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AgencyAnalytics vs modelbased

A side-by-side editorial comparison of AgencyAnalytics and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.

AgencyAnalytics vs modelbased: at a glance

FeatureAgencyAnalyticsmodelbased
SectorAnalyticsAnalytics
Velocity score6.30.0
Sparks · 30d10
Top themesagency-reporting, ai-assistant, usage-based-pricing, client-managementeasystats, marginal-effects, contrasts, mixed-models
Last editorial update1d ago1h ago
WebsiteVisit →Visit →

What is AgencyAnalytics?

Reporting features now exist mainly to feed the AI layer sitting on top of them.

AgencyAnalytics is shipping steadily across two tracks. The visible one is reporting ergonomics for agencies managing many clients: regex and contains filtering on custom metrics, client tags applied in bulk, and a Shares tab exposing every way a report has been sent. The second, and the one the roadmap language keeps pointing at, is AgencyAI — which gained saved reusable Skills in August, while the client Data tab was consolidated in July explicitly to give those answers more context to draw on.

Read the full AgencyAnalytics trajectory →

What is modelbased?

modelbased is turning marginal effects into a full contrast grammar

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

Read the full modelbased trajectory →

AgencyAnalytics vs modelbased: editorial side-by-side

A6.3

Reporting features now exist mainly to feed the AI layer sitting on top of them.

◆ Current state

AgencyAnalytics is shipping steadily across two tracks. The visible one is reporting ergonomics for agencies managing many clients: regex and contains filtering on custom metrics, client tags applied in bulk, and a Shares tab exposing every way a report has been sent. The second, and the one the roadmap language keeps pointing at, is AgencyAI — which gained saved reusable Skills in August, while the client Data tab was consolidated in July explicitly to give those answers more context to draw on.

◆ Where it's heading

The company is converting a reporting tool into an analysis layer, and monetising the AI separately — AI Tracker went to open beta as a metered add-on at twenty-five dollars per 250 credits rather than as an included feature. Each structural change now gets justified by what it gives AgencyAI to work with, which suggests the reporting surface is being reorganised around the assistant rather than the other way round. Data-source maintenance continues underneath, including removing a Microsoft Ads metric the upstream API could not support accurately.

◆ Prediction

Expect the Data tab to keep absorbing client context types as promised, and further metered AI capability to follow AI Tracker out of beta on the same credit model.

M
modelbased
ANALYTICS
0.0

modelbased is turning marginal effects into a full contrast grammar

◆ Current state

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

◆ Where it's heading

The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.

◆ Prediction

With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.

Alternatives to AgencyAnalytics and modelbased

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either AgencyAnalytics or modelbased.

See all AgencyAnalytics alternatives → · See all modelbased alternatives →

Recent activity from AgencyAnalytics and modelbased

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1d agoAgencyAnalyticsAdvanced filtering for custom metrics and KPIs
  2. 1d agoAgencyAnalyticsOrganize your clients your way with tags
  3. 6d agoAgencyAnalyticsReport Shares View
  4. 6d agoAgencyAnalyticsSkills in AgencyAI
  5. 16d agoAgencyAnalyticsEverything about your client's data, now in one tab
  6. 1mo agoAgencyAnalyticsMicrosoft Ads: Impression Share metric removed
  7. 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
  8. 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
  9. 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
  10. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  11. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  12. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures

Frequently asked questions

What is the difference between AgencyAnalytics and modelbased?

They serve adjacent needs but don't currently overlap on shipped themes. AgencyAnalytics is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is AgencyAnalytics better than modelbased?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. AgencyAnalytics is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to AgencyAnalytics?

Top AgencyAnalytics alternatives in Analytics are ranked by recent ship velocity. Browse the "AgencyAnalytics alternatives" section above for the current picks, or visit /alternatives/agencyanalytics for the full list with editorial commentary on each.

What are the best alternatives to modelbased?

Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.