B2B marketing teams face a visibility problem before they face an automation problem: buyers can establish vendor preferences while leaving only a partial record of their research. Findings from 6sense suggest that AI-driven go-to-market systems need to interpret that incomplete picture rather than simply accelerate outreach. The company’s planned capabilities connect buyer intelligence with brand visibility, advertising signals and sales execution, although several remain in beta or are scheduled to enter it.
Vendor Preference Forms Before Sales Gets a Clear Signal
In a new study, 6sense found that 94% of buyers identify a favored vendor before contacting vendors. That puts pressure on the marketing work that precedes a sales conversation. Brand exposure and research-stage content belong in the same strategic picture as account targeting and seller outreach.
The difficulty is that a recorded contact may reveal little about the wider decision. The study describes buying influence extending to consultants and analysts, as well as investors, distribution partners and systems integrators. Purchase authority and influence therefore need to be considered separately.
Form data adds another complication. Only 35.2% of surveyed buyers supplied their own contact details during the process. The reported alternatives show why a contact record cannot be treated as a complete account of demand.
Where the buyer record becomes incomplete
| Behavior reported by 6sense | Share of buyers | What marketers can reasonably infer |
|---|---|---|
| A colleague submitted the form | 31.6% | The recorded contact may differ from the person researching. |
| A personal or alternative email was supplied | 19.3% | The address may provide limited business context. |
| AI helped the buyer bypass form submission | 17.7% | Research can proceed without generating a conventional lead. |
| Gated material was avoided | 7.4% | Access requirements can leave some interest unrecorded. |
These figures describe reported behaviors; they do not establish how much revenue any behavior affects. They do, however, support a practical distinction: measuring identifiable responses and understanding a buying account are different tasks.
Explainability Belongs Inside the Revenue Workflow
6sense has adopted the positioning Partner for Agentic GTM. Its argument centers on shared context across people, systems and AI agents, rather than the number of agents a business deploys.
Amir Ravandoust, CEO, 6sense, argues that successful agentic go-to-market teams operate from a common understanding and can explain that understanding. Kelly Hopping, CMO, 6sense, similarly warns that AI operating without sufficient context can accelerate mistaken judgments.
The company’s Explainability capability is intended to make account scoring and predicted buying states easier to interpret. 6sense says it will explain their revenue significance and provide confidence scores to help users decide how heavily to rely on a prediction.
For marketing leaders, this creates a useful evaluation standard. A recommendation to prioritize an account should come with enough reasoning for the team to assess it. Otherwise, a score can move through an automated workflow while its limitations remain hidden.
The source provides no evidence of prediction accuracy or resulting revenue improvement. Explainability should therefore be understood as a proposed aid to judgment, not proof that the underlying judgments are correct.
AI Visibility Connects Brand Presence With Demand Intelligence
6sense describes AI Visibility as a way for revenue teams to see how their brands appear across major AI engines. That extends the visibility question beyond whether a buyer has clicked an advertisement or submitted a form.
The strategic connection is straightforward. If buyers establish preferences before direct contact, and some use AI to avoid forms, revenue teams have a reason to examine the brand information encountered through AI-assisted research. Visibility and account intelligence address different parts of the same buying process.
Still, the product description leaves substantial questions unanswered. It does not explain which engines are covered, how appearances are measured or whether the capability links those appearances to buying decisions.
Marketers should keep those distinctions intact. Knowing how a brand appears is different from demonstrating that its appearance generated demand. The stated capability supports observation; the available information does not establish attribution.
Advertising Signals Need Context Before They Trigger Outreach
The execution layer brings the broader strategy into individual account decisions. 6sense says New Destinations and Segment Sync recommends the next sales contact when an account considered in market clicks an advertisement. That proposed connection gives advertising a role beyond generating a response. It can supply a signal for sales prioritization, provided the account context is reliable enough to support the next action. The BDR Agent is intended to help sellers engage active buyers earlier in vendor selection while reducing research work. It is planned for beta release. Meanwhile, Competitive Threat and Deal Risk are models intended to flag competitive pressures early enough for teams to respond; both are scheduled for closed beta in November.
Questions to settle before automating the handoff
- Does the recommendation explain why the account merits attention?
- How much confidence does the system assign to its buying-state prediction?
- Does the suggested contact reflect the distinction between researcher and decision-maker?
- Is the capability available, in beta or still awaiting a beta release?
These checks connect campaign activity to seller action without treating every signal as equally decisive. They also keep product availability separate from promised functionality.
Shared Intelligence Is the Test for Agentic GTM
6sense says its Sales Intelligence MCP is available and can check whether accounts are actively buying and identify their buying stage. The releases also include keyword intent APIs in beta. These access points sit alongside the company’s stated ambition to give agents and human teams a common operating context.
Taken together, the capabilities outline a connected workflow: observe brand presence, interpret account interest, explain prioritization and guide outreach. That is a more useful frame for evaluating the offering than assessing each agent in isolation. The business case remains unproven in the supplied material. No performance results establish that the suite improves conversions, shortens sales cycles or changes competitive outcomes. Marketing leaders evaluating it should ask how shared context is maintained across their workflows, what evidence supports each recommendation and how beta features will be tested before broader use.
