A CRM that doesn't talk to your email, your ERP, or your marketing tools is a CRM your team has to update manually -- and won't.

Gmail integration via the Google Workspace Marketplace app (OAuth 2.0, Gmail API) and Microsoft Outlook/365 integration via Microsoft Graph API (Mail and Calendar scopes) -- both connecting to the user's mailbox server-side so emails are logged even when the rep sends from their mobile or from a desktop app rather than only from the CRM-embedded email composer. Sent and received emails matched to CRM records using a contact matching priority: exact email address match first (fastest and most reliable); domain match against known company accounts for unmatched sender addresses (emails from @acmecorp.com logged against the Acme Corp account regardless of which specific contact sent them); manual association for conversations the rep wants to log that don't match automatically. Contact, deal, and account linked simultaneously: an email from a prospect who is both a contact on Account A and is in Deal #247 appears in all three activity timelines without duplication. Calendar integration: events from Google Calendar (Google Calendar API) and Outlook Calendar (Graph API) with at least one attendee matching a CRM contact are imported as meeting activity records within 15 minutes of the event time passing. Meeting record includes attendees, duration, meeting type (in-person, video, phone), and a notes field for the rep to add outcome notes post-meeting. Zoom, Google Meet, and Microsoft Teams meeting URLs extracted from calendar events and stored in the meeting record so managers can review call recordings linked directly from the CRM activity log. Selective logging configuration: emails to internal domain addresses excluded by default; contacts in an exclusion list (competitors, personal contacts, press) excluded by email or domain; marketing tool sender addresses excluded by platform (Mailchimp From headers, HubSpot tracking addresses). Reps see their personal email activity with a clear audit of what is and is not being logged -- the transparency that prevents the "I didn't know that was being recorded" complaint.

Order history, invoice status, and payment data from the ERP surfaced on the CRM account record via a read-only sync so the sales rep can see the full commercial picture during a call without opening a separate system or asking finance to run a report. ERP integration approach per platform: SAP S/4HANA and SAP ECC via SAP OData services (for SAP Business Technology Platform-enabled systems) or RFC/BAPI function calls (for older ECC deployments) -- typically exposing Customer master data, Sales Order list, FI-AR open items, and Invoice list. Oracle ERP Cloud via Oracle REST API. NetSuite via the SuiteTalk REST Web Services API (SuiteQL for complex queries). Microsoft Dynamics 365 Business Central via the Business Central REST API (accounts, customer ledger entries, sales invoices). For on-premise ERP systems without a REST API, a scheduled ETL job (running every 15-60 minutes) reads from the ERP database directly via ODBC or a staging table and pushes updates to the CRM. Data surfaced on the CRM account record: last 24 months of orders with product, quantity, value, and delivery status; open invoices with days outstanding; payment history (on-time payment rate, average days to payment -- the behavioural data that tells the sales rep whether a new deal will create finance problems); credit limit and current credit utilisation; and any active disputes or credit holds. Quote-to-order flow: when a deal is marked won in the CRM, a sales order is created automatically in the ERP with the deal line items, pricing, customer reference, and delivery address mapped from the CRM record -- eliminating the manual re-entry that typically takes 15-30 minutes per deal and introduces errors from re-keying. Credit risk alerts: if a CRM account has an invoice more than 30 days overdue in the ERP, a visible alert appears on the account record in the CRM so the sales rep doesn't commit to additional credit terms on a new deal without knowing the outstanding balance.

Lead import from marketing automation platforms with campaign and source attribution preserved as first-class data on the CRM contact record -- not buried in a notes field where it becomes invisible. Integrations covered: HubSpot Marketing Hub (via HubSpot CRM API, bidirectional); Marketo (Marketo REST API, lead activity and campaign membership sync); Mailchimp (Mailchimp Marketing API, subscriber data and campaign engagement); Pardot/Marketing Cloud Account Engagement (Salesforce-integrated, via Connected App OAuth); and ActiveCampaign (REST API, contact and deal sync). UTM attribution preserved through the full chain: a lead who arrived via a LinkedIn ad (utm_source=linkedin, utm_campaign=q3-enterprise-series) carries that attribution into the CRM so the sales team can see which marketing channels produced leads that closed, not just which channels generated clicks. Email engagement sync: email opens, link clicks, and unsubscribes from the marketing platform synced to the CRM contact's activity timeline so a sales rep about to call a prospect can see "opened 3 marketing emails this week including the pricing page feature email" -- context that shapes the opening of the call without the rep having to check a separate marketing platform. Unsubscribe sync is bidirectional: a contact who unsubscribes from a marketing email is flagged in the CRM to prevent the sales team from manually emailing them outside the marketing platform (a GDPR/CAN-SPAM risk). CRM to marketing platform segment sync: contact segments defined by CRM fields (industry, company size, deal stage, product interest) are pushed to the marketing platform as audience segments for campaign targeting, updated on a scheduled basis so campaign audiences always reflect the current CRM state rather than a one-time export. MQL score sync: the marketing platform's lead score or MQL status surfaced in the CRM alongside the contact record so sales reps prioritise outreach to contacts the marketing system identifies as high-intent based on their content engagement, not just the date they were added.

Inbound and outbound call logging from VoIP platforms connected via their respective APIs and webhook events: Twilio Programmable Voice (call status callbacks, call recordings via RecordingComplete webhook); RingCentral (Glip/RingCentral Engage, call log API and event subscriptions); Aircall (real-time event webhooks: call.ringing, call.answered, call.ended); Dialpad (Dialpad API, call events and transcription webhooks); CloudTalk (REST API and webhooks). Each completed call creates a CRM activity record automatically with: the CRM contact matched by caller ID or inbound DID routing; call duration; call direction (inbound/outbound); call outcome field (connected, no answer, voicemail -- set automatically from call status); a link to the call recording stored in the telephony platform's cloud storage; and any post-call notes added by the rep via an after-call work screen. Caller ID matching: incoming calls are matched against CRM contacts by phone number (normalised to E.164 format to handle local vs. international number format differences) before the call is answered, so the rep sees the contact and account name on their screen at ring time without searching. Click-to-call from the CRM contact record: clicking a phone number initiates the call through the connected telephony platform without the rep dialling manually -- reducing dialling errors and keeping the call logged against the correct record from the start. Call recording integration with AI transcription: transcription via Gong, Chorus.ai (Zoominfo Chorus), or Fireflies.ai produces a searchable transcript stored on the CRM activity record within 10-15 minutes of call completion -- enabling managers to search for keywords across all call recordings and coaching teams to review specific conversations from the deal timeline rather than asking reps to forward recordings. After-call task creation: when a call ends with outcome "connected", the rep is prompted to log the call outcome and create a follow-up task before the call record closes -- capturing the "send proposal by Friday" commitment while the conversation is still active in working memory.

Contact and company data enrichment integrated as an automatic step in the lead creation workflow so records are enriched before a rep first opens them, rather than requiring manual lookups per contact. Enrichment providers connected via their APIs: Clearbit (Clearbit Enrichment API -- company data by domain, person data by email); Apollo.io (REST API -- company and contact data with phone number coverage); ZoomInfo (ZoomInfo API -- firmographic, technographic, and contact data); LinkedIn Sales Navigator (via SNAP API for authorised deployments -- company and person context for existing CRM contacts); Bombora (intent data API -- company-level topic intent scores overlaid on account records to prioritise outreach by purchase intent signal). On new account creation: the company domain is extracted from the contact's email address or manually entered, the enrichment API is called, and fields populated automatically include company size (employee count), industry (NAICS/SIC code and human-readable label), estimated annual revenue, headquarters location, technology stack (HR software, CRM, ERP systems in use -- from technographic data), funding status and last funding round, and the company LinkedIn URL. On new contact creation: contact enrichment populates job title, department, LinkedIn profile URL, direct phone number (where available from the enrichment provider), and seniority level -- so the rep can prioritise based on whether the contact is a decision-maker or an individual contributor without having to research each contact separately. Email validation at ingestion: new email addresses validated against an email validation API (ZeroBounce, NeverBounce, Hunter.io) before the contact is saved, flagging disposable email addresses, invalid domain MX records, and known catch-all addresses that will accept any email but deliver to no one. Enrichment refresh on a 90-day schedule: records re-enriched quarterly to catch headcount changes, job title changes, and technology stack updates -- important for accounts where the rep's original notes are now 12 months old and the organisation may have changed materially.

Per-integration health monitoring collecting metrics on every sync cycle: records processed, records successfully synced, records failed with error type, and sync duration. These metrics are collected to a monitoring store (typically a time-series table in the data warehouse or a dedicated observability platform) and surfaced in an integration health dashboard accessible to the CRM administrator without requiring access to infrastructure logs. Alerting thresholds: if an integration's success rate drops below 95% in a 1-hour window, an alert fires to Slack or PagerDuty; if a sync cycle has not completed within 2x its expected duration, an availability alert fires; if the record count processed in a sync cycle is more than 20% below the rolling average (indicating a silent API failure where the source system returned fewer records than expected without an error), a data volume alert fires. Silent failures are the most dangerous integration failure mode -- the sync appears to complete successfully, no errors are logged, but data has stopped flowing because an upstream API changed a response format or silently started returning an empty result set. The monitoring layer catches this category of failure that error-log monitoring would miss. Data quality reporting per integration: which CRM account records are missing the email field that should have been populated by data enrichment; which contact records are missing the job title field; which deal records are missing the expected ERP order reference that should have been populated by the quote-to-order integration. These reports surface gaps to the CRM administrator for remediation before they affect sales team productivity. Duplicate detection running weekly: contact and company deduplication using a probabilistic matching algorithm (Levenshtein distance on name fields, exact match on email and phone normalised to E.164) identifies likely duplicate records and presents them as merge candidates in a review queue -- the administrator reviews and approves merges rather than the algorithm automatically merging records, which prevents the accidental merge of two genuinely different contacts who share similar details.