CRM
Attio
Connect your AI to Attio
Sales reps, customer success managers, and RevOps teams run their relationships through Attio, but the full picture of an account is spread across companies, people, deals, tasks, notes, and meetings that each take a separate lookup. AI can pull that picture together in seconds, but only if access stays read-only, limited to what the connected workspace member can see, and personal contact details are not exposed beyond what the user needs.
Why it matters
Capabilities that matter most for Attio
01
Read-only by design
Popdock exposes Attio lists to AI as read-only tools scoped to what the connected workspace member can see, so answers never go beyond their access.
02
Every core Attio object
Companies, people, deals, tasks, notes, meetings, prospects, comments, files and workspace members are all available to ask about, with filters on the fields each list offers.
03
Ready-made jobs in the app store
Prompt apps cover pipeline reviews, account briefs, stale account checks and weekly activity digests, so teams start from a tested workflow instead of a blank chat.
03
Attio alongside your other systems
Cross-system jobs combine Attio with Zendesk, Asana, Mailchimp, Chorus, Bloomerang and other connectors, so one question can span the CRM and the tools around it.
05
Care with contact data
Prompts show only the contact details a job needs, which keeps personal information out of answers that do not call for it.
Use cases
Example AI Use Cases for Attio
scenario
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Finding out what happened in Attio last week means opening notes, meetings and comments one by one and counting them yourself. Decisions and open questions sit inside long note text, so a leader either skims and misses them or spends an hour reading.
What popdock provides
--
Say how many days to cover, and optionally name one record, and it reads the notes, meetings, comments and new deals from that period in Attio. It groups the activity by day, pulls out decisions, commitments and open questions, and counts meetings and notes per person. You get a headline with counts, the five items that matter with a reason each, new deals, and follow-ups. Nothing in Attio is changed, and if a source is empty or capped at 100 records it says so.
Business outcome
---
Leaders see the week in Attio at a glance, with follow-ups called out, and no records changed.
scenario
-
Missing emails, missing job titles and duplicate people in Attio only turn up when someone reviews records by hand. By then the same person may exist twice, and nobody knows which gaps to fix first.
What popdock provides
--
Optionally name a company, and it sweeps the people in Attio, up to 200 records, checking for missing emails, missing job titles, contacts with no company, shared emails or repeated name and company pairs, suspect names and dormant records. You get a count per check, a few examples of each, possible duplicate pairs and a suggested cleanup order. It only recommends, never edits or deletes, and limits the personal details it prints.
Business outcome
---
Data gaps and duplicate contacts in Attio come with a ranked cleanup order, and no record is edited or deleted.
scenario
-
Duplicate company records in Attio split people and deals across two or more versions of the same account. They are hard to spot, because the names differ by an Inc or a comma while the domain is the same.
What popdock provides
--
Optionally give part of a company name, and it reads up to 200 companies from Attio and groups them by shared domain and by name once suffixes like Inc, Ltd and punctuation are removed. For each group it counts the people and deals attached to every record and recommends which to keep, then says what would need to move first. Name only matches are marked as possible. It only recommends and never deletes or edits a company.
Business outcome
---
Duplicate Attio companies are grouped with a recommended record to keep and a list of what to move, without anything being deleted.
scenario
-
Accounts go quiet in Attio without anyone noticing, and some of them still carry open deal value. Spotting them means checking the last interaction on every company and then matching each one to its deals by hand.
What popdock provides
--
Give a number of days, and optionally a region, and it finds Attio companies with no interaction since then, plus companies that were never contacted. It checks their deals, ignores won, lost and closed ones, and lists quiet companies with open deals first, with stage, value and owner. It ends with a total of open deal value sitting in stale accounts. Nothing is changed, and it says when the company list is capped at 200 and the result is partial.
Business outcome
---
Quiet accounts with open deal value surface first, so follow-up goes where revenue is at risk.
scenario
-
Before a call, a rep clicks through the company page, then people, deals, notes, meetings and tasks in Attio, and still misses a stalled deal or an overdue task. The prep takes time and the picture is never quite complete.
What popdock provides
--
Name the company and how many days back to look, and it finds that company in Attio. If several companies match, it lists them with their domains and stops so you can pick. It then gathers the people, deals, notes, tasks and meetings and writes a one page brief with the profile, contacts, deals, recent activity, open tasks, risks and next steps. It only reads, never invents facts, and writes None found for an empty section.
Business outcome
---
You walk into the call with one page covering the account, based only on what Attio holds.
scenario
-
Preparing for a meeting means finding it in Attio, checking who is attending, opening each linked company, person and deal, and reading back through past notes. That spreads across several screens, and context gets missed.
What popdock provides
--
Give part of the meeting title, and optionally a start date, and it finds the meeting in Attio. If several meetings match, it lists them with start times and stops so you can pick. It then reads the attendees, linked records, deal stage and value and the last three notes on each linked record. You get a briefing with suggested talking points drawn only from those notes. It only reads and does not make up history.
Business outcome
---
You go into the meeting knowing who is attending, what is linked and what was said before, without opening each record.
scenario
-
Managers scan the Attio pipeline by hand, adding up values stage by stage. Deals with no owner, no company, no contact or no value slip through, and old deals sit in the first stage without anyone asking why.
What popdock provides
--
Optionally name an owner and a minimum value, and it reads up to 200 deals from Attio. It groups open deals by stage with totals, leaves won, lost and closed deals out of the open pipeline with a footnote, and ranks the open deals by value. It flags deals with no company, no people or no value, and deals stuck in the first stage for over 90 days. It ends with where to focus first. Nothing is changed.
Business outcome
---
Managers see the open pipeline by stage with weak deals flagged and a clear place to start, without editing any deal.
scenario
-
Prospect lists in Attio tend to get worked in the order they were added. A strong lead with no notes and no deal waits behind a low scoring one, because nobody has time to open each entry and check its history.
What popdock provides
--
Give the list and optionally a minimum score, and it reads up to 200 entries from that Attio list. For the 15 top scoring entries it reads the latest note and checks whether a deal already exists for the company. You get a ranked table, the entries with a high score and no notes or deal to contact first, and low scoring entries with plenty of past activity to consider removing. Nothing is changed, and it does not guess another list if the id returns nothing.
Business outcome
---
Reps and marketers contact the strongest prospects first, with notes and deal status in front of them and no list edited.
scenario
-
Overdue follow-ups in Attio hide across assignees and records. Nobody sees the whole list, so a task that was due weeks ago stays open until a customer asks about it.
What popdock provides
--
Optionally name an assignee, and it reads the open tasks in Attio that are past their deadline, up to 200. For the 30 oldest it finds the linked records, so you know what each task is about. You get tasks grouped by assignee, most overdue first, with days overdue, then a total and the three oldest. Tasks with no deadline are left out, nothing is marked complete, and if an assignee name matches nobody it checks the spelling against workspace members.
Business outcome
---
Every overdue Attio follow-up is visible by assignee with its linked records, and no task is changed.
scenario
-
Account reviews lean on CRM notes, which say nothing about a lapsed subscription or a failed renewal. Checking billing means finding the same people in a second system, and a company can look healthy in the CRM while its subscription has expired.
What popdock provides
--
Name a company, and it finds it in Attio. If more than one company matches, it lists them and stops. It then gathers the contacts, open deals and open tasks from Attio, and looks up each contact's email in 2Checkout for subscriptions, renewals and payment type. You get contacts, deals, tasks, subscription status and expiry, and a watch list, such as a lapsed subscription with a deal still open. Billing is matched by email only, never by name, and only the payment type is shown.
Business outcome
---
Account owners see billing problems next to CRM context in one briefing, with no records changed in either system.
scenario
-
Answering a customer question means checking the CRM, then the billing system, then pasting the two together by hand. The customer is often spelled or emailed differently in each, so mismatches go unnoticed.
What popdock provides
--
Give an email address or a company name, and it finds the customer in 2Checkout. If more than five customers match, it lists them and stops so you can choose. It then matches the person and company in Attio and reports contacts, open deals, recent notes, subscriptions with expiry and recent orders. It ends with a list of mismatches. One sided matches are reported as such rather than guessed, different domains are flagged as a guess, and nothing is written to either system.
Business outcome
---
Support sees one view of a customer across Attio and 2Checkout, with mismatches listed, and no record changed.
scenario
-
A deal marked as won is assumed to be billing, but nobody confirms that a subscription exists. Checking means opening each deal in Attio, finding its contacts, then searching their emails in the billing system, so missing subscriptions and lost revenue go unnoticed.
What popdock provides
--
Name a deal stage and how many deals to check, and it reads those deals from Attio, then the contacts at each company and their subscriptions in 2Checkout. You get a table of deals with the subscriptions found, and counts of deals with an active subscription, only lapsed ones, or none. It separates no contacts to check from no subscription, and warns that different emails can show a false gap. Nothing is changed in either system.
Business outcome
---
Finance sees which won deals are billing and which are not, with false gaps called out, and no record changed.
scenario
-
Customers pay through 2Checkout but never get entered in Attio, and finding them means exporting the billing customers and checking each email against the CRM by hand. Customers with only a company name or no email are easy to misjudge, so gaps stay hidden until someone asks why a paying customer has no record.
What popdock provides
--
Name a company and it lists the matching 2Checkout customers, then checks each email against Attio people. When a person is not found, it looks for the company in Attio so you can see whether only the person is missing. Results come in three groups: in both systems, company in Attio but person missing, and in neither. Emails are compared ignoring case, company names are treated as a hint only and labelled that way, and customers with no email go in a separate list. Nothing is changed in either system.
Business outcome
---
You see which paying 2Checkout customers are missing from Attio, with the details to create each one, and nothing is changed.
scenario
-
Renewals are chased from a 2Checkout export of expiring subscriptions, and nobody checks which Attio deal or owner sits behind each one. Matching every email to a person, company and deal across two systems takes long enough that it gets skipped, so a subscriber with no CRM record or no open deal is only noticed after the subscription has lapsed.
What popdock provides
--
Say how many days ahead to look, and optionally a product, and it lists the 2Checkout subscriptions that expire in that window, leaving out ones already disabled. It looks up each subscriber email in Attio once, finds the person's company, and pulls the deal name, stage, value and owner. You get a table in expiry order, with subscribers who are not in Attio grouped apart from those who have a person but no deal. It looks up at most 50 emails, tells you how many were left out, and changes nothing in either system.
Business outcome
---
Each expiring subscription shows its Attio company, deal and owner, so renewals go to the right person and the gaps are visible.
scenario
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Account managers flip between Attio and Asana to see whether delivery problems threaten a deal, and the picture is stale or partial. Deal stage and value sit in one system, while project status, the latest update and overdue tasks sit in another, so the link between them rarely gets checked before a renewal or a call.
What popdock provides
--
Name a customer and it finds the company in Attio and lists its deals with stage, value and owner. It then finds the matching Asana project, reads the latest status update and sorts open tasks into overdue, due soon and later. You get one page, closing with a short reading of whether delivery risk threatens the open deal value. It stops and asks when the company or project match is ambiguous, says plainly that the link between systems is a name match, and changes nothing in either system.
Business outcome
---
Account managers see deal value beside delivery status in one view, with the name match stated, before they walk into a conversation.
scenario
-
Open CRM tasks and Asana tasks are kept in step by hand, so work due in Attio often has no counterpart in Asana. Someone reads the Attio task list and searches Asana for each one by wording, and the ones that slip through are found only when the deadline is missed.
What popdock provides
--
Give a number of days ahead and optionally a keyword, and it lists open Attio tasks due in that window. For each one it searches Asana for an open task with matching wording and sorts them into matched, possible and missing. You get a table with deadline, assignees and status, missing tasks first, with the Asana link where one exists. Matching is on wording only, so possible matches are flagged for a person to judge, and nothing is created or changed in either system.
Business outcome
---
You see which due Attio tasks have no Asana counterpart, with doubtful matches flagged for you to judge, and nothing is created.
scenario
-
Won Attio deals are checked against Asana projects by eye, so a signed customer can be left with no delivery project. Someone reads the list of recent wins and searches Asana for each company, and the deal with no project is found only when the customer asks where their onboarding is.
What popdock provides
--
Give a lookback period and, if your stage is not called Won, its name, and it lists the Attio deals in that stage created in the window. For each company it searches Asana for a project and sorts deals into covered, archived only and missing, with near matches marked probable. You get a table with value, owner and project link, with missing deals first and their total value. It never creates a project and changes nothing in either system.
Business outcome
---
Signed customers with no delivery project are found, with the value at risk, before their onboarding is missed.
scenario
-
Someone compares the Attio workspace member list with Asana users by hand, matching email addresses one at a time. People with no Asana account are missed until work assigned to them fails to reach them, and a near match on a different address is easy to misread.
What popdock provides
--
Optionally name a member, or leave it blank for everyone, and it lists the Attio workspace members with their emails. It looks up each address in Asana, and when none is found it retries on the part before the at sign and flags a single hit as probable. You get a table marked exact, probable or missing, with counts and the list of missing members. Emails are compared ignoring case, two Asana users on one address are both listed rather than one being picked, and nothing is changed in either system.
Business outcome
---
You know who in Attio has no Asana account, and which matches need a person to confirm, without comparing lists by hand.
scenario
-
Before a call, a rep searches the BigCommerce admin for a customer's orders, then searches Attio for the same person, company and deals. The two systems never quite line up, with different company names or a missing record on one side, and the preparation can take longer than the call.
What popdock provides
--
Give an email and optionally how many days of orders to include, and it finds the customer in BigCommerce and totals their orders, then finds the person in Attio with their company and deals. You get the store profile, order count, revenue and latest order beside the CRM person, company and deals, and a closing line on whether name and company agree. The email is compared ignoring case, it stops if more than one record matches, reports a missing match on either side instead of guessing, and changes nothing in either system.
Business outcome
---
A rep opens a call with store history and CRM context in one view, and every mismatch between the two systems is shown.
scenario
-
To check whether pipeline numbers match real revenue, someone exports Attio deals and BigCommerce orders for the same account and compares them by hand. Store customers have to be found by company field or by each contact's email, and deal values and order totals are different measures, which makes the comparison easy to get wrong.
What popdock provides
--
Name a company and optionally a lookback period, and it finds the company and its deals in Attio, then finds its BigCommerce customers by company field and by the email of each Attio contact, removing duplicates. It totals their orders and compares won deal value with store revenue, calling out open deals for companies already ordering and lost deals for companies that kept ordering. It shows how each customer was matched, flags currency differences instead of converting, stops if the company match is ambiguous, and changes nothing.
Business outcome
---
Finance sees pipeline value next to real store revenue for an account, with the matching method and any currency issues stated.
scenario
-
Large store orders can come from accounts that sales has no deal for. Spotting them means reading the BigCommerce order list, working out who each buyer is, including guest checkouts, and then searching Attio person by person and company by company.
What popdock provides
--
Give a minimum order total and a start date, and it lists the BigCommerce orders at or above that total, leaving out cancelled and refunded ones. It identifies each buyer, using the billing details for guest checkouts, then looks for the person in Attio by email, and for their company and deals. You get a table of orders with no deal, sorted by total, showing whether the buyer exists in Attio at all, and a second table of orders that do have a deal. It says when a match was by company name only, lists unidentifiable buyers as unattributed, and changes nothing.
Business outcome
---
Sales can follow up on large store orders from accounts with no deal, without searching the CRM name by name.
scenario
-
New store customers never reach the CRM, and finding the gap means exporting recent BigCommerce customers and checking each email in Attio by hand. Capital letters in emails and customers who checked out with no email make the comparison untidy, so the gaps go unnoticed.
What popdock provides
--
Give a start date and how many customers to check, and it lists the BigCommerce customers created since then and checks each email against Attio people. Matching is on email only, ignoring case, and never on name. You get a table of customers missing from Attio with store id, name, email, company and date created, a table of matches, and counts of checked, matched, missing and unmatchable. Customers with no email are reported separately, it tells you when the maximum was reached so there may be more, and nothing is changed.
Business outcome
---
You see which new store customers are missing from Attio, ready to add, with counts that show how far the check went.
scenario
-
Finding which contacts at a company have given before means listing the company's people in Attio, searching Bloomerang for each one, and adding up their gifts by hand. Refunded gifts get counted by mistake, and people with no email or no donor record are quietly dropped from the tally.
What popdock provides
--
Name a company and optionally a lookback period, and it lists the company's people in Attio, then looks each one up in Bloomerang by email. For each match it reads their gifts in the window, skips refunded ones and says how many it skipped. You get a table with job title, account number, number of gifts, total and latest gift date, plus a company total. Matching is on email only, never name, people with no email or no Bloomerang match are listed separately, and nothing is changed in either system.
Business outcome
---
You see which contacts at a company are donors and what they gave, with unmatched people listed instead of dropped.
scenario
-
Before a deal conversation, the giving history and past contacts of the people involved sit in a different system and are often skipped. Pulling them together means finding each person on the deal, searching Bloomerang for their gifts and interactions, and reading through both.
What popdock provides
--
Name a deal and it finds it in Attio with its stage, value, owner and company, then reads each associated person. It looks each person up in Bloomerang by email and reads their ten most recent gifts and ten most recent interactions. You get a briefing with the deal in two lines, then a section per person with job title, giving totals, last gift and the last three interaction subjects, and up to three talking points drawn only from that data. It stops if several deals match, marks people who are not Bloomerang constituents clearly, and never updates the deal or logs anything.
Business outcome
---
You walk into a deal conversation knowing each person's giving and recent contact history, with nothing logged or changed.
scenario
-
Checking whether the people on a company in your CRM also exist in the donor database means opening both systems and comparing names and emails one at a time. People who were never added are easy to miss, and anyone without an email cannot be checked at all.
What popdock provides
--
Name an Attio company and optionally how many people to check, and it lists the people on that company in Attio, then looks up each email in Bloomerang. You get three results: who is missing from Bloomerang, who cannot be checked because they have no email, and how many were found. Emails are compared ignoring letter case. If several companies match the name it lists them and stops. Nothing is created in either system, and it points you to the add contact process for the people who are missing.
Business outcome
---
You see which CRM contacts never made it into Bloomerang, and which could not be checked, without comparing records by hand.
scenario
-
To see whether a CRM contact is also a donor, someone searches Attio, then searches Bloomerang, then compares the details by eye. Differences in phone, city or employer slip through, and it is unclear which system to trust.
What popdock provides
--
Give an email address and it looks the person up in Attio and the constituent up in Bloomerang. If Bloomerang has no match by email it tries once by last name and lists candidates without choosing one. You see name, email, phone, city, employer and job title side by side, each marked Match, Differs or Missing, plus a one line verdict. Emails are compared ignoring case and phones by digits. If several records match it lists them and stops, and it never decides which value is right or changes either system.
Business outcome
---
You know in one answer whether a contact is also a donor and where their details disagree.
scenario
-
Preparing for an account call means opening the Attio company, its people and its deals, then searching Chorus for recent calls and emails. Account names are typed differently in each system, so conversations get missed and nobody sees which deals have gone quiet.
What popdock provides
--
Name a company and how many days to look back, and it finds the company in Attio, then pulls its people and deals. It then reads the Chorus calls and emails for that account over the same window. If Chorus returns nothing it retries once with the company domain and tells you which spelling matched. You get the company details, deals, people and a dated list of conversations, plus the last conversation date, Attio people on no call, and open deals with no conversation. It stops on an ambiguous or missing Attio match and changes nothing in either system.
Business outcome
---
You get one account view across Attio and Chorus, with quiet deals and unengaged contacts called out.
scenario
-
Coaching a rep means looking at their deals in Attio, then their calls and emails in Chorus, and trying to line the two up by account name. Deals with no activity and activity with no deal are hard to spot across two screens.
What popdock provides
--
Give a rep's email and how many days to look back. It confirms the rep is an Attio workspace member, lists the deals they own, then reads their Chorus calls and emails for the same window. Deals are matched to Chorus accounts by company name. You see total open deal value, the number of calls and emails, each deal with its activity count, accounts with activity but no deal, and deals with no activity. It stops if the email is not an Attio member, does not widen the search to other owners, and changes nothing.
Business outcome
---
Managers see where a rep's pipeline and call activity do not line up, ready for a coaching conversation.
scenario
-
Reps rarely know which CRM contacts have never joined a call, or which people on calls are missing from the CRM. Deals stay single threaded because the gap only shows up when someone compares two systems by hand.
What popdock provides
--
Name a company and how many days to look back. It lists the people on that company in Attio, then reads the external participants on its Chorus calls and ignores your own internal users. Matches are made on email ignoring case, and where an email is missing it falls back to an exact name match and marks it WEAK. You get people in both, people only in Attio, and people only in Chorus with the details to add them, plus the share of Attio contacts seen on a call. It suggests additions but makes none.
Business outcome
---
You see which contacts are silent and which call attendees are missing from the CRM, so deals are not left single threaded.
scenario
-
Managers scan the pipeline in Attio and the call logs in Chorus separately to find deals that have gone quiet. Because the two are checked apart, the quiet ones slip through until the deal is already at risk.
What popdock provides
--
Give a deal stage, optionally an owner, and how many days to look back. It lists the Attio deals at that stage, working through the 50 largest by value if there are more, then checks Chorus calls and emails for each company. You get a table sorted by value with the last conversation date and days since, with deals that have no conversation in the window marked STALE and listed first, and a count of stale against active. A company Chorus does not know is shown as NOT IN CHORUS rather than stale. Nothing is changed.
Business outcome
---
Managers see which deals at a stage have gone quiet, without mistaking unknown accounts for stale ones.
scenario
-
Before a call, a rep checks Attio to see who the person is, then logs into Constant Contact to see what email they have opened. The second step is often skipped, so the rep does not know the person bounced, unsubscribed or never opens email.
What popdock provides
--
Give an email address and how many days to look back. It finds the person in Attio and the contact in Constant Contact, then reads their activity, clicks, bounces, unsubscribes and list memberships. You get their Attio name, title, company and last interaction, their permission to send, lists and tags, counts of sends, opens, clicks, bounces and unsubscribes, and the three most recent interactions, ending with whether they look engaged, quiet or opted out. It matches on exact email only, shows both values if the systems disagree, and changes nothing.
Business outcome
---
Reps walk into a call knowing how the person engages with email, not just who they are in the CRM.
scenario
-
Reps assume everyone on a deal can be emailed, then find out later that a key contact never opted in or is not in the email tool at all. Checking means looking up each person from the deal in Constant Contact one by one.
What popdock provides
--
Name an Attio deal and it finds the deal, then collects the people associated with it and their email addresses. It checks each address in Constant Contact, trying every address a person has before calling them missing, and reads their recent campaign activity. You get a table with each person's role, whether they are in Constant Contact, permission to send, number of interactions and last interaction, then a verdict on how many can be emailed and how many have engaged. A contact without permission to send is treated as not emailable. Nothing is changed.
Business outcome
---
You know before a campaign or outreach which people on a deal can actually be emailed and who has engaged.
scenario
-
Marketing exports CRM contacts and compares them to the email list by hand. New sales contacts never get onto campaigns, and nobody notices which existing contacts lack permission to send.
What popdock provides
--
Name an Attio company and optionally how many people to check, and it lists the people on that company in Attio. It then looks up each email address in Constant Contact. You get three lists: people missing from Constant Contact, people present but without permission to send, and people present and sendable, with counts. People with no email go in a separate list. Emails are matched exactly, and nobody is added or changed, though it points you to the add people process once you have reviewed the list.
Business outcome
---
Marketing sees which sales contacts are missing from the email list and who can be sent to, without manual exports.
scenario
-
The same person can have a different job title or company in the CRM and in the email tool. Nobody notices until a campaign goes to the wrong role, because finding the differences means comparing two systems record by record.
What popdock provides
--
Give a company name and optionally how many contacts to check. It reads the matching Constant Contact contacts, then finds each person in Attio by email. It compares full name, job title and company, ignoring case and extra spaces, and a blank on one side is reported as missing rather than as a difference. You get a table of differences with both values, the contacts that are not in Attio, and a count of full matches, along with which system you may want to fix. It does not choose a winner and changes nothing.
Business outcome
---
You find mismatched names, titles and companies between Constant Contact and Attio before they reach a campaign.
scenario
-
Unsubscribes and bounces from an email campaign are not connected to the customers and deals in the CRM. A key contact can opt out or stop receiving email and nobody on the account team notices.
What popdock provides
--
Name a campaign and it finds it in Constant Contact, then lists the people who unsubscribed or bounced with the reason or bounce type. Each email is looked up in Attio for the person's company and job title, and the company's open deals are added. You get two tables, unsubscribes and bounces, with rows that have an open deal first. For a bounce it suggests checking the address, and for an unsubscribe it suggests another channel, and it never suggests re adding someone who opted out. People not in Attio stay in the report. Nothing is changed.
Business outcome
---
Account owners hear about lost contacts on open deals and can follow up another way.
scenario
-
A campaign gets clicks and opens, but nobody tells the account owners which of those people sit on open deals. The hot signals go cold because matching a click list to the CRM takes too long to do by hand.
What popdock provides
--
Name a campaign and optionally how many people to include. It finds the campaign in Constant Contact, then collects the people who clicked it, adding people who opened it if there is room. Each email is matched exactly to a person in Attio, and their company's open deals are listed with stage, value and owner. You get people ranked by deal value, then those who engaged but are not in Attio and those with no open deal. If a company has several open deals it lists all of them rather than guessing, and nothing is changed.
Business outcome
---
Account owners see which campaign engagers are tied to open deals, ranked by value, while the interest is fresh.
scenario
-
Before a campaign goes out, nobody can easily see which people at an account are in the CRM but not on the email list. Someone opens the company, copies each email address and searches the email tool one by one, so contacts with no subscriber record get skipped without anyone noticing.
What popdock provides
--
Name an Attio company, and optionally how many people to check, and it lists the people at that company in Attio, then checks each email address in Drip. You get three lists: people already in Drip with their status and lead score, people missing from Drip, and people with no email address in Attio. A failed lookup is reported as unchecked rather than missing, and nothing is added or changed in either system.
Business outcome
---
You see which contacts a campaign would skip, with counts, and no records are changed in Attio or Drip.
scenario
-
Before a deal call, a rep opens the deal in the CRM, finds the company's contacts, then searches the email tool for each one to see whether they are on a nurture campaign and how engaged they are. It is slow, and an unsubscribed contact is easy to email by mistake.
What popdock provides
--
Name an Attio deal and it finds the deal and the people at its company, then looks each one up in Drip. You get a deal summary and one row per contact with job title, Drip status, lead score, tags and campaigns. If several deals match the name it lists them and stops. Unsubscribed contacts are flagged so they are not suggested for email, and nothing is changed in either system.
Business outcome
---
You walk into a deal knowing who is engaged and who must not be emailed, without opening two systems.
scenario
-
Comparing a CRM contact with the same person in the email tool means opening both, matching them by email and reading the fields side by side. Mismatched names, countries or opt-in states are easy to miss, so the two records drift apart without anyone noticing.
What popdock provides
--
Give a name or an email address and it finds the person in Attio, then looks up the Drip subscriber with the same email. You get a table of name, email, phone, city and country showing where each value matches or differs, plus the Drip status, state, lead score and tags and a one line verdict. Phone numbers and country codes are normalised before comparing. If the person is ambiguous, has no email or is not in Drip, it stops and says so, and nothing is changed.
Business outcome
---
You see every mismatch between a CRM contact and its email subscriber in one table, with nothing edited in either system.
scenario
-
The CRM does not show that a contact has unsubscribed in the email tool, so reps email people who opted out. Finding them means checking each contact at an account against the email list by hand.
What popdock provides
--
Name an Attio company and it lists its people, then checks each email address in Drip and treats any status other than active as not emailable. You get a do not email table with the Drip status, then the emailable people, then people Drip does not know. It never guesses a status for someone it cannot find, lookup failures are reported as unchecked rather than active, and nothing is changed in either system.
Business outcome
---
Reps know who not to email before they send, with unknown contacts kept separate from safe ones.
scenario
-
Preparing for a contact means searching the meeting notes tool and the CRM separately, then piecing together when you last spoke and which deals are open. Calls get missed, and it is easy to pick the wrong person with a similar name.
What popdock provides
--
Give a contact's email address and how many days back to look, and it finds the person in Attio with their company and deals, then pulls the meetings Granola has for that email in the period. You get a dated list of calls with a one line topic each, the deals with stage, value and owner, and the date of the last call. It stops if several Attio people share the email, never matches Granola by name, and changes nothing.
Business outcome
---
You get a dated call history and deal context for one contact in a single reply, without searching two systems.
scenario
-
Attendee lists in the CRM and the meeting notes tool drift apart. Someone was on the call but not logged in the CRM, or logged but never attended, and unless both lists are compared line by line nobody notices who was missed.
What popdock provides
--
Name a meeting and it finds it in Attio and in Granola, then compares the people each system lists by email address. You get three lists: in both systems, only in Attio and only in Granola. Where an email is missing it falls back to an exact name match and flags it as weaker, and it never merges two people on a name alone without saying so. Optionally it also marks people invited in Granola who did not attend. If several meetings match it lists them and stops, and nothing is changed.
Business outcome
---
You see who is missing from the CRM or the meeting record, with weak name matches flagged for you to judge.
scenario
-
Follow-ups promised on a call are easily forgotten because no task was created in the CRM. Checking means rereading the transcript, noting each commitment, then searching the CRM for a matching open task for each person on the call.
What popdock provides
--
Name a Granola call and it reads the transcript for commitments such as I will send or we will follow up, noting who owns each and any stated date. It finds the attendees in Attio, looks at their open tasks and compares each commitment with them. You get a table marking each commitment as covered, partly covered or missing. It only reports commitments actually in the transcript, lists attendees with no Attio record as unmatched, and creates or changes no task.
Business outcome
---
You see which promises from a call have no Attio task, so follow-ups are not dropped.
scenario
-
Calls recorded in the notes tool often never get logged as meetings in the CRM, so the CRM looks emptier than reality. Finding the gaps means going through each note and searching the CRM for a meeting at the same time with the same people.
What popdock provides
--
Give a start date, and optionally an owner email, and it lists the Granola meetings from then on and the Attio meetings in the same period. It matches them by start time within 30 minutes and shared title words, and checks attendee emails where a match is uncertain. You get a table of Granola calls with no Attio meeting, with date, owner and attendees, and a count of matched notes. Internal only meetings are marked so you can ignore them. It only reports gaps and creates nothing in Attio.
Business outcome
---
You see which recorded calls are missing from Attio, with internal meetings marked, so the CRM can be completed.
scenario
-
A rep who sees a meeting logged in the CRM has to hunt through the notes tool for the matching call, comparing dates and titles by eye. It is easy to open the wrong call, and the transcript is long to read.
What popdock provides
--
Name an Attio meeting and how far back to look, and it finds the meeting, then looks in Granola for the note starting around the same time with similar title words. You get the title, start time, attendees, a short summary of the discussion, decisions and action items with owners. If several Attio meetings match it lists them and stops, and if several notes match it picks the closest start time and says so. It shows both sides when titles or times differ, treats a missing transcript as a gap, and never writes to Attio.
Business outcome
---
You get the right call's summary, decisions and action items without searching Granola by hand.
scenario
-
Before reaching out, a rep checks the CRM for the person's deals, then Mailchimp for what they have been sent and opened, switching between two tools. One of the two is often skipped, so outreach ignores an opt-out or how warm the person really is.
What popdock provides
--
Give an email address and it finds the person in Attio with their company and deals, then looks the same email up in Mailchimp for audience status, tags and campaign opens. You get one profile with the Mailchimp status per audience, any unsubscribed or cleaned status shown before the engagement numbers, the campaigns they opened ranked by opens, and a closing line on whether engagement looks warm or cold for their deal stage. If the email matches several Attio people it stops. Both systems are read only.
Business outcome
---
You get a single read on a person's deals and email engagement, with opt-outs visible before you reach out.
scenario
-
Store revenue sits in Mailchimp while relationships sit in the CRM, so a big customer can be missing from the CRM or have no deal and no one notices. Spotting them means exporting the top spenders and searching the CRM for each email address.
What popdock provides
--
Set a minimum spend and how many customers to check, and it reads the matching Mailchimp store customers, then matches each by email to Attio people and their company deals. You get three tables sorted by total spent: customers not in Attio, customers in Attio with no deal, and customers with deals, showing spend beside deal value as separate measures. Opt-in status is shown so nobody emails an unsubscribed customer. Customers without an email are listed as unmatched, and both systems are read only.
Business outcome
---
Leaders see which high spending customers the CRM does not know about or has no deal for, without a manual cross check.
scenario
-
A contact unsubscribes in Mailchimp, but the deal lives in Attio, so the opt-out never reaches the rep. They keep emailing people who unsubscribed or bounced, and finding those people means matching an audience export against the CRM by hand.
What popdock provides
--
Name a Mailchimp audience and a status, unsubscribed by default, and it reads those members, matches each by email to Attio people and finds the deals they sit on. You get a table of affected people with company, Mailchimp status and reason, deals with stage and value, and deal owner, sorted by total deal value, plus a count of members with no Attio match. Ambiguous email matches are listed rather than guessed, it never suggests re-subscribing anyone, and both systems are read only.
Business outcome
---
Sales sees which deal contacts have opted out of email, so nobody relies on a channel that is closed.
scenario
-
After a campaign goes out, marketing hands sales a list of people who opened it, but nobody checks which of them are already in the CRM or have a deal open. Sales either chases cold names or misses warm ones because the Mailchimp report and Attio live in separate places.
What popdock provides
--
Give a Mailchimp campaign and a minimum number of opens, and it confirms the campaign exists, then reads the people who opened it that often. Each opener is matched to Attio by email, and you see their company, last interaction and deals. Openers who are not in Attio are listed separately and no records are created. Nothing is changed in Mailchimp or Attio.
Business outcome
---
Sales gets a ranked list of warm openers with their company and deal context, and gaps in the CRM are listed rather than guessed.
scenario
-
Marketing and sales keep contact lists in Mailchimp and Attio, and compare them by exporting both and matching emails in a spreadsheet. Gaps and unsubscribed contacts get missed, and people end up emailed, or left out, by mistake.
What popdock provides
--
Give a company and a Mailchimp audience name, and it reads the Attio people at that company, then looks each email up in the audience. You see who is in both, who is only in Attio, and who is unsubscribed or cleaned in Mailchimp. Matching is on email only, people with no email are listed separately, and it stops if the audience name matches more than one audience. Nothing is changed in either system.
Business outcome
---
You see exactly which contacts are missing or unsubscribed across Attio and Mailchimp without a spreadsheet, and nothing is edited behind your back.
scenario
-
Managers review a stage of the pipeline and have no idea whether the contacts on those deals are even receiving or opening email, because that lives in Mailchimp. A deal can look healthy in the CRM while every contact on it has unsubscribed or never opens a message.
What popdock provides
--
Give a deal stage and optionally a minimum value, and it lists the matching deals from Attio and finds the contacts on each one. Each contact's email is looked up in Mailchimp for status and average open rate. A deal is flagged when every contact is unsubscribed, cleaned, absent from Mailchimp or has a zero open rate, and a contact not in Mailchimp is kept apart from one who unsubscribed. Deals with no contacts are reported, not skipped, and nothing is changed.
Business outcome
---
Managers see which deals in a stage have contacts they cannot reach by email, ordered by value, before the follow up is missed.
scenario
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When a ServiceNow incident escalates, managers see the ticket but not the caller's account value, open deals or recent notes, which sit in the CRM. They end up pinging sales for context while the incident clock keeps running.
What popdock provides
--
Give a ServiceNow incident number and it reads the incident, finds the caller's email and matches that email to a contact in Attio. It then adds the company, open deals and the most recent notes to an escalation brief, with a short suggestion on how account value might affect urgency. If the caller has no email or is not in Attio, it stops and gives the incident details only. Nothing is changed in ServiceNow or Attio.
Business outcome
---
Managers get an escalation brief with account value, open deals and recent notes alongside the incident, without asking sales for context.
scenario
-
Reps find out a deal is at risk only when the customer complains, because open tickets live in the service desk and the deal lives in the CRM. Nobody checks the two together before a renewal or a proposal call.
What popdock provides
--
Give an Attio deal stage and optionally a priority level, and it lists the deals in that stage, finds the people on each one and matches them by email to ServiceNow users. It then pulls their open incidents at that priority or worse and shows the deals sorted by value with the worst incident for each. Deals where no contact matches a ServiceNow user are listed as unknown, not clean, and it stops if the stage matches nothing. Nothing is changed in either system.
Business outcome
---
Reps learn which deals have open high priority tickets before the customer calls, and unmatched deals are shown as unknown rather than safe.
scenario
-
Contact details drift between the CRM and the service desk, and nobody notices until a ticket goes to the wrong person or a call reaches an old number. Comparing the two means opening both systems and checking each person by hand.
What popdock provides
--
Give an Attio company name and it reads the people at that company, then looks each email up among ServiceNow users. It compares name, job title and phone numbers on every pair, ignoring case and phone formatting. You get three lists: people with no ServiceNow user, matched people whose details differ, and matched people whose ServiceNow user is inactive. Matching is on email only, it stops if the company name matches none or several, and it reports differences but never fixes them.
Business outcome
---
You find out where Attio and ServiceNow disagree about the same person, with the fix left in your hands.
scenario
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Judging how an account is doing means piecing together CRM contacts and deals with open tickets from a second system. The picture is built from memory or screenshots, and a contact missing from the service desk quietly looks like a contact with no problems.
What popdock provides
--
Give an Attio company name and optionally an incident state, and it finds the company, then reads its people and deals. Each person is matched by email to a ServiceNow user and their incidents are pulled. You get one summary with the company, deals, incidents grouped by contact and a one line health read. Contacts with no ServiceNow user are listed separately, and if nobody matches it says incidents are unknown rather than zero. Nothing is changed in either system.
Business outcome
---
Support gets one health summary per account, with unmatched contacts shown honestly as unknown instead of as zero incidents.
scenario
-
Support staff look a customer up in the CRM, then search ServiceNow by hand for their tickets. When names repeat, it is easy to open the history of the wrong person and answer the wrong question.
What popdock provides
--
Give a contact's email address and optionally a start date, and it finds that person in Attio, then matches them to a ServiceNow user on the same email. It lists the incidents they raised with number, description, state, priority, date and assignee, and ends with the count of open and resolved incidents. It stops if the contact is absent, if several people match, or if there is no ServiceNow user. Nothing is changed in either system.
Business outcome
---
Support sees the right customer's incident history in one answer, matched on email so a shared name never pulls up the wrong person.
scenario
-
Sales and delivery teams look up a deal in Attio and then hunt through Teamwork.com for its project. Status ends up stale or guessed, and a project with a similar company name is easy to mistake for the right one.
What popdock provides
--
Give a deal name and optionally a stage, and it finds the deal in Attio, then finds the Teamwork.com project for the deal's company. It reads the project health, milestones and open tasks and reports the health score, milestone deadlines and progress, and overdue tasks, then says whether delivery looks on track. It stops if the deal or project is missing or ambiguous and says which spelling it matched on. Nothing is changed in either system.
Business outcome
---
Sales and delivery get a delivery status for a deal from Teamwork.com in one answer, without a guessed or out of date status.
scenario
-
Comparing what was sold with what was billed means exporting deal values from the CRM and time logs from the project tool, then reconciling them in a spreadsheet. It is slow, and a capped export or a mixed currency can quietly distort the answer.
What popdock provides
--
Give a deal name, and it finds the deal in Attio, then finds the Teamwork.com project for the deal's company. It adds up billable totals, cost totals and hours logged and reports the billed amount as a percentage of the deal value, with a sentence on whether the project is over or under. It stops if the deal or project is ambiguous or missing, does not convert currencies, and says so if the result looks truncated. Nothing is changed in either system.
Business outcome
---
Finance sees billed time against the sold deal value in one answer, with the currency and truncation caveats stated.
scenario
-
Checking which customer contacts are already set up in Teamwork.com means copying emails between two apps one at a time. Matching by name instead is tempting, but names repeat and the wrong person gets linked.
What popdock provides
--
Give an Attio company name, and it lists the people at that company and looks up each email in Teamwork.com. You get a table with the Attio record, the Teamwork.com person, their type and role, or a mark that they are not in Teamwork.com, followed by counts of matched and unmatched. People with no email are listed as cannot match, duplicates on one email are flagged, and matching is on email only, never on name. Nothing is changed in either system.
Business outcome
---
You see which Attio contacts already have a Teamwork.com person, matched on email so no one is linked by a shared name.
scenario
-
Someone compares the Attio company list with Teamwork.com clients by hand, and spelling differences such as Inc or Ltd hide missing or duplicate clients. The two lists drift apart and nobody knows which side is right.
What popdock provides
--
Optionally give a company name, or leave it blank to compare up to 25 companies from each system. It matches Attio companies to Teamwork.com companies on domain first, then on name, marking name only matches as probable. You see three tables: in both, only in Attio and only in Teamwork.com, with counts. It never picks between several candidates, lists them instead, and says a result capped at 25 may be incomplete. Nothing is changed in either system.
Business outcome
---
Operations sees which companies are in both systems or only one, without ambiguous matches being guessed.
scenario
-
To see everything going on for one customer, you read their deals and tasks in Attio, then switch to Teamwork.com for the projects, the overdue tasks and the hours logged. The two views never line up, so a late project or a quiet account is easy to miss.
What popdock provides
--
Name a customer and how many days of logged time to look back, and it finds the company in Attio, then reads its open deals and tasks. It then reads the matching active projects in Teamwork.com with their open tasks and recent hours, and ends with the two or three things that need attention first. It stops if the company match is ambiguous or missing, says so when either side has no data instead of inferring, and nothing is changed in either system.
Business outcome
---
You get one view of a customer's sales and delivery work, with the overdue items called out, and nothing changed in either system.
scenario
-
Next steps for a deal live in two places: the deal and its tasks in the CRM, and your own task list in TickTick. Nobody lines them up, so a deal can sit with no open task anywhere and stall without anyone noticing.
What popdock provides
--
Name a company and it finds it in Attio, then shows its deals and open tasks. It also searches TickTick for tasks that mention the company or each deal and lists them with project, due date and status. Because the two systems share no id, TickTick results are labelled as name matches, and the report ends with the deals that have no open task in either system. It stops if the company is ambiguous, and nothing is changed.
Business outcome
---
Stalled deals show up because every next step from both systems sits in one place, with name matches labelled and nothing changed.
scenario
-
Judging someone's workload from the CRM alone hides the personal tasks they also carry in TickTick. A person who looks free in Attio can have a packed week, so overload goes unnoticed until something slips.
What popdock provides
--
Name an owner and how many days ahead to look, and it reads their open Attio deals and tasks and their TickTick tasks. It merges them into a day by day list with the source marked on each line, then shows open deals, overdue items and anything undated. Days with more than 5 items are flagged. If TickTick has no tasks under that name, it says which TickTick account the result came from. Nothing is changed.
Business outcome
---
Leaders see real workload across both systems and spot overloaded days before work slips, with nothing changed.
scenario
-
Reps compare CRM follow up tasks against their personal task list by eye. A commitment logged in Attio that never made it into TickTick drops through the gap, and nobody sees it until the customer chases.
What popdock provides
--
Say whose tasks to check, if you want to narrow it, and how many days ahead to look. It reads the open Attio tasks due in that window and searches TickTick for each one by its wording. You get two lists: tasks missing in TickTick and tasks already there, with counts. When several TickTick tasks could match, it marks the Attio task as ambiguous instead of guessing. Nothing is changed in either system.
Business outcome
---
CRM follow ups no longer slip through the gap, because every missing or doubtful match is listed for you to handle.
scenario
-
To judge an account, someone adds up what a company's people have bought and refunded in the store, then compares it with the CRM record. That means exporting orders and refunds into spreadsheets and matching them by hand, and risky accounts hide in the sums.
What popdock provides
--
Give the company domain and how many days to look back. It finds the company in Attio, collects the emails of its people, and reads each person's WooCommerce orders and refunds. You get orders, spend and refunds per person, plus company totals, the refund rate and the most common refund reasons. Accounts with a refund rate above 10 percent are flagged. It matches only on Attio contacts, totals each currency separately, and changes nothing.
Business outcome
---
Account managers see spend, refunds and refund risk for a company in one answer, matched only to known contacts.
scenario
-
Before a call, a rep looks a contact up in the CRM, then searches the store by hand for their orders. Refunds get missed and people with similar names get mixed up, so the conversation starts from the wrong picture.
What popdock provides
--
Give a contact's email and how many days to look back. It finds the person in Attio, then matches them to a WooCommerce customer by email, trying their other addresses if needed. It reports orders, refunds and net spend, and says whether the last order is more recent than the last Attio interaction. It matches on email only, stops if more than one person matches, totals each currency separately, and changes nothing in either system.
Business outcome
---
Reps walk into a call knowing a contact's orders, refunds and net spend, matched on email and not guessed.
scenario
-
New store customers do not always reach the CRM. Finding the gap means exporting recent WooCommerce customers and checking each one against Attio by hand, so buyers never get followed up.
What popdock provides
--
Choose a start date and how many customers to check. It reads the recent WooCommerce customers and looks each email up in Attio, ignoring letter case. You get the customers with no person in Attio, with name, email, company and country, plus counts of checked, matched, missing and unmatchable. Customers with no email are skipped and counted. For missing customers with a company, it notes whether that company already exists in Attio. Nothing is changed.
Business outcome
---
Marketing sees which new store customers are missing from the CRM, and which already have a company record, without a manual comparison.
scenario
-
A deal value in the CRM is supposed to be backed by orders in the store, but the two are compared by hand. Cancelled or refunded orders and mixed currencies make the totals drift, and nobody notices until the books are checked.
What popdock provides
--
Name a deal and, optionally, the date to count orders from. It reads the deal in Attio, finds the emails of its associated people, and reads their WooCommerce orders. It totals completed and processing orders and compares them with the deal value, giving one verdict: no orders, below, matches or exceeds. Cancelled, failed and refunded orders are listed apart, currencies that differ are not compared, ambiguous deals stop the check, and nothing is changed.
Business outcome
---
Finance can see whether a deal is backed by real orders, with excluded orders and currency gaps shown, and no data changed.
scenario
-
Account managers flip between the CRM and the help desk to judge how a customer is doing. Tickets filed under a differently named organization are easy to miss, so a quiet looking account can hide real support trouble.
What popdock provides
--
Name a customer and how many days to look back. It finds the company and its deals in Attio, then matches the Zendesk organization on domain first, falling back to name and saying which it used. It reads the tickets and satisfaction ratings for the window and reports ticket counts by status and priority, open tickets and scores. It ends with a one line verdict on whether support trouble puts a deal at risk. It stops on ambiguous matches, says which side has no data, and writes to neither system.
Business outcome
---
Account managers judge a customer's health from deals and support together, with the matching method stated and nothing changed.
scenario
-
Agents answer a ticket without knowing who the requester is, what they have bought or which deals are open. Context sits in the CRM, so replies are generic, or an agent spends minutes searching another system mid ticket.
What popdock provides
--
Give a Zendesk ticket number. It reads the ticket, then looks up the requester in Attio by their full email address. It shows the person, their title and company, the company's open deals and the most recent notes, then suggests in one sentence how that context should shape the reply. If the person is not in the CRM it says so and tries the company by email domain. It never guesses a missing company or deals, and nothing is written to either system.
Business outcome
---
Agents reply with the requester's company, deals and notes in hand, matched on full email and never guessed.
scenario
-
Reps often learn that a customer is unhappy only after a deal stalls, because open urgent tickets sit in the help desk and are invisible from the CRM. Checking each deal's company against Zendesk by hand takes more time than anyone has.
What popdock provides
--
Name a deal stage and, if you like, a ticket priority. It lists the Attio deals in that stage, finds each company's domains, matches the Zendesk organization on domain, and counts open tickets at that priority. You get the deals that have such tickets, sorted by value, with owner, ticket count, oldest ticket date and newest subject. Ambiguous companies are skipped, and it reports how many companies had no Zendesk match so a quiet result is not mistaken for a clean one. Nothing is written.
Business outcome
---
Reps see which deals in a stage are exposed to open urgent tickets, ranked by value, with unmatched companies counted.
scenario
-
Bad satisfaction scores sit in the help desk while the revenue they threaten sits in the CRM. Nobody connects the two, so an unhappy customer with a large open deal gets no attention until it is too late.
What popdock provides
--
Say how many days to look back. It finds recent bad satisfaction ratings in Zendesk, identifies the customer behind each one, and looks them up in Attio by domain. You get each customer with the number of bad ratings, the latest comment quoted word for word, the assignee and the open Attio deals, sorted by total open deal value. It counts customers with no CRM match and ends with the three most urgent follow ups. Nothing is written to either system.
Business outcome
---
Leaders see which unhappy customers have the most revenue at stake and who needs a follow up first, with comments unaltered.
scenario
-
Support staff check a customer company in Freshdesk, then look it up again in the CRM, and compare by eye. Mismatched domains, tiers or renewal dates slip through because nobody lines the two records up side by side.
What popdock provides
--
Give a company name, and optionally its domain, and it finds the company in Freshdesk and then in Attio, matching on domain first and name as a fallback. It adds ticket counts by status from Freshdesk and open deals by stage from Attio. You get a side by side table of name, domains, industry, renewal date, health score and created date with a column showing where the records differ. It stops and lists the names if several Freshdesk companies match, reports a missing side instead of guessing, and changes nothing.
Business outcome
---
You see exactly where a company's Freshdesk and Attio records disagree, with ticket and deal context, without checking each system by hand.
scenario
-
Answering a customer properly means searching their tickets in Freshdesk, then finding their person, company and deals in Attio. Two searches, two screens, and no easy way to judge whether support load fits the account.
What popdock provides
--
Give an email address and how many days of tickets to include, and it finds the contact in Freshdesk and counts their tickets by status and priority, noting escalations. It then finds the person in Attio by that email and carries their company across to list deals with stage and value. You see both systems side by side, recent tickets, open deals and a sentence on whether support load looks high for the deal value. It stops if several people match, shows both values when names or titles differ, and changes nothing.
Business outcome
---
One email gives you the customer's tickets, person, company and deals together, so you answer with the full picture.
scenario
-
Reps often do not learn that a customer on one of their deals has escalated or piling-up support tickets until it hurts the close. Checking means opening each deal in the CRM, finding the company's domain and searching the help desk for its tickets.
What popdock provides
--
Name a deal stage, and optionally a minimum value. It lists the Attio deals at that stage, finds each company's domain, and looks the company up in Freshdesk to count unresolved and escalated tickets and note the highest open priority. The report ranks deals by risk, High, Medium or Low, with the rule stated. Companies with no Freshdesk match are listed as unknown, not low risk. It checks at most 15 companies and is read-only.
Business outcome
---
Deals with support trouble are ranked ahead of the close, and companies the help desk has no record of are shown as unknown, not safe.
scenario
-
Preparing for renewals means pulling renewal dates from the help desk, deal owners from the CRM and ticket history for each customer, one company at a time. The pieces sit in different systems, so the brief is slow to build and the support story is often left out.
What popdock provides
--
Optionally set a look-ahead window and a maximum number of companies. It finds Freshdesk companies renewing in that window, with account tier, health score and renewal date. It matches each to Attio by domain to find open deals and owners, then reads 90 days of tickets for the ticket count, escalations and most common type. The brief is ordered by renewal date with a line on what to raise. It does not invent health scores or owners, and it is read-only.
Business outcome
---
A renewal brief for each upcoming customer, with the owner, deal and support history in one place, is ready without gathering it by hand.
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