What about GDPR when ContactOut sources personal emails for EU prospects?

ContactOut's reveal motion sources personal contact data linked to LinkedIn profiles, which under GDPR is personal data the prospect has not given your team consent to process. EU regulators have already moved on similar practices: the French CNIL fined KASPR for scraping LinkedIn contact details without satisfying its information and consent obligations. In the warehouse we keep the per-contact audit trail (reveal source, reveal date, requesting user, search list) so your DPO can answer a subject-access request, suppress a contact on request and document the lawful basis your team is relying on. The compliance call is yours; the data trail is in one place either way.

ContactOut connector

Use your ContactOut data for reporting, automation and AI.

Data Panda brings your ContactOut contact, search-list and credit-usage data together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.

ContactOut

About ContactOut

B2B contact data from LinkedIn, in one click.

ContactOut was founded in December 2015 by Rob Liu and Peter Deng, with Rob Liu running the company as CEO since launch. The product is bootstrapped, run profitably, and is best known for its Chrome extension that pulls personal and work emails plus direct dial numbers off LinkedIn profiles. Recruiters and SDRs at Microsoft, Google and Salesforce sit in the public reference list.

The product covers four pieces a sales or recruiting team genuinely touches: a Chrome extension that reveals contact data on top of LinkedIn and on company websites through ContactOut Anywhere, a web-based Search portal with around twenty filters for building lists from scratch, saved lists and prospect folders for outbound campaigns, and a Preview API plus enrichment API for teams that want the same data inside their own tooling without burning credits on duds. The company puts coverage at roughly three-hundred million profiles and claims an email hit rate near three-quarters on LinkedIn.

The reason to pull ContactOut into a warehouse is that the credit motion hides what finance and RevOps need most. Reveal credits spent per booked meeting, contact decay on enriched records, search-list ICP fit and the share of revealed contacts that ever reach a sequence reply all live in the gap between ContactOut, the CRM and the engagement tool. Next to billing and pipeline, that data turns into a real prospecting picture instead of a credit counter in a browser tab.

What your ContactOut data is for

What you get once ContactOut is connected.

Reveal spend versus booked meetings

ContactOut credit burn, contact freshness and search-list ICP fit sitting next to CRM outcome and invoiced revenue.

Credits spent per booked meeting per ICP segment and per rep
Contact decay on revealed records against bounce and job-change rate
Personal-versus-work-email hit rate per persona and seniority

Reveal-to-sequence handoff

Let a ContactOut reveal fire the right next step in the right tool, without rekeyed data.

ICP-matched reveal pushes the contact into the right sequence in HubSpot or Salesforce
Bounced or job-changed contacts route to a refresh queue automatically
Closed-won in the CRM retires the person from active outbound

AI workflows on prospect data

Train scoring and next-best-action on the contacts your team reveals every day.

Account scoring on firmographics, persona mix and reveal yield
Lookalike modelling from closed-won contacts against the ContactOut graph
Reveal-yield prediction per ICP segment, persona and source page

Custom apps on your prospecting data

Internal tools on ContactOut data for SDR leadership, RevOps and recruiting.

Credit-spend dashboard tied to pipeline produced per segment
ICP coverage view of target accounts with no revealed contact yet
Recruiter sourcing board with contact freshness and last-touch date

Use cases

Use cases we deliver with ContactOut data.

A list of concrete reports, automations and AI features we have built on ContactOut data. Pick the one that matches your situation.

Reveal-to-revenueWhich ContactOut reveal campaigns book meetings that close as deals.

Credit efficiencyContactOut credits spent per qualified opportunity, per segment and per rep.

Contact freshnessBounce and job-change rate on revealed records over time.

Personal vs work emailHit rate and reply rate split across personal and work email per persona.

Search-list ICP fitShare of saved-list profiles that match the ideal customer profile.

Phone reveal yieldDirect-dial reveal volume against connect rate and meeting outcome.

Anywhere vs LinkedInReveal yield from the LinkedIn extension versus ContactOut Anywhere on company sites.

Recruiter sourcingCandidate reveal volume tied to interview booked and offer accepted.

API enrichment ROIPreview API hit rate against credits that ended up spent on enrichment calls.

Account penetrationNumber of contacts revealed per target account in ContactOut.

Bounce decay curveHow fast revealed emails go stale across quarters and segments.

Compliance audit trailPer-contact log of reveal source, date and the user who pulled it.

Real business questions

Answers you will finally get.

Are we paying ContactOut for contacts that ever become pipeline?

ContactOut credit spend lined up against revealed contacts, sequence replies and CRM opportunity stage. Tells finance and RevOps the cost per qualified meeting and the cost per closed deal sourced through ContactOut, instead of leaving the credit counter as the only score.

How fresh are the ContactOut emails our SDRs are sending to?

Bounce rate, job-change frequency and reveal-date age on the ContactOut contact set, trended by quarter and segment. SDR ops sees when a sourced list needs a refresh cycle rather than waiting for reply rate to drop on the next campaign.

Where does ContactOut sit next to our other contact-data tool?

Reveal yield, hit rate and credit cost per qualified meeting compared between ContactOut and the second contact-data tool on the same target accounts and personas. Surfaces the segments where one tool covers what the other misses, and the segments where the second tool can be retired.

Value for everyone in the organisation

Where each function gets value.

For finance leaders

ContactOut credit and seat spend tied to pipeline produced and closed-won, not to reveals burned. Finance can see cost per qualified meeting per ICP segment, the real overlap with a second contact-data contract, and which seats consume credits without producing booked meetings.

For sales leaders

SDR effort scored against booked meetings and pipeline, per search list, per persona and per ICP segment. Coaching stops arguing about reveal counts and starts looking at the segments where this rep's ContactOut sourcing turns into reply, and the segments where it stalls.

For operations

Reveal source, contact freshness and search-list ICP fit in one picture, plus the per-contact audit trail compliance asks for when a prospect questions where the email came from. RevOps spots the lists that quietly burn credits and the segments where contact decay is outpacing reveals.

Ideas

What you can automate with ContactOut.

ContactOut

Pair with HubSpot

Land ContactOut reveals on HubSpot contacts and deals

ContactOut reveal data, search-list membership and credit-usage records land on the matching HubSpot company, contact and deal. HubSpot-native revenue teams see the source of every contact in the deal record, and a closed-won in HubSpot retires the person from active ContactOut search lists so the same prospect does not get re-revealed and re-sequenced.

ContactOut

Pair with Salesforce

Push ContactOut reveals to Salesforce as Lead or Contact

ContactOut reveal events become a Lead or Contact in Salesforce with the ContactOut credit cost, reveal source and search-list name written to a custom object on the record. AE managers see which Salesforce opportunities started with a ContactOut reveal, finance reconciles credit spend to closed-won, and duplicate-rules block a second reveal from creating a duplicate Lead.

ContactOut

Pair with Slack

Route ContactOut signals to the right Slack channel

Positive replies from a ContactOut-sourced contact, ICP-match reveals on target accounts and credit-burn alerts post into the right Slack channel, tagged to the account owner. SDR leaders see wins as they happen and finance sees a heads-up before the credit pool runs out mid-quarter.

ContactOut

Pair with monday.com

Run a ContactOut sourcing pipeline on a monday.com board

Revealed contacts move across a monday.com board through stages like sourced, validated, sequenced, replied and meeting-booked, with the ContactOut credit cost and reveal date on every item. Recruiting and SDR leads run a single weekly review board instead of switching between ContactOut, the CRM and a spreadsheet.

ContactOut

Pair with Calendly

Tie Calendly bookings back to the ContactOut reveal that started them

When a ContactOut-sourced prospect books a meeting through Calendly, the booking is joined to the original ContactOut reveal, search list and credit cost. Sales ops sees which sourcing motion produced each meeting on the calendar, and finance gets a credit-to-meeting cost ratio that does not need a manual stitch in a spreadsheet.

ContactOut

Pair with Intercom

Enrich Intercom inbound chats with ContactOut firmographics

When a new visitor opens an Intercom chat, ContactOut enrichment lands the company, role and seniority on the conversation before the rep types a reply. Sales chat handlers see whether the visitor matches the ICP, route the conversation to the right owner, and skip the qualification questions for the inbound prospects who already self-identified.

Your existing tools

Your data lands in a warehouse. Your BI tools read from it.

You keep the reporting tool you already have. We connect it to the warehouse where your ContactOut data lives.

Power BI Microsoft

Fabric Microsoft

Snowflake Data warehouse

BigQuery Google

Tableau Visualisation

Excel Sheets & pivots

Three steps

From ContactOut to answers in three steps.

Connect securely

OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.

Land in your warehouse

Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.

Reporting, automation, AI

We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.

Two ways to work with us

Pick the track that fits how you work.

Track 01

Self-serve

We set up the foundation. Your team builds on top.

ContactOut connector configured and running
Warehouse set up in your cloud account
Clean access for your Power BI, Fabric or Tableau team
Documentation on what's in the data model
Sync monitoring so you're warned before reports break

Best fit Teams that already have a BI analyst or data engineer and want to own the build.

Track 02

Done for you

We build the whole thing, end to end.

Everything in Self-serve
Dashboards built to the questions your team actually asks
Automations between your systems
AI workflows scoped to real tasks your team runs
Custom apps where a dashboard does not cut it
Ongoing delivery at a pace that fits your team

Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.

Before you book

Frequently asked questions.

Who owns the data?

You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.

How fresh is the data?

Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.

Do I need a warehouse already?

No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.

We already have ZoomInfo or Apollo. Why land ContactOut data too?

ContactOut wins on LinkedIn-sourced personal email coverage that ZoomInfo and Apollo have historically been weaker on. Teams running it next to a database vendor want to see the segments where each tool covers what the other misses before they decide to consolidate. In the warehouse we land both contact sets on the same target accounts and personas, so reveal yield, hit rate and credit cost per qualified meeting are directly comparable instead of two procurement renewal arguments living in two places.

GDPR-compliant

Data stays in the EU

You own the warehouse

A first deliverable live in four to six weeks.

We review your ContactOut setup and the systems around it. Together we pick the first thing worth building.

Book a call See our other connectors