How do I see which customers are slipping?

Build one Salesforce dashboard on SignalRx score history. Because SignalRx keeps a record of every Fit and Health change, a native dashboard answers the four questions leadership actually asks: how many customers lost health this month, whether it is getting worse, exactly which accounts, and where the loss is concentrated. It refreshes itself and needs no separate BI tool.

Illustrative build for a healthcare technology company. Anonymized from a live SignalRx implementation.

This is the CSM and RevOps working dashboard for spotting and acting on decline account by account. For the leadership and board reporting roll-up of renewal risk, see How do I report renewal risk to leadership?

The problem

A score is a snapshot. Leadership questions are about movement: how many customers lost health this month, is it getting worse, which segment is it concentrated in, who should we call first. Most scoring tools overwrite yesterday's number with today's and cannot answer any of those.

What SignalRx changes

SignalRx keeps a history of every score change in Salesforce: which account, what changed, from what to what, and when. That turns Fit and Health movement into something you can report on with standard Salesforce reports. A dashboard built on that history answers the leadership questions, refreshes itself, and needs no separate BI tool. This is the SignalRx pattern: it tags the right data and scores every account and contact on external and internal signals, then turns those scores into Revenue Plays and lists inside Salesforce for action, with the edge coming from internal signals like revenue, support, and product usage over time plus inference across sources.

Example

A practice-management software company wanted one dashboard that answered four questions in order, top to bottom. Health first, with a companion view for Fit.

• Row 1. How big is it?
• Row 2. Is it getting worse?
• Row 3. Who exactly?
• Row 4. Where is it concentrated?

01 · What the dashboard shows

Four rows, with one segment filter that applies to everything on the page:

• Row 1: How big is it? Four tiles: accounts that lost health, accounts that gained, total health points lost, and customers at risk today. Green, amber, red.
• Row 2: Is it getting worse? Health movement week by week, declines against improvements.
• Row 3: Who exactly? Two tables: the accounts that dropped most, which is the call list, and the accounts at risk today. They overlap, but they are not the same list.
• Row 4: Where is it concentrated? Health lost, by customer segment.

A companion view shows the same for Fit: newly scored accounts, increases, and decreases.

02 · How it is built

SignalRx delivers the dashboard, its reports, and the handful of helper fields they need as a package your admin installs, with access set up for the teams who need it. Everyone who opens it sees the same numbers.

03 · Read it right

Three lessons from the live build, now part of every SignalRx dashboard engagement:

• A cleared score is not a small decline. When an account leaves the scored population, its health score is removed rather than lowered. The dashboard counts the score that was lost and says so in its description.
• A spike on one day is usually a model change, not a wave of unhappy customers. The weekly view makes a spike visible instead of hiding it inside a monthly bar. Check with your SignalRx team before working that call list.
• Duplicate accounts double-count. If the same customer exists twice in Salesforce, their movement adds up. Fix the duplicates.

What the team sees and does

• Leadership. Opens one dashboard and gets the four answers, filterable by segment.
• CS leads. Click through the declining accounts table to the full list and assign calls.
• RevOps. Can tell whether the model moved or the customers moved, and asks the right question.

What to measure

• Health declines versus improvements per week, and the trend.
• Total health points lost, by segment.
• Customers at risk today, and how many join and leave that list.
• Time from appearing on the call list to the first logged activity.

Variations SignalRx customers run

• Fit movement view. Newly scored accounts, increases, and decreases by day, to see model updates and new-customer scoring.
• Revenue Play size over time. How many accounts join and leave each play per week.
• Per-account trajectory. One account's health over time, shown on the account page.

How do I read health over time?

Read the change, not the level. An account can still read high and be the real risk if it has slid for three straight months, while a genuinely stable account holds its tier period after period. The dashboard rows above report movement for exactly this reason: a single reading hides the slow declines that trajectory catches.

The clearest case is two accounts at the same tier. Two customers both read Maintain today: one has held that tier for a year, the other slid from Expand through two months of falling usage. The snapshot treats them as identical, but their history does not, and it is the second account that belongs in front of a CSM before it reaches Triage.

History also settles the question every save eventually raises: did the intervention work? Because SignalRx keeps each score change rather than overwriting it, you can watch health recover after a save instead of guessing whether the effort mattered. That same per-account history feeds the movement dashboard, so reading one account and reporting the whole base draw on the same record.

What SignalRx implements for you

• The reports and the dashboard, in a folder your teams can see.
• The segment filter and colour bands.
• A short written guide to reading it, including the caveats above.
• A revisit after the first quarter to switch from weekly to monthly and retune the tiles.

Kickoff to live dashboard: 1 week, once SignalRx has a few weeks of history to draw on.

See it in action: Increase Customer Revenue with SignalRx.

Admins who want the detail of how plays appear as Salesforce fields and drive automation can read Using SignalRx Natively in Salesforce.