OpenAI's DevDay 2026 (September 29) packed more than 20 announcements, but one matters far more than the rest for revenue teams: Dots — always-on ChatGPT agents that run on their own cloud computers, connect to 4,000+ apps, and keep working after you close the tab.

If the last two years were about chatting with AI, Dots are OpenAI's bet that the next two are about delegating to it. Here's what actually shipped, what it costs, where it breaks for sales use cases, and five workflows worth testing this month.

On September 15, 2026, the Salesforce in Claude plugin hit open beta on all paid Claude plans. It's the first shipping product from Claudeforce — the expanded Salesforce–Anthropic partnership announced on August 26 — and it puts 37 prebuilt sales skills inside Claude: meeting prep, account research, deal scoring, pipeline reviews, forecast narratives, and CRM updates that write back to Salesforce after you approve them.

Most coverage treated this as partnership theater between two giants. The practical story is simpler: the hours your AEs spend assembling context before calls and typing updates after them just became a chat message. If your team runs on Salesforce and anyone on it already uses Claude, this beta is worth a structured two-week pilot — not a shrug.

Here's what actually shipped, how to roll it out without scaring your admin, and the one thing Claudeforce fundamentally cannot do for your pipeline.

What Shipped, Exactly​

The facts, stripped of press-release gloss:

• Announced August 26, 2026 as "Claudeforce," with select pilot customers first. Open beta arrived September 15 on all paid Claude plans — no Enterprise-only gate.
• 37 prebuilt sales skills built jointly by Salesforce and Anthropic, covering the daily work of account executives: briefings, account research, call prep, deal-health scoring, post-call opportunity updates, pipeline dashboards with risk flags, and forecast drafts.
• Built on AIforce, Salesforce's enterprise harness that exposes CRM data and workflows through MCP servers and APIs. Translation: no custom integration project. Your admin authenticates once centrally, assigns access to groups, and every action routes through Salesforce's existing permission model.
• Approval-first writes. By default, Claude proposes a change (say, updating an opportunity from your call notes) and the seller approves it before anything is written to the CRM.
• Optional Slack integration pulls deal-channel summaries and account-team threads into the same context.
• More skills land in late 2026, with service, marketing, and commerce skills slated for the following quarter.

Two details matter more than the rest. First, permission inheritance: users can't see records through Claude that they can't see in Salesforce. That kills the most common security objection before it starts. Second, there's no self-service for individual reps — distribution runs through AgentExchange and your Salesforce admin. If you're a rep reading this, your first move is a Slack message to whoever owns your org.

The 37 Skills, Organized by When You'd Use Them​

Salesforce hasn't published the full list, but the skills cluster cleanly around the rhythm of a selling week:

When	What Claude does	The prompt that triggers it
Every morning	Daily briefing across accounts and tasks	"What do I need to handle today?"
Before a call	Account research and call prep from CRM, email, and Slack	"Prep me for the 2 pm with Acme"
Deal reviews	Scores deals against your sales methodology	"Score this deal against our process"
After a call	Drafts opportunity updates from your notes, writes after approval	"Update the opportunity from my notes"
Weekly	Pipeline dashboard with stage-by-stage risk flags	"Show pipeline by stage with risk"
Monthly	Forecast narrative for the leadership readout	"Draft my forecast narrative"

If you've been building this manually with prompts and exports, the table above probably looks familiar — it's roughly the workflow we documented in our complete guide to Claude for SDRs and the AI meeting prep guide. The difference is that the copy-paste tax is gone. Claude reads the live opportunity, the email thread, and the Slack channel itself.

The deal-scoring skill deserves special attention. Scoring "against our process" means MEDDIC, MEDDPICC, or whatever methodology your org runs — applied consistently, on every deal, without a manager spending Sunday night doing it. Forecast narratives similarly compress what is, for most sales leaders, a half-day of spreadsheet archaeology. (If you want to see how far AI forecasting can go beyond narratives, we broke that down in AI sales forecasting with Claude Code.)

How to Roll It Out Without a Committee​

The beta's admin-gated distribution is actually a feature for sales leaders: you can pilot with one pod instead of boiling the ocean.

Setup is five steps:

1. Request access through AgentExchange (Salesforce's marketplace — not the Claude app).
2. Your admin creates one organizational connection. No per-user OAuth dance.
3. Assign access to a pilot group — one team, not the whole org.
4. Optionally connect Slack for deal-channel context.
5. Reps sign in with their own Salesforce credentials, inheriting their existing permissions.

Then run a one-week ramp:

• Days 1–3: read-only. Briefings, account research, call prep. Zero risk, immediate time savings, and it builds trust in the output.
• Day 3: test deal scoring on a handful of live opportunities. Compare against your manager's read.
• Days 4–5: enable approved writes for one rep. Post-call updates are the highest-value, lowest-risk write path because the rep reviews every field change.
• Day 5+: add Slack. Context quality jumps when Claude can see the account team's actual conversation.

Measure one thing: minutes per rep per day spent on prep and CRM updates, before versus after. Sellers routinely lose 60–90 minutes daily to this. If the pilot claws back even half of that across a 10-rep team, that's roughly a full head of selling capacity you didn't have to hire.

One caution: billing is still separate. Your Salesforce contract and your Claude contract don't know about each other yet, and combined pricing hasn't been announced. Budget both lines.

What This Means for the AI-CRM Race​

Benioff's line for the launch — "UI is the AI" — is the tell. Salesforce spent two decades getting people into its interface, and it's now conceding that sellers would rather work where the reasoning happens. That's the same pattern we've tracked all year: Claude Docs and Slides moved deliverables into the conversation; Claudeforce moves the CRM into it too.

For buyers, the practical takeaway is that the "which AI does my stack support" question is collapsing. Salesforce built AIforce to serve any agent through MCP — Claude is simply first. If you're mid-evaluation between assistants, our Claude vs ChatGPT for sales teams comparison covers the reasoning-quality gap that likely drove Salesforce to lead with Anthropic, and the Opus 5.5 breakdown covers the current model ceiling.

It also raises the bar for every point tool charging for "AI meeting prep" or "AI pipeline summaries" as a standalone product. When the CRM vendor and the model vendor ship that natively for the cost of a Claude seat, the standalone version of those features is on a clock.

The One Thing Claudeforce Can't Do​

Read the skill list again. Briefings, prep, scoring, updates, dashboards, forecasts. Every single one operates on deals that already exist in your CRM.

Claudeforce makes your team dramatically faster at working pipeline. It does nothing to create pipeline. It can't tell you that a VP of Sales at a target account visited your pricing page twice yesterday, that a champion just changed jobs, or that an account that ghosted you in Q2 is suddenly researching your category. Salesforce only knows what someone put into Salesforce — and the buyers you most need to reach aren't in there yet.

That's the layer MarketBetter owns: identifying in-market accounts and the anonymous visitors already on your site, then telling your reps who to contact and exactly what to do next — not just summarizing what's already logged. Claude can then research those leads and draft the outreach, but the signal has to come from somewhere. (And no, Claude can't pull this from LinkedIn on its own either.)

The teams winning in 2026 run both layers: signal intelligence to fill the top of the funnel — because outbound isn't dead, it's just evolved — and AI-native execution like Claudeforce to work it without administrative drag.

Want the pipeline-creation layer to pair with your Claudeforce pilot? Book a MarketBetter demo →

FAQ​

What is Claudeforce? Claudeforce is the expanded Salesforce–Anthropic partnership announced August 26, 2026. Its first product, the Salesforce in Claude plugin, entered open beta September 15, 2026 with 37 prebuilt sales skills.

What Claude plans support Salesforce in Claude? All paid Claude plans. There's no free-tier access, and individual reps can't self-serve — a Salesforce admin must enable the plugin through AgentExchange.

Can Claude change my Salesforce data? Only with approval. By default, Claude proposes each write (like an opportunity update) and the seller confirms before it lands in the CRM. Users also inherit their existing Salesforce permissions — Claude can't touch records they couldn't already access.

Does Anthropic train on our CRM data? Anthropic states it does not train on Team and Enterprise data by default.

How much does it cost? There's no combined pricing yet. You pay for Salesforce and Claude separately under existing contracts.

Does this replace an SDR tool or signal platform? No. All 37 skills operate on existing CRM records. Identifying new in-market accounts, website visitors, and buying signals — the pipeline-creation layer — still requires a platform like MarketBetter.

In mid-September 2026, Anthropic quietly killed Claude Cowork as a separate mode, folded it into the main Claude app, and shipped two new surfaces in beta: Claude Docs and Claude Slides. Most of the coverage framed this as an office-suite play against Google and Microsoft.

That's the wrong frame for anyone who carries a quota. The right frame: the most expensive non-selling activity in sales — building documents and decks — just moved inside the AI conversation. Claude's output is no longer text you paste somewhere. The deliverable itself is the output.

We've been running Claude in production GTM workflows since early 2025 (start with the complete guide to Claude for SDRs if you're new). Here's what actually shipped, why it matters more for sales teams than for the "AI office suite" crowd, and five workflows worth stealing this week.

Contextual targeting places your ad based on what the page is about, not who the reader is. A CFO reading an article on revenue forecasting sees your FP&A tool's ad because of the article — no cookie, no device ID, no identity graph involved.

It's the oldest idea in advertising (trade magazines did this for a century) reborn as the default answer to a cookieless web. In 2026 it's also quietly one of the cheapest ways to put a B2B message in a relevant environment.

Here's how it works, what the current numbers say, and the one structural limit that decides where it belongs in your program.

How Contextual Targeting Works​

Modern contextual engines do four things in the milliseconds before an ad auction:

1. Crawl and classify the page. NLP models read the article — topic, entities, sentiment, even buying-stage cues ("comparison," "pricing," "implementation").
2. Match against your targeting profile. You buy categories ("enterprise software," "supply chain management"), keywords, or custom segments built from example URLs.
3. Apply brand-safety filters. Negative categories and sentiment thresholds keep you off pages you don't want to fund.
4. Bid. If page context matches your profile, your bid enters the auction like any other programmatic impression.

The critical distinction from behavioral targeting: nothing about the person is known or needed. Which is exactly why it survived cookie deprecation untouched.

Why It's Having a Moment in B2B​

Three 2026 realities pushed contextual from fallback to first-class:

• Reach. In cookieless environments, behavioral targeting loses 30–60% of addressable inventory. Contextual keeps 100% — it never needed the cookie.
• Cost. Advertisers report CPCs up to 48% lower and CPMs 20–30% lower than behavioral equivalents, and cookieless CPMs overall run ~22% below cookie-based ones.
• Performance parity. Recent studies put contextual within 5–8% of cookie-based behavioral targeting on CTR and conversion quality — a gap most B2B budgets happily trade for the cost savings.

And B2B is structurally a good fit: long, content-driven research cycles mean your buyers spend months reading exactly the pages a contextual engine can classify. Targeting the content of the research is a decent proxy for targeting the researcher.

Contextual vs. Behavioral vs. Account-Based​

	Contextual	Behavioral	Account-based (IP/identity)
Targets	Page content	Individual's history	Named companies
Data needed	None (page-level)	Cookies/device IDs	IP-to-company, identity graph
Privacy exposure	None	High	Moderate
Reach in 2026	Full inventory	Shrinking	Depends on match rates
Precision	Environment-level	Person-level (decaying)	Account-level
Typical B2B use	Category air cover	Retargeting	ABM programs

The three aren't rivals — mature programs layer them. Contextual finds relevant environments, account-based ad platforms (see our ABM tools roundup) find target companies, and first-party signals find in-market people.

Where Contextual Fits in an ABM Program​

Platforms like Propensity made contextual a standard channel in omnichannel ABM campaigns — and used well, it plays three roles:

1. Top-of-funnel air cover on a budget. Run category contextual against your solution space so that when your SDR calls, the brand isn't cold. At $3–10 CPMs this is the cheapest awareness you can buy. (For what the full program costs, see our omnichannel ABM cost breakdown.)

2. Intent amplification. When accounts on your in-market list surge on a topic, shift contextual budget onto that topic's content categories. You're betting the surging accounts are reading that content — often a good bet.

3. Competitive adjacency. Custom segments built from competitor-review and comparison URLs put your ad next to the exact moment of evaluation.

The Structural Limit Nobody Puts on the Slide​

Contextual targeting can never tell you who saw the ad or which account is now in-market. It's anonymous by design — that's the privacy feature. Which means:

• No account-level reporting beyond click-throughs
• No signal you can route to an SDR
• No way to know if the CFO who read the forecasting article works at a target account or a student newspaper

That's fine for awareness. It's fatal if awareness is your whole program, because nothing downstream converts impressions into conversations. The teams getting real pipeline from contextual pair it with a capture layer: person-level visitor identification on their own site, so that when the air cover works and the buyer shows up, someone actually knows — and routes the signal to a rep while it's warm.

Ads rent attention. Signals book meetings. Budget accordingly.

FAQ​

Is contextual targeting GDPR-compliant? Yes — it processes no personal data, which is why European budgets adopted it fastest. Standard consent rules still apply to any measurement pixels you add.

What does B2B contextual inventory cost in 2026? Display CPMs typically run $3–15 depending on category competitiveness; premium B2B publications and custom segments price higher. Still consistently 20–30% below comparable behavioral buys.

Can contextual targeting reach specific accounts? No. It targets content, not companies. If you need named-account delivery, that's account-based advertising — compare approaches in our MarketBetter vs Propensity breakdown.

Does contextual work for niche B2B categories? It's actually strongest there. Niche categories have well-defined content universes (trade pubs, analyst blogs, subreddits with display inventory), so classification is precise and waste is low.

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Air cover only pays off when you can see who showed up. MarketBetter identifies the visitors your ads send and turns their signals into booked meetings. Book a demo →

Geofencing draws a virtual boundary around a physical place — a convention center, a competitor's headquarters, an airport terminal during a conference week — and serves ads to the mobile devices inside it. The devices get captured into an audience you can keep retargeting for 30 days after they leave.

In consumer marketing it's a coupon cannon. In B2B it's something more interesting: one of the few ways to build an audience out of verified physical behavior — this device attended that industry event; this device works in that building.

Here's how B2B teams actually use it in 2026, what it costs, and the step most programs skip that decides whether it produces pipeline or just impressions.

How It Works​

1. Draw the fence. GPS/Wi-Fi/Bluetooth-based polygons around target locations — typically 100–300 meters for an office building (tight enough to avoid the coffee shop next door), or the exact footprint of a convention hall.
2. Capture device IDs. Devices that dwell inside the fence during your window get added to an audience segment.
3. Serve and retarget. Ads run on apps and mobile web while devices are in the fence — and, more valuably, for up to ~30 days afterward across their other devices via cross-device graphs.
4. Layer filters. Daypart to business hours (Mon–Fri, 8am–6pm) to bias toward employees over visitors; some platforms layer firmographic data on top.

Accuracy realities: outdoor precision is roughly 5–50 meters depending on device and environment. Good enough for a convention center; do not expect it to separate floor 12 from floor 14 of a shared tower.

The Four B2B Plays​

1. Trade show and conference capture. Fence the venue (and the headline hotels) during show week. Everyone captured is a verified industry attendee — a prequalified audience you retarget for the month after, precisely when follow-up matters. This pairs with the pre-event motion in our conference prospecting playbook: outreach books the meetings, geofenced air cover keeps the brand warm between touches.

2. Competitor's event or booth. Fence a competitor's user conference and spend the next 30 days putting your comparison content in front of their most engaged customers. Aggressive, legal, and common.

3. Competitor and partner offices. Fence competitor HQs to reach their employees (recruiting, or seeding doubt before a renewal cycle) or fence your target accounts' offices as an account-based display channel that doesn't depend on IP resolution.

4. Your own funnel's physical layer. Fence your own event, your roadshow stops, even the steakhouse where you ran the exec dinner — then retarget attendees with the follow-up asset instead of hoping they open the recap email.

What It Costs in 2026​

Line item	Typical range
Mobile/desktop display CPM	$3.50–$15
CTV geofencing CPM	$20–$50
Advanced (behavioral triggers, CRM sync)	up to $20–$25 CPM
Platform minimums	Often $1K–$5K/mo managed

A single-event fence with 30-day retargeting is typically a $2K–$10K line item — cheap enough to test, which is why it shows up as a standard channel in omnichannel ABM platforms like Propensity. (Full program math in our omnichannel ABM cost breakdown.)

The Honest Limits​

• Device ≠ decision-maker. Your convention-center fence captures the AV crew, the baristas, and 400 vendors along with the buyers.
• No account resolution. You know a device was at SaaStr; you don't know it belongs to the VP of Sales at a target account — most platforms can't close that gap reliably.
• It's still just impressions. Nobody ever geofenced their way directly to a booked meeting. It warms; it doesn't convert.
• Privacy drift. Location data sits in regulators' crosshairs; platform capabilities have narrowed each year and will keep narrowing.

The Step That Turns Location Into Pipeline​

Geofencing's output is an anonymous warm audience. Pipeline starts when a member of that audience does something identifiable — and for B2B, that moment is almost always a visit to your website.

That's the handoff most programs fumble. The event attendee you spent $8 CPM warming clicks through Tuesday morning, browses your pricing page, and leaves — anonymous — unless you have person-level visitor identification running. With it, the sequence completes: fence captures the audience → ads warm it → visitor ID names the ones who show up → the signal routes to an SDR the same day, while the conference is still fresh in memory.

Same principle as every ad channel: air cover doesn't book meetings — the capture layer does.

FAQ​

Is B2B geofencing legal? Yes, using platform-provided opt-in location data. Rules tighten yearly (and several US states now restrict sensitive-location fencing), so keep fences on commercial venues and follow your platform's compliance guidance.

How precise is a geofence? Roughly 5–50 meters outdoors. Building-level targeting works; suite-level doesn't.

How long can you retarget captured devices? Most platforms support ~30-day lookback windows after fence exit — the useful window anyway, since event intent decays fast.

Is geofencing worth it without an event? Rarely as a standalone. Fencing static office buildings produces thin, noisy audiences. It earns its budget around moments — shows, launches, renewal windows — when physical presence actually signals something.

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Warming an audience is the easy half. MarketBetter identifies the visitors your campaigns send and hands your SDRs the signal while it's hot. Book a demo →

At any given moment, roughly 5% of your total addressable market is actively buying what you sell. The other 95% fit your ICP perfectly and still won't take the meeting — not this quarter.

An in-market account list is the discipline of separating those two groups. Done right, it's the highest-leverage asset in your GTM stack: the same SDRs, the same sequences, the same budget, pointed at accounts that are actually shopping. Done wrong, it's a spreadsheet of companies that "surged" on a topic once and never thought about you again.

Here's the full build process.

What Counts as "In-Market"​

An account is in-market when there's evidence of active evaluation — not just fit. Three signal layers supply that evidence:

Layer	Source	Examples	Strength
First-party	Your own properties	Pricing-page visits, return sessions, demo-page views, doc reads	Strongest — they came to you
Second-party	Platforms you can observe	Review-site activity, competitor comparison views, LinkedIn engagement	Strong — category-specific
Third-party	Publisher networks & co-ops	Topic surge across research content (Bombora-style)	Broad but noisy — category-level, account-level

The mistake most teams make is building the list from the third layer alone, because that's what their intent vendor sells. Third-party surge tells you an account might be researching the category. First-party behavior tells you a specific person is evaluating you. Weight accordingly.

Step 1: Lock the ICP Filter First​

Intent without fit is noise. Before any signal enters the list, define the firmographic and technographic gate: industry, employee band, geography, tech stack, disqualifiers. An account that surges hard but can't buy (wrong size, wrong region, incompatible stack) should never reach a rep.

This is a filter, not a score. Binary. In or out. The scoring comes later — see our companion guide on how to score an in-market account list.

Step 2: Instrument First-Party Capture​

Your website is the single richest in-market signal source you own, and most teams are blind to it — 97%+ of B2B visitors never fill a form.

• Deploy person-level visitor identification so anonymous traffic resolves to named people at named accounts
• Flag high-intent paths: pricing, integrations, security/compliance pages, comparison pages
• Track return frequency — a second visit within 7 days is worth more than any topic surge

The full setup is covered in our B2B website visitor identification guide.

Step 3: Layer Third-Party Intent — as a Multiplier, Not a Source​

Add topic-surge data on top of the ICP-filtered universe to catch accounts researching the category before they hit your site. Rules that keep it honest:

• Recency: signals older than 14 days are history, not intent. Buying intent decays with a half-life measured in days.
• Repetition: one week of surge is noise; three consecutive weeks is a pattern.
• Relevance: surge on your category and competitor terms, not adjacent topics.

If you're choosing a vendor, our intent data provider roundup covers the trade-offs.

Step 4: Add Trigger Events​

Some accounts enter market because something happened: new VP of Sales, funding round, layoffs at an incumbent vendor, a compliance deadline, a champion changing jobs into a new account. Triggers are the earliest in-market signal that exists — often preceding any research behavior. Pipe them in from job-change alerts, funding feeds, and hiring data.

Step 5: Set Entry, Exit, and Ownership Rules​

A list without lifecycle rules bloats into uselessness within a quarter.

• Entry: ICP pass + at least one strong signal (first-party visit, repeated surge, or trigger event)
• Exit: no new signal in 21-30 days → account rotates out (it can re-enter)
• Ownership: every account that enters gets routed to a named rep within 24 hours — signal-based routing rules prevent the "great list nobody works" failure mode
• Cap: keep the active list at a size your team can actually touch (typically 5-10 accounts per rep per week entering)

The Mistakes That Poison Lists​

1. Static lists. In-market is a state, not a trait. A list built in January is fiction by March. Rebuild continuously or automate entry/exit.
2. Account-level worship. "Acme is surging" is not workable. Who at Acme? Resolve to people or the SDR is cold-calling into a warm account — which is just cold calling.
3. No speed contract. In-market accounts are in-market for everyone, including your competitors. If your motion can't get from signal to meeting inside 24-48 hours, the list's value evaporates before it's worked.
4. Treating intent as a magic bullet. Intent data multiplies a strong ICP and a working outbound motion. It cannot rescue a weak one.

How MarketBetter Automates This​

Everything above can be run manually with spreadsheets and three vendor contracts. MarketBetter runs it as one system: person-level visitor ID (step 2), blended first- and third-party intent (step 3), trigger signals (step 4), and routing rules with SLA timers (step 5) — feeding outreach that's drafted by AI and reviewed by a human before it sends. The list stays live, the exits happen automatically, and every entry ends in an attempted conversation, not a dashboard.

Book a demo to see your own in-market list built from your real traffic.

FAQ​

How big should an in-market account list be? As big as your team can work within the signal window — usually 5-10 new accounts per rep per week. A 5,000-account "in-market list" is a mailing list wearing a costume.

Is intent data enough to build the list? No. Third-party intent alone produces category researchers, not evaluators of you. Blend it with first-party behavior and trigger events, and gate everything through ICP fit.

How often should the list refresh? Continuously. If your tooling forces batch updates, weekly is the minimum viable cadence — intent signals lose most of their value within two weeks.

Building an in-market account list answers who might buy. Scoring answers the question your reps actually ask every morning: who first?

Most scoring models fail not because the math is wrong but because nobody trusts them — the weights were guessed in a workshop, the score never matches what reps see, and within a quarter everyone's back to gut feel. Here's a model built the other way: start from your closed-won data, keep the dimensions legible, and wire the score to routing so it changes behavior instead of decorating a dashboard.

The Three Dimensions​

Every workable account score combines three things:

Dimension	Question it answers	Example signals
Fit	Could they buy?	Industry, employee band, tech stack, funding stage, geography
Intent	Are they researching?	Topic surge, competitor comparisons, review-site activity, category searches
Engagement	Are they researching you?	Pricing-page visits, return sessions, demo views, email/LinkedIn replies

Keep them separate. A blended single number hides the difference between "perfect fit, zero activity" (nurture) and "mediocre fit, on your pricing page daily" (call now) — and those demand opposite plays.

Step 1: Calibrate Weights on Closed-Won, Not Opinion​

Pull your last 12 months of closed-won and closed-lost accounts. For each, reconstruct what was observable before the first meeting: firmographics, signals, site behavior. Then ask which attributes actually separated winners from losers.

Every team that does this honestly finds surprises. Common ones:

• First-party engagement outpredicts third-party surge by a wide margin — a pricing-page visit is worth more than a month of topic surge (our buying-signal hierarchy analysis ranks the common signals by closed-won correlation)
• One or two firmographic traits you thought mattered don't
• Negative signals (wrong stack, recent competitor contract, hiring freeze) predict losses better than positive signals predict wins

Recalibrate quarterly. Around three-quarters of B2B teams will run some form of AI-assisted scoring by end of 2026 — but AI calibration on top of unexamined assumptions just automates the guessing.

Step 2: Score Each Dimension 0-100​

A simple, legible structure beats a clever one:

Fit (gate + score). Hard disqualifiers first — wrong size, wrong region, incompatible stack → score 0, exit. Survivors get scored on weighted firmographic/technographic match.

Intent (recency-weighted). Score signals, then decay them: a signal this week at full value, halved next week, gone by week four. Intent has a half-life; a score that ignores decay ranks last month's shoppers above this week's.

Engagement (behavior-tiered). Not all touches are equal. A blog visit is a point; a pricing page is ten; a second pricing visit within a week is twenty; an identified decision-maker doing it is fifty. Person-level resolution matters here — knowing who is on the page is the difference between account warmth and an actual buyer.

Step 3: Convert Scores to Tiers​

Reps don't act on a 73. They act on tiers:

Tier	Threshold (typical)	Play	SLA
A — Act now	High fit + high engagement	Direct outreach to identified people, personalized	24 hours
B — Working	High fit + intent, low engagement	Warm outbound referencing category research	72 hours
C — Watch	Fit, weak/no signal	Automated nurture, monitor for signal	—
D — Disqualified	Failed fit gate	None. Genuinely none.	—

Set thresholds so Tier A matches your team's actual capacity. A tier system that flags 400 "act now" accounts for six reps is a random number generator with extra steps.

Step 4: Wire the Score to Routing​

This is where scoring lives or dies. A score that only sorts a dashboard changes nothing. The score should do things:

• Tier A entry → account routed to a named rep with the triggering signal attached, SLA timer running (routing rules here)
• Tier transitions → notifications, not reports ("Acme moved B→A: 3rd pricing visit this week")
• SLA breach → escalation or re-route

The signal-to-meeting playbook covers the outreach side of the handoff.

The Failure Modes​

1. Opinion-weighted models. If the weights came from a meeting instead of closed-won data, the model encodes the loudest person's intuition.
2. No decay. Scores that only go up produce a leaderboard of accounts that were hot in Q1.
3. Score without routing. If a tier change doesn't move work to a person with a deadline, the model is decorative.
4. Precision theater. Seventeen weighted sub-factors nobody can explain lose to four factors every rep understands. Trust drives adoption; adoption drives revenue.

How MarketBetter Handles Scoring​

MarketBetter scores accounts and people continuously — fit gate, blended intent with built-in decay, person-level engagement — and routes tier changes straight into SDR queues with the evidence attached and outreach drafted for human review. Calibration runs against your actual pipeline outcomes, not a static rubric.

Book a demo to see your accounts scored on live signals.

FAQ​

Account scoring vs lead scoring — what's the difference? Lead scoring ranks individual form-fills; account scoring ranks companies using signals from everyone in the buying committee, including people who never converted. In committee-driven B2B sales, account scoring is the one that matches how deals actually happen.

How many factors should the model use? As few as survive the closed-won analysis — usually 4-7. Every factor you add that reps can't verify against reality costs trust.

How often should scores update? Continuously, or daily at minimum. Weekly batch scoring means your fastest-moving buyers spend their hottest days invisible.

Propensity and MarketBetter both pitch themselves as the affordable answer to 6sense and Demandbase. Both de-anonymize website visitors. Both use intent data. Both cost a fraction of enterprise ABM.

And yet they are almost opposite products.

Propensity is an advertising engine: it builds audiences of in-market accounts and serves them ads across 20+ channels — display, native, CTV, audio, social, direct mail. MarketBetter is a meeting engine: it identifies the people already showing buying signals and routes them into SDR outreach that ends in a booked call.

One warms accounts. The other works them. Here's how to decide which layer to fund — or how to sequence both.

The Short Version​

	Propensity	MarketBetter
Core motion	Omnichannel ABM advertising	Signal-based outreach
Primary output	Impressions and account engagement	Booked meetings
Visitor de-anonymization	Account + contact level	Person-level identification
Intent data	Bombora topic surge	Blended first- + third-party intent
Channels	Display, native, video, audio, CTV, social, direct mail	Email + LinkedIn outreach, human-in-the-loop
Who runs it	Marketing	Sales/SDR teams (with marketing)
Pricing	$2,000-$4,000/month, channel-gated tiers	Flat platform pricing, no channel gates
CRM sync	Standard integrations	HubSpot, Salesforce, Pipedrive
Time to first result	Weeks (ad frequency builds)	Days (first signals routed to outreach)

For the full teardown of Propensity's tiers and hidden contact-data costs, see our Propensity pricing review.

What Propensity Actually Does Well​

Credit where due. Propensity's G2 reviews are strong (4.8/5), and the product delivers on its promise for a specific job:

• Ad activation without a DSP. Most SMB marketing teams can't run programmatic display, CTV, or audio campaigns themselves. Propensity packages that into a flat monthly fee with campaigns live in under 15 days.
• Audience building from intent. It combines Bombora topic surge with website visitor data to build lists of accounts that look in-market, then syncs those audiences to ad channels automatically.
• Channel breadth. Direct mail, geofencing, contextual — channels most B2B teams never touch — are in the box (LinkedIn is gated to the $3,000 tier, Google/YouTube to $4,000).

If your goal is awareness inside a defined account list — making sure the buying committee has seen your name before your rep calls — Propensity does that at a price 6sense can't match.

Where the Model Breaks​

The limits show up when you trace an ad impression to revenue.

1. Impressions don't book meetings. Propensity's output is engagement: lifted account activity, more site visits, better ad recall. Someone still has to convert that warmth into conversations. If you don't have an outbound motion ready to catch the accounts that heat up, you're paying to warm accounts that cool back down. Signal decay is brutal — buying intent has a half-life measured in days, not quarters.

2. Account-level warmth, person-level gap. Knowing an account is surging on "sales automation" doesn't tell your SDR who to contact. Contact data below the $4,000 tier is metered and accrues per campaign — reviewers on G2 flag exactly this. The moment you operationalize, costs stack.

3. Marketing owns it, sales waits. Propensity is a marketing tool. The pipeline conversation still depends on how well marketing hands accounts to sales — the handoff where most ABM programs quietly die.

What MarketBetter Does Instead​

MarketBetter starts from the opposite end: the people already acting.

• Person-level visitor identification. Not "someone at Acme visited" — which person, matched to title, LinkedIn profile, and contact data. See how that works in our visitor identification guide.
• Blended intent ranking. First-party signals (pricing-page visits, return sessions) blended with third-party intent, ranked by the signal hierarchy that actually predicts closed-won.
• Outreach built in. Signals route to SDRs with AI-drafted, human-reviewed email and LinkedIn sequences. The output isn't a warmed account — it's a meeting on the calendar.
• CRM-native. Syncs into HubSpot, Salesforce, or Pipedrive rather than asking you to run pipeline out of a separate ad console.

The philosophical difference: Propensity spends money to create engagement. MarketBetter captures the engagement that already exists — the 97% of visitors who never fill a form, the accounts surging on your category this week — and turns it into conversations now.

Which Should You Buy?​

Buy Propensity if:

• You have a defined target-account list and no way to advertise to it
• Your sales team is already at capacity and marketing's job is air cover
• Brand awareness inside your ICP is genuinely your bottleneck

Buy MarketBetter if:

• Your bottleneck is meetings, not awareness
• You're already getting traffic and signals but converting almost none of it
• You want sales working in-market accounts this week, not after a 90-day ad flight

The honest sequencing answer: if you can only fund one layer, fund the one that ends in a booked meeting. Ads without an outbound motion warm accounts nobody works. Outbound without ads still books meetings — it just works a slightly colder room. Add the air cover once the capture layer is running.

FAQ​

Is Propensity cheaper than MarketBetter? They're in a similar bracket, but they buy different things. Propensity's $2,000-$4,000/month buys ad activation with channel gates and metered contact data. MarketBetter's flat pricing buys person-level identification plus outreach execution. Compare cost per meeting, not cost per month.

Can you run Propensity and MarketBetter together? Yes, and the combination is coherent: Propensity warms your target list with ads; MarketBetter catches the accounts that heat up and books the meetings. Just sequence the capture layer first.

Is Propensity a 6sense replacement? For SMB ad activation, largely yes — at a tenth of the price. For revenue teams that need intent to drive outbound, neither Propensity nor 6sense closes the loop to a meeting. See our MarketBetter vs 6sense comparison and 6sense pricing breakdown.

What does MarketBetter cost? Flat platform pricing with no channel gates or metered contact data. Book a demo for numbers against your account list.

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Ready to work the accounts that are already in-market? Book a MarketBetter demo.

Ask five vendors what an omnichannel ABM campaign costs and you'll get five sales decks. The honest answer for 2026: a full program runs anywhere from $40,000 to $500,000+ per year all-in, and the spread depends on four line items most budgets never separate: platform, media, content, and people.

Here's the breakdown, a worked example for a 100-account campaign, and the line item almost every ABM budget forgets.

The Four Cost Buckets​

1. Platform: $24K-$150K+/year​

The software that builds audiences, activates channels, and measures engagement.

Platform class	Annual cost	Examples
Enterprise ABM	$60K-$130K+	6sense, Demandbase (pricing teardowns here)
SMB omnichannel ABM	$24K-$48K	Propensity ($2K-$4K/mo, full review)
Signal/identification layer	Varies, typically flat	Visitor ID + intent + outreach platforms

Watch the gates: on tiered platforms, LinkedIn activation, Google/YouTube, and unmetered contact data often sit in higher tiers, so the sticker price and the operational price diverge fast.

2. Media: The Per-Channel Reality​

2026 benchmark CPMs for B2B-targeted inventory:

Channel	CPM range	Notes
Programmatic display	$10-$50	Account-targeted; narrow audiences pay the high end
Native	$10-$30	Cheaper, weaker attribution
Contextual	~20-30% below behavioral	No identifier dependence
Geofencing	$3.50-$15 display	Event plays: $1,500-$5,000 per trade show
CTV/OTT	$25-$50	Great recall, hardest to attribute
LinkedIn	$40-$100+	The B2B workhorse; 100-account 1:1 campaigns run $5K-$20K/mo
Direct mail / gifting	$50-$500 per send	Tier-1 accounts only

Media allocation varies wildly by strategy — ad-led programs put 40%+ of total budget into media; outbound-led programs as little as 10%.

3. Content: The Quiet Budget Eater​

Ads need somewhere to land. Personalized landing pages, one-pagers per segment, case studies per vertical, creative refreshes every 6-8 weeks (B2B audiences are small; frequency burns creative fast). Dedicated ABM content budgets run $80K-$500K/year at the enterprise end. Lean teams can compress this, but zero-content ABM is just retargeting with a fancier name.

4. People: The Forgotten Line Item​

Someone has to run this — audience builds, channel ops, sales coordination, reporting. A fractional marketing ops hire or agency retainer adds $3K-$15K/month. Skip it and the platform becomes shelfware; the data on why ABM rollouts fail is mostly a story about missing owners, not missing tools.

Worked Example: 100 Accounts, One Quarter​

A realistic mid-market omnichannel campaign — display + LinkedIn + CTV + direct mail against 100 target accounts:

Line item	Quarterly cost
Platform (SMB ABM tier w/ LinkedIn)	$9,000
Display/native/contextual media	$6,000
LinkedIn media	$15,000
CTV flight	$5,000
Direct mail (20 tier-1 accounts × $150)	$3,000
Content & creative	$8,000
Ops (fractional)	$9,000
Total	~$55,000/quarter

~$2,200 per account per year. That's the honest unit cost of omnichannel air cover — before a single meeting is booked.

The Line Item Everyone Forgets: Capture​

Here's the uncomfortable math. That $55K/quarter produces impressions, engagement lift, and warmer accounts. It does not produce meetings. Meetings happen when someone notices an account heating up and reaches out — fast, to the right person, while the interest is live.

Most ABM budgets spend everything on warming and nothing on catching. The engaged visitors hit your site anonymously, don't fill the form (97% never do), and leave. The ad budget warmed them; nobody was watching the door.

The capture layer — person-level visitor identification, in-market account detection, routed outreach with an SLA — typically costs a fraction of the media budget and is the only part of the stack whose output is denominated in meetings. If your budget can't fund both, fund capture first: it monetizes the demand you already have, including demand your ads didn't create.

How to Right-Size Your Budget​

1. Work backward from pipeline math. Needed pipeline ÷ average deal size = deals; deals ÷ win rate = opportunities; opportunities ÷ account-to-opp rate = accounts to target. Budget for that list, not a round number.
2. Tier the spend. Full omnichannel (mail, CTV, 1:1 pages) for tier-1 only; display + LinkedIn for tier-2; contextual + capture-only for tier-3.
3. Cap media until capture works. If in-market accounts currently reach your site and nothing happens, every media dollar is leaking.
4. Measure cost per meeting, not cost per MQL. It's the only metric that survives contact with a sales team.

FAQ​

What's the minimum viable omnichannel ABM budget? Around $40K-$60K/year gets a small program: SMB platform, modest display + LinkedIn media, lean content, part-time ops. Below that, run capture + outbound only and skip paid media.

What ROI should ABM deliver? Programs that survive tie spend to sourced/influenced pipeline at 3-5x minimum. Engagement-lift reporting alone is how programs get cut in the next budget cycle.

Do I need CTV and direct mail? No. They're tier-1 seasoning, not foundations. Display + LinkedIn + a working capture layer outperforms a six-channel program with no one working the signals.

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Want the capture layer priced against your account list? Book a MarketBetter demo.

Propensity sells itself as the ABM platform for teams priced out of 6sense and Demandbase — flat monthly rates, no enterprise sales cycle, campaigns live in under 15 days. In 2026 that pitch comes with three tiers: Essential at $2,000/month, Strategic at $3,000/month, and Unlimited at $4,000/month.

If you've seen older reviews quoting $1,000-$2,000/month, note that pricing has moved up. Here's the current breakdown, what reviewers actually say, and the questions to ask before signing.

Propensity Pricing: The 2026 Tiers​

	Essential — $2,000/mo	Strategic — $3,000/mo	Unlimited — $4,000/mo
Website de-anonymization (account + contact level)	Yes	Yes	Yes
Intent data	Included	Unlimited	Unlimited
Contact data	Metered	Metered	Unlimited
Display / native / video / audio / CTV ads	Yes	Yes	Yes
Contextual + geofencing ads	Yes	Yes	Yes
LinkedIn + Facebook ads	—	Yes	Yes
Google, YouTube, TikTok, Reddit ads	—	—	Yes
Direct mail	—	Yes	Yes
Lead/account scoring	Standard	Custom	Custom
Dedicated account manager	—	Yes	Yes
API access	—	Yes	Yes
Users	Unlimited	Unlimited	Unlimited
CRM integration	Salesforce, HubSpot	Salesforce, HubSpot	Salesforce, HubSpot

Billing is monthly with no disclosed annual lock-in — genuinely rare in ABM, where 6sense and Demandbase quote six-figure annual contracts.

At list price that's $24,000, $36,000, or $48,000 a year. Cheaper than enterprise ABM by a wide margin; far from pocket change for the SMB growth teams Propensity targets.

The Costs That Aren't on the Pricing Page​

Three things to pressure-test on the sales call:

1. Contact data is metered below the top tier. G2 reviewers flag added contact-information costs that accrue with each new campaign launch — and "unlimited contact data" only appears at $4,000/month. If your motion is contact-level ABM (Propensity's whole differentiator), model this before assuming the $2K tier is your real price.
2. Channel gating drives upgrades. LinkedIn — the one paid channel most B2B teams actually want — requires the $3,000 Strategic tier. Google and YouTube require $4,000. The tier you'll actually run is probably not the tier on the ad.
3. Media spend is your problem. As with most ABM platforms, the subscription buys the targeting and activation layer. Budget your actual ad dollars on top, and ask explicitly what (if any) media spend is bundled at your tier.

What Reviewers Like​

Propensity holds a 4.8/5 on G2 across roughly 30 reviews, most from small-business users. The consistent themes:

• Speed and ease of use. Campaign setup is fast, with formats ranging from geofencing to 1:1 ABM plays, and implementation measured in days, not quarters.
• Native ad activation without a DSP. Running display and social campaigns against intent-surging accounts from one tool, with no separate ad-tech stack, is the platform's clearest value at its price point.
• Support that acts like an extension of your team. For a small marketing team without RevOps headcount, reviewers describe the Propensity team as doing real operational lifting.
• HubSpot integration with contact- and account-level performance tracking.

Where It Falls Short​

• Thin intent coverage. Reviewers and analysts note Propensity's intent data runs shallower on mid-market and lower-enterprise accounts than 6sense or Bombora. If your ICP is niche, sample the free intent report (top 100 accounts) before buying — that's what it's for.
• Small proof base. ~30 G2 reviews is a thin sample next to established platforms. The 4.8 average is real but easy to move.
• It's an advertising engine at heart. Propensity's channels — display, CTV, geofencing, contextual, paid social — build awareness at target accounts. What it doesn't do is put a rep in front of a specific in-market buyer. Impressions warm accounts; they don't book meetings.

Who Propensity Actually Fits​

Propensity makes sense if you're a 1-5 person marketing team that wants to run multi-channel ABM air cover — ads across display, CTV, and social aimed at intent-surging accounts — without an enterprise contract or a media agency. It's a legitimate budget answer to 6sense and Demandbase for that use case.

It's the wrong tool if your bottleneck is pipeline, not awareness. If the question you're asking is "which specific companies and people are in-market right now, and how do we get a seller in front of them this week," an ad-impression platform is solving one layer down from your problem.

The Signal-Based Alternative​

That second case is where MarketBetter takes a different architectural bet. Instead of spending the budget on impressions at target accounts, it identifies the people already showing intent — person-level website visitor identification, blended first- and third-party intent scoring — and routes them into human-reviewed email and LinkedIn outreach, synced to HubSpot, Salesforce, or Pipedrive.

The practical difference in one line: Propensity shows ads to accounts that might be in-market. MarketBetter starts conversations with the people who already are. Many teams run air cover and outbound together — but if you can only fund one layer, fund the one that ends in a booked meeting. (Full comparison logic in our MarketBetter vs 6sense breakdown — the same reasoning applies here at a smaller price tag.)

FAQ​

How much does Propensity cost in 2026? $2,000/month (Essential), $3,000/month (Strategic), or $4,000/month (Unlimited), billed monthly. Older reviews citing $1,000-$2,000/month reflect earlier pricing.

Does Propensity require an annual contract? No annual commitment is disclosed — pricing is presented as monthly flat rates, unlike most enterprise ABM platforms.

What's the catch in Propensity's pricing? Contact data is metered below the $4,000 tier and accrues per campaign, LinkedIn ads require the $3,000 tier, and Google/YouTube require the $4,000 tier. Ad spend is separate from the subscription.

Is Propensity a 6sense alternative? For multi-channel ABM advertising on a smaller budget, yes. For deep intent data on mid-market accounts, its coverage is thinner than 6sense or Bombora. See our 6sense alternatives roundup for the full field.

What should I compare Propensity against? Other account-based marketing tools for the air-cover layer — and signal-based outbound platforms like MarketBetter if your goal is booked meetings rather than account awareness.

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Want to see what person-level intent looks like on your own website traffic before you commit to an ad budget? Book a MarketBetter demo.