Intradiem GTM Signal Engine

Product Console

A product view of the same engine. What is instrumented and queryable today, where the data comes from, what to build first, and what to leave out. The other three tabs show the engine running. This one shows the build decisions behind it.

6

signals
instrumented

4

queryable live
via custom MCP

0

black-box models
all rule-based

90

day path to
live event API

Status: Four of the six signals return live JSON from a custom MCP server (get_expansion_signals(domain), list_monitored_accounts). Two are specced, not built. Usage values are modeled on public firmographics, not Intradiem's production event stream.

Signal taxonomy: every signal traces to a product event Instrumentation map

Signal	Product-event source	What it detects	Data path	Route	Status
Seat utilization	Active-agent count vs. contracted licenses	Near capacity → expansion timing	Native	AE	● Live in MCP
Coaching coverage	% of roster receiving automated coaching actions	Partial deployment → land-and-expand gap	Native	CSM	● Live in MCP
Automation volume drop	Automation events triggered, rolling window	Usage decline → churn risk before health scores	Native	CSM	● Live in MCP
CRM not connected	Integration registry, WFM live, CRM absent	Back-office expansion / second revenue line	Native	AE	● Live in MCP
Rule engine under 35%	Active rules vs. tier entitlement	Unfinished onboarding / undiscovered use case	Native	CSM	○ Specced
Champion job change	LinkedIn / Clay enrichment pass	Renewal risk → rebuild the relationship	External	AE + CSM	○ Specced

Why these and not clickstream

None of these are clickstream metrics. The expansion signal lives in contact-center outcome data: seats against contract, automation volume, idle time. A general-purpose PLG tool does not capture that. The build-versus-buy note below covers why.

Where the data comes from, day 1 to day 90 Roadmap

Day 1Nightly reporting export on a cron. No live API.

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Day 30Two signals validated, baselines set

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Day 45One signal worked into pipeline by a rep

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Day 60Lands in rep workspace before Salesforce opens

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Day 90Export swaps to a live event stream

Why the architecture holds

The processor reads 30-day rolling windows with 14-day suppression per signal per account. Day-one input is a daily CSV. Day-90 input is a live stream. Same logic, different source. That is why it is a thin signal layer, not a pipeline rebuild.

What to build first

Seat utilization. Lowest false-positive rate, tied to revenue, easy to validate against a closed expansion. Ship that signal, then add the rest. Every threshold stays a placeholder until the team that runs the motion sets it.

🧩Build vs. buy: why not point Pendo or Gainsight PX at it

Those tools instrument app clickstream for self-serve SaaS: feature adoption, funnel drop-off, in-app guides. Intradiem's expansion signal does not live in clicks. It lives in seat utilization against contract, idle time, and automation volume across a 250,000-agent install base, which those tools do not capture.

The call: the value is the signal logic and routing on the event stream you already own, not the telemetry plumbing. Build that layer. Do not add a second platform that ops has to govern and reps have to learn.

Wrong tool for this data shape

🚫What not to build

What to leave out:

A black-box health score on day one. Unauditable signals do not pass ops review.
Vanity signals (logins, dashboard views) that do not predict revenue.
The full six-signal taxonomy at once. Ship the one that proves value first.
A second analytics platform when a thin layer does the job.

Rule-based and auditable, because anything that writes to a system of record has to pass ops review

From 3 demo accounts to the full install base Scale

Today3 accounts, modeled data, live MCP

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Phase 1Full install base scored nightly

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Phase 2Signals route before Salesforce, no manual triage

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Phase 3Each outcome logged as a dated proof point

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OutcomeExpansion the system surfaces, not the rep recalls

Every account scored nightly, the highest-signal accounts on top before a rep opens Salesforce, each outcome logged as a dated proof point for marketing. The goal is expansion the system surfaces instead of a rep remembering to check, across 250,000+ agents.

What I'd want your read on

Platform modernization	When you modernized the data architecture in 2025, what did it expose at the event level that the GTM motion is not yet using? That is where I would start instrumenting.
Where to start	Is expansion-signal infrastructure on the existing install base the first motion to build, or is net-new PQL instrumentation the bigger opportunity? They are different builds, and I would sequence around your answer.
The bar for production	What is your bar for putting a signal-routing layer like this in front of a customer, on data that touches their usage?

⚠️ SAMPLE DATA These figures run on sample accounts and sample assumptions to demonstrate the engine. The $41.6M is estimated recoverable cost in front of reps, not booked revenue. Real numbers appear once live data and verified Intradiem benchmarks are in. Expand the breakdown below to see exactly how it is calculated.

Impact Scorecard

What this system has put on the table, the activity behind it, and the results realized so far. Opportunity surfaced is estimated recoverable cost in front of reps, not booked revenue. Realized is the number that grows as deals move.

⚠️ SAMPLE DATA Placeholder numbers that demonstrate the engine, not live Intradiem customer data. The scoring is real and deterministic. Swap accounts.csv for a real export to go live.

Signal Queue

The live install base. Every monitored account scored against the six signals, highest first, routed to AE or CSM. This is the daily view: open it, work the top of the queue. Generated from the signal processor, so it never drifts from the MCP.

PLG Signal Framework + PQL Routing

250,000+ agents generating product data every day. Six signals instrumented first: four expansion triggers that surface a product-qualified account, two churn risk signals that fire before health scores catch up. Each routes to the right motion automatically.

4

Expansion
signals

2

Churn risk
signals

2

Route
targets

Note on PLG motion: This framework covers the existing customer expansion case. If the primary mandate is free trial infrastructure from scratch, the data source shifts from Intradiem's usage event stream to a trial product event stream via Segment or Mixpanel, and the routing target becomes conversion rather than upsell. Same signal processor architecture, different event schema.

How it works in production Integration design

Intradiem Platform Usage events, coaching logs, schedule adherence, rule activity

→

          Signal Processor
          Threshold checks on rolling windows, flags anomalies, assigns signal type
        

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Routing Rules Expansion goes to AE. Health risk goes to CSM. Churn goes to both.

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CRM / CS Platform Task created, health score updated, Slack alert on urgent signals

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Rep Action Expansion call, health check, or renewal risk review

Production architecture

Runs on Salesforce and Gainsight, the stack most enterprise health plans and financial services companies already have. The only custom piece is the signal processor sitting between Intradiem's event stream and the CRM. Everything else is Salesforce Flow and Gainsight Rules Engine configuration.

Technical specifics

30-day rolling averages, not point-in-time snapshots. 14-day suppression window per signal per account so the same alert doesn't fire weekly. Failure-safe: writes to Salesforce via Flow, not direct API, so signals queue through outages rather than drop. Champion job change runs as a weekly Clay enrichment pass.

How this was built

Apollo MCP for company data, Clay for enrichment pipeline design, Claude in Cowork for routing logic. The signal processor is a standalone Python script: evaluates all six signals against rolling-window thresholds, applies the suppression window, outputs routing decisions. Runs against sample data out of the box. Code: github.com/dallasandrews1/intradiem-signal-processor

Day one reality

Not a live webhook stream. Day one is a daily CSV export from Intradiem's reporting module running on a cron job. The 30-day rolling average works fine on daily data. The architecture shown is the 90-day state. Start with one signal, one destination, one AE expansion before building the pipeline. Designing the full architecture up front means you know what you are building toward.

📈Agent Seat Utilization at 85%+Expansion

When a customer's licensed seats are running at 85% capacity, they need more before they've asked. The customer proved value and ran out of room.

Threshold: Licensed agents active at 85%+ over a rolling 30 days

Route to AE with expansion proposal and ROI model

🎓Coaching Coverage Under 60%Expansion

High coaching frequency but low roster coverage means they've deployed Intradiem on part of their team and stopped. They're getting value but leaving 40% of their agents unautomated.

Threshold: 20+ coaching sessions per day, but fewer than 60% of agents receiving them in the past 30 days

Route to CSM for deployment expansion conversation

⚙️Rule Engine Under 35% ActiveExpansion

If a customer is only using a third of the available rules, they either didn't finish onboarding or there's a use case they haven't discovered yet: back-office automation, VTO delivery, after-call work reduction. A QBR conversation fixes this.

Threshold: Active rules below 35% of what's available for their tier

Route to CSM for QBR with a use case discovery agenda

🔌WFM Connected, CRM NotExpansion

They set up the scheduling integration but never connected the CRM or back-office systems. That's a separate product conversation and a separate revenue line. 90 days of WFM usage with zero CRM connections is the tell.

Threshold: WFM integration active 90+ days, zero CRM or back-office connections

Route to AE for back-office expansion pitch

⚠️Automation Volume DroppingChurn Risk

If total automation events are down 20% month over month for two straight months, someone on the WFM team is working around the system. This doesn't show up in health scores until it's too late. The fix is a stakeholder mapping call, not a feature walk.

Threshold: Automation event volume down 20%+ MoM for two consecutive months

CSM initiates health check immediately. Urgent.

🔄Champion Changed JobsChurn Risk

The person who bought Intradiem just left. Their replacement didn't make the decision and has no attachment to it. If this happens within 90 days of renewal, the AE needs to own the relationship rebuild before procurement does.

Threshold: LinkedIn job change detected for the primary champion within 90 days of renewal

AE and CSM both get alerted. New stakeholder mapping starts immediately. Urgent.

Signal routing summary

Signal	Trigger	Route to	Action	Priority
Seat utilization 85%+	Rolling 30-day avg	AE	Expansion proposal + ROI model	High
Coaching coverage under 60%	30-day calculation	CSM	Deployment review + expansion path	High
Rule engine under 35%	Account tier benchmark	CSM	QBR agenda: use case discovery	Med
CRM not connected	90-day audit	AE	Back-office expansion pitch	Med
Automation volume down 20% x2	Weekly calculation	CSM	Health check + executive outreach	Urgent
Champion job change	Clay / LinkedIn monitoring	AE + CSM	Stakeholder map + renewal risk review	Urgent

Live Clay Enrichment Run June 10, 2026 Apollo + BuiltWith + LinkedIn job scraper across all 20 accounts. HOT = Tier 1 + active WFM/CC hiring signal.

Company	Verified Tech Stack	Active Hiring Signal	Open Jobs Found	ICP Score	Motion	Flag
Synchrony Financial	Genesys	YES	3	85	Direct AE	HOT
Centene Corporation	Verint	YES	10	85	Direct AE	HOT
CareSource	Five9	YES	1	82	Direct AE	HOT

Three accounts from the live enrichment run that scored HOT: Tier 1 ICP fit plus active WFM or contact center hiring confirmed. Enrichment stack: Apollo (firmographics), BuiltWith (tech stack), LinkedIn Jobs (hiring signal). Full 20-account scored table below with per-dimension breakdown.

Score dimensions

Industry /25

CC Scale /25

Tech stack /25

Pain signal /25

Tier 1 = 76+ (Direct AE) · Tier 2 = 55-75 (BDR) · Tier 3 = under 55 (Nurture) · Click a row to expand · Data: LinkedIn, ZoomInfo, BuiltWith, June 2026, best-effort estimates, not validated against Intradiem's CRM

Company	Industry	Employees	Tech stack	Pain signals	Score ↕	Tier	Motion

Scoring model

Four dimensions, 25 points each, 100 max. Sources are public: tech stack from ZoomInfo and BuiltWith, pain signals from LinkedIn job posts and press releases, employee count from LinkedIn. Best-effort estimates as of June 2026, not validated against Intradiem's CRM. Designed to refresh weekly via a Clay or Apollo enrichment run.

4

Score
dimensions

100

Max
score

3

Tier
thresholds

Score dimensions

Industry /25

Health Insurance: 25
Financial Services: 20
Banking: 20
Insurance: 18
Healthcare Services: 15
Other: 8

CC Scale /25

50,000+: 25
10,000-50,000: 22
5,000-10,000: 18
1,000-5,000: 12
Under 1,000: 5

Tech Stack /25

Five9 (partner): 25
Genesys (partner): 23
Verint (competitor): 20
Calabrio (competitor): 18
NICE inContact: 15
Unknown: 8

Pain Signal /25

WFM hiring + cost program: 25
Active WFM hiring: 22
Active CC hiring: 20
Cost reduction announced: 18
Digital transformation: 15
No signal: 5

Tier thresholds

Tier	Score	Motion	Logic
Tier 1	76-100	Direct AE	Strong fit plus a live signal. AE opens with research. Target: meeting in 10 days.
Tier 2	55-75	BDR Sequence	Solid fit, weaker signal or smaller scale. Multi-touch cadence. Target: meeting in 30 days.
Tier 3	Under 55	Nurture	Below current scale or no active signal. Watch for WFM hiring or tech stack change. Re-score monthly.

Intradiem GTM Signal Engine

Two halves of the GTM role.
One working prototype.

Product Console

Strike List

Impact Scorecard

Signal Queue

PLG Signal Framework + PQL Routing

Scoring model

Score dimensions

Intradiem GTM Signal Engine

Two halves of the GTM role.One working prototype.

Product Console

Strike List

Impact Scorecard

Signal Queue

PLG Signal Framework + PQL Routing

Scoring model

Score dimensions

Two halves of the GTM role.
One working prototype.