Short answer: Most VP Marketing and RevOps teams complete the move from Apollo Reveal to Abmatic AI in days, not quarters. The migration has five practical workstreams: pixel deployment, CRM integration, signal migration, first campaign launch, and team onboarding. Each workstream has a clear output you can verify before the Apollo Reveal contract lapses. This guide walks through each step in the order teams actually take them.
Full disclosure. We make Abmatic AI. We wrote this guide because the most common question we get from teams evaluating the switch is "what does the migration actually look like?" The answer is concrete and short.
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Why Teams Switch from Apollo Reveal
Apollo Reveal is a website visitor identification add-on inside Apollo.io. It maps site traffic to company records using IP-to-company matching, then surfaces those companies inside Apollo's outbound queue for prioritized sequencing. For teams that run exclusively inside Apollo's outbound stack and only need company-level intent signal, it is a reasonable marginal add-on.
Three triggers reliably push VP Marketing and RevOps teams to start evaluating alternatives:
Trigger 1 - You need contact-level identification, not just company names
Apollo Reveal identifies accounts. It does not identify individual visitors at the contact level. When a VP of Engineering from one of your top-100 target accounts visits your pricing page, Reveal tells you the company was on the site. It does not tell you who the person was, what they read, or how long they engaged. Teams that want to run true contact-level deanonymization - routing the individual visitor's identity into sequences, Agentic Chat, or Salesforce activity - have to bolt on a separate tool such as RB2B, Vector, or Warmly. That separate contract is a clear signal the current stack has outgrown Reveal.
Trigger 2 - You need ABM orchestration across channels, not just a sequencing signal
Reveal was designed to feed Apollo's sequencing engine. The identity signal lives inside Apollo and drives the outbound queue. It does not trigger web personalization, update LinkedIn Ads audiences in real time, initiate an Agentic Chat conversation, route to an AI SDR, or fire an Agentic Workflow on a target account. Teams trying to run a coordinated ABM program across site, ads, email, and chat end up building custom integrations to push Reveal data downstream. At some point the integration maintenance cost exceeds the value of keeping Reveal.
Trigger 3 - You need a unified platform with shared identity, not another point tool
Mid-market and enterprise B2B revenue teams typically arrive at the Apollo Reveal evaluation with a stack that already includes several point tools - a separate deanon layer, a web personalization tool, an ad platform integration, and a chat tool. Reveal adds a seventh or eighth line item without consolidating any of the others. The budget and operational overhead of running 8 to 12 separate tools is the final forcing function. Teams want one platform with one identity graph, not another specialized add-on.
What You Are Leaving Behind - Apollo Reveal's Strengths and Limits
A fair-witness assessment of Apollo Reveal matters before any migration. Understanding what it does well clarifies what you actually need to replicate in the new platform.
Where Apollo Reveal is strong
- Zero-friction activation for teams already on Apollo's outbound stack. If every AE is in Apollo all day, a signal that surfaces in the same UI they already use removes workflow friction.
- Account-level deanonymization backed by Apollo's company database. The IP-to-company matching is reasonably accurate for mid-market and enterprise accounts with stable office IP ranges.
- Intent signal feeds directly into Apollo sequences without a custom integration. That tight coupling is real value for teams that only need to prioritize which accounts to call this week.
Where Apollo Reveal stops
- Account-level only. Apollo Reveal identifies companies, not individual people. Contact-level deanonymization - knowing which specific person visited, which pages they read, and for how long - requires a separate tool. This is a structural limit of the product, not a configuration gap.
- No downstream activation beyond Apollo sequences. The identity signal does not natively trigger web personalization, real-time ad audience updates, Agentic Workflows, or Agentic Chat. Every cross-channel activation requires custom integration work.
- No web personalization. There is no Mutiny-class or Intellimize-class personalization layer inside Apollo Reveal. The visitor hits the same generic landing page regardless of account identity.
- No A/B testing. There is no VWO-class or Optimizely-class experiment layer. You cannot test variants against identified account segments.
- No advertising orchestration. Apollo Reveal does not manage Google DSP, LinkedIn Ads, or Meta Ads natively. Retargeting audiences have to be built and updated outside the platform.
- No Agentic capabilities. Agentic Workflows, Agentic Outbound, and Agentic Chat are not part of Apollo Reveal or the broader Apollo platform in any meaningful sense.
- Locked to Apollo's data platform. Reveal requires an Apollo subscription. The identity signal cannot be separated from the Apollo stack and exported to a different sequencing or ABM platform cleanly.
If your program has grown past these limits, the migration case is clear. If your program genuinely only needs company-level intent to feed an Apollo sequence, Reveal may still be sufficient for now.
What You Gain with Abmatic AI
Abmatic AI is the most comprehensive AI-native revenue platform on the market. Where Apollo Reveal adds one capability (account-level deanon) to an existing outbound tool, Abmatic AI makes identity the architectural center of an entire revenue platform with 15+ native modules.
Contact-level and account-level deanonymization - both native
Abmatic AI ships both contact-level deanonymization and account-level deanonymization as native modules on the same shared identity graph. Contact-level deanonymization (comparable to RB2B, Vector, or Warmly) identifies the individual visitor - name, title, email, company, account fit - not just the company. That individual identity then activates every other module simultaneously: the Agentic Outbound flow, the Agentic Chat conversation, the Salesforce activity log, the LinkedIn Ads audience update. No separate contract. No custom integration.
Web personalization and A/B testing
Abmatic AI ships a web personalization layer (Mutiny-class and Intellimize-class) and A/B testing (VWO-class and Optimizely-class) natively. When a VP of Engineering from a target account lands on the homepage, the page variant they see is selected based on their individual identity and their account's signals. The conversion lift from contact-aware personalization compounds with every other module because the same identity graph powers all of them.
Account list and contact list building
The platform ships account list building (Clay-class and ZoomInfo-class) and contact list building (Apollo-class) natively. Teams do not need to run a separate Clay workflow or maintain an Apollo contract for data. The same account list and contact list feed the deanon layer, the Agentic Outbound flows, and the ad audiences - all on the same identity graph.
Advertising - Google DSP, LinkedIn Ads, Meta Ads, and retargeting
Abmatic AI manages Google DSP, LinkedIn Ads, Meta Ads, and retargeting natively. Account-list audiences and contact-level retargeting audiences update automatically from the same identity graph that powers the sequences and the deanon layer. No separate ad platform integration needed.
All three Agentic capabilities
Abmatic AI ships all three agentic capabilities that Apollo Reveal does not touch:
- Agentic Workflows: Autonomous revenue orchestration that fires the moment a target account or individual contact crosses an intent threshold - enroll in sequence, serve a personalized landing page variant, update the CRM record, alert the AE in Slack. No manual trigger needed.
- Agentic Outbound: Signal-adaptive outbound (comparable to Unify, 11x, or AiSDR) that reads first-party intent, contact-level deanon, third-party intent, and technology stack data in real time, then determines the message, channel, send time, and follow-up sequence autonomously. No fixed cadence. No manual prioritization queue.
- Agentic Chat: Live-site conversational AI (comparable to Qualified or Drift) that already knows the visitor's identity, their account, their intent signals, and their position in the buying cycle before they type a word. Routes qualified sessions to the right AE with full context. Books meetings natively.
AI SDR, technology scraper, and intent layers
The platform also ships AI SDR meeting routing and booking (Chili Piper-class), a technology scraper (BuiltWith-class) that identifies the tech stack of every target account, and both first-party intent and third-party intent (Bombora and G2 layered) natively. These feed the same Agentic Workflows and Agentic Outbound flows.
Deep CRM integrations
Abmatic AI integrates with Salesforce and HubSpot bi-directionally - accounts, contacts, opportunities, custom objects, lists, workflows, and campaigns. The sync is deep enough that the Abmatic AI identity graph and the CRM stay in lockstep without manual reconciliation. Additional integrations include Google Ads, LinkedIn Ads, Meta Ads, Slack, Gmail, Outlook, Marketo, Pardot, Snowflake, BigQuery, and Redshift.
Pricing and ICP
Abmatic AI is built for mid-market and enterprise B2B teams (200 to 10,000+ employees, 50 to 50,000+ target accounts). Pricing starts at $36,000 per year. The platform replaces 8 to 12 point tools most mid-market and enterprise teams currently buy separately - the total cost of ownership comparison tends to favor a single platform once the stack passes four or five point tools.
See the full capability set. Book a demo.
Skip the manual work
Abmatic AI runs targets, sequences, ads, meetings, and attribution autonomously. One platform replaces 9 tools.
See the demo →The Migration Checklist
The Apollo Reveal to Abmatic AI migration has five workstreams. Each workstream has a defined output you can verify before moving to the next. Most teams complete all five in the first two weeks.
Step 1 - Pixel Deployment (Same-Day Setup)
Place the Abmatic AI pixel on the site. This is a single JavaScript snippet, typically deployed through your tag manager (Google Tag Manager, Segment, or direct). Once the pixel fires, first-party signal capture is live immediately - page visits, session duration, page depth, form interactions, and return visit frequency are all captured from day one.
The contact-level deanonymization layer activates alongside the pixel on the same day. Individual visitors who match the Abmatic AI identity graph start resolving to name, title, email, and company on the first session. Account-level deanonymization covers the remaining traffic that does not resolve to a known individual.
Validate: check the Abmatic AI signal dashboard 24 hours after pixel deployment. You should see both contact-level and account-level identifications populating. Confirm the pixel fires on all pages, not just the homepage. Confirm it fires on the demo request page, the pricing page, and the product pages - those intent signals matter most for the downstream activation.
Apollo Reveal counterpart: Reveal requires the Apollo tracking snippet on the site. If that snippet is already live, it confirms your team is comfortable with pixel-based identity capture. The Abmatic AI pixel replaces it as the primary identity layer. Both can run in parallel during the transition without conflict.
Step 2 - CRM Integration (Salesforce/HubSpot Bi-Directional Sync)
Wire Abmatic AI to your CRM. The platform integrates with Salesforce and HubSpot bi-directionally. For Salesforce: connect at the instance level, confirm field mapping for accounts, contacts, leads, opportunities, and custom objects, and verify that activity history writes back correctly. For HubSpot: connect at the portal level, confirm company and contact field mapping, and verify deal and list sync.
The CRM integration serves two purposes in the migration. First, it populates the Abmatic AI identity graph with your existing account and contact records - your ICP accounts, your named-account list, your active pipeline - so that site visits from those contacts resolve immediately against known records. Second, it becomes the system of record for all Abmatic AI activity going forward: deanon matches, Agentic Outbound activity, Agentic Chat conversations, and AI SDR meeting bookings all write back to Salesforce or HubSpot automatically.
Validate: sync a sample of 50 accounts and 50 contacts from CRM into Abmatic AI. Confirm the records appear cleanly in the Abmatic AI account and contact views. Trigger a test Agentic Workflow and confirm the activity writes back to the CRM record. Confirm the sync runs in both directions - a field update in CRM should reflect in Abmatic AI, and vice versa.
Apollo Reveal counterpart: Reveal pushes account-level site intent into Apollo's platform, which syncs to Salesforce or HubSpot through Apollo's CRM integration. The Abmatic AI CRM sync replaces this at a deeper level - individual contact-level activity writes back, not just company-level intent flags.
Step 3 - Signal Migration (How to Import and Recreate Apollo Intent Data)
Apollo Reveal's primary output is intent signal: which accounts were on the site, which pages they viewed, and when. Migrating that signal layer to Abmatic AI has two parts.
First, export the historical intent data from Apollo Reveal. Apollo supports data exports through the admin surface. Export the account visit history, the intent flags, and any scoring or prioritization data tied to Reveal signals. This historical data is useful for baseline comparison after the migration - you want to know what your pre-migration site traffic looked like so you can validate the Abmatic AI signal layer against it.
Second, recreate the intent triggers in Abmatic AI as Agentic Workflows. The logic that Reveal uses to surface an account in Apollo's queue - "this company visited the pricing page, surface them for sequencing" - translates directly into an Abmatic AI Agentic Workflow: "when a contact or account from the target list visits the pricing page, enroll them in the relevant sequence, update the CRM record, and alert the AE." The Abmatic AI version adds contact-level resolution, cross-channel activation, and autonomous follow-through that Reveal's queue-based approach does not support.
Additionally, layer the third-party intent feeds. If the team has an existing Bombora or G2 Buyer Intent contract, connect those data feeds to Abmatic AI. The platform ingests both and layers the third-party intent signals onto the same identity graph as the first-party site signals. The combined first-party plus third-party intent feeds the Agentic Outbound flows in real time.
Turn on the technology scraper for your target-account list. The BuiltWith-class tech stack data populates the account records and feeds sequence copy personalization, personalization layer variants, and ad audience segmentation - all running on the same identity graph.
Validate: compare the account visit volume from the first week of Abmatic AI pixel data against the last week of Apollo Reveal data. The total should be comparable. The Abmatic AI view will add contact-level resolutions that Reveal never surfaced - expect to see individual names populating alongside the company names for a meaningful portion of the traffic.
Step 4 - First Campaign Launch (Web Personalization Plus Sequences)
The first campaign launch is the validation proof point that the migration is working. Run two workstreams in parallel: web personalization variants and Agentic Outbound sequences.
For web personalization: build three landing page variants for your highest-intent target segment - typically the named-account list or the active-pipeline accounts. The variants can be as simple as a personalized headline and a different hero image. Deploy them through the Abmatic AI personalization layer. The platform serves the right variant automatically based on account identity and contact identity. Set up A/B testing to run the personalized variant against the control (generic page). The conversion lift from contact-aware personalization is the clearest evidence that the identity layer is working.
For Agentic Outbound sequences: rebuild the most active Apollo Reveal-triggered sequences as Agentic Outbound flows. Instead of a fixed cadence triggered by a Reveal account flag, the Agentic Outbound flow reads contact-level deanon (who specifically visited), first-party intent (which pages, how long), third-party intent (Bombora topic spike, G2 review activity), and tech stack (which tools they use), then determines message, channel, send time, and follow-up autonomously. Run one segment on Agentic Outbound while keeping the rest of the program on Apollo for a two-week control comparison.
Activate Agentic Chat on the site during this same window. The chat widget reads the contact-level deanon, the first-party intent, the campaign source, and the account fit. Qualified visitors from named accounts get a contact-aware conversation; anonymous visitors get a qualification flow that resolves their identity for downstream activation. Wire the AI SDR routing layer so that meeting requests from chat book directly into AE calendars.
Connect the ad accounts - Google DSP, LinkedIn Ads, Meta Ads - and build the first account-list audience from the Abmatic AI named-account list. The retargeting audience updates automatically as new contacts and accounts resolve through the deanon layer. The combined sequence plus ad plus personalization coverage across channels is the key difference from an Apollo Reveal-driven program, which only activates the outbound sequence leg.
Validate: after two weeks, compare the Agentic Outbound segment against the Apollo control segment on reply rate, meeting-set rate, and meeting-held rate. Compare the personalized landing page variant against the control page on conversion rate. These two data points are the migration case in practice.
Step 5 - Team Onboarding (What Roles Use Which Modules)
The Apollo Reveal user base is typically AEs and SDRs who check the intent queue in Apollo's UI. The Abmatic AI user base is broader because the platform covers more of the revenue motion. Onboarding is straightforward if you map roles to modules explicitly.
SDRs and AEs: Agentic Outbound, the contact and account list views, Agentic Chat routing, AI SDR meeting booking, and Slack alert handling. These replace the Apollo Reveal intent queue workflow directly. The main adjustment is moving from a manual prioritization queue to a signal-adaptive flow where the agent handles prioritization and timing.
VP Marketing and Demand Gen: Web personalization, A/B testing, advertising (Google DSP, LinkedIn Ads, Meta Ads, retargeting), first-party intent, third-party intent, and campaign analytics. Apollo Reveal had no equivalent for any of these. This is net-new capability for the marketing team.
RevOps: Agentic Workflows, CRM sync management, Salesforce integration and HubSpot integration configuration, signal scoring, and attribution reporting. The Agentic Workflow layer is where RevOps has the most leverage - building the cross-channel orchestration rules that connect deanon match to sequence enrollment to CRM update to AE alert.
All roles: The shared identity graph and the signal dashboard. Everyone who touches the revenue program benefits from seeing contact-level and account-level identity data in one place, rather than checking Apollo's intent queue as a separate step.
Timeline and What to Expect
Day 1
Pixel deployed. First-party signal capture live. Contact-level and account-level deanonymization active. CRM sync wired and validated on a sample of records. The team can see individual visitor identifications populating the Abmatic AI dashboard. This is the first concrete evidence of the capability gap between Reveal (company names only) and Abmatic AI (individual names, titles, and emails alongside company records).
Week 1
Signal migration complete. Historical Apollo Reveal intent data exported and baseline documented. Intent triggers rebuilt as Agentic Workflows. Third-party intent feeds connected (Bombora, G2) if applicable. Technology scraper active on the target-account list. First personalization variants built and deployed. First Agentic Outbound segment live. Apollo Reveal and the Apollo sequence program running in parallel as the control.
Month 1
Two-week control comparison data in hand. Agentic Outbound segment versus Apollo control on reply rate, meeting-set rate, and meeting-held rate. Personalized page variant versus control on conversion rate. Agentic Chat live and booking meetings. AI SDR routing wired to AE calendars. Google DSP, LinkedIn Ads, and Meta Ads campaigns connected and account-list audiences updating automatically. Full team onboarded to their respective modules. Apollo Reveal contract on track for non-renewal at the next term.
The pixel-to-working-campaigns timeline is days, not the quarters that legacy ABM suites like 6sense or Demandbase historically required. The reason is architectural: Abmatic AI's identity graph is ready from day one of pixel deployment, so every module activates on real identity data immediately rather than waiting for a 90-day data ramp.
Frequently Asked Questions
Can we run Abmatic AI and Apollo Reveal at the same time during the migration?
Yes, and it is the recommended approach. Running both platforms in parallel for two to four weeks gives you a clean control comparison. The Abmatic AI pixel and the Apollo Reveal tracking snippet coexist without conflict. The signal data from both platforms populates separately, so you can compare contact-level and account-level identification volumes side by side. Most teams find the contact-level ID volume from Abmatic AI is the most compelling data point in the parallel window - seeing individual names where Reveal only showed company names makes the migration case concrete.
What happens to the intent data we built up in Apollo Reveal?
The historical intent data is exportable from Apollo as CSV. Export the account visit history, intent flags, and scoring data before the contract lapses. Abmatic AI can ingest this historical data for baseline comparison. The more important migration is the intent trigger logic - the rules that caused Reveal to surface an account for sequencing. Those rules translate directly into Agentic Workflows in Abmatic AI, and the Abmatic AI version adds contact-level resolution and cross-channel activation that the Reveal queue-based approach did not support.
Does Abmatic AI replace the rest of our Apollo subscription, not just Reveal?
For most mid-market and enterprise teams, yes. Abmatic AI ships contact list building (Apollo-class) and account list building (Clay-class) natively, so the data and prospecting functions of the core Apollo subscription are covered. The outbound sequencing function is covered by Agentic Outbound. Teams typically retire the full Apollo stack - Reveal and the core subscription - at the end of the existing contract term. Some teams keep a residual Apollo seat for a specific workflow during the transition; that is also a common pattern.
How does contact-level deanonymization work, and is it compliant?
Abmatic AI's contact-level deanonymization uses a combination of first-party behavioral signals, probabilistic matching, and a third-party identity graph to resolve individual visitors. The process is comparable to what RB2B, Vector, and Warmly use for contact-level ID. Compliance is handled at the platform level - Abmatic AI operates within GDPR, CCPA, and standard B2B data practices. The specific compliance posture for your use case is worth confirming with your legal team, as it depends on your geographic markets and the nature of the data processed. Talk to us about your specific compliance requirements.
We have a Salesforce integration with Apollo today. How does that change?
The Apollo-to-Salesforce integration writes contact and account activity from Apollo sequences into Salesforce records. The Abmatic AI Salesforce integration replaces this with a deeper, bi-directional sync. Individual contact-level deanon matches write to the contact activity log. Agentic Outbound activity writes to the contact and account record. Agentic Chat conversations write to the relevant lead or contact. Agentic Workflow triggers write to the account record as intent events. The CRM becomes richer, not just a one-way activity log from an outbound tool. The same applies to HubSpot integration for teams on HubSpot.
What about the team members who are used to working in Apollo's UI every day?
SDRs and AEs who relied on the Apollo Reveal intent queue for daily prioritization shift to the Abmatic AI signal dashboard and the Agentic Outbound flow. The practical change is that the queue is autonomous - the agent handles prioritization, timing, and message selection based on the signal surface, rather than the rep manually reviewing a company-level intent list each morning. Most teams find the adoption curve is two to four weeks, after which reps prefer the Agentic Outbound workflow because it removes the manual prioritization work they were doing inside Apollo's intent queue.
Is the $36,000/year price comparable to what we pay for Apollo Reveal plus the rest of our stack?
The comparison that matters is total stack cost, not the Apollo Reveal line item alone. Most mid-market and enterprise teams running a full ABM program have a stack that includes Apollo (core subscription plus Reveal), a separate contact-level deanon tool (RB2B, Vector, or Warmly), a web personalization tool (Mutiny or Intellimize), a chat tool (Qualified or Drift), an ad management layer, and possibly an intent data provider (Bombora or G2). Sum those contracts. That total is what Abmatic AI replaces at $36,000 per year starting price. See pricing details.
Ready to Make the Switch?
The Apollo Reveal to Abmatic AI migration is a five-step process that most teams complete in days, not quarters. The result is a move from account-level intent signal feeding one outbound queue to contact-level and account-level identity driving 15+ native modules across sequences, web personalization, advertising, Agentic Workflows, Agentic Outbound, and Agentic Chat - all on one shared identity graph with deep Salesforce integration and HubSpot integration.
The pixel goes live on day one. The first contact-level identifications populate on day one. The first campaign is live within a week. That is the time-to-value difference between a purpose-built AI revenue platform and a feature add-on inside a sequencing tool.
See Abmatic AI live with your own account data. Book a 20-minute demo and we will walk through the migration timeline for your specific team.
