Keen

Name: Keen
Brand: Keen

Powerful stories, told simply.

Est 2000|2 Ref Customers

LinkedIn 129|Website|FTEs 13|HQ New York, New York, US

01Competitive Landscape

Narrative analysis: where alternatives excel

- For out-of-the-box product analytics (funnels, cohorts, experiments, session replay), Mixpanel and Amplitude offer faster self-serve insights for non-engineering stakeholders. - For clearer cost predictability and explicit spending caps, tools with event-based pricing and advertised spending limits may be preferable. - For extensive relational analytics (joins) and heavy modeling, a warehouse + BI approach (BigQuery/Snowflake combined with a BI tool) often provides more flexibility at the expense of additional engineering and operations.

When customers choose competitors instead

When buyers prioritize a product analytics user interface for non-technical stakeholders with minimal custom engineering.
When budgeting requires a clearer events-in = cost model and explicit spending caps.

	Keen (keen.io)	Mixpanel	Amplitude	PostHog
Starting Price	Usage-based; compute priced by "properties scanned" (pricing not displayed as simple tiers)	Free tier; paid plans increase with events (public pricing)	Starter free; paid tiers available (public pricing)	Free tier; usage-based after free limits
Typical Use Case	Developer teams embedding custom analytics dashboards into a SaaS product; control over event schema and queries	Product teams needing an out-of-the-box product analytics UI	Product organizations needing MTU-based analytics and experimentation features	Teams wanting an open, product-led stack with analytics and feature tools; explicit billing controls
Notable Features	API-oriented custom analytics and embedding tools; visualization libraries and embedding components	Mature product analytics UX, standard reports, and broad feature set for product teams	Integrated analytics and experimentation feature set	Generous free tier and billing limit options; self-host or cloud deployment options
Considerations	Read/query pricing model can be difficult to forecast; fewer out-of-the-box product analytic features; limitations on joins/data mutation	Less suited for fully bespoke white-labeled analytics without additional engineering	Pricing can increase with scale depending on MTUs; enterprise upsell paths	More self-serve setup required to reach equivalent embedded analytics maturity

01Competitive Landscape

Narrative analysis: where alternatives excel

For out-of-the-box product analytics (funnels, cohorts, experiments, session replay), Mixpanel and Amplitude offer faster self-serve insights for non-engineering stakeholders.
For clearer cost predictability and explicit spending caps, tools with event-based pricing and advertised spending limits may be preferable.
For extensive relational analytics (joins) and heavy modeling, a warehouse + BI approach (BigQuery/Snowflake combined with a BI tool) often provides more flexibility at the expense of additional engineering and operations.

When customers choose competitors instead

When buyers prioritize a product analytics user interface for non-technical stakeholders with minimal custom engineering.
When budgeting requires a clearer events-in = cost model and explicit spending caps.

	Keen (keen.io)	Mixpanel	Amplitude	PostHog
Starting Price	Usage-based; compute priced by "properties scanned" (pricing not displayed as simple tiers)	Free tier; paid plans increase with events (public pricing)	Starter free; paid tiers available (public pricing)	Free tier; usage-based after free limits
Typical Use Case	Developer teams embedding custom analytics dashboards into a SaaS product; control over event schema and queries	Product teams needing an out-of-the-box product analytics UI	Product organizations needing MTU-based analytics and experimentation features	Teams wanting an open, product-led stack with analytics and feature tools; explicit billing controls
Notable Features	API-oriented custom analytics and embedding tools; visualization libraries and embedding components	Mature product analytics UX, standard reports, and broad feature set for product teams	Integrated analytics and experimentation feature set	Generous free tier and billing limit options; self-host or cloud deployment options
Considerations	Read/query pricing model can be difficult to forecast; fewer out-of-the-box product analytic features; limitations on joins/data mutation	Less suited for fully bespoke white-labeled analytics without additional engineering	Pricing can increase with scale depending on MTUs; enterprise upsell paths	More self-serve setup required to reach equivalent embedded analytics maturity

Keen

01Competitive Landscape

Narrative analysis: where alternatives excel

When customers choose competitors instead

02Market Map

01Competitive Landscape

Narrative analysis: where alternatives excel

When customers choose competitors instead

02Market Map