Skip to content
SPECIFICTION
Get listed

Akkio vs WorthSignal

Akkio

akkio.com

WorthSignal

github.com

Side by side

FigureAkkioWorthSignal
Price from—Free
Free plan—Yes
Free trialYes—
Open source——
WebYesYes
Windows—Yes
macOS—Yes
Linux—Yes
APIYes—
Self-hostedYesYes
Plans published11
Spec score · Customer Lifetime Value Software8.1 (#8)7.9 (#12)
HeadquartersCambridge, Massachusetts, United StatesNorway
IntegrationsListed integrations include Databricks, MongoDB, Amazon Redshift, PostgreSQL, MySQL, MariaDB, Google Analytics 4, HubSpot, Airtable, Snowflake, BigQuery, Salesforce, Google Sheets, and Zapier.The README documents file-based input and Excel or JSON downloads, and says the app can be deployed on Streamlit Community Cloud from a GitHub repository.

Plans

Akkio

  • Enterprise AI Analytics PlatformPriced on request

Akkio pricing →

WorthSignal

  • WorthSignalFree

WorthSignal pricing →

In their own words

Akkio

Akkio has no write-up on Specifiction yet; its figures are above.

Visit akkio.com

WorthSignal

WorthSignal is a free, open-source toolkit that turns spreadsheet and data files into customer value analyses for marketers. It reads XLSX, XLS, XLSM, CSV and JSON files, suggests column mappings and lets users correct them without changing the uploaded file. Its analyses cover nine areas, including RFM targeting, customer lifetime value, customer equity, acquisition and retention budgets, Markov switching ROI, contractual retention, BG/NBD, BG/BB and complaint recovery. Results can be downloaded as Excel or JSON. In local mode, analysis runs in memory on the user's computer; WorthSignal says uploaded customer data is not intentionally sent to its maintainer or a third-party API. Hosted deployments process files on the chosen server, and that operator is responsible for access controls, logs, retention and privacy obligations. The app requires Python 3.10 or newer and can be launched on Windows or Mac, through terminal instructions for any operating system, or with Docker. Its documented methods are described as classic, deliberately simple models. The project uses the AGPL-3.0-or-later license, with commercial use subject to its conditions.

Visit github.com