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Pipeline Influence Tracking

Capability Slug: deal_influence_tracking Plan Tier: Command Credit Cost: 15 credits per analysis Category: Intelligence & Attribution Default mode: content_attribution

Overview

Pipeline Influence Tracking is the attribution layer that infrastructure tools don't have. AWS Partner Central shows you marketplace metrics. Your CRM shows you deal stages. Your analytics tool shows you UTM clicks. Pipeline Influence Tracking correlates them — surfacing which content, campaigns, and engagement events actually move deals through the funnel and onto AWS Marketplace.

The capability is honest about what it is: AI-powered correlation analysis over your data. You bring the inputs (or connect the integrations); Claude finds the patterns.

Replaces the old LinkedIn content-to-marketplace correlation feature

The retired linkedin_graph_analysis capability bundled a content-to-marketplace correlation mode that worked on user-pasted LinkedIn data. When that capability was reframed to LinkedIn Ad Intelligence (competitor ad teardown), the attribution work moved here — multi-source, multi-channel, and not bound to a single platform. See the LinkedIn Ad Intelligence page for the rename context.

What you can correlate

Six input types feed the eight tracking modes. Each input has a defined data source — some are internal to Vellocity, some require an AWS Marketplace connection, some need an external integration.

Input Slug Data source What it provides
UTM-tagged referral links utm_tracking Internal Click-through from content to your Marketplace listing via UTM parameters
AWS Marketplace Private Offer events private_offers AWS Marketplace API Private-offer creation, acceptance/rejection, contract value
Metering / usage events metering_usage AWS Marketplace API Usage spikes correlated with campaign engagement
CRM deal-stage changes crm_deal_stages External integration (HubSpot, Salesforce) Stage transitions, deal value changes, contact activity
Email / calendar events email_calendar External integration Demo requests and meeting bookings from content distribution
Content engagement metrics content_engagement Internal Asset downloads, page time, return-visit patterns from owned properties

The richer the input set, the more cross-source correlations Claude can find — but you don't need all six to get value. content_attribution and engagement_correlation work on internal-only data; private_offer_correlation only needs the AWS Marketplace connection.

The eight tracking modes

Pass the mode as the tracking_type parameter when invoking the capability.

1. content_attribution — which content drove pipeline?

The default mode. Maps content touchpoints to pipeline creation and progression. Answers: which blog posts, social posts, or emails preceded deal creation? What content was consumed before PDP visits? Which topics correlate with deal acceleration? Returns first-touch and last-touch attribution, plus a multi-touch content journey.

2. marketplace_correlation — content → AWS Marketplace actions

Correlates GTM content with Marketplace actions: PDP traffic spikes, demo requests, Private Offer requests, subscriptions, co-sell triggers. Identifies content types that drive each action, the time lag between content and conversion, and themes that accelerate deals through Marketplace.

3. pipeline_velocity — content's effect on deal-cycle length

Compares deals with high vs. low content engagement to surface what shortens (or lengthens) sales cycles. Reports content patterns of fast-moving deals, content gaps that stall deals at specific stages, and the optimal content cadence for velocity.

4. touchpoint_analysis — buyer-journey stage map

Maps content touchpoints across the five-stage buyer journey (Awareness → Consideration → Decision → Purchase → Post-purchase). For each stage: what content gets consumed, the average number of touchpoints, the most effective pieces, the gaps causing friction.

5. utm_correlation — UTM-tagged campaign performance

Correlates UTM-tagged links (utm_source, utm_medium, utm_campaign, utm_content, utm_term) with pipeline events. Reports which sources drive Marketplace visits, which campaigns correlate with deal creation, and time lag between click-through and conversion. Useful for ROI estimation per campaign.

6. private_offer_correlation — what content drove Private Offers?

Treats AWS Marketplace Private Offers as high-intent signals. Analyzes what content was consumed before each Private Offer request, content patterns of accepted vs. rejected offers, time from content engagement to offer creation, and offer-value correlation with content depth.

7. crm_sync_analysis — CRM stage progression vs. content

Requires a HubSpot or Salesforce integration. Correlates CRM stage transitions (MQL → SQL → Opportunity → Closed) with content engagement to surface which content accelerates each stage, win-rate correlation with engagement, average content touches before close, and high-value-deal content patterns.

8. engagement_correlation — depth-of-engagement signals

Looks at asset downloads, page time, return-visit patterns, video completion rates, and interactive-element engagement. Reports which engagement types predict deal creation, engagement-depth vs. deal-value correlation, and engagement thresholds that signal sales readiness.

What the response looks like

Every mode returns the same JSON shape:

{
  "success": true,
  "tracking_type": "content_attribution",
  "credits_used": 15,
  "analysis": {
    "insights": ["...", "..."],
    "recommendations": ["...", "..."],
    "data": { /* mode-specific structured data */ },
    "summary": "Executive summary of findings"
  },
  /* mode-specific top-level keys, e.g. */
  "high_impact_content": [...],
  "attribution_model": {...},
  "content_journey": [...],
  "_schema": { /* DealInfluenceSchema-typed projection */ }
}

The _schema block is a typed projection of the result keyed by DealInfluenceSchema — useful when piping the output to downstream automations or dashboards that need a stable shape.

When to use it

Scenario Recommended mode
Marketing leadership asking "which content drove pipeline?" content_attribution
Quarterly review of campaign ROI utm_correlation
Justifying Marketplace investment marketplace_correlation
Sales asks why deals are stalling pipeline_velocity + crm_sync_analysis
Building a buyer-journey content plan touchpoint_analysis
Forecasting Private Offer pipeline private_offer_correlation
Lead-scoring model tuning engagement_correlation

It is not:

  • A CRM. Connect HubSpot or Salesforce as the CRM source.
  • A web analytics tool. UTM tracking lives in your analytics stack; this capability correlates the UTM data you already have.
  • A campaign-builder. For campaign generation, use Joint GTM Campaign Planner (joint_gtm_planner) or Generate Content Series (generate_content_series).
  • A vibe-based attribution model. You provide the data; Claude finds patterns. No data, no findings.

Getting started

1. Connect your inputs

Input How to enable
AWS Marketplace events Cloud Connectors → AWS — see AWS Marketplace Connector Setup
HubSpot / Salesforce Integrations → CRM (manage_integrations scope)
UTM tracking Tag your campaign URLs with utm_source/utm_medium/utm_campaign and they'll flow into the correlation engine automatically when visitors land on your owned properties
Email / calendar Integrations → Workspace
Content engagement Tracked automatically on content published through Vellocity Social Media Publishing or hosted on your linked properties

2. Pick a mode and run

Navigate to Analytics → Pipeline Influence, choose a mode, set the date range and filters, and click Run analysis. Most analyses return in under 30 seconds.

3. Review insights and recommendations

Each analysis returns:

  • Insights — pattern observations Claude found in your data
  • Recommendations — concrete actions (e.g. "Increase technical case studies by 40%; they precede 3.2× more Private Offer requests than product announcements")
  • Mode-specific structured data (attribution journeys, touchpoint maps, content lists)
  • Executive summary — one-paragraph read for stakeholders

API access

Pipeline Influence Tracking is exposed through the agent runtime as deal_influence_tracking. Partner API keys scoped with manage_content or view_marketing_analytics plus the agent capability slug can run analyses programmatically through the agent execution endpoint. See Partner API Capabilities and Authentication & API Keys.

See also

Capability slug: deal_influence_tracking · Handler: DealInfluenceTrackingCapability · Default mode: content_attribution