Feature · Dashboard Creation

Dashboard creation that goes from blank canvas to shared view in an afternoon.

Creating a dashboard should not require a sprint. In Strkr the creation flow is a drag-and-drop canvas tied to live CRM records, with role templates, saved views, drill-through, and scheduled distribution ready on day one. The seat price covers the capability on every tier, no viewer meter and no separate reporting SKU.

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The creation flow, step by step

What dashboard creation looks like when the data lives in the CRM.

The old pattern was to brief a BI analyst, wait a sprint, iterate on screenshots, and finally ship a dashboard that was already stale by review. Strkr collapses the flow into a single canvas on top of the record of truth. The cards below walk the steps a sales ops lead moves through on their first dashboard build.

Start from a template

The role picker is the first choice.

The creation flow opens on a template picker keyed to role: AE, SDR, manager, VP, CRO, RevOps. Each template is a working dashboard with the common tiles for that role already configured. A new build starts from a template 80 percent of the time; the blank canvas is there for the long tail.

Blank canvas

Grid, drag palette, preview.

The blank canvas is a 12-column responsive grid with a tile palette on the left and a live preview on the right. Dragging a tile into the grid snaps it to a column span. Resizing is a corner drag. The creation surface feels like a design tool, not a form.

Pick a data source

The source picker lists CRM objects.

Every tile asks for a data source. The source picker lists the CRM objects (deals, contacts, accounts, activities, leads, products, orders) and any custom objects the tenant has configured. Picking a source scopes the field list to that object. No SQL, no LookML, no dbt model.

Choose a measure

Count, sum, average, median, percent.

Measures are a dropdown: count of records, sum of a numeric field, average, median, percentile, percent of a group. The measure updates the preview in real time. A sales ops lead who used to write a SQL window function finishes the same thing in three dropdowns.

Add filters

Scope the tile to the question.

Filters apply at the tile level: open deals only, this quarter, Enterprise segment, won in the last 30 days. Filters compose as AND or OR groups. The preview reflects the filter immediately. The dashboard builder sees the real number before publishing.

Set role scope

The same tile, scoped per viewer.

Role scope is a toggle on the tile: scope to viewer (rep sees own, manager sees team), scope to team, or no scope (floor-wide). The scope is a permission check at render, not a copy-paste per role. One tile serves three audiences.

Preview and iterate

The preview is the final render.

The preview panel renders exactly what the published dashboard will render. No separate "preview mode" with different data. The builder iterates against the real tile and sees the real number, not a sketch. The feedback loop is seconds, not days.

Save and share

A URL and a permission list.

Saving a dashboard generates a URL. Sharing is a permission list: individuals, roles, teams. The dashboard inherits the tenant permission model, so shared views respect record-level and field-level masking automatically. The creation flow ends with a copyable link.

Clone and remix

Fork an existing dashboard.

Any dashboard can be forked. The clone opens as a new draft with the same tiles, filters, and scope. The builder tweaks the clone for a different team or segment without touching the original. Fork lineage is preserved so updates can propagate when the parent changes.

The tile types that cover the common sales questions

Fifteen tile shapes that answer most dashboard questions out of the box.

A dashboard is a composition of tiles. The right tile types turn a creation flow into a quick build instead of a design exercise. Strkr ships fifteen tile shapes that cover the questions a revenue leader asks on a Monday morning. The cards below walk the most-used ones.

Big number

One metric, big and legible.

The big-number tile shows a single measure (pipeline coverage, forecast attainment, lead response time) in a large readable size with the week-over-week delta on a chip. It is the headline tile for the top of a dashboard. One glance tells the viewer the state.

Trend line

A metric over time.

The trend-line tile plots a measure across a time axis: pipeline by week, forecast by month, activity by day. Hovering a point shows the exact value and the records behind it. The slope answers the "which direction" question.

Bar chart

A measure sliced by a dimension.

The bar-chart tile slices a measure by a dimension: pipeline by stage, deals by owner, activity by rep. Sorting is a dropdown. The viewer sees who is ahead and who is behind in one glance. Bars drill through to the deal list.

Pie or donut

Share of a total.

The pie or donut tile shows share of a total: deal mix by product line, lead source distribution, pipeline by segment. Reserved for the handful of cases where share of a total is the right question. Overused pie charts clutter dashboards; the picker nudges toward bars when the slice count is high.

Table tile

The record list, right there.

The table tile embeds a filtered record list directly: top 10 deals at risk, SDR touches by day, accounts in the renewal window. Columns are configurable per tile. The table respects permissions so viewers see their own scope.

Funnel tile

Stage conversion, step by step.

The funnel tile shows the pipeline funnel with conversion rates between stages: lead to opportunity to proposal to close. Each step shows the drop-off percentage. The funnel is role-aware so a rep sees their own funnel and a manager sees the team funnel.

Heatmap

Density across two dimensions.

The heatmap tile plots density across two dimensions: activity by rep by day of week, pipeline by stage by segment. Hot cells are high-value spots. The viewer finds the gaps and the hotspots without reading a table.

Progress bar

Toward a goal.

The progress-bar tile shows a measure as progress toward a target: quota attainment, pipeline coverage against goal, forecast attainment against the committed number. The target is editable per tile. One glance tells the viewer if they are on track.

Leaderboard

The rank list, bright and simple.

The leaderboard tile ranks a dimension by a measure: reps by closed revenue, SDRs by meetings booked, teams by quota attainment. Ties break on a secondary measure. The tile doubles as a motivation surface in the pit without requiring a separate SPIFF tool.

Why the creation flow stays fast at scale

How dashboards remain workable when the tenant has hundreds of them.

The honest problem with dashboard tools is not the first dashboard; it is the hundredth. Teams end up with a library of stale, forked, half-maintained dashboards and no way to navigate them. Strkr builds library hygiene into the creation surface itself. The cards below walk the mechanisms.

Folders and tags

The library is organized.

Dashboards live in folders with tags for team, product line, segment, and audience. Browsing the library is a filtered tree view. New dashboards inherit the folder context of the user who created them, so the organization emerges naturally rather than being enforced after the fact.

Ownership

Every dashboard has a steward.

Every dashboard carries an owner field. When the owner leaves the organization, the dashboard flags for re-assignment rather than silently going stale. Managers see ownership distribution in the admin surface and reassign in bulk.

Freshness indicator

Last viewed, last edited.

Each dashboard shows last-viewed and last-edited timestamps in the library view. Dashboards that have not been opened in 90 days flag as candidates for archival. The library stays curated without someone having to run a quarterly cleanup pass.

Template promotion

A good dashboard becomes a template.

Any dashboard can be promoted to a template with one click. The template becomes available in the role picker for future builds. Good dashboards propagate across the organization instead of being rebuilt by every new sales ops lead.

Version history

Every change is recoverable.

Dashboards keep version history. A change that broke a tile is a one-click rollback. A manager who tweaked the dashboard before a QBR can review the diff and restore the previous version if the new render reads less cleanly.

Shared parameters

One filter, many tiles.

A dashboard-level parameter (date range, segment, region) propagates to every tile that opts in. Switching the parameter rerenders the whole dashboard. The viewer changes last-quarter to this-quarter at the top and the entire operating picture shifts.

Embedded tiles

A dashboard tile on a record page.

Dashboard tiles can be embedded on individual record pages. The deal detail page shows a tile scoped to the deal. The account detail page shows a tile scoped to the account. The creation flow outputs reusable tiles, not just full-page dashboards.

API access

A dashboard is also an endpoint.

Every published dashboard exposes a JSON endpoint that returns the tile data. Teams that want to render the data in an internal portal or on a wall display pull from the API with an authenticated token. The dashboard capability extends past the Strkr UI through an open API.

Audit trail

Who edited what, when.

Every edit on a dashboard writes to the audit log with the actor, the field, the before-value, and the after-value. A tile that silently changes meaning raises questions; the audit trail resolves them in seconds. Compliance posture improves without extra effort.

How Strkr compares to the typical dashboard-creation tools

the tradeoff against BI tools and spreadsheet dashboards.

Teams evaluating dashboard-creation tools usually look at Tableau, Looker, Power BI, Google Sheets, and the CRM-native option. The right answer depends on the use case. The cards below cover the tradeoff.

Tableau or Power BI

Analytical, warehouse-based, batched.

Tableau and Power BI are strong exploratory analytics tools when the organization has a warehouse and an analytics team. For operational sales dashboards tied to the record of truth, the warehouse-replication lag and the per-viewer licensing are usually a mismatch. Creation requires LookML or workbook authoring skills.

Looker

Powerful BI, analyst-heavy.

Looker is powerful when the team maintains the LookML models. Creation of a new dashboard assumes the models already exist. For a sales ops lead building a new tile at 9 AM for a 10 AM meeting, the stack is heavier than the question.

Google Sheets

The spreadsheet dashboard.

A lot of teams run their operational dashboard in Google Sheets with manual data pulls. Creation is fast and familiar, but the data is static and the sheet drifts from the CRM record the moment the next export runs. The cost is accuracy, not setup.

Strkr

Live, role-shaped, no-code.

Strkr builds dashboard creation inside the CRM. Drag-and-drop tiles, role templates, live data, drill-through, scheduled reports, and permission inheritance come out of the box. The sales ops lead builds the dashboard in an afternoon, not a sprint. The ongoing maintenance is one tenant admin, not a BI team.

When BI is still right

Cross-source analytics belong in a warehouse.

For analytics that cross CRM, finance, product, and marketing data at warehouse scale, Looker or Tableau on top of a dbt-modeled warehouse is still the right answer. Strkr integrates with both. The operational dashboard lives in Strkr; the analytical dashboard lives in the BI tool.

The decision test

Does a rep open this dashboard every day?

If the answer is yes, the dashboard belongs in the CRM and the creation flow should be minutes. If the dashboard is a quarterly deep-dive that joins finance and product data, the warehouse-plus-BI stack earns its keep. The two use cases should not collapse into one tool.

Dashboard creation that starts with a template, ends with a shared URL, and never asks for a BI team.

Open a free trial, clone an AE or RevOps dashboard, add the tiles your team opens every morning, and share the link with the floor. Pre-built templates for pipeline, forecast, activity, lead response, quota, deal risk, account health, and renewal are included on every paid tier.

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Common questions

What buyers ask about this feature.

How long does dashboard creation take in Strkr?

The common build starts from a role template and takes under an hour. A sales ops lead picks the AE or RevOps template, swaps one or two tiles for team-specific measures, applies role scope so the dashboard renders per viewer, and shares the URL with the floor. A full custom build from a blank canvas, with ten or more tiles, typically takes an afternoon. The creation flow stays fast because the data is already in the CRM; there is no warehouse replication, no LookML model, and no cross-system join to wait for.

Do I need a BI analyst or an engineer to create a dashboard?

No. Dashboard creation is a drag-and-drop canvas with a tile palette, a data-source picker, a measure dropdown, and a filter panel. The configuration surface is designed for sales ops and revenue leaders, not analysts. No SQL, no LookML, no dbt model, no workbook authoring. Teams with an analytics function still run exploratory analysis in a warehouse-plus-BI stack; Strkr integrates with Looker and Tableau for those use cases. The operational dashboards live inside Strkr and get built by the ops team directly.

Can two dashboards share filters without copy-pasting?

Yes. Dashboards expose shared parameters (date range, segment, region, product line, owner) that each tile can opt into. Switching the parameter at the top rerenders every opted-in tile. Changing the dashboard from last-quarter to this-quarter updates the pipeline, forecast, activity, and deal risk tiles together. Parameters remove the need to maintain multiple copies of the same dashboard for different time windows or segments. The parameter definitions live on the dashboard, so forks of the dashboard inherit them automatically.

What happens when the dashboard author leaves the team?

Every dashboard carries an owner field. When the owner is deactivated, the dashboard flags for reassignment in the admin surface. A manager picks a new owner (or the system assigns the next sales ops lead by default). The dashboard keeps working through the ownership change; the flag is a prompt to assign a steward, not a block on viewers. Version history and audit coverage mean the new owner can see what the previous owner changed and when, so continuity is preserved.

How is dashboard creation priced?

Dashboard creation is included on every paid Strkr tier. The seat price covers the capability. There is no separate reporting SKU, no per-dashboard charge, and no viewer-based pricing. Pre-built role templates ship on day one. Custom dashboards, saved views, scheduled reports, and anomaly alerts are included on Pro and above. Strkr AI commentary on tile movement, mobile push alerts, and multi-dashboard screens are included on Scale and Enterprise. The listed seat price is the full price for the capability.

Is the dashboard data secure under the Strkr compliance posture?

Yes. Dashboard rendering inherits the tenant permission model, so record-level and field-level masking apply automatically. Scheduled reports respect the recipient scope. Audit coverage captures every dashboard load, edit, and share. Strkr is HIPAA compliant with a BAA available for healthcare tenants and GDPR plus CCPA compliant for European and California data subjects. The SOC 2 Type II report is in progress through 2026-Q4 and tenants can request the readiness letter from the account team until the final report is issued.

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