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Business Intelligence · head to head

Quantum Metric vs Sisense

Quantum Metric logo

Quantum Metric

Business Intelligence

Continuous product design platform

From
On request
Rated
-
Sisense logo

Sisense

Business Intelligence

Infuse analytics everywhere

From
$10000/year
Rated
-

The short version

  • Each has a real cost: Quantum Metric only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum; Sisense pricing lacks transparency with opaque scaling costs and hidden fees for onboarding and training
  • They diverge on capability: Quantum Metric covers Session Replay, Sisense covers Embedded Analytics.

Where they differ

Only the attributes on which Quantum Metric and Sisense actually diverge.

Attributes where Quantum Metric and Sisense differ
AttributeQuantum MetricSisense
Starting priceOn request$10000/year
Pricing modelsubscriptionUnknown
PlatformsWeb, MobileWeb, Cloud, On-premises
Founded20152004

Identical on both: free tier (No), user rating (Not yet rated), category (Business Intelligence).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Quantum Metric

  • Session Replay
  • Opportunity Analysis
  • Anomaly Detection
  • Real-time Alerts
  • Impact Scoring
  • Adobe Analytics
  • Google Analytics
  • ServiceNow

Only in Sisense

  • Embedded Analytics
  • AI/ML Integration
  • In-chip Technology
  • White-labeling
  • REST API
  • Snowflake
  • AWS
  • Azure

Both cover

  • Salesforce
  • Web support
  • Mobile support

What people use each for

The jobs each tool is most often brought in to do.

Quantum Metric

  • Session replay and digital experience analytics for large web and mobile propertiesnot Sisense
  • Quantifying friction and conversion loss in checkout and signup flowsnot Sisense
  • Streaming behavioural insights into a data warehousenot Sisense

Sisense

  • Self-service analyticsnot Quantum Metric
  • Data explorationnot Quantum Metric
  • Ad-hoc reportingnot Quantum Metric
  • Collaborative analysisnot Quantum Metric
  • Embedded analyticsnot Quantum Metric

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Quantum Metric

  • Only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum
  • The page states plans are built around your business, with the only routes being a personalised discussion, a live demo or product tours
  • There is no self-serve tier, free plan or trial published

Sisense

  • Pricing lacks transparency with opaque scaling costs and hidden fees for onboarding and training
  • Limited connector ecosystem compared to competitors; missing native connectors to many data sources
  • Dashboard customization options are limited; widgets cannot span multiple rows, restricting layout possibilities
  • Performance issues reported with large datasets and stability problems with data cubes

Pricing, plan by plan

Quantum Metric

On request
  • CustomFree
    • Full Platform
    • Real-time Analytics
    • Enterprise Support

Sisense

$10000/year
  • Small Team$10000/year minimum
    • Basic analytics dashboards
    • Limited data sources
  • Mid-Market$null/custom
    • Advanced analytics
    • Multiple data sources
    • Custom integrations
  • Enterprise$60000/year+
    • Advanced AI analytics
    • Premium support
    • Custom development

Which should you pick?

Choose Quantum Metric if

  • You need session replay.
  • You work on Web, Mobile.
  • You also want opportunity analysis.

Choose Sisense if

  • You need embedded analytics.
  • You work on Web, Cloud, On-premises.
  • You also want ai/ml integration.

Questions people ask

Is Quantum Metric or Sisense better?
Neither clearly leads. Quantum Metric starts at On request and Sisense at $10000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Quantum Metric or Sisense?
Quantum Metric starts at On request and Sisense at $10000/year.
Does Quantum Metric or Sisense run on more platforms?
Quantum Metric runs on Web, Mobile. Sisense runs on Web, Cloud, On-premises.
What is Quantum Metric best used for?
Quantum Metric is most often used for session replay and digital experience analytics for large web and mobile properties, quantifying friction and conversion loss in checkout and signup flows, streaming behavioural insights into a data warehouse. Of those, session replay and digital experience analytics for large web and mobile properties and quantifying friction and conversion loss in checkout and signup flows are not what Sisense is typically brought in for.
What can Quantum Metric do that Sisense cannot?
Quantum Metric covers Session Replay, Opportunity Analysis, Anomaly Detection, Real-time Alerts. Sisense covers Embedded Analytics, AI/ML Integration, In-chip Technology, White-labeling. Both handle Salesforce, Web support, Mobile support.

Answered from the vendors’ own pages

Sisense: What is Sisense primarily used for?

Sisense is an embedded analytics platform that combines data ingestion, modeling, and dashboarding, allowing organizations to embed analytics and insights directly into their applications and workflows.

Source
Sisense: Does Sisense have a transparent pricing model?

Sisense pricing is not publicly listed and requires contacting sales. Typical costs start at $10,000 per year for small teams but can scale to $60,000+ annually depending on users, data volume, number of data sources, and complexity. AI capabilities typically add 20-30% to base costs.

Source
Sisense: What data sources can Sisense connect to?

Sisense provides pre-built connectors for popular applications including Salesforce, Google Analytics, Zendesk, and others. It also supports custom connections through APIs and SDKs for specialized data sources.

Source
Sisense: Is Sisense easy to use for non-technical users?

Sisense requires significant technical expertise to set up, particularly for creating Elasticubes (database caches) which often need SQL code. While it promotes codeless reporting, typical implementations require a technical resource.

Source

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