The setting
offers , a cloud platform that captures customer conversations and data from customer relationship software. Sales reps, managers and revenue leaders use it for sales insights, forecasting, coaching and workflow automation.
Mid-market buyers want fewer revenue tools but still need proof that AI changes execution.
A consolidation story must protect budget discipline while making governed revenue context feel materially more useful than another assistant.
Who you’d be doing this for
“My CRO asked which tool we’d cut, and I still can’t show what each one actually changes.”
Alma Sundberg · Vice President of Revenue Operations · a character in this brief
Leads a mid-market revenue organization reviewing overlapping forecasting, CRM, and AI tools.
What is at stake
Mid-market buyers question another revenue platform while cheaper AI tools promise deal-risk signals. You must decide which consolidation concern earns a meeting and what proof belongs in the first message.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- platform consistency vs. segment-specific relevance
- meeting volume vs. sales acceptance
- consolidation economics vs. product depth
- AI-generated variants vs. message precision
Why Gong
Gong Engage and Clay can turn a precise consolidation hypothesis into a measurable mid-market pipeline motion.
Written with these in mind
Not your kind of problem? 21 more at Gong, or browse every organization.
Where the organization context comes fromThe postings this brief was written from, and the reporting read before it.
The organization context comes from public information. The situation and characters are written for the brief.
Job postings it was written from
Public descriptions of the work at Gong. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- Principal Product Marketing Manager (opens in a new tab)
- Own the technical buyer narrative — define positioning and messaging that earns credibility with CIOs and RevOps leaders evaluating enterprise AI infrastructure for revenue.
- Your job is to make the integrated picture feel inevitable to a technical buyer who has spent the past 18 months evaluating fragmented point solutions and wondering why none of them hold up in production.
- Email Marketing Manager (opens in a new tab)
- Support the automated sales MQL follow up and signal-led motions in partnership with Pipeline Ops and Sales leadership, building Gong Engage flows, reply-driving templates, and personalization frameworks that feel human, relevant, and worth responding to
- Lead and execute email programs across the full lifecycle, from 1:many brand and nurture programs to 1:few segment campaigns to 1:1 sales-style outreach that drives MQL conversion, ensuring every send has a clear audience, purpose, and next action
- Vice President, Product Marketing (opens in a new tab)
- Lead with customer outcomes over technology, ground claims in measurable proof and accuracy, and sharpen positioning against both horizontal foundation-model providers and point solutions, anticipating how the competitive set will keep shifting.
- As Vice President of Product Marketing, you’ll lead the global Product Marketing function and shape the story, strategy, and go-to-market (GTM) execution that define Gong’s leadership in Revenue AI.
- Sr. Director of Web Strategy & Experience (opens in a new tab)
- Sr. Revenue Marketing Manager, Commercial & Mid-Market (opens in a new tab)
- In this role, you will be a key driver of pipeline creation and acceleration for Gong's Corporate segment, spanning Commercial (SMB) and Mid-Market segments.
- Track deals beyond the MQL-to-SQL handoff, and hold yourself accountable for what converts to revenue.
Reporting read before this brief was written
The pieces closest to the situation in this brief.
On October 13, 2026, Seismic announced a Deal Agent, available in Highspot by Seismic and Seismic platforms, that combines CRM activity, meetings, emails and buyer engagement to surface deal risks, missing stakeholders and next-best actions.
Seismic Everywhere: Agentic Revenue Execution for GTM (opens in a new tab) · seismic.com · Oct 13, 2026
In Salesloft's September 2026 survey, about 26% of organizations were actively consolidating revenue technology, another 32.6% were evaluating where to consolidate, and 26.4% still preferred specialized point solutions.
Salesloft Releases 2026 US Revenue Benchmark Report (opens in a new tab) · salesloft.com · Aug 28, 2026
In its Q3 2026 Forrester Wave on revenue orchestration platforms (published September 25, 2026), Forrester found that buyers want revenue context shared across systems and AI agents while many providers try to keep that context inside their own platforms.
The Future Of Revenue Orchestration: Three Findings From The Forrester Wave™ (opens in a new tab) · forrester.com · Sep 25, 2026
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.
Where similar work appears
Other live briefs connected to this one, and what connects them.
Similar problems at other organizations
Like this one, each of these is about betting growth on an outside partner or launch.
Enterprise prospects want buyer-intent workflows, but partners cannot yet position a repeatable commercial path.
You have to weigh fast partner activation against a package RevOps leaders can govern and buy.
Partners lack a repeatable way to turn consolidation interest into qualified enterprise pipeline.
You must weigh partner economics against a focused motion that reaches real economic buyers.
Enterprise buyers cannot turn AI-readiness interest into a bounded first engagement, so partner proposals keep expanding.
You must weigh a repeatable partner motion against the proof each buyer needs before committing.
The same setting, from another role
Each is set around Gong’s Gong Revenue AI OS, written for a different role. They’re separate briefs, not the same scenario.
Sales managers spend 40 minutes checking proposed CRM changes in each evaluation.
You must choose what to prototype and prove customers can operate it themselves.
A customer will delete 60,000 interactions tonight, with consent unresolved for 3,200.
You must weigh permanent evidence loss against irreversible disclosure.
A customer rehearsal has 8 broken inspections out of 20.
You must weigh a reusable handoff change against a fixed dataset that preserves today's session.
Other problems with a similar purpose
In each of these, as in this one, the aim is to turn ambiguous signs of buyer interest into a concrete, measurable step toward commitment.
Too few paused mid-market pros resume lead spend after reaching the budget and targeting message.
You need to weigh a sharper service-specific claim against a clean test that preserves confidence in iROAS.
Enrolled brands are stalling before their first Insider Partnership action.
You must choose which brands need tailored coaching and which need a clearer scaled path.
New users are arriving from AI-assistant questions, but their path is hidden inside generic referral traffic.
You have to weigh a focused eight-week test against a broader discovery bet with less interpretable learning.
