Feature · Marketing Dashboard Examples

Marketing dashboard examples built on the same database as your pipeline.

Marketing teams spend half their reporting cycle gluing data from the CRM, the campaign platform, the ad accounts, and the attribution tool into a slide deck. The useful version lives inside the CRM, reads from the record directly, refreshes on live data, and ships with scheduled exports. This page walks through the dashboard shapes that revenue teams actually run: pipeline contribution, campaign ROI, funnel conversion, channel attribution, cohort retention, and the executive summary. Build the layouts in the Strkr dashboard builder on your real data.

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The pipeline contribution dashboard

What marketing sourced, what marketing influenced.

The single dashboard every CMO owes the CRO is a pipeline contribution view. The question is simple and the implementation is hard: of the pipeline that is in play right now, how much did marketing source, how much did marketing influence, and what is the quality trend over time. The pipeline contribution dashboard answers both the sourced and influenced versions, splits the data by campaign and channel, and shows the trailing twelve months of weekly cadence. Strkr pulls the numbers from the pipeline record itself, so the dashboard is always current and never requires a weekly export.

Sourced pipeline $

The ARR marketing created, this quarter.

A tile summing the ARR of open opportunities where the lead source is marketing-attributable. Breaks out by segment and by channel. The quarter-to-date and the forecast-to-end-of-quarter both appear with the delta. Compared against the quarter target, the tile also carries pacing percentage so the CMO sees whether the number is tracking.

Influenced pipeline $

The ARR marketing touched on the way to open.

A tile summing the ARR of open opportunities where any marketing touch happened before stage two. The influenced number is almost always larger than the sourced number. The delta between the two tells leadership how much of the open book has marketing fingerprints on it, even when the first-touch attribution went to another channel.

Pipeline count

Deals in the funnel from marketing.

A tile counting open opportunities with a marketing source. Pairs with the dollar tile so a high dollar count driven by three mega-deals shows against a smaller deal-count. Volume and value both earn a view, not one or the other.

Average deal size

Dollars per marketing-sourced deal.

A derived tile showing total marketing-sourced pipeline divided by marketing-sourced opportunity count. Trends over the trailing twelve months. The number helps answer the frequent question of whether marketing is bringing in bigger or smaller deals as the ICP shifts.

Pipeline age

How long marketing-sourced deals have been open.

A histogram of days-in-pipeline for marketing-sourced open opportunities. Compared against the overall pipeline age distribution. If marketing-sourced deals age slower than sales-sourced, the lead quality is credible. If they age faster, the signal is on the dashboard before the quarterly review surfaces it.

Pipeline velocity

Days to close for marketing deals.

A tile tracking the average days-to-close for marketing-sourced deals that closed in the trailing quarter. Compared against the same metric for sales-sourced deals. The velocity gap is one of the harder-to-fake quality metrics for marketing contribution.

By segment

Mid-market, enterprise, SMB, each in a row.

A table splitting the sourced and influenced pipeline by segment. Each row shows ARR, count, and pacing. The segment view surfaces where marketing is overindexed and where it is underindexed against the segment targets.

By channel

Paid, organic, events, partner, each a row.

A table breaking the sourced pipeline by channel. Paid search, paid social, organic search, direct, referral, events, partner, email, webinars. Each row shows ARR and count. The channel mix is the first scroll a CMO reads before any attribution-model conversation.

Weekly cadence

Trailing twelve months, week by week.

A line chart showing marketing-sourced pipeline $ created each week for the trailing twelve months. The cadence catches the seasonal shape of the demand funnel. A missed week shows against the trend, and the chart renders the four-week moving average on top of the raw series for smoothing.

The campaign ROI dashboard

Which campaigns paid for themselves and which did not.

A campaign ROI dashboard is the second-most-asked view after pipeline contribution. The CFO wants to see which specific campaigns in the quarter returned real pipeline, which returned real revenue, and which absorbed budget without producing a measurable return. The dashboard has to show spend, pipeline, and revenue for each named campaign, over the time horizon that matches the campaign's expected payback period. Short-cycle campaigns measure on a quarterly horizon. Longer-cycle campaigns measure on a six-to-nine-month trailing window. Strkr pulls the data straight from the opportunity record and the integrated ad accounts, so the dashboard answers the ROI question without a spreadsheet.

Spend per campaign

Dollars committed, by named campaign.

A table listing every active campaign with the committed spend to date. Ad spend from integrated ad accounts, event spend from the campaign record, content spend from the production ledger. One column, one number, auditable per campaign.

Pipeline per campaign

ARR sourced, by named campaign.

A column alongside spend showing open pipeline ARR attributable to each campaign. Attribution respects the first-touch or multi-touch model configured for the tenant. The ratio between the two columns is the raw pipeline-to-spend multiple.

Revenue per campaign

Closed-won $ sourced, by campaign.

A column showing closed-won ARR attributable to each campaign over the measurement window. Longer than pipeline because deals need to close. The CFO looks at this column first, the CMO defends both.

ROI multiple

Revenue divided by spend, per campaign.

The derived column every executive scrolls to first. A number above 1 is positive. A number above 5 is healthy for most B2B motions. A number below 1 is a hard conversation, but at least it is a conversation grounded in the same dashboard both sides agreed to.

CAC per campaign

Cost to acquire a customer from this source.

Spend divided by won customer count. Different from ROI because it isolates the acquisition economics from the deal size. A high ROI with a high CAC is a big-deal strategy. A moderate ROI with a low CAC is a volume strategy. Both are legitimate, the dashboard surfaces which is which.

Payback period

Months to recover the campaign spend.

A derived metric showing how long it took the won deals to recoup the campaign spend. For most B2B motions the healthy range is nine to eighteen months. Longer periods compound against gross margin and change the budget conversation.

Pipeline-to-close ratio

What percent of pipeline from this campaign closed.

A column showing the historical conversion rate from campaign-sourced pipeline to closed-won. Campaigns with high pipeline numbers but low close rates signal lead-quality problems. Campaigns with lower pipeline but higher close rates often deserve a bigger share of next quarter's budget.

Attribution model toggle

See the same campaign in different lenses.

A control on the dashboard switches between first-touch, last-touch, linear, time-decay, and account-level attribution. The same table changes shape under each model. The CMO sees which model treats which campaign fairly and defends budget allocations with the appropriate lens.

Historical cohorts

Previous quarters alongside the current one.

A side panel showing the ROI of the same named campaign in previous quarters. A campaign running for a fourth consecutive quarter with declining ROI is a different conversation than a new campaign still in its ramp window. The historical view protects experiments from unfair quick kills.

The funnel conversion dashboard

Where leads enter, where they drop, where they close.

A funnel conversion dashboard tracks the shape of lead flow from visit to closed-won. The useful version shows stage-to-stage conversion rates, median time at stage, and the specific drop-off points where a disproportionate share of leads exit the funnel. Teams often lose the plot by displaying a six-stage funnel with aggregated numbers that mask the real bottleneck. The honest shape is a stage-by-stage conversion chart with the leaky stage flagged, the hypothesis for why, and a trend line showing whether the fix is working. Strkr builds the funnel from the lead and opportunity records directly.

Visit to MQL

What percent of visits become qualified leads.

A tile showing the conversion rate from site visitor to marketing-qualified lead. Typical ranges are 1 to 5 percent. The baseline matters less than the trend. A sudden drop signals a form change, a landing page issue, or an upstream channel-quality problem.

MQL to SQL

What percent of MQLs become sales-qualified.

The handoff conversion rate between marketing qualification and sales acceptance. A low number means marketing is sending leads sales does not consider ready. A high number but low SQL-to-opportunity means marketing qualified correctly but sales is not working the leads. The dashboard separates the two signals.

SQL to opportunity

What percent of SQLs open as opportunities.

The conversion rate from accepted lead to formal opportunity. Sales owns this metric. The dashboard shows marketing the handoff reality so the two sides share a view of where the funnel actually leaks.

Opportunity to closed-won

Overall win rate from the top of pipeline.

The end-to-end win rate from opportunity opened to closed-won. The denominator is opportunities, not leads. For most B2B motions the healthy range is 15 to 25 percent, with meaningful variation by segment and product.

Time at each stage

Median days a lead spends at each stage.

A bar chart showing median days-at-stage for every funnel step. A stage with disproportionate time is a bottleneck. The chart surfaces where the funnel physically slows, not where the volume thins. Both insights matter and the dashboard shows them separately.

Drop-off reasons

Why leads exit at each stage.

A grouped bar at each stage breaking out the reasons leads exited: disqualified, no response, timing not right, lost to competitor, lost on price. Pulled from the lead and opportunity drop reason fields. The reasons surface which fix matters most at each stage.

Funnel velocity

Average days from first touch to closed-won.

A tile showing the end-to-end cycle time. Trends over the trailing twelve months. Shorter cycles correlate with higher capacity. Longer cycles usually signal bigger deals, more approvals, or a shift in ICP.

Segment funnels

The same funnel, by segment.

A control on the dashboard filters the funnel by segment. Enterprise funnels are longer, SMB funnels are faster, mid-market lives in between. The segment view often answers whether a funnel issue is global or specific.

Historical overlay

Last quarter's funnel against this one.

An overlay chart comparing the current quarter's funnel shape to the same stage last quarter. The lift or regression at each stage shows against the comparable baseline. Executives read the overlay in seconds.

The channel and attribution dashboard

Where the pipeline came from, honestly measured.

A channel attribution dashboard answers the budget-allocation question: which channels are earning their share of the marketing spend. The useful version avoids last-click oversimplification and runs multiple attribution models in parallel so the team can see the same channel through different lenses. Paid search, paid social, organic search, direct, referral, events, email, webinar, partner, and content syndication each get a row. First-touch, last-touch, linear, and time-decay each get a column. The dashboard surfaces the channels where every model agrees the contribution is real and the channels where the models disagree, which is often where the attribution conversation gets interesting.

First-touch channel mix

Where did the lead find us first.

A pie or bar showing first-touch channel distribution for closed-won deals in the measurement window. Over-indexes awareness channels. Rewards the top-of-funnel work that competes for the first impression. Rarely the only lens, but part of any honest budget conversation.

Last-touch channel mix

Which channel was the last before conversion.

The counterweight to first-touch. Over-indexes bottom-of-funnel channels that close the deal. Branded search, direct, and retargeting typically win. The combination of first-touch and last-touch starts to tell the real story of how channels contribute at different stages.

Linear attribution

Equal credit to every touch.

Linear attribution gives each channel in the journey equal credit for the deal. Favors multi-touch channels. The model is naive but useful as a baseline because the simplicity makes it easy to explain in a budget meeting.

Time-decay

More recent touches earn more credit.

Time-decay weights later touches more heavily. Good for shorter sales cycles. The model is defensible when deal cycles are predictable and the recency of a touch really does correlate with its influence on conversion.

Account-based attribution

Credit shared across every stakeholder.

For B2B motions with multiple stakeholders per deal, account-based attribution rolls up every touch across every contact at the account into one credit allocation. The model matches how enterprise deals really work and is often the most defensible lens for named-account programs.

Multi-touch summary

How many touches per closed-won deal.

A tile showing the average number of touches on a closed-won deal. For enterprise motions, the number often sits between 15 and 50. The count helps calibrate expectations for how many touches the funnel needs to budget for before a deal closes.

Channel spend overlay

Channel contribution vs channel budget.

A chart overlaying channel attribution with channel spend. A channel that is 20 percent of the attribution and 40 percent of the spend is overfunded. A channel that is 30 percent of attribution and 10 percent of spend is underfunded. The overlay drives next quarter's budget conversation.

Model agreement

Where all four attribution models agree.

A derived column showing which channels every attribution model agrees are contributing. Agreement across models is the strongest signal that a channel is real. Disagreement is where the attribution-model conversation starts.

Dark channel estimate

The chunk of pipeline that attribution misses.

A tile showing the share of pipeline for which no measured channel contact exists. Direct traffic, word of mouth, and offline referrals often live here. The honest dashboard carries the dark channel number rather than pretending every deal has a measurable source.

The executive summary dashboard

One page the CMO opens before the exec meeting.

An executive summary dashboard is the page the CMO opens five minutes before the ELT review. The job of the page is to answer the five or six questions that always come up: Is pipeline on target? Is spend on budget? Which campaigns are working? Which channels are overfunded? What is the top risk this quarter? The executive summary is not a replacement for the other dashboards. It is the index page that links to the detail views when the exec wants to drill in. Strkr builds the summary from the same tiles the detail dashboards use, so the number on the summary is always the same number on the drill-in page.

Pipeline pacing

Marketing-sourced pipeline $ vs quarter target.

A single tile with the quarter-to-date pipeline $, the target, and the percent pacing. Green above pacing, yellow near target, red below pacing. One tile answers the top question in most ELT marketing reviews.

Spend pacing

Spend to date vs quarter budget.

A tile mirroring the pipeline pacing but for budget. The combination of pipeline pacing and spend pacing is the first scroll the CFO reads. Both green is a healthy quarter. Pipeline red and spend green is a lead-quality problem. The dashboard distinguishes them cleanly.

Top-performing campaigns

The three campaigns earning this quarter.

A short list of the three campaigns with the highest ROI multiple so far this quarter. Each row shows campaign name, spend, pipeline, revenue, ROI. Clicks through to the full campaign ROI dashboard for the detail view.

Underperforming campaigns

The three campaigns at risk.

The counterweight to the top performers. The three campaigns with the lowest ROI or the slowest pipeline velocity. The intent is not shame. The intent is early visibility so a mid-quarter pivot is possible. Clicks through to the campaign detail.

Funnel health

A one-sentence funnel summary.

A sentence written by Strkr AI summarizing the funnel shape: "Funnel velocity is 8 percent faster than last quarter, MQL to SQL conversion is holding, and the opportunity-to-close rate is up 2 points." The summary is a plain-English rollup of the four or five metrics the exec would otherwise ask about.

Top risk

The single most pressing issue.

A tile flagging the one risk that most needs executive attention. Could be a campaign underperforming, a channel's cost going up, a funnel stage leaking, or a target the pacing says will miss. One risk, highlighted, with a link to the detail. More than one risk and the summary becomes a list, which the executive will skim and ignore.

Executive narrative

A three-paragraph brief, drafted by Strkr AI.

A three-paragraph narrative drafted nightly by Strkr AI summarizing the state of the business from a marketing lens. Reads like the briefing a chief of staff would prepare. The CMO edits before the ELT meeting, saves the final version to the dashboard, and the next day's briefing picks up where the last left off.

Linked drill-ins

One click to the detail dashboard.

Every tile on the executive summary clicks through to the full detail dashboard that produced the number. The exec on the executive summary clicks through on the surprising number, lands on the detail page with the full breakdown, and asks the right follow-up question without a side conversation.

Scheduled snapshot

The dashboard, delivered on a cadence.

The executive summary can snapshot to PDF and email to a distribution list every Monday morning. The leadership team arrives at the week with the same view the CMO sees. The snapshot links back to the live dashboard for drill-in. One source of truth, one weekly rhythm.

A full set of marketing dashboards wired to the live record.

Pipeline contribution, campaign ROI, funnel conversion, channel attribution, and the executive summary all ship as templates in the dashboard library. Add tiles, change filters, schedule exports. Strkr AI drafts the narrative panels nightly. Nothing lives in a separate BI tool, nothing requires an export, nothing goes stale between the dashboard and the record.

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Common questions

What buyers ask about this feature.

What should a marketing dashboard actually show, versus what most marketing dashboards show?

Most marketing dashboards show vanity metrics: impressions, website visitors, social followers, email list size. Those metrics measure activity, not business impact. A real marketing dashboard shows pipeline contribution, campaign ROI, funnel conversion rates, channel attribution, and the executive summary of whether the function is pacing to its revenue targets. The vanity metrics belong on a tactical operations dashboard for the team doing the work, not on the executive view the CMO shares with the CRO. Strkr's dashboard library ships the right shapes for each audience: tactical dashboards for the practitioners, executive dashboards for the leaders, and detail drill-ins that connect the two.

How often should marketing dashboards update, and who should see which views?

Executive dashboards update on an hourly cadence against the live database and refresh nightly on batch-computed derived metrics like attribution and funnel stage averages. Tactical dashboards update in real time or near-real time because the team doing the work needs the current state to intervene. Audience split: the CMO owns the executive summary and shares it with the CRO and CFO on a weekly cadence. Campaign managers own the campaign ROI dashboard and review it twice a week. Demand gen owns the funnel and channel dashboards and reviews them daily during the quarter. Strkr supports permission-scoped sharing so each audience sees the dashboard shape that matches their role without a separate publishing step.

How does attribution work in Strkr dashboards?

Strkr ships five attribution models out of the box: first-touch, last-touch, linear, time-decay, and account-based. The attribution model is a dashboard-level control, so the same tile can show different numbers under different models. The model agreement view surfaces channels where every model agrees the channel is contributing, which is the strongest signal for budget decisions. Dark channel attribution is tracked separately: the share of pipeline for which no measured channel contact exists shows as its own tile rather than being distributed across the measured channels through a wishful fallback rule. Admins can also pin a canonical attribution model per report so budget conversations are grounded in one agreed lens before the model-switch exploration starts.

Can we build custom marketing dashboards, or are we limited to templates?

The templates are starting points, not limits. The Strkr dashboard builder supports any tile the data model can produce: metric cards, line charts, bar charts, pie charts, tables, funnels, cohort grids, geographic maps, and custom tiles. Every tile reads from a saved report or a direct database query. Permissions on the dashboard carry down to the tile and the underlying data, so a dashboard shared with the CRO shows the full numbers while the same dashboard shared with the CFO can hide fields the finance team should not see on a sales operations view. The template library is a quick-start; the real production dashboards are usually customized within the first week.

How do we handle the gap between marketing-sourced and marketing-influenced pipeline?

Show both numbers on the dashboard and define each one explicitly. Marketing-sourced is pipeline where marketing was the first-touch channel. Marketing-influenced is pipeline where any marketing touch occurred before the opportunity opened. The sourced number is almost always smaller than the influenced number, and the ratio between them is a credible operational metric: a healthy ratio often sits between 1:1.5 and 1:3 depending on segment and sales motion. Strkr's dashboards show both tiles side by side so the CMO can defend contribution with the sourced number in a strict conversation and with the influenced number in a nuanced one. The attribution model toggle on the dashboard also lets executives switch lenses in real time rather than requesting a separate report.

Can we export dashboards to PowerPoint or PDF for an executive review?

Yes. Any dashboard can snapshot to PDF with one click, with the tile layout preserved and the data frozen at the snapshot time. Snapshots can be scheduled to a distribution list on a weekly, monthly, or quarterly cadence. The PDF links back to the live dashboard so the recipient can drill in on a surprising number. For PowerPoint, Strkr can export the dashboard as a set of images that drop into a slide template, with the data stamp on each image so the audience knows when the snapshot was taken. The snapshot is the one artifact that leaves the dashboard, and the dashboard is the one source of truth. No separate BI tool, no PowerPoint deck that drifts out of alignment with the live number.

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