Each dashboard below exists as a template in the Strkr gallery. The widgets, the slicer logic, and the row expansion behavior ship pre-configured. The fork takes under ten minutes to adapt to your tenant data model, which is the gap between we have dashboards and the manager actually opens them.
Executive dashboards answer a different question than operational dashboards. The CRO wants the forecast confidence and the headwind indicators; the CFO wants the ARR trajectory and the cohort retention; the board summary wants everything on one page. These three ship with the widgets, not vague placeholder guidance.
Widgets: current-quarter forecast with confidence band from Strkr AI, pipeline coverage ratio by stage, closed-won trailing-twelve ARR trend, top five at-risk deals (stage-stuck plus late close date), slipped-last-quarter deal count, and the win rate trend by segment. The dashboard answers will we hit the quarter in roughly 90 seconds of reading.
Widgets: ARR trajectory with new-ARR versus churned-ARR waterfall, net revenue retention by cohort quarter, trailing-six churn reasons by cluster, days-sales-outstanding on AR, forecast cash collections, and the gross margin by product line. The dashboard reads the full revenue picture without a monthly board-prep spreadsheet reconciliation pass.
Widgets: current quarter attainment versus plan, net revenue retention trailing twelve, logo count with net change, cash runway. Signals: one leading indicator per focus area (pipeline coverage ratio for new business, Net Promoter Score for retention, time-to-first-value for product). The page is designed for a board deck screenshot, not an analytical drill-in surface.
A grid of reps with their quarter-to-date attainment, pacing versus the straight-line plan, open pipeline coverage, and forecast call. Managers see at a glance which reps are on track, which need help, and which are overachieving. The grid is the operational companion to the CRO view; both reconcile to the same forecast number.
Widgets: slip rate on committed deals (deals that moved out of the quarter after being forecasted), average deal size trend, cycle length trend, pipeline generation versus prior quarter, win rate on competitive deals. The radar surfaces decline before the forecast miss arrives. The posture is leading-indicator, not lagging-indicator.
A rotating briefing for the executive account review: top 20 accounts by ARR, current health score, open opportunities, open support cases, executive sponsor, last executive-level touch. The format drives the monthly or quarterly strategic review. Leadership never arrives at the review unprepared on the account state.
Operational dashboards drive the daily and weekly decision cadence. The AE pipeline view, the CSM renewal view, the SDR activity view each sit on a user home page and get opened multiple times per day. The widgets are chosen to drive a next action, not to inform a vague update.
Widgets: open opportunities grouped by stage, deals forecasted this quarter with a go-no-go toggle, stuck deals (no activity in 14 days) with a tap-to-nudge action, upcoming meeting prep cards, Strkr AI next-step suggestion per open deal. The dashboard is the AE home page; opening it drives the first 20 minutes of the day.
Widgets: renewals within 30, 60, 90 days with health score and value, at-risk accounts with the risk signal (NPS detractor, exec sponsor departure, usage decline), expansion opportunities to recommend, this-week-renewal-prep tasks, trailing-90 renewal rate. The CSM opens the view Monday and runs the renewal motion from it.
Widgets: today dials and connects versus daily target, meetings booked this week versus weekly target, leads touched versus assigned, top prospects to call next (sorted by lead score), hot inbound queue depth, conversion rate from meeting-booked to opportunity-created. The SDR sees the pacing and the next three records to work.
Widgets: team rep scorecards (talk ratio, discovery completion, next-step rate), top five calls to coach from the last week (surfaced by Strkr AI), 1:1 agenda items pre-filled from the week signal, missed-SLA incidents by rep. The dashboard turns coaching from a vague Monday intention into a agenda the manager runs through.
Widgets: open cases by status, SLA state (green, yellow, red) with time remaining per case, agent workload (open case count per agent), first-response time trend, reopen rate trend, top five escalations. The queue manager opens the view and triages escalation and workload balance in one surface.
For service motions: open work orders on a map with technician current location pins, next-up order per technician, SLA state per order, technician utilization today, parts-availability flags on open orders. Dispatch rebalances workload in minutes rather than running the day on tribal knowledge.
Marketing dashboards answer different questions than sales dashboards. The marketing lead wants attribution, pipeline sourced, and MQL-to-SQL conversion. The ops lead wants data hygiene, duplicate detection, and workflow failure rate. Both land on specific widgets.
Widgets: pipeline sourced per channel (paid search, organic, event, referral, outbound) with cost-per-pipeline-dollar, MQL to SQL conversion by source, campaign ROI with the campaign names, content performance (opens, replies, clicks) by piece. The dashboard drives the quarterly channel-mix decision.
Widgets: MQL volume this period, MQL-to-SAL conversion rate, SAL-to-SQL conversion rate, SQL-to-Opportunity conversion rate, average time between stages. The waterfall surfaces the stage where the funnel narrows; marketing adjusts qualification criteria based on evidence rather than intuition.
Widgets: fields with over 20 percent null rate on open opportunities, duplicate contact candidates by match confidence, open flow failures from the dead-letter queue, workflow run failure rate by flow, data-sync lag per integration. The ops lead opens the view and spends an hour a week keeping the record of truth clean.
Widgets: feature adoption by role (percent of reps using sequences, dashboards, dialer, document templates), unused templates older than 90 days, top five adopted features vs plan, specific reps who have not adopted a required feature. The dashboard turns enablement from a feel into a measurable function.
Widgets: API latency P95 by endpoint, error rate by surface, integration health badges (Gmail, Office 365, Slack, dialer vendor), last successful sync per integration, open incident queue. The dashboard is the technical ops companion to the business ops hygiene view.
Widgets: pending access reviews, upcoming retention purges, documents under legal hold, trailing-30 permission changes, audit log size and coverage. For teams on HIPAA with BAA or SOC 2 Type II (in progress through 2026-Q4), the compliance dashboard surfaces the posture state without reconstructing from scattered audit entries.
Dashboards on Strkr follow a consistent grammar. Widgets render from queries against the record database. Slicers filter the dashboard scope globally. Drill-ins open the matching records in a sortable table view. The grammar is uniform; the specifics differ per widget type.
The widget library covers five types: KPI tile (single number with delta vs comparison period), trend chart (line over time with optional multi-series), distribution chart (bar, pie, or stacked bar on categorical data), table (row-level drill-in with sort and filter), geographic map (points or heat on tenant data). Mixing widget types fits the question each dashboard answers.
Each widget binds to a query defined through a point-and-click builder. The builder covers entity selection, filter conditions, group-by selections, aggregations, time slicing. The underlying query is the same engine that powers list views and reports. Admins who prefer SQL can author raw SQL for widgets that outgrow the builder.
Dashboards carry global slicers at the top: date range, territory, team, product line. Changing a slicer re-queries every widget on the dashboard with the new scope. Reps looking at the pipeline view flip the slicer from my records to team records and see the comparison in one tap. The pattern replaces per-widget filter editing.
Tapping any widget opens the underlying records in a sortable table side panel. A KPI tile showing 42 open opportunities drill-ins to the 42 records; the user sorts by close date, by amount, by owner. Row actions on the table (reassign, add task, change stage) work from the drill-in without navigating to each record.
Any dashboard can schedule itself as a PDF email on a tenant-configured cadence (daily, weekly, monthly). The schedule sends the current state to a configured recipient list. Executives who do not log into Strkr daily still see the headline numbers Monday morning. The PDF embeds the KPI tiles and the key charts as a readable summary.
Widgets honor the viewer permission matrix. A dashboard shown to an AE renders only the AE records; the same dashboard shown to a manager renders the team records. The query layer applies permission filtering at the database level, so no widget can leak data a user should not see. The posture matters most for territory-based teams.
Forking a dashboard template takes about thirty minutes end to end. The loop runs: fork, edit slicer scope, swap widget field bindings for tenant-custom fields, test with sample users, publish. The loop is designed for a RevOps lead; it never requires a database engineer.
The dashboard gallery lives inside the Reports module. Picking a template clones it into the tenant with widgets, slicers, and bindings intact. The forked dashboard is editable; the original template remains unchanged. Teams can fork a template multiple times for different purposes (team-specific pipeline views, product-specific attribution).
Edit the global slicers to the tenant data shape: a sales team covering US-West sets the territory slicer to that region, a two-product company sets a product-line slicer. The slicers are the user-facing filters; the configuration here determines what defaults the dashboard surfaces when a user opens it.
A template widget binding to opportunity.amount works on tenants that keep the standard amount field. Tenants with a custom MRR field swap the binding in the widget editor; the widget re-queries against the new field. The pattern avoids rewriting widgets from scratch when the data model differs from the template default.
The impersonation preview shows the dashboard as a user would see it, with their permission scope and record visibility. The pattern catches binding mistakes before the dashboard reaches the real user. A manager previewing the AE view as an AE sees exactly what the AE will see on Monday.
Publishing a dashboard assigns it to a role, a team, or a user list. Users see the dashboard on their home page the next time they log in. Publication is reversible; unpublish removes the dashboard from the assigned users without deleting the configuration. The pattern supports gradual rollout and A/B testing of dashboard designs.
A healthy dashboard surface iterates monthly. Add a widget that answers a recurring question; remove a widget nobody drills into; swap a slicer that reduces user tap count. The usage analytics on each dashboard show widget hover and drill-in counts; the signal drives the refinement direction. The pattern turns dashboards into a living surface rather than a one-time configuration.
Fifteen minute walkthrough: fork one of the eight templates above, swap the field bindings for your record model, publish to a role, open as the end user.
Yes. The dashboard builder opens on a blank grid. Admins drag widgets, bind each to a query through the point-and-click builder, add slicers, publish. Teams with specific analytical needs often build custom dashboards from scratch after the first month of using the templates. The template library is a starting point, not a ceiling.
Widgets query the record database through the standard index path. For tenants with over ten million records, aggregation widgets (counts, sums, averages) typically render in under two seconds; trend charts over a year window render in under four seconds; large table drill-ins paginate at 100 rows per page. The engineering team benchmarks dashboard rendering per release; the current P95 latency sits comfortably under the manager will not wait threshold.
Scheduled PDF exports fit the Slack-posting and Confluence-embed use cases without needing a direct embed. For live embeds, the dashboard API returns the widget data as JSON through the open API (OpenAPI 3.1 at the trust center) so an external tool can render the data in its own surface. The embed path respects the viewer permission matrix; data a user cannot see in Strkr does not leak through the API.
Yes. The responsive dashboard layout reflows widgets to a single column on mobile screens. KPI tiles render first, then charts, then tables with horizontal scroll. The pattern suits the common mobile dashboard use case (CRO glances at the forecast between meetings) better than forcing a full-desktop layout onto a phone. Reps on the mobile app see dashboards in the same inventory as desktop with the mobile-reflowed layout.
Yes. Dashboards are cross-module; a widget can query opportunities from CRM, campaigns from Marketing, and projects from Projects in the same dashboard. The design treats modules as domains within one data model rather than separate systems. A customer-success dashboard commonly mixes CRM (account health), Projects (open implementation state), and Marketing (nurture engagement). The cross-module posture is the reason mid-market teams consolidate onto Strkr.
Multi-currency tenants carry a tenant default currency and per-record transaction currency. Widgets query currency-aware aggregations: amounts convert to the tenant default at the configured rate (daily spot or quarter-close rate per tenant policy) before aggregation. Reps viewing their pipeline see the transaction currency; executives viewing the global forecast see the tenant default. The dashboard behavior is consistent with the broader multi-currency posture across reports and forecasting.
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