The same prospect shows up as alice@acme.com in HubSpot,
Alice.Johnson@acme.com in LinkedIn Sales Navigator, and
alice@acme.com again from your VA's manual scrape. Their
phone is (415) 555-1234 in one source and
4155551234 in another. DataTools fuzzy-matches across
sources, normalizes phones to E.164 with per-row country awareness,
and produces one canonical lead per real person — without uploading
a single contact to a third-party tool.
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.
What it costs: $200–$800 per 1 k duplicate contacts — recurring, every month.
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.
What it costs: catastrophic — entire email programme degraded for 2–6 weeks.
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.
What it costs: 4–8 weeks of legal-review delay per tool, every time.
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.
What it costs: 1–3 days per campaign of manual unification + judgement calls that drift across team members.
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.
What it costs: compliance risk + churn-back cost + stakeholder trust.
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.
What it costs: rep productivity × failure rate × team size.
The demo below loads a 25-row lead worksheet combining HubSpot,
LinkedIn Sales Navigator, and manual scraping — with the same prospect
appearing in two or three sources, country names spelled three
different ways (USA, US, United
States), and 13 different international phone formats. Click
Run pipeline and watch the 5-step pipeline (text
clean → format → missing → column map → dedup) collapse 25 rows to 19
with a single canonical record per prospect.
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.
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.
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.
Your HubSpot list has (415) 555-1234. Your scraped
list from the same prospect has +1 415 555 1234. Your
Italian prospect entered +39 06 6982. Your Brazilian
lead has 11 3071 0000. Each comes from a row tagged
with its country — DataTools reads that column per row and parses
every phone correctly to E.164.
USA / US / United States all resolve to the same ISO-2 code.HubSpot prices on contacts. Klaviyo prices on contacts. Marketo, Iterable, ActiveCampaign — all priced on contacts. Every duplicate you don't catch is a recurring tax on your campaign. DataTools catches them once, before import, with a fuzzy matcher that's tuned to the cross-source noise you actually see.
Cloud lead-cleaning tools require you to upload your audience. That audience is your single most valuable agency asset — and once it's on someone else's server, your client's privacy story is no longer in your hands. DataTools is a desktop app. There is no upload step.
Fuzzy match across email + phone + name + company; merge survivors with most-complete fields.
Smart quotes from copy-paste, NBSP from spreadsheet exports, BOM from Excel.
E.164 phones with per-row country, canonical emails, name casing, ISO dates.
Detect TBD, (unknown), — across vendor exports.
Project to your CRM's required schema, coerce score to integer, reorder for import.
Save the cleanup as JSON. Drop next campaign's combined export on it. Same dedup, automated.
Available when 3+ bundles ship. Includes everything in the RevOps pack plus the Shopify and Bookkeeper bundles. Save $48.
Coming when readyNo — it cleans data before 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.
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 US, USA, United States, +1, JP, Japan) and DataTools parses each row in its own region. No more UK numbers bucketed as malformed US.
Yes. The licence is per-operator, not per-client. Run it on every agency client's lead list for the same $49.
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.
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.
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.
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.
Get DataTools — $49 →