Causal

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Causal
Score 10.0 out of 10
N/A
Causal, from the company of the same name in London, presents a way to perform calculations, visualise data, and communicate with numbers. It helps build models faster, connect them directly to data, and share them with interactive dashboards and visuals. Suggested use cases are financial planning, planning CPC campaigns, track KPIs, or determine employee compensation.
$50
per month
Pricing
Causal
Editions & Modules
Pro
$50
per user, per month
Business
Contact Sales
Offerings
Pricing Offerings
Causal
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
No
Entry-level Setup FeeNo setup fee
Additional Details
More Pricing Information
Features
Causal
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Causal
9.3
1 Ratings
14% above category average
Pixel Perfect reports8.01 Ratings
Customizable dashboards10.01 Ratings
Report Formatting Templates10.01 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Causal
8.3
1 Ratings
6% above category average
Drill-down analysis9.01 Ratings
Formatting capabilities8.01 Ratings
Report sharing and collaboration8.01 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Causal
8.0
1 Ratings
2% below category average
Publish to Web8.01 Ratings
Publish to PDF8.01 Ratings
Report Versioning8.01 Ratings
Report Delivery Scheduling8.01 Ratings
Delivery to Remote Servers8.01 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Causal
8.0
1 Ratings
3% above category average
Predictive Analytics8.01 Ratings
Pattern Recognition and Data Mining8.01 Ratings
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Causal
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User Ratings
Causal
Likelihood to Recommend
10.0
(1 ratings)
User Testimonials
Causal
Likelihood to Recommend
Causal, Inc
Definitely suited best for B2B / B2B2C product modelling. We used this for B2B / B2B2C / C2C and the C2C side of things was always more complex to model out due to this being dependent on marketing spend (CAC) and factors around virality which really cannot be forecasted (not a shortcoming of Causal, just implied by the mechanics of modelling)
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ScreenShots