Feature · Create Dashboard

Create a dashboard without opening a BI tool.

Pick a layout, drag chart tiles onto a canvas, pick dimensions and measures from the field picker, drop a filter, save a view. The dashboard renders against the live records on every open. No ETL, no BI engineer, no two-week ticket.

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What creating a dashboard should actually involve

Seven steps that cover the standard dashboard build.

Creating a dashboard should be a 10-minute job for a non-technical ops lead, not a two-week ticket to a BI engineer. The seven steps below are what shipping a new dashboard looks like inside Strkr. Each step takes under a minute at the median, which is why the whole motion lands in 10 minutes for the standard dashboard shape and in an afternoon for an advanced custom build. No training videos, no certification path, no admin salary required.

Step 1

Clone a template or start blank.

The dashboard library ships pre-built templates for exec, sales manager, rep home, marketing, customer success, finance, and operations roles. Clone the closest template or start from blank. Cloning gets a working dashboard in under a minute. Starting blank gives a grid canvas with the chart tile sidebar open.

Step 2

Drag chart tiles onto the canvas.

The chart tile sidebar lists 15 chart types: bar, column, stacked bar, line, area, pie, donut, funnel, sankey, cohort, scatter, bubble, map, big-number tile, table. Drag tiles onto the grid canvas in the layout you want. Resize by dragging edges. The grid snaps to a responsive layout that renders cleanly on desktop and tablet.

Step 3

Pick dimensions and measures.

Click a chart tile to open its configuration panel. The field picker exposes every field on every record (standard and custom) with the same grammar reps use in advanced search. Pick dimensions (how to break the data) and measures (what to aggregate). The chart renders on save with sample data from the live records.

Step 4

Drop a filter.

Filter the chart to a segment, product, date range, pipeline, or any custom field. Filters use the same ALL-of and ANY-of grammar as workflow conditions and dashboard filters, so the mental model stays consistent. Dashboard-level filters apply to every chart on the dashboard, and chart-level filters narrow the chart further.

Step 5

Add a period comparison.

Toggle period comparison on any chart to render this quarter versus last quarter versus year-ago with absolute delta and percent delta inline. The comparison respects whatever fiscal calendar the tenant configured. Managers tracking a trend read three bars instead of three screenshots in a slide deck.

Step 6

Save as a view, publish to the team.

Save the dashboard as a personal view or publish to the team library with permission scoping. Published dashboards respect the record access model inline so the dashboard built once on the exec seat renders differently on a rep seat. The permission scoping takes seconds and prevents accidental cross-team visibility.

Step 7

Schedule a send.

Schedule the dashboard to send daily, weekly, or monthly to a user, team, Slack channel, or email list. The render fires at send time against the live records so the number in the Monday email matches the number on the dashboard a minute later. Scheduled sends include the audit trail for compliance teams.

How Strkr dashboards work under the hood

Live-record, drill-through, permission-scoped.

The surface above is what creating a dashboard looks like. The surface below is what the dashboard does once published. Every tile reads from the live record on every open. Every scheduled send renders at send time. Every drill-through lands on the records behind the number. The dashboard and the records share one database, so the KPI tile and the CRM view match without a sync in between.

Live rendering

Every open reads from the record.

The dashboard renders against the live record on every open. A deal that moves at 10 AM shows on the 10:01 AM dashboard view. The Monday forecast call runs on data reflecting weekend activity, not a Friday snapshot or a Monday-morning extract. Live rendering is why native dashboards earn their keep over spreadsheet-based reports.

Drill-through

Click any number, land on the records.

Every chart element (bar, segment, cell, bucket, line point, big-number tile) is clickable. The click opens a side panel with the filtered record list behind the number, using the same columns the rep sees in the pipeline view. Drill-through respects viewer permissions so a rep clicking a team-wide number sees only their own records.

Permission scoping

A property of the viewer, not the chart.

A dashboard built once on the exec seat renders differently on a rep seat because the permission filter is a property of the viewer, not the chart definition. The ops lead stops maintaining three separate dashboards for exec, manager, and rep views because the one dashboard scopes to whoever opens it.

Chart configuration

Every chart tile saves its own config.

Each chart tile has its own dimensions, measures, filters, chart type, period comparison, and target lines. The configuration saves with the dashboard so the layout persists exactly as the ops lead left it. The ops lead who tweaks a chart does not touch the rest of the dashboard, which keeps change management clean.

Dashboard library

Share, clone, publish, promote.

Published dashboards land in the team library where other users can clone them. Cloning preserves the layout and configuration so a new ops lead inherits the current dashboards instead of starting from scratch. Promotion moves a dashboard from a personal view to the team library with permission scoping applied in the same step.

Export

CSV, Excel with live links, PDF, PNG.

Every dashboard exports to CSV (raw rows per chart), Excel (formatted with live links), PDF (boardroom-ready), or PNG image (deck-ready). Exports preserve the filter set and timestamp so the finance team can trace a QBR number back to the records behind it in two clicks instead of a half-day rebuild.

Audit log

Every render, every drill, every send.

Every dashboard render, every chart drill-through, every schedule send, and every export writes an audit record with the viewer, timestamp, filter set, and records returned. The audit log satisfies SOC 2 Type II (in progress 2026-Q4) and HIPAA access-tracking requirements for teams on the BAA. Compliance queries resolve in two clicks.

External shares

Read-only links for investors and partners.

External share creates a read-only link that renders the dashboard against a snapshot or against the live records depending on share type. For investor updates or customer-facing exec summaries, snapshot shares freeze the numbers at send time. For partner co-selling, live shares respect a scoped permission filter so the external viewer only sees agreed segments.

Three dashboards a new user creates

What the first day of dashboard building looks like.

The dashboards below are the ones most Strkr customers create on day one of go-live. Each one takes 10 to 20 minutes to build from a template or 30 to 60 minutes to build from blank. The pattern repeats across customers because the three dashboards cover the standard operating rhythm of a growing sales org: an exec view for the Monday staff meeting, a rep view for the daily motion, and a manager view for the one-on-one. Build these three, schedule the sends, and the manual-report ritual goes away.

Exec dashboard

Six KPIs across the top row.

Pipeline coverage, forecast commit, closed-won week over week, new logos, net revenue retention, average deal size. Six big-number tiles across the top row with trend sparklines. A trend chart row below shows the trailing 12 weeks for each KPI. Scheduled send fires Monday 6 AM. Build time: 15 minutes from the exec template.

Rep home

What to do first today.

Next-best-action ranked task list, hot replies today, meetings today, stalled deals, week-to-date pipeline created, meetings held, calls made. Rep home opens on login so the AE knows where the first hour of the day goes without reading three separate views. Build time: 20 minutes from the rep template.

Manager one-on-one

Team cut, pre-prepped for coaching.

Rep performance side by side with pipeline, activity, win-rate, nudged-deal list, risk flag list. Manager opens the one-on-one dashboard filtered to the AE before the call. The coaching conversation starts with data on the table instead of a Google Sheet pulled up on the second monitor. Build time: 25 minutes from the manager template.

Marketing dashboard

Campaign-to-revenue in one view.

Campaign attribution, marketing-sourced pipeline, marketing-influenced pipeline, lead-to-opportunity conversion, nurture engagement. Marketing dashboard answers "how much pipeline did Q3 campaigns contribute" in one query because the campaigns and the deals share one database. Build time: 20 minutes from the marketing template.

CS dashboard

Health, risk, expansion signal.

Account health distribution, renewal risk watchlist, expansion-ready accounts, support ticket volume by segment, NPS trend. CS director runs the weekly team meeting from the dashboard instead of pulling four separate reports from four separate tools. Build time: 20 minutes from the CS template.

Finance dashboard

Pipeline-to-cash on one timeline.

Pipeline value, forecast commit, closed-won revenue, invoiced amount, collected amount, DSO. Finance dashboard shows the funnel from pipeline to cash on one timeline so the controller spots collections risk weeks before the aging report lands. Build time: 25 minutes from the finance template.

Advanced moves

Where a 10-minute dashboard becomes a hundred.

The surface above covers the standard dashboard build. The surface below covers the advanced moves that elevate a basic dashboard into something a VP of Revenue reads daily. Each advanced move takes 5 to 15 minutes once the ops lead learns the mechanic. The pattern repeats across customers because the mature teams run on dashboards with these advanced controls layered in, not on dashboards built in the first week and left static.

Segment breakouts

Any dimension on any chart.

Break pipeline health, revenue, or activity by segment, product, source, SDR, AE, manager, region, or custom field. Breakouts are additive, so the exec dashboard slices by segment by AE by product on the same screen without three separate boards. Advanced breakouts land after the first week once the ops lead reads the pattern.

Target lines

Threshold ranges color-code the tile.

Every KPI tile supports target lines and threshold ranges. Pipeline coverage with a 3x target renders a reference line on the sparkline. Forecast commit against quota renders progress bar. Threshold ranges color-code the tile (green at target, yellow near target, red below target) so the exec reads status at a glance.

Cohort analysis

Retention by month cohort.

Cohort chart groups customers by onboarding month or first-close month and renders retention or expansion over time. The CS director reads cohort retention to spot onboarding pattern changes. The exec reads cohort expansion to track motion maturity.

Sankey view

Deal flow and stage leakage.

Sankey chart renders deals moving between stages with volume, value, and conversion rate on each edge. Leakage points show up as thick lines going backwards or to Closed Lost. The exec board uses the sankey to find the stage that costs the quarter and the rep board uses it to pattern-match stalled deals.

Custom field tiles

Any custom field, any aggregation.

Custom fields get the same tile treatment as standard fields. A tenant tracking a custom "deal champion level" field aggregates it on the dashboard with the same mechanic as amount or close date. Custom objects get the same picker surface. The ops lead extends the dashboard to the business model without a schema change on the dashboard tool.

Nested filters

Dashboard-level and chart-level filters.

Dashboard-level filters apply to every chart. Chart-level filters narrow the chart further. The combination lets a dashboard show segment-filtered pipeline across every chart while one specific chart drills into a sub-segment. Nested filters are the advanced move that turns a 10-minute dashboard into a layered analytical surface.

Create a dashboard on every paid tier. Drag-and-drop, live records, scheduled sends.

The dashboard builder, 15 chart types, every field on every record, scheduled sends, drill-through, and permission scoping ship on every paid tier. External shares, snapshot renders, and advanced cohort analysis land on Pro. Audit log ships across all paid tiers so compliance queries resolve in two clicks.

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Common questions

What buyers ask about this feature.

How long does it take to create a dashboard in Strkr?

A standard dashboard built from a template takes 10 to 15 minutes. The template library ships pre-built dashboards for exec, sales manager, rep home, marketing, customer success, finance, and operations roles. Clone the closest template, swap in the fields that match the business model, drop a filter, schedule a send. A dashboard built from blank takes 30 to 60 minutes depending on complexity. Advanced custom dashboards with nested filters, cohort analysis, and sankey views take an afternoon. The practical pattern is to start from the closest template, publish fast, iterate as the exec feedback lands.

What chart types does Strkr support?

The chart library ships 15 chart types: bar, column, stacked bar, line, area, pie, donut, funnel, sankey, cohort, scatter, bubble, map, big-number tile, and table. Each type picks the right dimension and measure defaults based on the field types selected. The chart-type picker lets the ops lead switch types with one click so trying different renderings is a trivial operation. For teams needing specialized visualizations beyond the 15 types (violin plots, radar charts, geo heatmaps with custom shapefiles), the export to CSV covers hand-off to a BI tool for the advanced cases.

Can I use any field on any record in a dashboard?

Yes. The field picker exposes every field on every record (standard and custom) with the same grammar reps use in advanced search. Custom fields get the same picker surface as standard fields. Custom objects get the same picker surface as standard objects. The ops lead who tracks a tenant-specific "deal champion level" or a "security review completion date" field aggregates them on the dashboard with the same mechanic as amount or close date. The dashboard builder watches the schema automatically because the dashboard and the schema live in the same system.

Who can create dashboards?

Dashboard creation is permission-scoped. By default any user with dashboard-edit permission can create personal views that only they see. Publishing to the team library requires dashboard-publish permission, which admins typically grant to RevOps leads, team managers, and the exec staff. The permission model prevents accidental publishing of experimental dashboards to the whole team and keeps the team library clean. For teams running a strict governance model, admins can scope publish permission by workspace or by role.

Can dashboards update automatically or do I need to refresh?

Dashboards render against the live record on every open, so there is no manual refresh. A deal that moves at 10 AM shows on the 10:01 AM dashboard view. For scheduled sends, the render fires at send time so the number in the Monday email matches the number on the dashboard a minute later. For always-on displays (TV dashboards in an office, big-screen team views), the dashboard auto-refreshes on a configurable interval. The practical result is that the dashboard view always matches the record view without a sync, extract, or manual refresh.

How is this different from building a dashboard in Tableau or Looker?

Tableau and Looker are general-purpose BI tools that read from any data source via an extract or a direct query. Strkr dashboards live inside the CRM and read from the record directly. The practical difference is that a BI dashboard requires an engineer or analyst to configure (define the data model, write the SQL, build the chart), while a Strkr dashboard configures by drag-and-drop in 10 minutes. For teams whose dashboards only need CRM data, Strkr covers the job without the BI subscription or the data engineer. For teams whose dashboards need warehouse data from product-usage, finance, and marketing joined with CRM data, run both: Strkr for the sales reporting layer, BI for the warehouse-sourced dashboards.

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