Custom dashboards: who should see which number?

Tuesday, 9.40 a.m. A field sales rep opens the dashboard and finds fourteen tiles: company revenue for the month, last quarter's channel split, average support resolution time, three separate funnel charts and an annual target gauge. The only decision she has to make this morning is which eight opportunities to call. None of the fourteen tiles answers that. The dashboard is full and the decision is empty.

What follows is an order of operations for turning a dashboard from a data display into a decision tool: first the three tests a number must pass before it earns a tile, then separate number lists for reps, sales managers, executives, marketing and finance, then the trio of definition, freshness and access scope, and finally the maintenance routine that keeps a dashboard from rotting within a couple of quarters.

Why one dashboard for everyone always fails

A single shared dashboard sounds appealing from the top: if everyone looks at the same number, everyone argues about the same reality. What actually happens is that the dashboard squeezes people with very different decision cycles onto one screen. A rep's cycle is measured in hours, a manager's in weeks, an executive's in quarters. Publish all three on one screen and every user has to hunt for their own tile among ten that do not concern them. That hunt is usually abandoned by the third week.

An abandoned dashboard is not harmless. Nobody looks at it, so nobody catches its errors, and months later a badly defined revenue tile shows up in a meeting as evidence. Designing a dashboard around roles is therefore a maintenance decision rather than an aesthetic one: a dashboard people use gets corrected, and one nobody opens keeps being quietly wrong.

The practical consequence is reassuring. Adding another dashboard is far cheaper than adding another number to a shared one. Custom Dashboards let you drag widgets into order and hide the ones you do not need, and the layout is stored per user, so the order a rep sees never disrupts the order a manager sees. Seven ready dashboard templates mean no role has to start from an empty screen.

What three tests should a number pass before it gets a tile?

Adding a tile feels free at the moment you do it, which is exactly why dashboards bloat. Apply three tests and send anything that fails one of them to the report library instead.

The first test is decision: if this number moves today, what does the person looking at the screen do differently? If the honest answer is “I would be aware of it”, the number belongs in a monthly summary, not on a dashboard. The second test is ownership: when the number breaks, is there exactly one name responsible for fixing it? Unowned metrics generate discussion, not action. The third test is cycle: how long does this number take to move meaningfully? Put a ratio that shifts once a quarter on a screen someone opens daily and you train that person to look at a static picture — and then to keep ignoring it on the day it finally moves.

These three tests follow the same logic as the other CRM customisation choices you make at field and view level: every addition creates a surface someone will be responsible for later. The real question when you build a dashboard is not “can we show this number” but “who will defend this number six months from now”.

What belongs on a sales rep's dashboard?

A rep's dashboard is a work queue, not a report card. Opened in the morning it should answer “where do I start today”, and closed in the evening it should answer “what did I leave behind”. That is why it holds numbers that drill down to individual records rather than aggregated company metrics.

• Tasks due today plus anything overdue — clickable straight through to the list.
• Their own open opportunities, split by stage, with the total value.
• Deals with no activity for a set number of days, in a tile of their own.
• Their leads that have crossed the churn risk threshold.
• A progress bar against this month's personal target.

Keeping that list to five is deliberate. A rep checks the dashboard several times a day, usually between two calls; a screen that cannot be scanned will not be scanned. When a tile opens into the paginated list of records behind it, the dashboard becomes a queue — Deep Analysis does exactly that, taking you from a slice of a chart down to a single record. And a stage split is only meaningful if your stage definitions are clean, so how many sales stages you actually need is a question to settle before you design the tiles.

How is a sales manager's dashboard different?

A manager decides about people and weeks: who to coach, which deal to step into, where to push to close the quarter. So the manager's dashboard is not the sum of the reps' dashboards; it asks different questions.

Three families of numbers do the work here. The first is pipeline health: open value by stage and the speed of movement between stages. The second is the forecast; Sales Forecast multiplies open opportunity value by win probability and gives a weighted projection broken down by month, stage and probability bucket, so the manager sees the gap between what the team hopes for and what the model expects on one screen. The third is the team: the Team Scoreboard turns revenue, closed deals, completed tasks and calls into a single combined score. That score is not a verdict on anyone's performance, but it does tell you which question to ask in the next one-to-one.

The most common mistake here is showing team averages with no way into the individual split. An average can look healthy while the distribution underneath it is broken — two strong months hide four weak ones. Leave a path from every aggregated tile down to the per-person breakdown.

How many numbers does an executive dashboard need?

There is a practical ceiling for an executive dashboard: one screen, no scrolling, six to eight tiles. Its job is not to solve the problem but to say where the problem is. Revenue, gross margin, new customers, a period comparison, progress to target and one cash view cover most companies.

Goal Tracking earns its place here: enter the monthly revenue and deal targets and the progress bar on the KPI card fills, turning colour when the target is met. That moves the conversation from “are we doing well” to “how much is still open”, and only the second question is measurable.

What executive dashboards usually miss is profitability. Revenue can grow while margin erodes, and a single revenue tile hides it completely. At least once a quarter, put customer profitability analysis next to the dashboard: the account that brings the most revenue and the account that leaves the most profit are rarely the same one.

What do marketing and finance need from a dashboard?

Marketing's dashboard works at channel level and ties to one question: where should the next budget go? Lead counts alone cannot answer it; you need revenue per source. Source Attribution assigns won opportunity revenue to the lead's first-touch source and puts revenue per source next to revenue per lead. With those two columns side by side, the difference between a channel that produces volume and a channel that produces money becomes visible — that is what lead source analysis looks like on a dashboard.

The second job of a marketing dashboard is turning lists into action. RFM segmentation scores customers on recency, frequency and spend and splits them into Champions, Loyal, At Risk and Lost, which turns a segment tile into the audience for the next campaign; pushing those lists out as custom audiences on ad platforms is the step that connects a dashboard to a campaign.

New channels face the same three tests when they arrive. Where search behaviour shifts toward AI assistants, for instance, the things worth measuring change; which KPIs matter for AI visibility is a separate discussion, and until those metrics mature they belong on the marketing dashboard rather than the executive one. Finance wants something more definite: Cash Flow Projection spreads issued invoice due dates and expected collections across future periods, so the effect of a late payment shows up before the month closes.

Where is a number's definition and freshness written down?

Most dashboard arguments are not about the metric but about its definition. Is revenue won opportunity value, invoiced amount, or collected cash? Was the close date used as the date field, or the invoice date? When two people look at the same tile and quote different numbers, the problem is usually the definition rather than the data.

That is why the definition has to live on the dashboard itself. The Methodology Panel next to each metric states which records, which filters and which date field produced that number, so the definition is not renegotiated in a meeting; everyone reads it from the same place. The Data Freshness Indicator shows when the card was last updated. The Live KPI Dashboard refreshes itself roughly every twenty minutes while the tab is open, and the refresh button bypasses the cache — seeing the age of a number the moment you doubt it is what stops you from acting on a stale figure.

The library of thirty-eight ready reports covers most needs, but when a tile represents a cut specific to your business, you author the definition yourself: building your own sales report with the custom report builder means your choices of source, fields, filters, grouping and aggregation are the definition of that number. Do not put a tile on a dashboard whose definition is not written down.

How often should each number be checked?

Viewing frequency is the most practical way to decide what goes on which dashboard. The table below shows an example arrangement; the figures are illustrative, so tune them to your own cycle.

Role	Viewing frequency	Tiles on screen	Decision it triggers
Sales rep	Several times a day	4-5	Who do I call today
Sales manager	Daily and weekly	6-8	Who to coach, which deal to join
Marketing	Weekly	5-7	Where to shift the budget
Finance	Weekly and monthly	4-6	Which collection to chase first
Executive	Monthly and quarterly	6-8	Where to allocate resources

The rule behind the table is that viewing frequency and the speed at which a number moves have to match. A quarterly ratio does not deserve space on a screen opened several times a day, and a daily-swinging number on a monthly executive dashboard only manufactures false alarms. For low-frequency numbers a Scheduled Report suits better than a tile: you set the send time and the report lands in recipients' inboxes as a PDF or Excel file.

Who sees which rows, and how is scope set?

The quiet half of dashboard design is visibility. The same tile has to contain different rows depending on who opens it, or else a rep sees the whole company's data and a manager cannot see half of their own team. Permission-Based Scope solves this at report level: a report shows the rows the person running it is allowed to see, so a team-scoped user gets only their team's data. One dashboard template then produces different but correct results for people with different permissions.

Numbers that leave the company need a separate discipline. When you want to show a report to an investor or a partner, a Shared Report Link creates a login-free URL with an optional password, expiry date and view limit that you can revoke at any time. The rule is simple: every link that leaves the building gets an expiry date.

There is also visual scope. If two people open the same dashboard with different filters, they read different numbers from the same tile. Saved filters and custom views handle this: you save the combination of filter, date range, grouping and column layout as a view and share it with the team, so everyone is looking at the same slice.

How does a dashboard rot, and how do you prune it?

A dashboard that was right on the day it was built can be wrong six months later. The product mix changes, the team grows, a campaign leaves an unexplained spike in a chart. The first symptom of rot is specific: if someone reads a number on the dashboard and then opens a separate report to verify it, that tile has lost its credibility.

Tie maintenance to three habits. First, annotation: pin a note like “campaign launched on 12 August” to that date on the chart and nobody has to re-litigate the spike months later, because the reason sits next to the data. Second, evidence: when a metric moves unexpectedly, the “Why did it change?” evidence drawer lists the records behind the movement — which opportunities were added, which dropped out — so you see the rows before you offer an interpretation. Third, alerting: with Report Alert Rules you define the metric, the threshold, the period and the recipient yourself, which removes the burden of watching the screen — that is also the logic of being told when a number breaks.

Finally, book a pruning session in the calendar. At the start of each quarter, open every dashboard and ask one question per tile: which decision changed because of this tile in the last three months? No answer, no tile. Teams that shrink their dashboards are the ones that keep looking at them.

If you want to try role-based dashboards against your own data, create a free Rocketly account and start from one of the ready templates.

FAQ

How many dashboards should we build?

Not one per role, but one per distinct decision cycle. Four usually covers a small or mid-sized team: reps, sales management, marketing and finance, plus an executive summary. If two roles make the same decisions at the same cadence, they can share a dashboard.

How many tiles is too many?

Any tile you cannot see without scrolling is too many. The practical ceiling is four to eight tiles per screen; beyond that, each addition lowers the odds that an existing tile gets read. Rather than deleting the extras you can hide them and bring them back when needed.

Should everyone see the same number?

Everyone should see the same definition, not the same rows. The definition must be single and readable from the methodology panel; row scope narrows with the viewer's permissions. A shared definition ends the argument, while shared scope only creates unnecessary data exposure.

What if a dashboard tile disagrees with a report?

Check freshness first: if the card's last update time differs from the moment you ran the report, that is the gap, and the refresh button bypasses the cache. Then compare definitions, because the date field or filter on the two screens is often not the same. The third step is the evidence drawer, which shows exactly which records create the difference.