Articles on where go-to-market data is going, playbooks you can run today, and reports on what the data says - written by the team building the agents that source, enrich, verify and deliver it.
Explore 64 guides to AI agents, prospecting, business data and reliable delivery, with examples and sources.
Call the similar-companies tool over MCP from your own agent: a seed domain in, 25 lookalikes out as JSON with headcount, industry and a similarity score, schema included.
A nightly job that reads new customers from your warehouse CSV, adds them to suppression list <name> and refreshes the LinkedIn and Meta audiences with them excluded.
A script against the REST API that scores every domain in a CSV against ICP definition <name>, appends score and reasons, and writes the ranked file back, retries included.
One CLI command that verifies every email in <file.csv>, writes <out.csv> with status and confidence columns, and exits non-zero when more than 5% of the rows are invalid.
Connect Cursor to the MCP server so your coding agent can resolve any company by domain, find a person by name and company, verify emails and add rows to list <name>.
An hourly polling loop in TypeScript that reads new intent signals on <topic> for list <name> through the REST API and returns only the rows changed since the last cursor.
A REST recipe your app calls on signup: send an email, get back company domain, headcount, industry, tech stack, fit score and a verified flag as JSON, with the credit cost shown.
A cron-driven CLI job that refreshes list <name> against its saved criteria, verifies every new email and posts the added, removed and changed rows to #sales.
Give a Claude Code session live access to list <name> over MCP: read rows, filter by fit score and trigger enrichment, with the server URL, a scoped key and an example call.
The 20 highest-scoring accounts on list <name> as a JSON array your outbound agent can consume, each with reasons, the latest signal and a verified primary contact.
Every Friday, the week's LinkedIn leads and inbound signups scored against your ICP, the quality mix and source campaigns charted, and the scorecard emailed with the CSV attached.
The 40 most relevant companies in a category with headcount, funding, HQ and core technologies, charted and summarized for a board in Google Docs with the full table in Sheets.
Target accounts checked for a verified contact, a full buying committee, a live signal and a HubSpot owner, charted by territory and posted to #sales-leadership with Asana tasks.
Your site and won accounts read, the market split into six to eight scored segments with evidence, the ranking charted, and a deck on where next quarter's pipeline comes from.
Every Monday, the week's GTM data - list growth, signals by type, verification rates, audience sizes and match rates - charted in a Google Doc with the summary posted to #revops.
A thousand verified contacts built in batches of 100, each batch posted into the Slack thread for a spot-check and corrections, the final list saved with a CSV.
Send a name and company to your WhatsApp agent and get back a contact card with a verified work email, a direct number where found, and a one-line note on the person's role.
Missions projected over a credit threshold ask first in the channel they started from, with the estimate and deliverable; your 'yes' runs it, silence leaves it queued.
Forward a prospect's email to your agent address and get back the research on the sender and their company, a fit score, and a reply drafted in your voice.
Message a Telegram bot 'check <company.com>' and get the compressed read within a minute - what they do, size, stack, recent moves - with the full profile saved to Notion.
The ten companies with the strongest new intent posted to #sales each morning; a reply like 'take 3 and 7' enriches those, finds verified contacts and drafts the first touch.
A prospect list built from criteria in a Slack thread, ten sample rows shown first for correction, then the full 500 built, saved as a list and pushed to HubSpot.
Message a domain in Slack and get the two-minute read in the thread: what they do, size, stack, hiring, funding, the buyer verified and the question that opens the call.
A sourced comparison brief on how a company positions itself, the rivals it names, the claims it makes against each, and how its three closest competitors answer.
Named customers, partners and integrations read from a company's site and public sources, resolved with headcount and industry, mapped in Sheets with the source per entry.
A saved list broken down by industry, headcount band, region and top technologies, each breakdown charted, delivered as a Google Doc with the charts and a CSV of the counts.
Every Friday, what changed at the 25 accounts on a list - news, funding, leadership changes, notable job posts - posted to #accounts with one line per account and source links.
WHOIS registration date, registrar and registrant organization pulled for every domain in a CSV, young or masked domains flagged, and the CSV returned with the columns added.
The leadership team at one company with titles, tenure and recent changes, verified emails for executives in a chosen function, and the senior roles currently open, in Google Docs.
Ten companies most similar to <company.com>, compared on headcount, funding, stack and hiring momentum in a Google Sheet, with headcount charted against total raised.
The funding history of <company.com> and its five closest peers - rounds, dates, amounts, lead investors and shared investors - charted as a raise timeline in a Google Sheet.
The technologies <company.com> runs across CRM, marketing, data, analytics and infrastructure, dated by first sighting and marked where your product fits, in a Google Doc.
A profile of <company.com>: what they do, headcount and growth, offices, stack, latest funding, leadership and three recent news links, saved as a Notion page under Accounts.
An account plan for <company.com> from live data: offer, size, stack, hiring, funding, news, a verified buying committee and your angle, as a Google Doc plus a #sales summary.
Dormant Omnisend subscribers enriched and split into three segments, a reactivation email written per segment, and the series staged with the sunset logic described.
Twenty dream accounts researched for news, hiring and stack, the CEO or relevant VP verified, and a genuinely specific email per account written in your voice as Gmail drafts.
LinkedIn Lead Gen Form leads segmented by their form answers and company profile, a three-touch follow-up written per segment, emails verified, drafts staged in Gmail.
Three hundred contacts split into three industry segments, a tailored version of this month's announcement written per segment, and the sends staged unsent in ActiveCampaign.
Lemlist campaign replies classified - interested, objection, referral, later, unsubscribe - logged on the HubSpot contact, with the interested ones posted to #sales.
New Klaviyo subscribers enriched with company and role, a welcome email drafted that names their industry and one relevant use case, staged as a flow email for review.
A one-page brief for tomorrow's call - who they are, stack, hiring, funding, objections and three questions - with the Zoom scheduled and the brief in Google Docs.
A one-page proposal drafted in your template from the account plan and the attached scope notes, created in PandaDoc ready to send, with a WhatsApp ping when the link is ready.
Companies researching a topic this week, the buyer verified, a first-touch line per contact that references the research signal, and everyone pushed into a paused Apollo sequence.
A 300-character connection note and a follow-up message per contact, grounded in their role and their company's latest signal, placed in Sheets for you to send yourself.
Closed-lost deals older than six months filtered to companies with a fresh trigger, a trigger-referencing winback sequence per contact, loaded paused into ActiveCampaign.
Call notes for 30 accounts - what the company does, size, stack, latest signal, likely objection and the opening question - assembled in a Google Doc in dial order.
Two-line openers that quote each buyer's own job posting and bridge to what you do, written per contact and drafted in Gmail for the first 20.
A list split by industry and role, a three-step sequence written per segment from its shared evidence, and the campaigns created paused in Instantly with leads loaded.
A first-touch email per contact written from the row's latest signal - hiring, funding or technology change - in your voice, loaded into an unsent Lemlist campaign.
The accounts on a list divided into three territories balanced by fit score and region, with the assignment rules proposed and the mapping delivered in Sheets for RevOps sign-off.
Every lead in an Instantly campaign verified before it starts, risky and invalid addresses removed, leads deduped against your other campaigns, and removals reported with reasons.
A CSV of signups resolved to companies and scored against your ICP, the top tier posted to #sales with suggested next steps and the rest added to an ActiveCampaign nurture list.
Every phone number on a list normalized, checked for line type and connection, disconnected numbers dropped, and a calling sheet of only the numbers that pass exported to Sheets.
Duplicate companies in Attio found by domain and name variants, merges proposed with normalized names and domains, and a change log CSV to approve before any record is merged.
Every Zoho CRM contact email verified, bounced and invalid addresses set to do-not-email, catch-all domains flagged for review, and a before-and-after report sent via Zoho Mail.
This week's LinkedIn Lead Gen Form leads enriched, scored against your ICP with the reason shown, and upserted into HubSpot with the source campaign kept on every record.
Customers in HubSpot, the companies on your competitor and partner CSV and do-not-contact domains removed from list <name>, saved as <name> - suppressed with a count per reason.
A messy prospect CSV normalized, domains resolved, every email verified, deduped against Pipedrive and imported as clean additions only, with a change log you approve first.
Every HubSpot company scored 0-100 against your ICP, score and top reason written back to custom properties, and the ranked book of business charted in Google Sheets.
Every company on list <name> scored 0-100 against your ICP on industry, headcount, region, technologies and intent on <topic>, with reasons per row and a ranked Google Sheet.
Every email on list <name> verified into deliverable, risky, catch-all and invalid, deduped on email and domain, with only the clean rows pushed to a HubSpot static list.
Closed-won HubSpot deals from LinkedIn staged weekly as conversion events with value and close date, sent as one approved batch so campaigns optimize toward revenue.
Each week's LinkedIn Lead Gen Form leads scored against your ICP, conversion events staged for only the qualified ones so campaigns optimize toward buyers, approved per batch.
Customers marked churned in Pipedrive in the last 18 months built as Meta and Reddit custom audiences on your connected accounts, with both match rates reported to #paid.
Monthly re-run of the criteria behind an audience: new matches added to the LinkedIn and Meta audiences, new customers removed, and the size delta posted to #paid.
Companies detected running a competitor's tool, cut to your market by size and region, created as a LinkedIn company-matched audience with the matched count posted to #paid.
Event registrants enriched with company and title, built as a LinkedIn matched audience, plus a suppression file so acquisition campaigns stop paying to reach them.
A saved list exported in the exact customer-list upload formats TikTok, X and Pinterest each expect, saved to a Drive folder with a field mapping and hashing note per platform.
HubSpot contacts split by lifecycle stage into one Meta custom audience per stage on your connected account, with a targeting note and size for each in a Google Doc.
ICP-fit companies showing buying intent on a topic this month created as a LinkedIn company-matched audience on your account, with the size and list posted to #paid.
The buying committee at 50 target accounts found and verified, created on LinkedIn Ads as a contact-matched audience and a company-matched audience, both sizes reported.
Current customers, open opportunities, partners and competitors removed from a list before any audience is built, saved as a clean list with the counts removed at each step.
A saved list exported as a Google Ads Customer Match file with the exact columns and hashing Google expects, saved to Drive with upload steps and expected match coverage.
The contacts on list <name> become a Reddit Ads custom audience on your connected account, normalized and hashed the way Reddit expects, with the size and status posted to #paid.
Every HubSpot contact on a closed-lost deal from the last 12 months, minus current customers, becomes Meta custom audience <name> on your connected ad account, match rate reported.
List <name> becomes a company audience and a contact audience on your connected LinkedIn Ads account, with the matched sizes posted to #paid once LinkedIn finishes processing.
A HubSpot task for the account owner whenever a company on a list raises funding, posts a target role or adopts a technology, with the signal, source and a suggested opener.
Public threads where people describe the problem you solve or compare tools like yours, participants' companies identified where public, qualified and posted to #signals.
Companies whose recent job postings require a competitor's tool, the posting captured, the hiring department's leader verified, and both added to Attio with the posting quoted.
A daily 8am Telegram message naming the five companies with the strongest new intent on a topic overnight, one line of context each, and a link to the full list.
Open roles today versus 90 days ago for every company on a list, ranked by hiring growth, the top 20 charted, and the chart with the ranked table posted to #sales.
Companies that announced a new office, market entry or expansion in a region in the last 60 days, enriched, with the local leader verified and the announcement linked in Sheets.
Companies that run a competitor's tool and are researching your category right now, the tool owner verified, loaded into an unsent Lemlist campaign for a replacement pitch.
Every HubSpot company checked against this month's intent data for a topic, surges marked, score and topics written to the record, and the ten strongest posted to #sales.
Weekly check of target accounts for new VP and C-level hires, each leader added to Pipedrive with a verified email and the announcement noted on the organization.
A continuous watch on every company on a list that posts to #account-alerts when one hires a leader, raises a round or changes a core technology, with evidence attached.
This week's companies showing buying intent on a topic, ranked by score and momentum, cut to your ICP, the likely buyer verified, top 25 sent to #sales and the full list emailed.
Companies in an industry that raised in the last 90 days, the executives announced since the round found and verified, delivered as an account sheet with the round details.
Every company that removed a competitor's tool or added a named technology this quarter, the direction and date of each change recorded, enriched and posted to #sales with a CSV.
Companies where a named technology was first detected in the last 30 days, enriched and cut to your ICP, saved as a refreshable list with a CSV in Google Drive.
A Monday feed of ICP-fit companies that began hiring a specific role in the last two weeks, each with the hiring manager verified, posted to #sales with a CSV attached.
The gaps a company database leaves behind, filled by reading the company site, filings and press coverage, with a source and a confidence on every value.
Current price, stock status and stockists filled in for every product on a list, each answer written with the page it came from so a number can be checked.
Each week's new Klaviyo subscribers enriched with company, role and headcount, ICP fits tagged in Klaviyo, and the count plus the ten best signups posted to #marketing.
The intent topics each company on a list is researching this month attached with scores, surges on a chosen topic marked, and the list exported to Sheets intent-first.
Zoho CRM leads filled with size, industry and a verified email, scored against your ICP with the score written back, and the top 50 emailed through Zoho Mail.
Open-role count, hiring departments and latest posting title written to every company in a HubSpot segment, and the segment exported to Sheets sorted by open roles.
Two more stakeholders from a chosen function added to every account on a list, verified, so no account is single-threaded, and the additions pushed to HubSpot.
HubSpot contacts at closed-won accounts checked for job changes in the last 90 days, movers marked, their replacements found and verified, and the new contacts added with a note.
A sheet of company names typed by hand resolved to official domains and legal names, duplicate rows merged, and the clean result written into a new Resolved tab.
Every Pipedrive organization missing headcount, industry or technology data filled through the waterfall and written back, with a saved filter created for the ones inside your ICP.
A direct or mobile number found for every contact on a list where one exists, the number type recorded, the list updated, and a calling CSV of the rows with numbers saved to Drive.
A CSV of names and companies completed with a work email per person, each verified and labelled deliverable, catch-all or risky, returned with status and confidence columns.
Latest round, date, amount, total raised and lead investors added to every company on a list, recent raises marked, and a summary of the newly funded accounts posted to #sales.
Detected technologies by category added as columns to a saved list, accounts running a competitor flagged, and the enriched list exported to Google Sheets.
Signups from personal email domains resolved to the person and their employer, the employer enriched with firmographics, and both written into Attio as linked people and companies.
HubSpot companies missing employee count, industry or HQ filled through the enrichment waterfall and written back, with a before-and-after coverage summary emailed to you.
A CSV of companies and contacts completed through the waterfall: domains, headcount, industry, HQ, stack, latest round and a verified email filled, with coverage per column.
Twenty-five companies qualified on how they operate rather than what they look like, with the page or job ad that proves the capability is run in house.
Twenty-five agencies qualified on published proof of work in your vertical, each with the case-study page that proves it and a verified contact, written into Attio.
A 25-store list where the platform and the product category are both checked against the storefront itself, with the finding behind every row kept as evidence.
A standing Monday refresh of any saved list: new matches added, lapsed companies removed, a verified contact found for each newcomer, and the additions posted to Slack with a CSV.
Your own website read for what you sell, turned into scored ICP segments with the reasoning shown, and a first list of 50 companies with verified decision-makers pushed to HubSpot.
A hundred consultancies and agencies that list clients in your industry and run a named technology, with the partnerships lead verified and written to Zoho CRM as sourced leads.
Companies whose domain was registered in the last 90 days and that already show a team and a clear business, with the founder verified and posted weekly to Slack with a CSV.
Three hundred companies currently running a competitor's tool, cut to your ICP's size and industry, with the tool owner verified, saved as a list and exported to Drive.
CFOs and VPs of Finance at mid-market companies in one industry and country, every email verified and the survivors loaded into a paused Apollo sequence named after the segment.
Operators of a business type with three or more locations in one state, every location captured, the parent domain resolved and the owner verified, sorted by size.
An event's sponsor and exhibitor list read from its site, resolved to domains, enriched with size and industry, and completed with a verified partnerships lead in Sheets.
Mid-size companies detected running one technology and showing no sign of a second, complementary one, with the evidence per company, saved as a list and exported to Drive.
Every company in a region that announced a seed or pre-seed round in a given month, with the founders verified and loaded as the audience of an unsent Lemlist campaign.
Direct dials and mobiles for every contact on a list where a number can be found, with email as fallback, laid out as a calling sheet in Google Sheets sorted by fit score.
Companies in one country that posted a specific role this month, matched to the VP or Director who will manage the hire, verified and delivered to Instantly as an unsent lead list.
E-commerce companies in one country on a named platform with 20 or more staff, a verified e-commerce or marketing lead at each, saved as a list and exported to Sheets.
The economic buyer, technical evaluator, champion and procurement contact at one account, verified and delivered as a Docs account sheet plus HubSpot contacts.
Marketing and web agencies of 10-200 people whose own sites or client work run a named technology, with the founder verified and written into Attio alongside the evidence.
Recently funded companies in a region that just posted a RevOps or Sales Ops role, with the CRO or VP Sales verified and loaded into Pipedrive as tagged organizations and people.
Every highly rated local business of one type in a city with a working website, captured with address, phone, rating, review count and domain, in a CSV and a Sheet.
Two hundred companies that resemble your ten best customers on industry, size, stack and stage, scored 0-100 for fit with the reasons shown, saved as a list and mirrored in Sheets.
The marketing leader at every company on a list, found by title and seniority, email-verified, and pushed to HubSpot as a static list with the status on each contact.
A 100-company list scoped by industry, headcount, a named technology and an open role, saved as a refreshable list and exported to Drive with the evidence per row.
The most underrated buying signal, worked end to end: define the tell, sweep and score postings, find the humans the posting implicates, and open with the evidence - checklist and funnel math included.
Signals, fit, verified contacts and grounded personalization - the pipeline loop an agent can run every week.
Open a workspace and the playbook library is waiting - describe the outcome and the agents carry it end to end, on your plan's monthly credits.