Feature · Data Analysis Dashboard

A data analysis dashboard that pulls from the typed record, not a stale warehouse copy.

Most data analysis dashboards sit on a nightly warehouse export, lag the live record by a day, and still charge a per-seat BI fee on top of the CRM seat. Strkr builds the dashboard inside the record so the chart on the home surface reflects what the sales lead typed into the opportunity 90 seconds ago. The data model is typed, the panels are composable, the drill-through lands on the live row, and the price is a flat seat with no per-query tax.

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Why the dashboard sits inside the record

Six reasons the live record beats a nightly warehouse export.

The dashboard that reads the live record and the dashboard that reads a nightly warehouse export are the same shape on the first screenshot and very different on the twentieth operational meeting. Pipeline moves, deals get retyped, bookings slip or pull in, and the warehouse export catches up tomorrow. Six reasons the live-record approach wins the operational meeting.

No lag

The chart reflects what was typed a minute ago.

When the sales lead retypes the opportunity amount on a strategic deal, the forecast panel reflects the change on the next page load. The common failure where the Monday pipeline review runs against Friday numbers because the warehouse replication slipped overnight does not happen because the panel reads the typed row.

Drill-through

Click the point, land on the row.

A click on a pipeline point lands on the typed opportunity row rather than opening a separate BI tool with a filter. Investigation stays inside the record. The common frustration where a sales lead sees a weird forecast number, hunts through BI, and gives up gets avoided because the drill-through is one click to the source.

Typed data

Field semantics the chart honors.

The amount field is a currency, the close date is a date, the stage is an enum. The chart reads the typed semantic and plots accordingly. The common failure where a BI tool treats a currency column as a string because the warehouse schema lost the type does not happen because the typed record is the source.

Permission-aware

The panel honors who can see what.

A sales rep sees their own pipeline, a sales lead sees the team pipeline, a VP sees the division. The panel honors the record-level permissions so one dashboard definition serves every role without a parallel BI permission matrix. The common failure where a BI dashboard shows numbers the viewer should not see does not happen.

No per-query fee

The flat seat covers the chart.

A team that opens the dashboard 40 times a day pays the same seat price as a team that opens it four times a day. The flat seat covers the dashboard. The common failure where a BI vendor charges per query and the ops team ends up rationing dashboard access to junior reps does not happen on Strkr.

Single source of truth

The chart and the forecast tell the same story.

When the pipeline panel on the home surface and the forecast rollup in the weekly review disagree, the sales lead loses trust in both. The typed record is the shared source. The chart derives from the same row as the forecast. The numbers reconcile because they share the row.

What the dashboard ships with

Eight panel types the ops lead composes on day one.

A new tenant lands on the dashboard with eight panel types ready to drop onto the home surface and the module home. Each panel honors permissions, drills through to the typed row, and refreshes on page load. The ops lead composes a dashboard in minutes rather than filing a BI ticket and waiting a sprint.

Pipeline funnel

Stage by stage, with conversion.

The pipeline funnel panel plots opportunity count and amount by stage with stage-to-stage conversion overlaid. Click a stage to land on the filtered opportunity list. The sales lead sees the stuck stage without opening a report tool. The forecast conversation starts from the funnel rather than a copy-pasted deck.

Activity volume

Calls, emails, meetings by rep.

The activity volume panel plots calls, emails, and meetings by rep over a rolling window. Click a rep bar to land on the filtered activity list. The sales lead spots the rep who skipped outreach without reviewing individual activity cards. Coaching conversations start with a visual.

Win rate trend

Rolling win rate by segment.

The win rate trend panel plots rolling win rate by segment, product, or source. The ops lead spots the segment where win rate is sliding before the forecast gets missed. The common failure where a declining win rate shows up in the quarter-end postmortem rather than mid-quarter does not happen because the chart lives on the home surface.

Revenue forecast

Committed, pipeline, risked.

The revenue forecast panel plots committed, pipeline, and risked buckets against the quarter target. Click a bucket to land on the opportunity list. The sales lead sees the gap before the weekly forecast call. The forecast number on the dashboard reconciles with the forecast number in the submit lock because they share the row.

Lead source ROI

Cost per won deal by source.

The lead source ROI panel plots cost per won deal by source, pulling spend from the marketing module and won amount from the opportunity. The marketing lead sees which channel actually pays back rather than which channel attributed the most clicks. The attribution is on the typed record.

Account health

Risk signals grouped by account.

The account health panel plots risk signals (open support cases, missed invoices, declining usage) grouped by account. The CSM lead sees the at-risk accounts before the renewal conversation. The health field is external-write today with the risk score deferred until the signals stabilize.

Custom chart

Build any panel on any typed field.

The custom chart panel builds on any typed field in any object. The ops lead picks the object, the field, the aggregation, and the grouping. The chart renders without engineering. The common failure where a custom metric lives in a spreadsheet because BI is backlogged does not happen on Strkr.

KPI tile

One number with a sparkline.

The KPI tile shows one number (ARR, pipeline coverage, win rate) with a sparkline for the trend. The ops lead composes a KPI row at the top of the home surface so the sales lead sees the top-line numbers on login. The sparkline shows the direction without opening a chart.

Cohort retention

Account cohorts and retention curves.

The cohort retention panel plots account cohorts (by signup month, by segment, by product) with retention curves overlaid. The CSM lead spots the cohort that is churning harder than expected before the renewal cycle. The cohort definition is on the typed record so the panel updates as accounts move segments.

The engineering underneath

What makes the dashboard hold at scale.

A dashboard that renders fast on 1,000 rows and chokes on 100,000 is a demo. One that renders fast on 100,000 rows and still honors permissions and drills through to the typed source survives the operational meeting. Strkr ships the primitives that keep the dashboard working as the tenant grows.

Server aggregation

Group-by runs on the API, not the browser.

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. The common failure where a BI panel on 100,000 opportunities freezes the browser does not happen because the aggregation is server-side.

Caching layer

Short TTL cache per permission scope.

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 without serving stale numbers across the TTL boundary. The cache invalidates on typed-record writes to keep the panel honest.

Permission scope

Record filter applied before aggregation.

The permission scope applies as a record filter before aggregation rather than filtering results after the fact. A sales rep aggregating pipeline sees only their own rows contribute to the chart. The common failure where a BI dashboard reveals aggregated numbers that let the viewer back out individual rows does not happen.

Composable panels

Admin picks object, field, aggregation.

A panel is a function of object, field, aggregation, grouping, and filter. The ops lead picks each dimension from a dropdown. No engineering. The composed definition saves to the typed layout record so the panel renders consistently across the home surface and the module home.

Open API

Pipe the series to any downstream tool.

Every panel exposes its series on the open API. Teams that run a parallel BI tool can read the Strkr aggregation as a source. The API returns the typed series with the permission scope applied. The common failure where a parallel BI tool reads from a stale warehouse while Strkr renders live gets closed off at the API.

Audit log

Every panel view lands on the audit.

Every panel view lands on the audit log keyed on the viewer, the panel, and the filter scope. Compliance queries like asking who viewed the forecast panel in the week before the earnings release are a filter on the audit page. The audit log is append-only with cryptographic integrity.

Where teams land in practice

Three deployment patterns from live customers.

A 45-seat regional sales team, a 220-seat multi-product SaaS, and a 480-seat healthcare SaaS each compose the dashboard differently. The platform plumbing stays the same. The panel definitions and the home layouts flex to the business.

Regional team

Pipeline funnel plus activity volume.

A 45-seat regional sales team runs a two-panel home with the pipeline funnel and the activity volume side by side. The sales lead opens the home each morning, sees the stuck stage and the quiet rep, and starts the day with coaching rather than hunting for reports. Monday forecast calls run on the funnel panel directly.

Multi-product SaaS

Product-split panels on the home.

A 220-seat multi-product SaaS splits every panel by product. The pipeline funnel, the win rate trend, and the revenue forecast each carry a product filter overlay. Product leads see their slice, VPs see the combined view, and the ops lead maintains one dashboard definition rather than four.

Healthcare SaaS

HIPAA posture plus cohort retention.

A 480-seat healthcare SaaS runs the standard panels plus the cohort retention panel grouped by hospital segment. HIPAA posture holds across every panel: BAA signed, PHI never leaves the tenant, audit log retention set to the regulated horizon. The dashboard reads the same typed record the CSM team edits.

Weekly cadence

Forecast review opens on the funnel.

The weekly forecast review opens on the pipeline funnel panel rather than a copy-pasted deck. The sales lead walks through the stuck stage, drills into the typed opportunity, and the forecast conversation stays on the live record. The number on the panel reconciles with the number on the forecast submission.

Monthly cadence

Win rate trend drives segment calls.

The monthly segment review opens on the win rate trend panel. The ops lead walks through the segment where conversion is sliding, the sales lead picks a plan, and the panel reflects the plan outcome on the next monthly review. The reporting cycle shortens because the trend is already on the home.

Quarter close

Revenue forecast panel locks the number.

At quarter close, the revenue forecast panel reconciles against the submitted forecast and the actual bookings. The audit log carries the panel view history for the exec team so the quarter-close debrief can trace which numbers the leaders saw at which point in the quarter.

A data analysis dashboard that reads the typed record on every refresh.

Strkr composes a live-record dashboard on the home surface. Eight panel types, permission-aware aggregation, drill-through to the typed row, open API, flat seat price with no per-query fee. HIPAA BAA available, SOC 2 Type II in progress.

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Common questions

What buyers ask about this feature.

How is a data analysis dashboard different from a BI tool like Tableau or Looker?

A BI tool reads a warehouse export, lags the live record by a day, and charges a per-seat BI fee on top of the CRM seat. The Strkr dashboard reads the typed CRM record on every refresh, lags nothing, and the price is a flat seat with no per-query fee. For teams that already run Tableau or Looker, the Strkr open API exposes every panel series as a source so the warehouse pipeline can read the aggregated numbers rather than hitting the raw row store. The two approaches coexist: Strkr for the operational dashboard inside the record, the BI tool for the finance consolidation that needs to join across CRM, ERP, and HR.

How does the dashboard honor record-level permissions?

The permission scope applies as a record filter before aggregation rather than filtering results after the fact. 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. One dashboard definition serves every role because the permission scope is applied at the row filter boundary, not at the panel definition. The common failure where a BI dashboard reveals aggregated totals that let the viewer back out individual rows does not happen because the row filter runs first.

Will the dashboard stay fast with 100,000 opportunities?

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. Live customers run the dashboard on 100,000+ typed records without the browser noticing.

Can an ops lead build custom panels without engineering?

Yes. A panel is a function of object, field, aggregation, grouping, and filter. The ops lead picks each dimension from a dropdown. No engineering. The composed definition saves to the typed layout record so the panel renders consistently across the home surface and the module home. The common failure where a custom metric lives in a spreadsheet because BI is backlogged does not happen on Strkr because the panel builder is self-serve.

Does the dashboard support HIPAA posture for healthcare SaaS customers?

Yes. Strkr is HIPAA compliant with a BAA available on request. PHI never leaves the tenant boundary. The audit log carries panel view history keyed on the viewer, the panel, and the filter scope. Audit log retention is configurable up to the regulated horizon per tenant. SOC 2 Type II is in progress through 2026-Q4 with Type I attestation available on request. Live healthcare SaaS customers run the dashboard on their HIPAA posture without a parallel BI compliance review.

Does the dashboard cost extra on top of the Strkr seat?

No. The dashboard is included in the flat $50 per seat. No per-query fee, no per-panel fee, no BI add-on seat. A team that opens the dashboard 40 times a day pays the same as a team that opens it four times a day. The common failure where a BI vendor charges per query and the ops team ends up rationing dashboard access to junior reps does not happen on Strkr. The seat price on the pricing page is the full price for the dashboard capability.

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