Where to find it | Sidebar → Client Health → Service Expansion |
Who can see it | Everyone except standard-access users |
Can you change data here? | Yes — dismissals, notes, follow-ups, tasks and AI drafts |
How fresh is it? | Scores refresh weekly; the page caches for a few minutes |
What it's for
Growing an existing client costs less than winning a new one. But knowing which client is ready — and which pitch would backfire because they're quietly unhappy — used to live entirely in individual Account Directors' heads.
A weekly model scores every client's readiness for an expansion conversation, built from contract history, revenue performance, sentiment from calls and check-ins, invoice health and past deal behaviour. This page ranks clients by that score, flags who's ready, recommends the specific services to propose and explains why, and can draft a phased growth roadmap to hand off to Iris.
What you'll see
The ranking table, sorted by readiness:
Readiness score — 0 to 1
Is Ready — the model's own yes/no, which is not just the score
Blueprints / Performance / Sentiment — the three components, labelled Strong, Moderate or Low
SE Status — an open opportunity, or one recently lost
Recent (3m) — wins in green, losses in red. Hover for the opportunity names, and lost deals carry the verbatim reason we lost.
Days to End — days until the contract ends
Close Rate — the client's historical close rate, hidden by default
Top Recs — the recommended services
Filters for Account Director, Group Director, and a ★ My Accounts star.
Expand any client for:
Tab | What's in it |
Service Details | The top recommended services with the reasoning behind each |
Key Signals | Up to four plain-English flags, like "contract up in 52 days — ideal expansion window" |
AI Summary | A written account of the opportunity, refreshed weekly |
Strategic Growth Roadmap | A generated phased plan, grounded strictly in the data on the page |
Salesforce | Open opportunities and full deal history with links |
POC Contacts | Per-contact sentiment from call analysis |
Readiness Score History | The weekly trend |
Brand Intel | External context, generated with live web search |
Notes, follow-ups and Asana tasks | Your working layer |
Plus Currently Running / Previously Ran / Never Ran service lists — often the fastest way to see the gap.
How to use it
Weekly book review. Filter to yourself or tick ★ My Accounts. The table is already sorted by readiness. Clients with a Ready badge, Strong performance and sentiment, and no open opportunity are this week's pitch list. Pick two or three.
Pick the pitch. Open Service Details to see which services the model recommends and why — what similar clients added, what this client has never run, where their department mix is inefficient. That's the proposal.
Time the ask. Check Days to End and Key Signals. A contract ending in 31–60 days is flagged the ideal expansion window; 30 days or fewer means renewal is already in motion, which is a different conversation. Then cross-check sentiment and churn risk.
Heed the mixed-signals warning. When the score clears the threshold but Is Ready says No — usually because churn risk is present — you get a warning icon. Read it as: expandable on paper, but fix the relationship first. Expansion can double as a retention play, but not blindly.
Build the case. Generate the Strategic Growth Roadmap, then use Copy for Iris or Continue on Iris to enrich it there with call quotes and KPI packs before anything goes to a client.
Work the list down. Dismiss non-viable clients with a reason — not interested, already selling, bad timing, relationship issue — so the active list stays honest. Create tasks or follow-ups for committed next steps.
Post-mortem the losses. Filter to clients with recent losses and read the verbatim reasons in the deal history. Budget objections, timing, service gaps — the pattern is usually visible, and it should change the next pitch.
Understanding the scores
Readiness score — 0 to 1, the model's estimate that the client is ready for an expansion conversation.
Is Ready — the model's own decision. It can say No while the score is high, and that's the single most useful thing on the page.
The ready threshold is set by the data team and can be retuned, so don't memorize a number.
Blueprints — contract-structure signals: expansion history, retention, contract recency and timing, business type.
Performance — revenue trend, marketing efficiency, goal pacing, receivables.
Sentiment — budget signal, satisfaction, relationship health, mood, check-in sentiment, and NPS when present.
All three are labelled Strong from 0.7, Moderate from 0.4, Low below.
Recommended service scores combine four signals: what services co-occur in similar clients, what clients typically expand into, what's common in the client's industry, and where their current department mix is inefficient.
What you can change
Everything lands in Signal or Asana. Nothing writes back to the model, Salesforce, finance or Nova.
Dismiss or reactivate a client, with a reason. Audit-logged.
Generate or regenerate the AI Summary, roadmap or Brand Intel. Brand Intel costs roughly 50 cents per fresh run and has a daily limit per person.
Triage recommended actions, and attach notes.
Manual follow-ups with a severity.
Client notes — shared with Churn Risk and Portfolio Review.
Asana tasks, with status syncing back.
★ Star a client — the star works across every page that shows it.
Good to know
Known label issue: the "Ready Clients by Tier" chart currently counts all clients per tier, not ready ones. Read it as a book-composition chart, not a readiness chart, until it's fixed.
A dismissed client comes back on its own when its readiness score moves by about 0.15 from where it was when you dismissed it — in either direction. The row reactivates with a note recording the change. That's intentional: a dismissal is "not now", not "never".
The readiness score differs slightly from Portfolio Review. This page shows the latest weekly snapshot; Portfolio Review shows the live model value, which can lag. Both are correct.
The model is built outside Signal. How the readiness and component scores are calculated lives in the data team's pipeline. Signal labels and displays; it doesn't compute.
The Performance score is inverted relative to Churn Risk. Here, high is good. On Churn Risk, high performance risk is bad. The two numbers will never match, by design.
"Recent failed SE" means lost in the last two weeks, while wins use a three-month window. The windows are deliberately different.
The POC "decision maker" flag is never set — it's awaiting an upstream field. The rest of the POC data is real.
The roadmap is a draft. Its prompt forbids sources outside the data on the page and requires every recommendation to cite a specific figure — but the intended workflow is still to verify it in Iris before it reaches a client.
Contract-window and score bands are current values, not policy.
Common questions
What does the readiness score mean? A weekly model's 0–1 estimate of how ready a client is for an expansion conversation, from contract history, revenue performance, sentiment, invoice health and past deal behaviour.
Why does a client show a high score but "Is Ready: No"? Because Is Ready is the model's own judgement and it can override the score — usually when churn risk is present. Validate relationship health before pitching.
Why doesn't the score match Portfolio Review? Different snapshots of the same model. See "Good to know".
How fresh is this? The model runs weekly; the page caches a few minutes on top. Salesforce deal data rides along with the weekly run.
Where do the recommended services come from? The model's service-recommendation scoring — co-occurrence in similar clients, typical expansion paths, industry frequency, and department inefficiency.
I dismissed a client and it came back. By design, when the score moves meaningfully. Dismiss it again if it's still not viable.
Does dismissing change the model or Salesforce? No. Every write here stays in Signal or goes to Asana.
Can I trust the roadmap's numbers? It's grounded in the data on the page and required to cite it, but it's still a draft. Verify in Iris before anything is client-facing.
Why don't the revenue figures match finance exactly? They originate in finance but arrive via the weekly pipeline plus a short cache, so they can trail by up to a week.
Related
Churn Risk — the retention side, from the same weekly pipeline
Portfolio Review — both sides on one screen
ETCR (Beta) — whether expansion actually covered churn, per person
POC Management — the contact sentiment shown here, in depth
Glossary — expansion score, ETCR