Feature · Dashboard Examples

Dashboard examples that solve a job, not just display a chart.

A gallery of the dashboards our customers run against real pipeline, real campaigns, real retention, and real admin SLA data. Each example is clonable, each has a shaped job, and each shows the specific decisions the view supports.

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What makes a dashboard worth cloning

The design principles behind the examples below.

Most dashboards fail the same way: too many tiles, no decision supported, no clear owner, and no action anywhere on the view. The dashboards our customers actually open every morning share a different pattern. Six principles separate the examples a team adopts from the ones that die in a tab the week after launch.

One job per view

Each dashboard answers one question.

Is our forecast at risk? Is marketing-sourced pipeline healthy? Which admin SLAs are breaching? One dashboard, one job. The sprawling 24-tile view that tries to answer everything answers nothing. Our best-performing templates all pass the "say the question out loud" test.

Comparison, not snapshot

Numbers next to context.

A revenue number alone is noise. Alongside quota, prior quarter, prior week, and plan, it is signal. Every tile on a good dashboard carries the comparison the viewer needs to decide if the number is good or bad.

Drill rather than clutter

Headlines on top, drills behind.

The top layer of a good dashboard reads in 30 seconds. The second layer answers "why." Each tile links to a filtered list, a cohort view, or a longer report. The dashboard stays tight because detail lives one click deeper.

Action adjacent

The next step is a button, not a note.

The best dashboards include the action next to the signal. Call list, draft outreach, start a Flow, open a Projects issue. The dashboard becomes a dispatch surface rather than a view-only artifact.

Role-filtered

The AE sees her number, not the team's.

The same dashboard template viewed by an AE shows her pipeline, by a manager shows the team roll-up, by the VP shows the segment. Role filtering happens at render, not through 15 duplicated dashboards that drift.

Live, not refreshed

The number is current, every time.

Strkr dashboards read from the live transactional store. No overnight ETL, no stale materialized view, no "the dashboard is 36 hours behind." The number the morning stand-up sees is the number from the last five minutes of pipeline activity.

Sales dashboard example

Pipeline health, open opportunities, next actions.

The dashboard every sales manager actually opens Monday morning. The job: understand pipeline health for the quarter in under five minutes and identify the three deals that need intervention this week. Six tiles plus two side panels. Clone the template, filter to your team, done.

Coverage

Pipeline to quota ratio, trended.

Open pipeline weighted by stage probability, divided by remaining quota. Compared against last week, last quarter at the same point. Red if below 3x for enterprise, 4x for mid-market. The headline tile that answers "are we on track."

Stage distribution

Where the deals live right now.

A horizontal bar chart with deal count and total value at each stage. The classic diagnostic: too much weight in early stages means poor conversion ahead, too much in late means the quarter is already set and the next one is thin.

Stale deals

Open deals with no activity in 10 days.

A dense table of stale commit and best-case deals with owner, last-activity date, next-step field, and age in stage. The direct intervention list. Clicking any row opens the deal and offers a one-tap Flow to send a Strkr AI-drafted nudge.

Rep activity

Calls, emails, meetings per rep this week.

Simple bar chart of activity counts by rep. Red where below the floor the manager sets. Not for coaching the top performer, for surfacing the quiet rep whose activity dropped two weeks before the pipeline will show it.

Win rate trend

Last 8 weeks, by segment.

Rolling win rate (closed won divided by closed won plus closed lost) over 8 weeks, split by segment or product. The trend is the leading indicator; the quarter-end snapshot comes too late to adjust.

Commit at risk

Deals in commit without recent champion engagement.

Strkr AI scans every commit-stage deal for silent-champion warnings: no reply from the champion in 14 days, no site visit, no email open, no last meeting booked for the critical compliance review stage. The flagged list is the "call before Friday" set.

Marketing dashboard example

Sourced pipeline, campaign ROI, lead-to-SAL conversion.

The dashboard a VP Marketing walks into the quarterly review with. The job: defend the marketing budget by showing sourced pipeline per dollar, which campaigns are producing, and where the funnel is leaking. Nine tiles that read in three minutes, with cohort drills behind each.

Sourced pipeline

Open pipeline attributed to marketing campaigns.

Total value of open opportunities with a marketing-touch attribution. Multi-touch and first-touch displayed side by side so the CFO sees both perspectives. Compared to goal for the quarter and to the same point last quarter.

Campaign ROI

Sourced revenue per dollar spent.

Grouped bar chart of campaigns ranked by sourced closed revenue divided by cost. The campaigns at the top are the ones to double; the ones at the bottom are the ones to retire. The quarterly budget conversation runs off this view.

Funnel conversion

MQL to SAL to opportunity to closed won.

Funnel view with percentages between each stage. The leaks surface instantly: a 42 percent MQL-to-SAL means marketing is producing noise, a 28 percent SAL-to-opportunity means sales is slow to accept. The weekly ops meeting runs off this.

Lead response time

Median SLA on inbound demo requests.

Median time-to-first-touch on demo requests this week. Red if above the SLA target. Breaks down by rep so the chronic laggards are visible. Fixing lead response is the highest ROI marketing-adjacent lever most B2B teams never pull.

Top-performing content

Pages and assets ranked by engaged-contact lift.

Content ranked not by raw views but by the lift in SAL-stage conversion for contacts who touched it. A whitepaper with 300 downloads that produces zero deals is noise; a 40-download comparison guide that correlates with 18 SALs is signal.

Account engagement

Target accounts active this week.

Count of target accounts with 3-plus engaged contacts this week. The ABM scoreboard. The accounts on the list get the exec-sponsor play; the accounts not on it get a nurture refresh.

Nurture performance

Open and click rate by sequence.

Each active nurture sequence with open, click, and reply rates against the baseline. Underperforming sequences get flagged for revision; overperforming ones get copied. The marketing-ops lead reviews this surface weekly.

Rejection reasons

Why sales reject marketing leads.

Donut chart of rejection reasons on marketing-sourced leads: bad fit, no budget, duplicate, student, competitor. The pattern tells marketing which campaigns and segments need retargeting. The classic finger-pointing meeting becomes a specific operational conversation.

Pipeline cohort by month

MQLs sourced in each month, their outcome.

A matrix: rows are the month the MQL came in, columns are the subsequent outcome stage. Reveals aging: marketing-sourced leads from Q1 that are still open in Q4 may need re-engagement rather than fresh prospecting.

Operations dashboard example

Admin SLA, workflow health, data hygiene.

The dashboard a RevOps lead runs against the operational stack: Flows that are failing, SLAs that are breaching, data-hygiene signals that will produce bad reporting next month if left alone. Seven tiles, mostly red-green indicators, aimed at keeping the operating system healthy before leadership asks.

Workflow SLA adherence

Percent of runs completing within SLA.

Rolling 7-day SLA adherence across every active Flow. Green above 95, yellow at 90, red below. Breaches drill down to the specific workflow and the specific actor pattern responsible.

Flow failure rate

Workflow runs that errored this week.

Count of failed runs per Flow, with the top five surfaced. A sudden spike indicates upstream data drift (field renamed, enrichment vendor rate-limiting). Catching it on this dashboard beats catching it in a rep complaint ticket Friday.

Open approvals

Approvals pending beyond SLA.

List of approval requests that have aged past their SLA window, with approver and age. The dashboard surfaces chronic approver bottlenecks (which usually means capacity, not laziness) so staffing adjustments happen before Q-end.

Data hygiene score

Required fields missing on active records.

A composite: percent of open opportunities with a close date, next step, and amount; percent of active accounts with industry and ARR; percent of contacts with role and consent status. A single number that trends over quarters.

Duplicate pile

Suspected duplicates waiting for merge review.

Strkr AI surfaces likely duplicate contacts and accounts. The dashboard tile shows the count and links to the merge queue. The weekly data-hygiene ritual: review 20 pairs, decide, done. The alternative (duplicates compound into contaminated reporting) is the real cost.

User provisioning health

Clerk sync status, orphan rows, permission drift.

Count of Clerk-synced users, count of orphan user_id rows requiring cleanup, permission groups out of sync with role template. The dashboard that keeps a sync problem from compounding into a weekend recovery.

Audit event trend

Volume of audit-logged events this week.

Rolling line of audit events written per day. The ambient telemetry: a sudden drop usually indicates a logging regression, a sudden spike usually indicates an admin bulk action. The RevOps lead glances at it for anomalies.

CS and retention dashboard example

Health, renewal risk, expansion signal.

The dashboard a VP Customer Success opens before every CSM 1:1. The job: identify the three accounts at risk this week and the five accounts ripe for expansion. Six tiles, each tied to specific CSM action, each refreshed off live product-usage and support-ticket data.

Health distribution

Account health across the book.

Donut of accounts by health band (green, yellow, red). Headline number: percent in green. Trend arrow against last quarter. The CRO opens with this tile in the QBR.

Renewal risk

Accounts in red health, 90 days to renewal.

List of accounts entering the renewal window with declining health scores. The CSM save-motion queue. Each row carries the Strkr AI-drafted save play, the historical signals that pushed the account red, and a one-tap Flow to open an exec sponsor letter.

Expansion signal

Accounts with product-usage patterns that correlate with upgrade.

Strkr AI watches usage patterns across the customer base. Accounts hitting the signals that correlate with a tier upgrade (feature adoption, user growth, API usage) surface as expansion plays. The CSM gets a drafted expansion conversation starter.

Support ticket volume

Open tickets per account, aged.

Count of open support tickets per account, sorted by age. Rising ticket count usually precedes falling health. The dashboard catches the pattern early so a proactive outreach happens before the account escalates.

NPS trend

Last four quarters, rolling.

Line chart of NPS by cohort, by segment. The trend separates the "we promoted a feature everyone hated" story from the "entire customer base is drifting" story. Both require intervention, but very different interventions.

CSM activity

Executive touches per account per quarter.

Count of exec-sponsor and quarterly business review activities per account. Accounts without a QBR in the current quarter get flagged. The CSM scheduling conversation has data.

Executive dashboard example

The one view a CEO actually opens.

The dashboard the CEO opens before the board meeting. The job: understand the business in six minutes with no filtering, no drill-down, no questions. Seven tiles with comparisons, no trend lines longer than four quarters, no acronyms. Each tile answers one board-level question.

ARR

Annual recurring revenue, with net new.

Current ARR, net new ARR this quarter, variance to plan. Three numbers, one tile. The board reads it in 10 seconds.

Burn and runway

Cash out the door, months of runway.

Trailing-three-month burn, cash on hand, implied runway. Dialed in from the Stripe-plus-AP feed so the number is live, not a pulled report.

Pipeline coverage

Weighted pipeline to quarter quota.

Open weighted pipeline divided by remaining quarterly quota. Compared to the ratio at the same point last quarter. The leading indicator of whether the quarter will close in plan.

Net retention

NRR last trailing twelve months.

The single number investors ask about more than any other B2B metric. Trending by cohort, compared to the quarterly plan.

Sales efficiency

New ARR per sales-and-marketing dollar.

The LTV-to-CAC approximation at the quarterly level. The board uses it to judge whether the GTM machine is working or needs reinvestment.

Hiring plan status

Open requisitions, time to fill.

Open requisitions by function, median days to fill. The signal that the plan is executable or that recruitment is a bottleneck. One tile; the CEO already knows which function is lagging.

Top three risks

Qualitative, curated weekly.

A short list of three things the leadership team wants the board to see this quarter: a specific competitive loss trend, a legal matter, a customer-concentration shift. The one qualitative tile the executive dashboard needs; without it, the dashboard reads as spin.

How to adopt these examples

Six habits of teams whose dashboards survive.

Cloning a template is the easy part. Making the dashboard the thing the team actually opens every morning is the hard part. The customers whose dashboards became load-bearing (meaning the standup moves if the dashboard breaks) share six specific habits.

They put the dashboard on a wall

Visibility reinforces the behavior.

The teams whose dashboards stick put the view on an office wall display or a shared second monitor. The ambient visibility makes the data real. A 40-rep logistics team we work with cut their lead-response SLA breach rate 60 percent inside a quarter after mounting the ops dashboard in the SDR room.

They name tiles like statements

The tile title tells the viewer what to notice.

Not "Pipeline" but "Pipeline Coverage, Below 3x Needs Attention." The title is the headline, the number is the proof. Dashboards whose tiles read as statements get adopted; dashboards whose tiles read as nouns get glanced at.

They retire what nobody uses

A quarterly audit cuts 20 percent.

The dashboards that stay useful are the ones that get pruned. Every quarter the RevOps lead reviews view-count logs and retires the tiles nobody clicked. Dashboards grow by addition and die by addition; the audit cycle breaks the pattern.

They tie action to tile

Every tile has a next step.

The dashboard shows the number and the button to act on it. Stale deal list links to a one-tap nudge Flow. Breached SLA links to the specific run. The dashboard becomes the dispatch surface rather than a view-only trophy case.

They review in the standup

The dashboard runs the meeting.

The daily or weekly team standup opens with the dashboard on screen and the three red tiles get discussed in order. The meeting is 10 minutes faster, the dashboard stays trustworthy, and the discussion stays operational rather than philosophical.

They tell the story in notes

A short written interpretation on the dashboard.

The best teams add a short written note to the dashboard each week: "coverage below 3x because enterprise deal slipped, intervention planned Thursday." The note becomes institutional memory. A VP RevOps who left a 60-rep cybersecurity vendor said the dashboard notes were the single most useful handoff artifact for her successor.

Dashboards ship on Pro, including every example above.

Clone the templates, filter to your team, publish to a wall display this afternoon. Every tile is wired to live data, every drill links to the records behind the number.

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Common questions

What buyers ask about this feature.

What makes a good dashboard example worth adopting?

A good dashboard example answers a specific question for a specific role, carries comparisons so numbers mean something, drills down rather than cluttering the surface, puts an action next to each signal, filters by role so the right person sees the right slice, and reads off live data rather than overnight ETL. The examples on this page meet all six criteria and ship as clonable templates inside Strkr: sales pipeline health, marketing-sourced ROI, operations and admin SLA, CS and retention, executive summary. Each template includes the specific tiles, filters, and drill links described in the sections above.

Are company dashboard examples different from sales dashboard examples?

Yes. A company dashboard is executive-level, synthesizing the operating state across functions: ARR, burn, pipeline coverage, net retention, hiring, risks. A sales dashboard is operational, focused on pipeline health, rep activity, deal risk, and win-rate trend. Marketing dashboards focus on sourced pipeline and campaign ROI. CS dashboards focus on health and renewal risk. The patterns differ because the decisions differ. The executive dashboard template on this page captures the company view; the sales, marketing, CS, and ops templates each capture a function-specific view with the drill-downs the operating team needs.

Do these dashboard examples work without an external BI tool?

Yes. Every example above ships natively inside Strkr, reading off the live transactional store with no external BI vendor, no overnight ETL, and no separate permissioning. For teams that want to extend into a dedicated BI tool (Looker, Mode, Tableau), Strkr exposes read-only database access and a public API so the external tool can pull from the same source. The native dashboards cover 90-plus percent of the mid-market operating dashboard need; the external BI tier is reserved for the specialized analyst audience.

How often should dashboards get refreshed or redesigned?

The data refresh is live: every tile reads from the transactional store on open, so a deal moved five minutes ago shows up immediately. The design refresh follows a quarterly cadence in the teams whose dashboards stay useful. Each quarter the RevOps lead or dashboard owner reviews view-count telemetry, retires tiles nobody opened, adds the tiles leadership started asking about verbally, and renames tiles whose titles no longer describe the current measure. The quarterly rhythm matches the business cadence and prevents dashboard sprawl.

Can we role-filter one dashboard template for multiple audiences?

Yes. Role filtering happens at render inside Strkr. The sales dashboard template viewed by an individual AE shows her pipeline, by a manager shows the team roll-up, by the VP shows the segment, by the CRO shows the company. The underlying template is one artifact; the filters apply from the viewer's role and territory. The pattern avoids the trap of maintaining 15 drifted duplicates of the same dashboard across the org.

Who should own a dashboard inside the organization?

Every dashboard that survives has a named owner, which is the pattern we see across our highest-adoption customers. The owner reviews the dashboard weekly, writes the interpretation note, retires stale tiles, and responds when a tile breaks. For sales dashboards the owner is usually the VP Sales or sales operations lead; for marketing, marketing operations; for CS, the VP Customer Success; for the executive dashboard, the chief of staff. Dashboards without an owner drift within two quarters; dashboards with a named owner tend to stay load-bearing for years.

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