Multi-Tenant Analytics Platform

Build Less.
Deliver More.

One solution. Unprecedented time to value.
The only turnkey multi-tenant analytics solution that empowers development teams to ship faster and reduce maintenance.

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multi-tenant analytics

The Only Purpose-Built Solution for Multi-Tenant Analytics

The multi-tenant analytics platform for SaaS applications with a unified data pipeline that empowers development teams to ship fast regardless of data source, data type or front-end framework.

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Easy to Implement Permissions

A native semantic layer that inherits tenant and user level security models

Scalable Data Lake

Built-in data lake optimized for scalable tenant isolation for embedded analytics

Full Suite of APIs

Analyze more with APIs built for data ingestion and reporting

HOW IT WORKS

A Full-Stack Approach to Multi-Tenant Analytics

As self-hosted software, Qrvey gives you the flexibility to go from data to analytics using a single data pipeline, eliminating data transfers, and costs associated with building in-house.

STEP 1

Deploy

Qrvey is a fully deployed solution. You get the best of security and scalability within your cloud platform utilizing easy to manage deployment packages built on serverless technology.

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STEP 2

Connect

Using native data connectors and push APIs, you can connect to any data warehouse or database to ingest data of any type opening up the possibilities of what you can offer users.

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STEP 3

Integrate

Connect the built-in data lake to your SaaS application using a suite of APIs you can easily map to your tenants, users and permission structure without duplicating users and roles.

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STEP 4

Analyze

Using JS-based embedded data visualization widgets or reporting APIs, you can be up and running fast offering customizable analytics experiences your users will love.

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CASE STUDY

See How JobNimbus deployed Qrvey to 6,000 customers and saw an immediate reduction in customer churn.

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USE CASES

A Solution For Any Challenge You May Face

With a purpose-built, multi-tenant analytics platform for SaaS applications, the possibilities are endless.

custom data model

Custom Data Models Per Tenant

Create unlimited data models down to the tenant and user level to empower users to analyze data differently based on their own requirements.

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Personalize Any Data Visualization

By offering visualization widgets and APIs, you can create personalized experiences tailored to user needs.

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Analyze Multiple Data Sources On One Dashboard

Visualize data from different sources on the same dashboard mixing synced and live data sources to reduce querying costs.

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custom deployment

Deploy Assets to Specific Tenants

With a content deployment system designed for multi-tenancy, you can release new content to users incrementally, create betas or MVPs.

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REVIEWS FEATURED ON G2

More Insights

multi-tenant analytics

Why is Multi-Tenant Analytics So Hard?

BLOG

Creating performant, secure, and scalable multi-tenant analytics requires overcoming steep engineering challenges that stretch the limits of...

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grow revenue

Pricing Strategies to Maximize Revenue from Analytics

GUIDE

Unlock the full potential of your SaaS business with our comprehensive guide on pricing and packaging strategies. 

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jobnimbus case study

How JobNimbus deployed Qrvey to 6,000 customers

CASE STUDY

Discover how JobNimbus deployed Qrvey to 6,000 customers and saw an immediate reduction in customer churn....

Read The Case Study

FAQs About

Multi-Tenant Analytics

Multi-tenant analytics for SaaS applications refers to analyzing data from many different customers (tenants) within a single platform. Unlike traditional analytics solutions where each customer gets their own isolated environment, multi-tenant uses a shared infrastructure while keeping each tenant’s data secure and separate. This makes it a flexible and efficient way for SaaS companies to provide analytics capabilities to their users.

Scalability and Cost-Effectiveness: One platform can serve numerous customers, reducing infrastructure and development costs per user.

Reduced Time to Insights: Analytics and reporting capabilities are readily available, empowering tenants to make data-driven decisions quickly.

Improved Engagement and Retention: Granular insights empower tenants to optimize their experience with the SaaS application, leading to better engagement and lower churn.

Product Development Insights: Analyzing aggregated, anonymized data across tenants provides valuable insights for product improvements and future features.

These are some examples of use cases for multi-tenant analytics by SaaS companies:

Customer-facing dashboards: Tenants can analyze their own usage data, track KPIs, and monitor performance within the SaaS application.

Embedded analytics: Integrate real-time insights directly into the application interface, offering users actionable information at their fingertips.

Benchmarking and insights: Compare individual performance against anonymized industry or peer group data for competitive benchmarking and strategic decision-making.

Product usage analysis: Aggregate and analyze usage data across all tenants to identify trends, understand common pain points, and make informed product development decisions.

Sales and marketing analysis: Track campaign performance, analyze customer acquisition costs, and identify high-value customer segments for targeted marketing efforts.

Financial and operational reporting: Generate reports on key financial metrics, resource utilization, and operational efficiency across the entire customer base.

While building your own multi-analytics solution might seem tempting for complete control and customization, in most cases, it’s actually better for SaaS companies to buy a purpose-built solution. Here’s why:

Time and Cost Efficiency:

  • Buy: Ready-made solutions are available quickly, reducing development time and resource allocation. You avoid hefty up-front costs associated with building, testing, and launching your own platform.
  • Build: Expect significant investments in development, testing, maintenance, and ongoing updates. Launching can take months or even years, delaying value realization.

Expertise and Features:

  • Buy: Dedicated vendors focus on multi-tenant analytics – also known as embedded analytics – offering advanced features, integrations, and security protocols unavailable in-house. Regular updates ensure you benefit from the latest advancements.
  • Build: Achieving similar feature parity requires a dedicated team with expert knowledge and ongoing research, which can be expensive and drain resources from core tasks.

Focus on Core Business:

  • Buy: Free up your team to focus on product development, customer support, and marketing, where your specific value lies.
  • Build: Diverting resources to build and maintain analytics becomes a secondary focus, potentially impacting core business activities.

Scalability and Maintenance:

  • Buy: Purpose-built solutions are designed to scale seamlessly with your customer base, eliminating concerns about infrastructure and maintenance burdens.
  • Build: Scaling your own solution may require costly infrastructure upgrades and additional development efforts, increasing complexity.

Security and Compliance:

  • Buy: Established vendors prioritize security and compliance with industry regulations, reducing your risk and liability.
  • Build: Ensuring robust security and compliance requires specialized expertise and ongoing monitoring, adding to your responsibilities.

Data Privacy:

  • Buy: Reputable vendors have established data privacy protocols and ensure tenant data remains secure and separate.
  • Build: Implementing robust data privacy measures becomes your responsibility, requiring significant expertise and resources.

Ongoing Support:

  • Buy: Benefit from dedicated support teams specializing in the analytics tool, ensuring smooth operation and resolution of any issues.
  • Build: Relying on your own team for troubleshooting and updates can be time-consuming and expensive.

However, the decision isn’t always black and white. Consider these factors before making a choice:

  • Unique needs: If your analytics requirements are highly specific and differ significantly from standard options, building might be justifiable.
  • Technical expertise: Does your team have the necessary skills and bandwidth to build and maintain a complex solution?
  • Budget: Can you afford the initial and ongoing costs associated with building and maintaining your own platform?

Remember, even large companies with significant resources often opt for buying multi-analytics solutions due to the efficiency and expertise they offer. Carefully evaluate your specific needs and resources before making a decision that suits your company’s best interests.

See Qrvey in Action!

Learn about Qrvey’s embedded analytics platform and get quick answers to your questions by scheduling a demo with one of our embedded analytics experts. See why we’re the logical choice for SaaS companies like you.

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