Most dashboard sample galleries are decorative. A screenshot without the tiles, the metrics, the filters, or the interactions. Strkr's sample library is browsable, interactive, and clonable: every dashboard renders with sample data, every tile exposes its definition, and the maker clones the sample into their own tenant to start from a running draft.
The sample library is not a screenshot gallery. Each sample is a running dashboard rendered against synthetic but realistic data. The maker browses, filters by role or industry, opens a sample, inspects every tile, and clones the whole dashboard into their own tenant with one click. The samples teach by showing, not by describing.
Samples render as real dashboards against synthetic data. The maker hovers, filters, drills, and cross-filters just like a production dashboard. The interactions teach how the tiles respond, not what a screenshot cannot show.
The maker clicks a tile and sees the full definition: the metric, the filters, the chart form, the state logic, the drill target. The sample is transparent, not a black box. The maker learns the recipe for every tile.
A Clone to my tenant button copies the sample into the maker's workspace, remapping tiles to the maker's own data model. The maker starts from a running draft rather than a blank canvas. The sample is a seed, not an aspiration.
The library filters by role (AE, Manager, VP, Admin), industry (SaaS, healthcare, financial services, manufacturing, retail), and job to be done (weekly review, forecast, pipeline hygiene, service SLA). The maker finds a matching sample fast.
Strkr publishes new samples as new features land: a new metric, a new chart form, a new industry integration. The library stays current. The maker returns to the gallery for refreshers as the product evolves.
With permission, Strkr customers publish their best dashboards (scrubbed) into the public sample library. The community library grows beyond Strkr's own curation. Peer organizations learn from each other's layouts.
The sales library covers every seat on a modern revenue team: individual contributor, front-line manager, second-line manager, VP, CRO. Each sample is tuned to the altitude the reader works at. The AE dashboard is dense with their accounts. The CRO dashboard is sparse with portfolio metrics. The samples teach altitude as much as content.
The AE weekly sample carries open pipeline by stage, activity for the week, forecast call for the quarter, and a drill table of accounts needing attention. The sample is tuned for the hour before Monday's standup. The AE reads it on the way in.
The manager pipeline review sample shows the team's open pipeline, pacing to quota, forecast variance, and stuck deals. The sample is tuned for the Thursday pipeline call. The manager spots coverage gaps and coaching opportunities in a single scroll.
The VP forecast sample carries the forecast call across teams, the variance against plan, and the top ten accounts driving the quarter. The sample is tuned for the Monday leadership meeting where the VP reports up and asks down.
The CRO portfolio sample stays at altitude: ARR, net new, net retention, portfolio pipeline, and a short list of must-win deals. The sample is tuned for the board update and the all-hands. The CRO reads it in two minutes.
The SDR activity sample carries dials, connects, meetings booked, meetings held, and conversion to pipeline. The sample is tuned for the daily huddle. The SDR team reads it and spots who is on pace and who needs a lift.
The deal desk sample surfaces deals awaiting approval, non-standard terms, discount variance, and desk turnaround times. The sample is tuned for a commercial ops lead who maintains velocity on deal approvals.
Service teams run on different metrics than sales. First response, time to resolution, SLA adherence, CSAT, backlog shape. The service library carries samples for agents, team leads, service managers, and customer success. Each sample reads at the altitude the reader needs, with the metrics that actually drive the next decision.
The agent queue sample shows the agent's open cases, SLA clocks, next action due, and a list of cases needing a reply. The sample is tuned for the agent's shift. The agent reads it in the morning and triages immediately.
The team lead sample carries team SLA adherence, open backlog by priority, agent utilization, and escalations needing a lead's touch. The sample is tuned for the daily team huddle where the lead reorders the queue.
The service manager sample surfaces portfolio SLA, CSAT trending, backlog aging, and a drill into the longest-aging cases. The sample is tuned for the weekly ops review where the manager spots systemic drift before it hits the exec.
The CSM portfolio health sample carries account health, open cases, renewal timing, product adoption, and NPS trend across the CSM's book. The sample is tuned for the weekly CSM pipeline review.
The support manager sample tracks response time by channel, backlog shape, deflection, and top escalation reasons. The sample is tuned for the Thursday service standup where the manager pivots staffing or focus.
The VP of service sample stays at altitude: aggregate CSAT, SLA attainment, cost per contact, and a short list of accounts needing exec attention. The sample is tuned for the board update and the cross-functional ops meeting.
Beyond sales and service the sample library covers marketing attribution, revenue operations, and finance. These functions read dashboards differently: attribution reads over long windows, RevOps reads the data quality itself, FP&A reads financial outcomes. The library carries samples tuned for each.
The attribution sample carries pipeline sourced by channel, campaign, program, and content. Trailing windows show influence over long sales cycles. The sample is tuned for the monthly marketing review where the team ties spend to pipeline.
The campaign sample tracks engagement, response, pipeline generated, and ROI per campaign. The sample is tuned for the campaign manager who runs multiple programs and reads them against each other weekly.
The content sample tracks organic traffic, ranking movements, content performance, and conversion to signup or pipeline. The sample is tuned for the content lead who ships weekly and watches ranking shifts.
The RevOps hygiene sample surfaces missing fields, stale deals, duplicate accounts, and process adherence metrics. The sample is tuned for the RevOps lead who runs the hygiene cadence and knows that bad data breaks every downstream read.
The FP&A monthly sample carries revenue by product and segment, ARR movement, bookings vs billings, and a short budget-to-actual summary. The sample is tuned for the finance lead who closes the books and reports to the exec.
The board snapshot sample stays short: ARR, net new, retention, pipeline, and three strategic callouts. The sample is tuned for the board deck appendix. It is designed to be read in a meeting, not studied before one.
Dashboards shaped for SaaS do not translate to healthcare or financial services. Strkr's industry library carries samples tuned for each sector's mechanics: SaaS reads ARR and retention, healthcare reads clinic throughput and encounter mix, financial services reads AUM and client concentration. The library helps a maker in a industry start from the right conceptual shape.
SaaS samples carry ARR movement, net dollar retention, gross retention, pipeline coverage, and churn risk. The samples reflect the subscription business: recurring revenue, cohort math, product-led signals. Makers in SaaS clone and tune.
Healthcare samples track encounters per clinic, payer mix, A/R aging, and clinician utilization. HIPAA posture applies by default. The samples read for ops leaders in group practices, specialty clinics, and health systems.
Financial services samples track AUM, new client acquisition, client concentration risk, and advisor productivity. Compliance stamps apply by default. The samples read for RIAs, wealth managers, and private banking teams.
Manufacturing samples track order book, lead time, yield, and inventory turns. The samples read for commercial leaders in industrial manufacturing where the sales cycle intersects with production capacity.
Retail samples track conversion rate, average basket, repeat purchase, and category trends. The samples read for ops leaders in e-commerce and multi-location retail where unit economics shift weekly.
Professional services samples track utilization, realization, project margin, and backlog. The samples read for leaders in agencies, consulting firms, and services arms of product companies where billable hours drive the P&L.
A sample is useful only if the maker converts it into their own dashboard. The method is simple: clone, remap, trim, extend, publish. Strkr's workflow supports each step. The maker turns a sample into a production dashboard in a day, not a week.
The maker clicks Clone to my tenant. Strkr copies the layout, the tiles, and the configurations. The clone attempts to remap tiles to the maker's data model automatically. The maker starts with a running draft rather than a blank canvas.
Any tile that could not auto-remap carries a visible unbound chip. The maker opens the inspector and points the tile at the right field in their own model. The clone becomes a real dashboard reading real data.
The sample carries a dozen tiles. The maker's dashboard needs eight. The maker removes the tiles that do not fit the local audience. Trimming is encouraged. A sample is a starting point, not a required list.
The maker adds tiles specific to the organization: a local segment, a custom calculated metric, a bespoke drill. The sample becomes a tenant-specific dashboard. The extensions do not interfere with the sample's pattern.
The maker publishes the dashboard to the audience. A sprint later the maker reviews what readers actually used. Low-use tiles retire. High-use tiles get polish. The dashboard converges to its production form through use.
When the maker's tuned version proves useful, they can contribute it (scrubbed) back to the Strkr community library. Peer makers in similar organizations learn from the variant. The library grows through real-world adaptation.
A browsable, interactive, clonable library of real dashboards organized by role, industry, and job to be done. Every sample renders against synthetic data, exposes its tile definitions, and clones into the maker's tenant with one click.
Yes. The clone action remaps tiles to the maker's data model where it can and marks the rest as unbound. The maker completes the mapping in the inspector. The sample becomes a real dashboard reading real data in a few minutes.
The sample library is included in every Strkr tenant. Prospective customers see a selection of public samples on the website. Full access to the library ships with the product trial.
Yes. Each tenant can publish internal samples visible only to users in that tenant. The internal library accelerates onboarding and standardizes dashboard practice across teams.
Samples ship against synthetic data. Cloning into a regulated tenant inherits the tenant's security posture. Strkr is HIPAA compliant with a BAA available, pursuing SOC 2 Type II with completion targeted through 2026-Q4, GDPR, and CCPA compliant.
Strkr publishes new samples alongside major product releases and whenever a customer-contributed sample is accepted into the public library. The library grows continuously, with the newest additions highlighted on the gallery page.
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