Feature · Dynamic Dashboard

A dynamic dashboard that reshapes to the viewer, not the admin's template.

A dashboard that renders one layout to every user is a static page with charts on it. A dynamic dashboard reshapes to the viewer: the sales lead sees pipeline and forecast, the rep sees their open deals and today's activity, the CFO sees committed revenue and discount flow, and each view honors record permissions on the aggregation. Strkr builds the dashboard with role-keyed layouts, per-user filter overlays, live record reads, and the admin keeping the base template so the system does not devolve into a sprawl of hand-built dashboards.

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What dynamic means in practice

Seven axes of flex the dashboard supports.

A dashboard that is dynamic along one axis (viewer role) is less flexible than it looks. The seven axes below cover how real teams actually need the dashboard to reshape without devolving into a sprawl.

Role axis

Rep, lead, VP each see different panels.

The dashboard template is role-keyed. The rep opens the home and sees their open deals, today's activity, and this week's forecast. The sales lead sees the team pipeline, the stuck stages, and the forecast rollup. The VP sees the division. One template definition serves every role because the layout maps to the role field.

User overlay

Individual pins override the role template.

An individual user can pin their own panels on top of the role template. A rep who cares about activity volume more than the role template emphasizes pins the activity panel to the top. The overlay saves on the user record so it survives sessions. The admin still maintains the base template.

Time axis

Rolling, period, or custom range.

Each panel carries a time axis the viewer can flex: rolling (last 7 days, last 30 days), period (this quarter, this year), or custom range. The viewer's choice persists on the panel. The common failure where a dashboard anchors to one time range and the quarterly review runs on last quarter's data gets avoided.

Filter axis

Segment, product, source overlays.

Each panel accepts filter overlays: segment, product, source, geography. The viewer applies the filter to the whole dashboard rather than panel by panel. The sales lead filters to a product line and the entire dashboard reshapes to that slice.

Permission axis

Aggregation honors record scope.

The aggregation honors the viewer's record permission scope. A sales rep aggregating pipeline sees only their own rows contribute. A sales lead sees the team rows. The common failure where a dynamic dashboard reveals aggregated totals that let the viewer back out individual rows does not happen because the row filter runs first.

Mobile axis

Layout reflows on narrow screens.

The dashboard reflows for narrow screens. The desktop two-column layout stacks into one column at mobile width. Charts resize. The viewer on a phone during a commute reads the same numbers as the viewer on a desktop. The common failure where a dashboard breaks at mobile and the mobile user falls back to screenshots gets avoided.

Theme axis

Dark mode without manual palette work.

The dashboard honors the viewer's theme preference (light or dark). Palette tokens drive both. The common failure where a dashboard looks fine in light mode and breaks in dark (because colors were hardcoded) gets avoided when the palette is tokenized.

What keeps the dashboard honest

Six guardrails against dashboard sprawl.

Dynamic dashboards sprawl when every user builds their own and the admin loses the single source of truth. Six guardrails below keep the dynamism from devolving into chaos.

Admin base template

Role template is authoritative.

The admin maintains the role base template. Individual user overlays sit on top but cannot delete the base panels. The common failure where every user builds their own dashboard and the sales lead loses visibility into what the team sees gets avoided when the base template is admin-owned.

Panel library

Admin-curated set of composable panels.

The panel library is admin-curated. Users compose their overlays from the library rather than inventing panel definitions. The library carries the vetted definitions (pipeline funnel, activity volume, forecast rollup, win rate, revenue, custom KPI). The common failure where a user builds a panel on a bad metric definition gets avoided.

Definition versioning

Panel definition changes track history.

Every panel definition carries versioning. When the admin edits the pipeline funnel definition (changes a stage filter, adjusts an aggregation), the version increments. A later audit of which definition drove which displayed number reads the version in effect. The common failure where a dashboard number silently changes meaning gets avoided.

Shared cache

Aggregation cached per permission scope.

Panel aggregations cache per panel definition and viewer permission scope. Panels load fast on repeat view without serving stale data across the TTL. The cache invalidates on typed-record writes. The common failure where a dynamic dashboard renders slow because every panel re-aggregates on every view gets avoided.

Change audit

Admin edits lands on the audit log.

Every admin edit to the base template or the panel library lands on the audit log. A compliance query identifying when the forecast panel definition last changed is a filter on the audit page. The audit chain survives admin turnover so the team can trace definition drift over years.

Open API

External tools pull panel series.

Every panel exposes its aggregated series on the open API with the viewer's permission scope applied. External tools (BI consolidation, finance warehouse) pull the series rather than recomputing from raw rows. The common failure where a parallel BI tool disagrees with the dashboard because the two aggregations drifted gets avoided.

The engineering underneath

What makes the dynamism hold at scale.

Dynamic dashboards work on 1,000 rows and break on 100,000. One that renders fast on 100,000 rows, honors permissions, and reshapes per viewer survives the operational meeting. Strkr ships the primitives.

Server aggregation

Group-by runs on indexed queries.

Panel aggregations run on the API with indexed queries rather than pulling raw rows to the browser and grouping client-side. The browser receives the aggregated series. The common failure where a dashboard on 100,000 rows freezes the browser gets avoided because the aggregation is server-side.

Permission pre-filter

Row filter before aggregation.

The permission scope applies as a row filter before aggregation. A viewer aggregating pipeline sees only rows they can access contribute to the chart. The common failure where a dashboard reveals aggregated information that leaks individual rows gets avoided when the filter runs first.

Role lookup

Layout picks on viewer role at render.

The layout picks on the viewer role at render time. A role change propagates to the next page load. The common failure where a role change leaves the user on the old dashboard until a cache clears gets avoided because the lookup is at render time.

Overlay merge

User pins merge over role base.

The render merges the user overlay on top of the role base template. A user pin that duplicates a base panel resolves to the user pin. A user pin that moves a base panel updates the position. The merge is deterministic so two viewers with the same role see the same base.

Cache invalidation

Writes invalidate the relevant scope.

A typed-record write invalidates the cache entries for the panels that depend on that record. The next viewer sees the fresh aggregation. The common failure where a dashboard lags the live record because the cache does not invalidate on write gets avoided.

Theme tokens

One palette drives light and dark.

Theme tokens drive color across both light and dark mode. A theme switch does not require a page reload because the tokens cascade. The common failure where dashboard colors look fine in one theme and break in the other (because colors were hardcoded) gets avoided when the palette is tokenized.

Where dynamic deploys

Three live customer dashboard patterns.

A 50-seat regional sales team, a 220-seat enterprise SaaS, and a 500-seat healthcare SaaS each configure the dynamic dashboard differently. The platform plumbing stays the same. The role templates and the panel library flex to the business.

Regional team

Three role templates, light user overlay.

A 50-seat regional team ships three role templates (rep, lead, VP). User overlays stay light (a pinned panel or two). The common failure where every user builds their own dashboard and the team loses shared ground truth does not happen because the base templates are the anchor.

Enterprise SaaS

Product-split templates on top of roles.

A 220-seat enterprise SaaS layers product filters on top of role templates. A rep in Product A sees pipeline filtered to A. A VP sees combined with product filter overlays available. The admin maintains one template definition rather than four variants.

Healthcare SaaS

HIPAA posture plus cohort panels.

A 500-seat healthcare SaaS runs the standard role templates plus cohort retention panels in the CSM template. HIPAA posture holds across every panel: BAA signed, PHI never leaves the tenant, audit log retention set to the regulated horizon.

Monthly review

Ops lead audits user overlays.

Monthly, the ops lead audits user overlays. If a pattern appears (five reps pinned the same panel to the top), the pattern lands on the base template so new reps inherit it. The common failure where organic patterns stay invisible to the admin gets avoided through the monthly audit.

Quarterly refresh

Panel library expands with new metrics.

Quarterly, the admin expands the panel library based on business evolution. A new product line gets a dedicated pipeline funnel panel. A new segment gets a cohort retention panel. Users compose overlays from the expanded library.

Annual audit

Definition versions trace year-over-year.

Annually, the audit team traces panel definition versions year-over-year. If a forecast panel definition changed mid-year, the audit log carries the version chain. The common failure where year-over-year dashboard numbers compare across quietly-changed definitions gets avoided through definition versioning.

A dynamic dashboard that reshapes to the viewer.

Role-keyed layouts, user overlays, live record reads, permission-aware aggregation, versioned panel library, admin audit. Flat seat pricing with no per-query fee. HIPAA BAA available, SOC 2 Type II in progress through 2026-Q4.

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Common questions

What buyers ask about this feature.

How does a dynamic dashboard differ from a static dashboard?

A static dashboard renders one layout to every viewer. A dynamic dashboard reshapes along multiple axes: role (the sales lead and the rep see different panels), user overlay (an individual pins their favored panels on top), time (rolling, period, custom range), filter (segment, product, source), permission (aggregation honors the viewer's row scope), mobile (layout reflows on narrow screens), and theme (light or dark). Each axis is a declared configuration rather than a hand-built variant, so the admin maintains one template definition rather than a sprawl of per-user dashboards.

Can individual users customize the dashboard?

Yes, within guardrails. An individual user pins their own panels on top of the role base template. The overlay saves on the user record and survives sessions. The admin still maintains the base template so the overlay cannot delete the base panels. The pattern keeps the admin's single source of truth intact while giving the user a personalization layer. Monthly, the ops lead audits user overlays for patterns: if five reps pinned the same panel to the top, the pattern lands on the base template so new reps inherit it rather than reinventing.

Does the dashboard honor record-level permissions on aggregation?

Yes. The permission scope applies as a row filter before aggregation rather than after. A sales rep aggregating pipeline sees only their own rows contribute to the chart. A sales lead sees the team rows. A VP sees the division. The row filter runs first so the aggregated chart cannot leak information about rows the viewer could not otherwise see. The common failure where a dynamic dashboard reveals aggregated totals that let the viewer back out individual rows gets avoided because the filter runs at the row boundary, not the result boundary.

Will the dashboard stay fast with 100,000 rows?

Yes. Panel aggregations run on the API with indexed queries rather than pulling raw rows to the browser and grouping client-side. The browser receives the aggregated series ready to plot. A short-TTL cache sits in front of the aggregation keyed on the panel definition and the viewer permission scope. Panels load fast on repeat view and refresh on typed-record writes. Live customers run the dashboard on 100,000+ typed records without the browser noticing the volume.

How does the dashboard track definition changes over time?

Every panel definition carries versioning. When the admin edits a definition (changes a stage filter, adjusts an aggregation, renames a label), the version increments. The audit log records the edit with the actor and the delta. A later audit asking why a year-over-year number shifted reads the definition version in effect at each read. The common failure where a dashboard number silently changes meaning (because an admin tweaked the definition and nobody noticed) gets avoided through versioning. The audit chain survives admin turnover so the team can trace definition drift over years.

Can external tools read dashboard panel series?

Yes. Every panel exposes its aggregated series on the open API with the viewer's permission scope applied. External tools (BI consolidation, finance warehouse, parallel reporting) pull the series rather than recomputing from raw rows. The API returns the typed series. The common failure where a parallel BI tool disagrees with the Strkr dashboard (because the two aggregations drifted on definition) gets avoided when the external tool reads from the shared panel definition. The flat seat pricing covers the API access with no per-query fee.

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