Factors.ai vs Northbeam in 2026: B2B account intent vs DTC media mix modeling
Both are enterprise-priced, demo-gated analytics platforms with no self-serve signup past the lowest tier. But Factors.ai is built for B2B pipeline and Northbeam is built for ecommerce ad spend, and the buyer for one is rarely the buyer for the other.
Factors.ai
Northbeam- Factors.ai starts at $199/month for a Lite tier before jumping to $6,000/year Basic. Northbeam has no published pricing at all across any of its three tiers, all three require a sales conversation.
- Northbeam combines multi-touch attribution with media mix modeling that covers channels with no user-level tracking, like streaming and podcast ads. Factors.ai has no MMM capability; its attribution is limited to trackable digital touchpoints.
- Factors.ai unmasks anonymous B2B website visitors to named companies. Northbeam has no company identification feature; its unit of analysis is ad spend and revenue attribution for ecommerce transactions.
- Northbeam updates attribution data on a near-real-time or daily basis, faster than legacy MMM providers on weekly or monthly cycles. Factors.ai does not publish a specific data refresh cadence.
- Northbeam includes a dedicated onboarding team and CSM on its Scale and Enterprise tiers as standard. Factors.ai does not detail a dedicated onboarding program in its public documentation.
- Factors.ai automates LinkedIn ad audience sync from account intent. Northbeam has no LinkedIn-specific automation; its native integrations focus on Meta, Google, TikTok, Snapchat, and Pinterest for ecommerce ad spend.
Factors.ai and Northbeam share a business model more than they share a use case: both require a sales conversation for their serious tiers, both target teams spending real advertising budget, and both position themselves as smarter than what platform-native reporting can tell you. Where they split is the customer. Factors.ai is built for B2B demand gen and RevOps teams who need to identify which companies are researching them and automate LinkedIn targeting off that intent. Northbeam is built for DTC and ecommerce brands spending $50k or more a month across Meta, Google, and TikTok who need a first-party, cookieless view of which channels actually drove revenue. If your business model is B2B pipeline, Factors.ai is the relevant one; if it is ecommerce checkout revenue, Northbeam is.
The tools at a glance
Factors.ai
AI-first ABM platform that turns account intent signals into pipeline actions
Factors.ai identifies companies visiting your website and, from the Basic tier, unmasks 75%+ of those visits to named accounts. It adds G2 intent data, firmographic enrichment, and full-funnel attribution that credits first-touch, last-touch, and influenced interactions rather than just the last click before a form fill.
LinkedIn AdPilot closes the loop between identification and action by syncing intent-based audiences directly into LinkedIn campaigns and feeding enhanced conversion signals back to improve targeting, which matters for B2B teams whose primary paid channel is LinkedIn rather than Meta or TikTok.
The MCP integration exposes account intelligence and attribution data to AI agents, positioning Factors as a structured GTM data source for automated workflows, an angle that Northbeam, focused on ecommerce media spend rather than B2B account data, does not address at all.
| Feature | Lite $199/month | Basic $6,000/year | Growth $20,000/year | Enterprise $30,000+/year |
|---|---|---|---|---|
| Company identification | Yes | Yes | Yes | Yes |
| Unmask 75%+ of visiting companies | No | Yes | Yes | Yes |
| LinkedIn Ads influence tracking | No | Yes | Yes | Yes |
| G2 intent data | No | No | Yes | Yes |
| Predictive account scoring | No | No | No | Yes |
Northbeam
Multi-touch attribution and media mix modeling for DTC and ecommerce brands
Northbeam is built for direct-to-consumer and ecommerce brands running significant paid spend across Meta, Google, TikTok, and streaming channels who no longer trust platform-native ROAS numbers. Its first-party pixel and server-side tracking maintain attribution accuracy in a cookieless, post-iOS-14 environment where each ad platform tends to overstate its own contribution.
The platform runs multi-touch attribution and media mix modeling side by side. MTA tracks individual customer journeys across channels; MMM uses statistical modeling to estimate the causal contribution of channels with no user-level tracking, like TV, podcast, and streaming ads, and refreshes near-real-time rather than on the weekly or monthly cycle typical of legacy MMM providers.
Budget scenario planning turns that modeling into a decision tool: media buyers can simulate shifting spend between channels and see a projected revenue outcome before making the change. Onboarding takes two to four weeks and includes pixel implementation, so this is a considered purchase rather than a quick trial, reflected in the fact that all three tiers require a sales conversation.
| Feature | Growth Contact sales | Scale Contact sales | Enterprise Contact sales |
|---|---|---|---|
| Multi-touch attribution | Yes | Yes | Yes |
| Media mix modeling | No | Yes | Yes |
| Budget scenario planning | No | Yes | Yes |
| Data refresh cadence | Daily | Near real-time | Near real-time |
| Dedicated CSM | No | Yes | Yes |
Head-to-head feature comparison
| Feature | Factors.ai | Northbeam |
|---|---|---|
| Core function | AI-first account-based marketing and intent platform | Multi-touch attribution and media mix modeling |
| Target customer | B2B SaaS and demand gen teams | DTC and ecommerce brands with $50k+/month ad spend |
| Starting price | $199/month | Contact sales (no published price) |
| Self-serve signup | Yes (Lite tier only) | No (demo required for every tier) |
| Account-level identification | Yes (75%+ unmasked from Basic tier) | No |
| Media mix modeling | No | Yes (from Growth tier upward) |
| Ad platform automation | Yes (LinkedIn AdPilot audience sync) | No (measures Meta/Google/TikTok spend, does not automate campaigns) |
| AI agent / MCP integration | Yes (MCP feeds account data to AI agents) | No |
| Data refresh cadence | Not publicly specified | Daily on Growth, near real-time on Scale and Enterprise |
| Dedicated onboarding/CSM | Not detailed publicly | Yes (from Growth tier, standard on Scale/Enterprise) |
| CRM sync | Yes (Salesforce, HubSpot from Basic) | No (CRM not the focus; ecommerce platforms instead) |
| BI connector | Not itemized by tier | Yes (BI connector to Power BI, Tableau, Looker from Growth) |
| Support model | Standard account support | Dedicated CSM from Growth tier |
| Best for | B2B demand gen and RevOps teams | DTC and ecommerce brands scaling paid spend |
Which should you choose?
Factors.aiNorthbeamFactors.aiNorthbeamFactors.aiFactors.aiThe overlap between Factors.ai and Northbeam is thinner than the shared "enterprise-priced, demo-gated" pricing model suggests. Factors.ai's entire value proposition rests on identifying anonymous B2B visitors and turning that into LinkedIn ad action; it has nothing to say about media mix modeling or ecommerce checkout attribution. Northbeam's entire value proposition rests on defensible, first-party attribution for ecommerce ad spend across Meta, Google, and TikTok; it has no concept of account identification or B2B pipeline. A company is genuinely choosing between these two only if it happens to run both a B2B motion and a high-spend ecommerce operation, which is rare enough that most buyers will find the decision already made by their business model.
Bottom line
Choose Factors.ai if you are a B2B company that needs to know which named accounts are researching you and want that intent data flowing into LinkedIn campaigns, starting at $199/month with real value unlocking around the $6,000/year Basic tier. Choose Northbeam if you are a DTC or ecommerce brand spending at least $50k a month across paid channels and have stopped trusting platform-reported ROAS, budgeting for a sales conversation and a two-to-four week onboarding before you see attribution data. Neither substitutes for the other; they answer different questions for different business models.
Frequently asked questions
Does Northbeam do account-based marketing like Factors.ai?
No. Northbeam has no company identification or account intelligence capability. It measures ad spend and revenue attribution for ecommerce transactions across channels like Meta, Google, and TikTok, not anonymous B2B website visitors. Factors.ai is the tool built for that identification use case.
Can Factors.ai replace Northbeam for ecommerce ad attribution?
No. Factors.ai's attribution model tracks trackable digital touchpoints in a B2B buyer journey and has no media mix modeling component to measure channels without user-level tracking, like streaming or podcast ads. Northbeam is purpose-built for the ecommerce media mix problem that Factors.ai does not address.
Which tool is cheaper to start with, Factors.ai or Northbeam?
Factors.ai publishes a Lite tier at $199 a month, making it possible to start using the platform without a sales call, though the account unmasking feature that makes it valuable is not included until Basic at $6,000 a year. Northbeam publishes no pricing at all; every tier requires contacting sales, so there is no comparably cheap entry point.
Is Northbeam worth it for a brand spending less than $50k a month on ads?
Probably not yet. Northbeam's own guidance is that brands under roughly $50k monthly ad spend will not generate enough data volume to make its multi-touch attribution and media mix models statistically reliable, meaning the cost is unlikely to be justified by the accuracy gained at that spend level.
Do either Factors.ai or Northbeam offer AI agent integrations?
Factors.ai does, through an MCP integration that exposes account intelligence, intent signals, and attribution data to AI agents in tools like Claude or ChatGPT. Northbeam does not document any MCP or AI agent integration; its AI-adjacent capability is limited to statistical media mix modeling, not agentic data access.