you for the life of the contract.</h2>
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<p>
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HubSpot prices on contacts. Klaviyo prices on contacts. Marketo,
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Iterable, ActiveCampaign — all priced on contacts. Every duplicate
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you don't catch is a recurring tax on your campaign. DataTools
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catches them once, before import, with a fuzzy matcher that's
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tuned to the cross-source noise you actually see.
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</p>
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<div class="callout">
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<strong>Real numbers from the demo:</strong> 25 input rows from
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three sources collapse to 19 — that's 6 duplicates the cross-source
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noise was hiding. On a 50,000-row campaign list, that ratio
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typically saves 12,000+ contacts a month, every month.
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</div>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">The thing every cloud cleaner can't say</div>
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<h2>Your prospects' contact info never leaves your computer.</h2>
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<p>
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Cloud lead-cleaning tools require you to upload your audience.
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That audience is your single most valuable agency asset — and once
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it's on someone else's server, your client's privacy story is
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no longer in your hands. DataTools is a desktop app. There is no
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upload step.
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</p>
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<div class="terminal"><span class="prompt">$</span> python -m src.cli_pipeline campaign_q1.csv --pipeline revops_pipeline.json --apply
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Reading campaign_q1.csv...
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53,802 rows, 14 columns
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Executing pipeline:
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<span class="ok">✓</span> text_clean (160 ms) {cells_changed: 8,205}
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<span class="ok">✓</span> format_standardize (1.4 s) {cells_changed: 41,889 — 50 country codes}
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<span class="ok">✓</span> missing (140 ms) {sentinels_standardized: 6,710}
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<span class="ok">✓</span> column_map (220 ms) {columns_renamed: 4, columns_added: 1}
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<span class="ok">✓</span> dedup (4.8 s) {duplicates_removed: 12,344, merged: 12,344}
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Initial rows: 53,802 → Final rows: 41,458
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Total elapsed: 6.7 s
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<span class="prompt">$</span> # 12,344 fewer contacts to pay for. for $49.</div>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">In the bundle</div>
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<h2>Six tools. One pipeline. One $49 download.</h2>
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<div class="grid">
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<div class="card"><h3>1 · Find Duplicates</h3><p>Fuzzy match across email + phone + name + company; merge survivors with most-complete fields.</p></div>
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<div class="card"><h3>2 · Clean Text</h3><p>Smart quotes from copy-paste, NBSP from spreadsheet exports, BOM from Excel.</p></div>
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<div class="card"><h3>3 · Standardize Formats</h3><p>E.164 phones with per-row country, canonical emails, name casing, ISO dates.</p></div>
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<div class="card"><h3>4 · Fix Missing Values</h3><p>Detect <code>TBD</code>, <code>(unknown)</code>, <code>—</code> across vendor exports.</p></div>
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<div class="card"><h3>5 · Map Columns</h3><p>Project to your CRM's required schema, coerce score to integer, reorder for import.</p></div>
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<div class="card"><h3>6 · Automated Workflows</h3><p>Save the cleanup as JSON. Drop next campaign's combined export on it. Same dedup, automated.</p></div>
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</div>
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</div>
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</section>
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<section>
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<div class="container">
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<div class="eyebrow">Pricing — pay once, own it</div>
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<h2>$49. No subscription. No per-campaign fee.</h2>
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<div class="pricing">
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<div class="card featured">
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<div class="row"><div class="price">$49</div><div class="price-suffix">one-time</div></div>
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<h3>DataTools for RevOps</h3>
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<ul>
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<li>All 6 tools, full pipeline</li>
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<li>Mac · Windows · Linux installers</li>
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<li>Code-signed (no Gatekeeper warnings)</li>
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<li>Free updates for the v1.x line</li>
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<li>Bonus: 3-source unification pipeline preset</li>
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<li><strong>Use on any number of clients</strong> — no seat limits</li>
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</ul>
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<a class="btn btn-large" href="https://gumroad.com/l/datatools?from=revops" rel="noopener">Buy on Gumroad →</a>
|
||
</div>
|
||
<div class="card">
|
||
<div class="row"><div class="price">$149</div><div class="price-suffix">one-time</div></div>
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<h3>Full DataTools Suite</h3>
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<p class="muted">Available when 3+ bundles ship. Includes everything in the RevOps pack plus the Shopify and Bookkeeper bundles. Save $48.</p>
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<a class="btn btn-ghost btn-large" href="#" aria-disabled="true">Coming when ready</a>
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||
</div>
|
||
</div>
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
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<div class="container">
|
||
<h2>Questions</h2>
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||
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<details class="faq">
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<summary>Does this replace HubSpot's deduplication?</summary>
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<p>No — it cleans data <em>before</em> import to HubSpot (or LinkedIn, Marketo, Klaviyo, etc.). HubSpot's dedup runs on already-imported contacts; DataTools catches duplicates that haven't yet cost you a contract slot.</p>
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||
</details>
|
||
|
||
<details class="faq">
|
||
<summary>Does it handle international phones correctly?</summary>
|
||
<p>Yes — via Google's libphonenumber, with 50+ country codes. The killer feature is per-row country: point a column at it (any column with values like <code>US</code>, <code>USA</code>, <code>United States</code>, <code>+1</code>, <code>JP</code>, <code>Japan</code>) and DataTools parses each row in its own region. No more UK numbers bucketed as malformed US.</p>
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||
</details>
|
||
|
||
<details class="faq">
|
||
<summary>Can I use it on multiple clients without paying again?</summary>
|
||
<p>Yes. The licence is per-operator, not per-client. Run it on every agency client's lead list for the same $49.</p>
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||
</details>
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||
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||
<details class="faq">
|
||
<summary>How does fuzzy match work across columns?</summary>
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||
<p>Out of the box, the dedup engine builds default strategies based on column names — typically email + phone with exact match, name with Jaro-Winkler at 85%. You can override via JSON: pick which columns to match on, which algorithm, and what threshold. Strategies survive in the saved pipeline so next campaign uses the same rules.</p>
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||
</details>
|
||
|
||
<details class="faq">
|
||
<summary>What's the audit trail look like?</summary>
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||
<p>A row-by-row CSV: every modified cell with its original value, new value, and which rule fired. A separate JSON file describes the pipeline that produced it. Together they reproduce the cleanup deterministically — your client can verify it on their machine.</p>
|
||
</details>
|
||
|
||
<details class="faq">
|
||
<summary>What's your refund policy?</summary>
|
||
<p>Try the live demo above on the sample dataset before you buy. If DataTools doesn't fit your workflow within 14 days, email for a refund — no questions asked.</p>
|
||
</details>
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
||
<div class="container" style="text-align: center;">
|
||
<h2>Stop paying twice for the same contact.</h2>
|
||
<p class="lead" style="margin: 0 auto 28px;">One $49 download. Catches the cross-source duplicates HubSpot and LinkedIn can't see, normalizes phones for 50+ countries, and saves a pipeline you can re-run on next campaign's combined list.</p>
|
||
<a class="btn btn-large" href="https://gumroad.com/l/datatools?from=revops" rel="noopener">Get DataTools — $49 →</a>
|
||
</div>
|
||
</section>
|
||
|
||
<footer>
|
||
<div class="container">
|
||
<div>
|
||
<p><strong>DataTools</strong> — local data-cleaning for Shopify, bookkeepers, and RevOps teams.</p>
|
||
<p class="muted">© 2026 · Built solo · Shipped from a small office.</p>
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||
</div>
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||
<div>
|
||
<p>
|
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<a href="../shopify-pet/">For Shopify operators</a> ·
|
||
<a href="../bookkeeper/">For bookkeepers</a><br />
|
||
<a href="https://gumroad.com/l/datatools?from=revops">Buy on Gumroad</a> ·
|
||
<a href="mailto:hello@datatools.app">Email support</a>
|
||
</p>
|
||
</div>
|
||
</div>
|
||
</footer>
|
||
|
||
</body>
|
||
</html>
|