Salesforce can't answer it solo.
CRM in Salesforce is only one input; the forecast stalls without predict close rates alongside it.
Your forecast is only as fresh as the slowest tab. Accurate forecasts guide resource planning. Yet the inputs sit split across Gong / HubSpot / Salesforce.
The forecast pays for it.
CRM in Salesforce is only one input; the forecast stalls without predict close rates alongside it.
To aggregate pipeline data you'd merge predict close rates with crm by hand, every single time.
Identify risks surfaces in HubSpot ahead of time, but that tab is closed during sales forecasting.
Under The Hood
CRM
Sales Engagement Platforms
Financial Systems
One forecast: Aggregate pipeline data, predict close rates, identify risks, recommend actions, update forecasts. Ranked by priority, top risks flagged, a next step on each.
The Context Store
To aggregate pipeline data, the Context Store pre-joins CRM, Sales Engagement Platforms, Financial Systems, BI Tools across Gong / HubSpot / Salesforce and 1 more on the deal key. One query, one truth.
Your agent queries one surface instead of three APIs. Faster responses, lower cost per query, and results that work because the relationships were built before you asked the question.
The Prompt
Two steps. Your data, your results, under 60 seconds.
I want to aggregate pipeline data by combining Salesforce, Gong, and HubSpot data, then report back.
SETUP
Use the Airbyte MCP layer. 4+ connected sources behind one natural-language surface.
WORKFLOW
check connectors, connect Salesforce, Gong, and HubSpot, query CRM, Sales Engagement Platforms, Financial Systems, BI Tools, reconcile per deal, summarize. Missing tools tell you how to link them. One quick authorize step.
TASK
Aggregate pipeline data, predict close rates, identify risks, recommend actions, update forecasts, then give me a single forecast: sorted by what needs me first, each line with the why and the move.The Outcome
10x
~10x. Sales forecasting drops from a 2-hour chore to one query.
90%
~90% cheaper: zero new infra and no seats added to aggregate pipeline data.
3 -> 1
3 sources, 1 prompt: Salesforce, Gong, and HubSpot reconciled before sales forecasting runs.
Based on internal benchmarks comparing Context Store queries to sequential API calls across equivalent datasets.
01 · Output
Every deal scored 1-10, so sales forecasting surfaces what needs you first instead of an alphabetized list.
02 · Signal
When your call platform and your system of record disagree on aggregate pipeline data, the gap is flagged. Not averaged into a guess.
03 · Context
Predict close rates from Gong and HubSpot sits beside each item, letting you aggregate pipeline data without switching tabs.
04 · Action
Sales Forecasting closes each deal with a recommendation. The play and the person to run it. Ready to run.
05 · Brief
The forecast arrives meeting-ready: CRM first, sources attached, Salesforce, Gong, and HubSpot reconciled.
Sales teams run forecasts on stale, scattered data: Gong + Gmail + Salesforce each hold a piece, none hold the whole. Deal context lives across 5-7 systems with different data models.
The data for your forecast already exists in Stripe + Salesforce + Gong. The problem is no one view joins it. Approaching a customer about an upgrade when they're hitting limits has 3x the success rate of cold outreach.
Detect downgrade requests shouldn't take a morning of tab-switching across Salesforce + Gong + Intercom. A cancellation request is the last moment to intervene.
Didn't find your answer? Please don't hesitate to reach out.
Can Sales Forecasting really join Salesforce, Gong, and HubSpot on one deal?
What Salesforce data does Sales Forecasting touch?
Which clients run sales forecasting?
Can Sales Forecasting run on a schedule?
Wire Salesforce, Gong, and HubSpot and 49+ sources into the Airbyte MCP layer and build sales forecasting on data you already own.