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rfm vs susier

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

Shared themes:r-package

rfm vs susier: at a glance

Featurerfmsusier
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, customer-analytics, segmentation, dependenciesr-package, statistical-genetics, fine-mapping, cpp-bindings
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is rfm?

A customer segmentation package that went quiet for six years and returned with dependency hygiene

rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.

Read the full rfm trajectory →

What is susier?

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

Read the full susier trajectory →

rfm vs susier: editorial side-by-side

R
rfm
ANALYTICS
0.0

A customer segmentation package that went quiet for six years and returned with dependency hygiene

◆ Current state

rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.

◆ Where it's heading

The 0.4.0 release says more about maintenance posture than about product direction — the version jump past 0.3.x with only two bug fixes and a dependency reshuffle suggests a package being brought back to a releasable state rather than resuming development. Promoting plotly and gganimate to Imports makes the visualization stack mandatory, which is a heavier install in exchange for a simpler code path. The core RFM computation itself has not changed in this window.

◆ Prediction

The entries show a package returning from dormancy rather than pursuing a roadmap, so further small fixes are more likely than new segmentation capability.

S
susier
ANALYTICS
0.0

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

◆ Current state

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

◆ Where it's heading

The version-number churn understates how narrow this work is — four consecutive releases touching the same trimming and residual-variance machinery suggests one area where the implementation and the intended behavior had drifted apart. The 0.16.0 binding migration is the only structural change, and it is invisible to users while mattering for build portability and long-term maintenance. Development is clearly active, with automated release tooling and dependency bumps flowing through the same stream.

◆ Prediction

With the binding migration just landed, near-term releases are likely to address fallout from it alongside continued fixes in the same trimming and residual-variance code.

Alternatives to rfm and susier

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 rfm or susier.

See all rfm alternatives → · See all susier alternatives →

Recent activity from rfm and susier

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

  1. 3mo agorfmrfm 0.4.0
  2. 3mo agosusierMigrates C++ bindings from Rcpp to cpp11 and cpp11armadillo
  3. 3mo agosusierFixes alpha0/beta0 handling under Servin-Stephens
  4. 4mo agosusierCorrects the null space ELBO term for RSS with X
  5. 5mo agosusierFixes null effect trimming with non-uniform prior weights
  6. 5mo agosusierFixes null effect trimming under Servin-Stephens estimation
  7. 6y agorfmrfm 0.2.2
  8. 6y agorfmrfm 0.2.1
  9. 7y agorfmrfm 0.2.0
  10. 8y agorfmrfm 0.1.1
  11. 8y agorfmrfm 0.1.0

Frequently asked questions

What is the difference between rfm and susier?

Both compete on the same themes — r-package — within Analytics. rfm and susier are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is rfm better than susier?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rfm and susier are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to rfm?

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

What are the best alternatives to susier?

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