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Signal:a data event that tells you a prospect is in-market before they raise their hand: a pricing page visit, a funding round, a job change, a replyEnrichment waterfall:querying data sources in sequence until you get a value: Clay tries source A, then B, then C. Better coverage than any single providerGTM Engineering:treating your go-to-market motion as a software system: ICP as filter, signals as triggers, sequences as logic branches, Slack as the delivery layerIntent:behavioral evidence that an account is actively researching a problem you solve, before they contact sales or fill a formOutbound infra:the sending domains, mailboxes, DNS records, and warm-up cadence that keep your email out of spam and your main domain cleanICP filter:the exact definition of which companies and personas belong in your pipeline, expressed precisely enough that a machine can execute itWarm lead:a prospect who has taken a signal action (pricing page, reply, meeting request) that moves them ahead of every cold contact in your sequenceClay waterfall:a Clay table that pulls from LinkedIn, Apollo, and 50+ sources simultaneously, scoring and filtering prospects in real time before they reach a repEnrichment cost:the per-row credit spend of running a Clay workflow: easy to burn through budget fast when calling Clay from an AI agent without guardrails; controlling this requires knowing which enrichments to run, in what order, and when to stopSignal:a data event that tells you a prospect is in-market before they raise their hand: a pricing page visit, a funding round, a job change, a replyEnrichment waterfall:querying data sources in sequence until you get a value: Clay tries source A, then B, then C. Better coverage than any single providerGTM Engineering:treating your go-to-market motion as a software system: ICP as filter, signals as triggers, sequences as logic branches, Slack as the delivery layerIntent:behavioral evidence that an account is actively researching a problem you solve, before they contact sales or fill a formOutbound infra:the sending domains, mailboxes, DNS records, and warm-up cadence that keep your email out of spam and your main domain cleanICP filter:the exact definition of which companies and personas belong in your pipeline, expressed precisely enough that a machine can execute itWarm lead:a prospect who has taken a signal action (pricing page, reply, meeting request) that moves them ahead of every cold contact in your sequenceClay waterfall:a Clay table that pulls from LinkedIn, Apollo, and 50+ sources simultaneously, scoring and filtering prospects in real time before they reach a repEnrichment cost:the per-row credit spend of running a Clay workflow: easy to burn through budget fast when calling Clay from an AI agent without guardrails; controlling this requires knowing which enrichments to run, in what order, and when to stop
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RB2B Review: Person-Level Visitor Identification for B2B GTM

RB2B identifies US-based site visitors by name and LinkedIn profile, pushes them to Slack in real time, and has a free tier. We have run it for clients. Here is what it actually does, where it falls short, and how to make it useful.

Most visitor identification tools tell you which company visited your site. RB2B tells you which person. That is a meaningful difference when you are running outbound. Knowing that Acme Corp visited your pricing page is a weak signal. Knowing that Sarah Chen, VP of Marketing at Acme Corp, visited your pricing page and stayed for four minutes is something you can act on.

The caveat is that RB2B only does this for US-based visitors. If your ICP is global, that is a real constraint. If your ICP is primarily US-based, RB2B is one of the most cost-effective signal tools in the stack.

What RB2B actually does

You install a JavaScript snippet on your site. When a US-based visitor lands on a page, RB2B cross-references their IP and browser signals against its identity graph to resolve them to a LinkedIn profile. If it gets a match, it pushes a record to your configured destination: a Slack channel, a webhook, or directly to a connected CRM.

A typical RB2B payload includes: full name, LinkedIn profile URL, job title, company name, company domain, and the page they visited. It does not include email addresses directly (LinkedIn data does not carry verified emails). You get the identity; you close the loop on contact data via an enrichment step downstream.

The match rate for US visitors is typically 20–40%, depending on your traffic composition. B2B-heavy traffic from organic search and paid campaigns targeting businesses tends toward the higher end. Consumer-adjacent traffic or heavily VPN-using audiences trends lower.

What you get per identification

  • Full name
  • LinkedIn profile URL
  • Current job title
  • Company name and domain
  • Page visited and timestamp
  • Session source (where available)

What RB2B does not do

The US-only constraint is the most important limitation to understand before committing. If you pull up your analytics and 40% of your traffic comes from Europe, RB2B will miss those visitors entirely at the person level. You will get company-level data for some of those sessions (the standard IP-to-company matching), but not the person.

RB2B also does not provide intent scoring, account health tracking, or CRM-native syncing out of the box. It identifies and pushes a record. What you do with that record is your problem. That is by design, and it is actually one of the reasons it is easy to wire into a custom stack, but it means there is no built-in scoring or prioritization.

Finally, RB2B requires traffic to work. The tool is not useful at 200 monthly visitors. If your US organic and paid traffic is below 500 sessions per month, the volume of signals you will receive is too low to build a repeatable workflow around. Check your analytics before signing up.

Pricing

RB2B has a free tier that gives you 100 person-level reveals per month. That is enough to validate whether the tool works with your traffic and see what the Slack output looks like before spending anything.

For most Series A companies running meaningful outbound, the paid tier is the right place to be. At $19–$49/month for the volume most early-stage companies need, the ROI is not a hard calculation if you are actively working the signals.

What makes it genuinely good

Three things stand out when you are actually running RB2B for clients:

The Slack integration is excellent. The notification format is clean: name, title, company, page visited, LinkedIn link, and a timestamp. A rep can look at a Slack ping, click the LinkedIn profile, and have context to act within 30 seconds. Most Slack integrations from GTM tools feel like an afterthought. RB2B's feels like the primary use case, which it is.

Person-level identification is rare. Most visitor identification tools (Clearbit Reveal, Leadfeeder, 6sense) resolve to the company. RB2B resolves to the person. For outbound, this removes a research step. You do not need to guess which person at the company to reach out to. You know who was on the site.

Signal quality is high for US traffic. The match rate is lower than company-level tools (20–40% vs. 60–80% for IP-to-company), but the signals that do match are high-quality. A person-level match on a pricing page visit is a much stronger buying signal than a company-level match on a homepage visit.

Limitations worth understanding before you buy

RB2B vs Koala

These two tools get compared often and they are solving adjacent but different problems.

RB2B is person-level identification with a Slack-first delivery model and a free tier. The product is built around getting a signal into a rep's hands quickly. The workflow is: identify visitor, push to Slack, rep takes action.

Koala is account-level identification with CRM-native scoring. It identifies companies (not individuals), tracks engagement history per account, scores accounts based on intent signals, and syncs into your CRM with rules you configure. The workflow is: identify account, score based on engagement, surface to the CRM for follow-up.

DimensionRB2BKoala
Identification levelPerson (US only)Company (global)
Signal outputSlack / webhookCRM + Slack
ICP scoringNone built-inYes, configurable
Email in payloadNoNo (company data)
Free tierYes (100/mo)Limited trial
PricingStarts ~$19/moStarts ~$750/mo
Best forOutbound GTM EngineeringABM / marketing workflows
Geographic coverageUS only (person-level)Global (company-level)

For outbound GTM Engineering, RB2B wins. Person-level identification is more actionable for a sequencing workflow. For ABM programs and marketing teams who need account scoring and CRM-native workflows, Koala is better suited and worth the higher price point.

Some teams run both: RB2B for person-level outbound signals on high-intent pages (pricing, demo, docs), and Koala for account-level scoring across all traffic for the ABM layer. That combination covers both use cases but adds cost and operational complexity.

How to use RB2B in a GTM Engineering stack

RB2B by itself is a notification tool. The leverage comes from what you do with the signal downstream. The standard stack integration looks like this:

RB2B signal flow

RB2BIdentifies US visitor, fires webhook with person-level data
n8n / ZapierReceives webhook, checks if person passes ICP criteria (title, company size, industry)
ClayEnriches the record: verified email, tech stack, funding stage, LinkedIn summary
InstantlyAdds enriched contact to a targeted sequence (e.g., "pricing page visitors: VP Marketing")
SlackNotifies the team with contact card, LinkedIn link, and context about the visit

The n8n step is the filter layer. Without it, every RB2B identification (including people who are not remotely in your ICP) hits the sequencer. With it, only records that pass your ICP criteria (title contains VP or Director, company headcount 15–200, industry is SaaS or fintech) move forward. The Clay enrichment step closes the email gap: RB2B gives you the LinkedIn profile, Clay waterfall enrichment finds the verified work email from People Data Labs, RocketReach, or similar providers.

The end state is a person who visited your pricing page landing in a sequence within five to fifteen minutes of their visit, with a first email that can reference relevant context, and a Slack ping to the account owner with enough information to act immediately if they want to call instead of sequence.

For the broader signal-based outbound framework this fits into, see signal-based outbound. For where RB2B sits in the full stack, see the GTM Engineering stack.

The bottom line

RB2B is one of the more straightforward tools in the GTM Engineering stack to evaluate. The free tier lets you see exactly what you get before spending anything. The Slack integration takes 20 minutes to set up. You will know within two weeks whether your traffic volume justifies the paid tier.

The US-only constraint is real and you should check your traffic data before assuming the tool will solve your visitor identification problem entirely. For companies with global traffic and a global ICP, RB2B covers a subset of the opportunity. Pair it with a company-level tool for non-US traffic if that matters for your pipeline.

For US-focused B2B companies at Series A with 500+ monthly visitors and an active outbound program, RB2B is a high-ROI addition to the stack. Person-level identification at $19–$49/month is genuinely cheap for what it surfaces.

Frequently asked questions

Is RB2B free?

RB2B has a free tier that gives you 100 person-level reveals per month. That is enough to validate whether the tool works for your traffic before committing. Paid plans start at around $19/month and scale based on reveal volume. For most Series A companies with meaningful traffic, the paid tier pays for itself within the first month if you are actively working the signals.

Does RB2B work for non-US visitors?

No. RB2B identifies US-based visitors only. For non-US traffic, you will get company-level identification for some sessions but not the person-level LinkedIn profile. If a meaningful portion of your ICP is based in Europe, APAC, or LATAM, RB2B will miss those visitors at the person level. This is the most significant constraint of the tool and it matters a lot for companies with international GTM.

How does RB2B compare to Clearbit Reveal or 6sense?

Clearbit Reveal and 6sense identify visitors at the company level and add intent scoring. RB2B identifies at the person level for US traffic. These are complementary, not equivalent. If you need account-level intent data across all traffic, 6sense is the tool. If you want to know which specific person at a target company visited your pricing page, RB2B is more useful. They serve different parts of the identification and intent workflow.

How much traffic do I need for RB2B to be useful?

As a rough benchmark: fewer than 500 monthly US visitors will produce a low number of reveals per month, and it is hard to build a repeatable workflow around that volume. At 1,000+ monthly visitors from a US-heavy audience, the volume gets interesting. Check your analytics: look at US organic and paid traffic specifically, not total sessions. The match rate applies to that US subset, not your total traffic.

RB2B vs Koala: which should I use?

Use RB2B if your priority is person-level identification for outbound, you have US-focused traffic, and you want a simple Slack-based signal flow. Use Koala if you are running an ABM program that needs CRM-native scoring, account health tracking, and company-level intent signals across all traffic. For outbound GTM Engineering, RB2B wins because person-level identity is more actionable than company-level. For marketing workflows and ABM, Koala is better.

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We wire RB2B into your full outbound stack.

RB2B signal capture, Clay enrichment, ICP filtering in n8n, and sequencer routing in Instantly. Built and running inside your accounts within two weeks.

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