tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of AgencyAnalytics and textrecipes — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Text features finally stay sparse all the way to the model.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
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.
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.
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.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
Two forces drive this package. One is memory: text produces wide, mostly-zero matrices, and the sparse work is the direct answer, landing in the same period that workflows learned to fit and predict on dgCMatrix input. The other is upstream churn — the tweets tokenizer was deprecated because tokenizers deprecated it, the politeness feature disappeared when textfeatures left Suggests. The package's own agenda is consistency; its release timing belongs to its dependencies.
Expect the sparse argument to spread to the remaining column-producing steps, since only four of them have it, and expect more steps to be reworked as recipes' own sparse-data support matures.
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 textrecipes.
Finished, widely taught, and shipping roxygen fixes.
The package that made calibration a step instead of an afterthought.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork stopped being a ggplot composer and became a page composer.
See all AgencyAnalytics alternatives → · See all textrecipes alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
Top textrecipes alternatives in Analytics are ranked by recent ship velocity. Browse the "textrecipes alternatives" section above for the current picks, or visit /alternatives/textrecipes for the full list with editorial commentary on each.