Build a Custom Marketing Analytics Dashboard Using AI in Minutes
Turn a plain-English description of your Marketing Analytics Dashboard into a production-ready build, from design to deployment, in minutes. No code needed.
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Emergent Key Features for Building a Marketing Analytics Dashboard
Attribution, cohort and incrementality models generated from your own data, with the method visible rather than hidden.
Several Attribution Models Together
First touch, last touch and multi touch results appear side by side, so the choice of model becomes a visible assumption rather than a hidden one.
Customer Level Joining
Spend, touchpoints and revenue are matched at customer level, which is what makes acquisition cost and lifetime value comparable by channel.
Cohort Revenue Tracking
Customers are grouped by acquisition period and followed forward, showing when a cohort repaid its cost and whether recent cohorts are better.
Platform Claim Reconciliation
Reported conversions from each platform are compared against your own record, quantifying the double counting that inflates channel results.
Stated Assumptions
Model logic and windows are shown in the dashboard, so finance can interrogate the method instead of distrusting the output.
New Models on Request
A different window, model or segmentation is added by describing it, so measurement can evolve without a data science project each time.
Marketing Analytics Dashboard Use Cases You Can Build in Minutes
See What Each Attribution Model Actually Claims
Conversions and revenue credited to every channel under first touch, last touch, linear and position based models side by side, with the difference per channel and the average touchpoints behind a conversion.
window.awbMockup = { attributionModelComparison: "Build an attribution dashboard showing conversions and revenue credited to each channel under first touch, last touch, linear and position based models side by side, the difference between models per channel, how many touchpoints an average conversion involves, and which channels gain most under multi touch.", customerAcquisitionCost: "Build a unit economics dashboard calculating blended and channel level customer acquisition cost from total spend and new customers, showing lifetime value by acquisition channel, the resulting value to cost ratio, payback period in months, and which channels acquire customers that retain longest.", marketingIncrementality: "Build an incrementality dashboard comparing periods and regions where spend changed against a holdout or baseline, showing modelled incremental conversions versus platform reported conversions, implied overlap between channels, incremental cost per acquisition, and confidence in the result given the sample.", campaignCohort: "Build a cohort analysis dashboard grouping customers by acquisition month and channel, tracking revenue and retention forward by month, showing cumulative revenue per cohort against acquisition cost, the month each cohort became profitable, and how cohort quality has shifted over the last year."};
Work Out What a Customer Really Costs
Blended and channel level acquisition cost from spend and new customers, lifetime value by channel, the resulting value to cost ratio, payback period in months and which channels acquire customers who stay.
window.awbMockup = { attributionModelComparison: "Build an attribution dashboard showing conversions and revenue credited to each channel under first touch, last touch, linear and position based models side by side, the difference between models per channel, how many touchpoints an average conversion involves, and which channels gain most under multi touch.", customerAcquisitionCost: "Build a unit economics dashboard calculating blended and channel level customer acquisition cost from total spend and new customers, showing lifetime value by acquisition channel, the resulting value to cost ratio, payback period in months, and which channels acquire customers that retain longest.", marketingIncrementality: "Build an incrementality dashboard comparing periods and regions where spend changed against a holdout or baseline, showing modelled incremental conversions versus platform reported conversions, implied overlap between channels, incremental cost per acquisition, and confidence in the result given the sample.", campaignCohort: "Build a cohort analysis dashboard grouping customers by acquisition month and channel, tracking revenue and retention forward by month, showing cumulative revenue per cohort against acquisition cost, the month each cohort became profitable, and how cohort quality has shifted over the last year."};
Test Whether the Spend Was Incremental
Compare periods and regions where spend changed against a holdout or baseline, showing modelled incremental conversions against platform reported ones, implied channel overlap and confidence given the sample.
window.awbMockup = { attributionModelComparison: "Build an attribution dashboard showing conversions and revenue credited to each channel under first touch, last touch, linear and position based models side by side, the difference between models per channel, how many touchpoints an average conversion involves, and which channels gain most under multi touch.", customerAcquisitionCost: "Build a unit economics dashboard calculating blended and channel level customer acquisition cost from total spend and new customers, showing lifetime value by acquisition channel, the resulting value to cost ratio, payback period in months, and which channels acquire customers that retain longest.", marketingIncrementality: "Build an incrementality dashboard comparing periods and regions where spend changed against a holdout or baseline, showing modelled incremental conversions versus platform reported conversions, implied overlap between channels, incremental cost per acquisition, and confidence in the result given the sample.", campaignCohort: "Build a cohort analysis dashboard grouping customers by acquisition month and channel, tracking revenue and retention forward by month, showing cumulative revenue per cohort against acquisition cost, the month each cohort became profitable, and how cohort quality has shifted over the last year."};
Follow Acquisition Cohorts for Years, Not Weeks
Group customers by acquisition month and channel, track revenue and retention forward, compare cumulative revenue per cohort against acquisition cost and see the month each cohort became profitable.
Follow Acquisition Cohorts for Years, Not Weeks
Group customers by acquisition month and channel, track revenue and retention forward, compare cumulative revenue per cohort against acquisition cost and see the month each cohort became profitable.
Build a custom marketing analytics dashboard in 4 simple steps
Move past channel reporting to measurement, with attribution models, incrementality and cohort analysis on your own marketing data.
Start with what you are trying to prove, whether that is which channels create demand, what a customer is worth by source, whether spend was incremental or how long payback takes. Emergent builds the analysis for those questions rather than a channel summary.
Link ad platforms, analytics, CRM and billing so cost, every recorded touchpoint and realised revenue sit in one model. Emergent joins them at customer level, which is the requirement for attribution work that platform reporting cannot do.
Ask for a different attribution window, an extra model side by side or cohorts defined another way, and the analysis rebuilds. Measurement evolves without a data science project each time.
Publish one link showing each model side by side with its assumptions stated. Marketing and finance argue about strategy instead of about whose number is right, because both are reading the same build.
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Why choose Emergent?
Most tools give you a demo you have to rebuild. Emergent gives you a product that is ready to run.
| Comparison | Other Tools |  |
|---|---|---|
| Built for | Demos and MVPs | Products you keep growing |
| What you get | Front end shell only | Full stack, wired end to end |
| Backend and database | Set it up yourself | Built and connected for you |
| Customization | Surface level styling | Deep workflow control |
| Integrations and APIs | Manual glue work | Connected from a prompt |
| Code ownership | Locked to the platform | Clean code you can export |
| Time to launch | Weeks of patching and setup | Live the same day |
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