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Customer Analytics Platform

Understand Your User Engagement without Creating Data Silos

Scale customer insights securely to all corners of your organization.

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Enterprises make significant investments in centralizing their data to understand the full journey of a customer. Why send it out to a third party to be analyzed?
Get the most out of your governed data warehouse with Kubit’s purpose-built self-service reports.

Key features

Time Series Analysis

Visualize metrics over time and break down to analyze performance.
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Funnel Conversions

Understand how customers are converting through key flows within your product.
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Behavioral Cohorts

Create cohorts on the fly to further analyze individuals contained within your data points.
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User Paths

Customize a user path based on the experience or the audience to understand customer experience.
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User Retention

Measure your product’s stickiness by analyzing both retention and usage intervals.
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Kubit customer analytics solution

Get a peek into Kubit and explore product analytics features such as engagement, user paths, conversion, retention, and cohort analysis.
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Time Series Analysis

Visualize metrics over time using Kubit’s Query report. You can break down metrics by valuable data points to quickly surface high and low performance. Drill deeper into each data point for granular information. Data can be visualized using line bars, stacked bars, or pie charts.

Use Cases

eCommerce

See average revenue per user by brand or country to understand high or low performance.

Streaming

Contrast percentage of total minutes watched by new users against existing users to understand how much impact they have.

B2B

Report on all businesses and their engagement metrics sliced by any characteristic.

Funnel Conversion

Understand how customers are converting through key flows within your product. Within a funnel, you can see drop-off and conversion metrics with the ability to break down or segment funnels based on additional data. Data can be visualized using traditional conversion, conversion over time, and frequency before conversion.
kubit Funnel Conversion | Product Analytics

Use Cases

eCommerce

Identify points of friction within the purchase funnel and react quickly to respond to customer need.

Streaming

Compare new user onboarding to their first watch by various marketing campaigns to understand which is performing best at driving engagement.

B2B

Measure feature adoption for an entire organization or by each user to better predict customer health and retention.

User Retention

Learn which users return, or never come back to utilize core features and how consistently they retain in the following days. You can construct a retention model that fits your needs as well as decide how you want to visualize this critical metric whether it be retention or churn rates. You are able to analyze your Retention Model as a standard retention curve, retention over time, or usage intervals.

Use Cases

eCommerce

Understand long and short term retention of users who purchase items with a coupon or promotional code and see if that truly increased their likelihood of additional purchases.

Streaming

Learn about “binge watchers” and what subset of users you may want to exclude from future marketing campaigns, saving dollars and resources.

B2B

Visualize the Monthly Churn metric broken down by customer tier to understand what area could need intervention to mitigate churn. Once identified, you can segment those with high churn potential by the core features they leverage and understand their impact.

Behavioral Cohorts

Further analyze individuals contained within your data points. You can create cohorts on the fly or by defining them in the Cohort builder. Once a cohort is created, you can reuse it as a segment in any analysis, compare two cohorts, or sync them to a third-party tool to drive targeted outreach.

Use Cases

eCommerce

Create cohorts from dropped-off users and retarget them to send a push motivating them to complete their purchase.

Streaming

Target a group that has high affinity for a specific content group and promote new content to drive engagement.

B2B

Build a robust cohort that aims to target users that have not engaged in a new feature and visualize their paths through the product to best place in-product messages.

User Paths

Paths are some of the most powerful ways to understand exactly what is happening within the majority of your users’ experiences. Customize a path in Kubit based on the experience or audience, or break down two paths to see them side-by-side. Paths are visualized using pathing, top paths, and path adjustment to remove noise.
kubit User Path | Product Analytics

Use Cases

eCommerce

View the top paths of users who go from a product page to checkout and ensure the path is clear—or see if they are getting lost.

Streaming

Visualize paths of iOS vs. Android users to identify why one platform performs better than the other.

B2B

If a new user sign-up flow is particularly complex, use path analysis to identify which steps could be consolidated and when users exist without completing all items.

Kubit product analytics

Give your team easy access to product analytics without disrupting your data warehouse strategy. Contact us to book a demo.
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“Within a month of onboarding Kubit we were able to analyze and improve our onboarding flows, increasing ROI by over 30%, which paid for the whole year of service many times over.”
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Daniel Todd

CEO, Influence Mobile

Frequently Asked Questions

What is customer analytics?

Customer analytics provides businesses with methods and tools to collect, validate, and analyze customer data across various channels to better understand customer needs and make more informed business decisions. In a nutshell, customer analytics provides the insights needed for businesses to anticipate, respond to, and prepare for the demands of their customers…and ultimately win and retain more business.

Using customer analytics, businesses can group their customers based on certain data points and use that information to deliver optimized customer experiences. There are various ways of approaching customer analytics, depending on the type of insights you’re looking for:

  • Collecting user data provides you with details about individual customers.
  • Collecting engagement data reveals information about the ways that customers are interacting with your brand through digital channels.
  • Collecting behavioral data helps you understand how customers have behaved in the past to help you predict how they will behave in the future.
  • Collecting attitudinal data helps you understand customer sentiments about your brand.
  • Collecting product analytics data gives digital businesses such as providers of ecommerce, digital apps, and media and entertainment a data-driven method of understanding exactly how users are engaging within their digital products.

By using the various tools and methods available for customer analytics to gain a more in-depth understanding of the customer experience, businesses can leverage these insights to increase customer engagement and retention to support innovation that is more directly aligned to customer needs.

For product managers that want to learn as much as possible about the customer experience within their digital product so they can identify high-value areas for optimization, warehouse-native customer analytics tools enable them to increase the quality and velocity of their decision-making using the power of their own data warehouse. When you want to understand the complete journey and experience of your customers, product analytics is your go-to tool.

Today’s customers expect an excellent customer experience, and in the current competitive climate, businesses can’t risk not delivering. That’s why many businesses rely on customer analytics to drive data-driven decision making and guide strategic initiatives to improve customer engagement, boost customer retention, and provide more personalized experiences.

Customer analytics can benefit many different teams organization-wide, including:

  • Product managers: Analyze behavioral cohorts, user paths, retention, and conversion metrics, leveraging a trusted data set with their own data warehouse. Use their data as a single source of truth to explore, iterate, and take decisive actions to innovate with confidence.
  • Data scientists: Empower the entire organization to do more with their data by deploying self-service product analytics, leveraging the existing data model. Deliver reliable data that can be leveraged by all product, analytics, and marketing teams via a self-service UI. Ensure best-in-class governance and security tethered to their data warehouse.
  • Sales leaders: Understand customer behaviors such as usage patterns and customer journey, which features are most valuable, and which features drive conversion. Better understand different market segments and their unique needs. Train the sales team to focus on the features that drive the most value for customers.
  • Executive leadership: CEOs and those in executive leadership can use product analytics to make more informed, data-based, strategic decisions about the future of digital products. When the C-level endorses and engages in a data-driven culture from the top, it creates an environment that encourages the use of data in making decisions at every level in the organization.

When optimally deployed, product analytics reveals numerous paths and opportunities to better engage customers across the entire customer experience journey. With product analytics, organizations can take a data-driven approach to optimizing customer experiences using up-to-date insights about the ways that users are interacting with digital products. Product analytics supports organizations to exceed user retention goals, reduce churn rate, and foster customer loyalty.

Kubit is the first warehouse-native product analytics platform with zero-ETL. It fully leverages cloud data warehouses and data-sharing capabilities of the modern data stack. Its unique architecture reduces engineering efforts and can deliver actionable insights from your cloud data warehouse within a week.

The best way of getting started with customer analytics is not by copying a proprietary data model developed a decade ago by one of the traditional platforms. The new stage of data modeling is specifically designed for your product and your business and can adapt to your specific needs. With Kubit, you can use your data warehouse and data model of choice. Kubit delivers live insights from your custom data model and leverages your clickstream events with operational data dynamically. No data silos, no complex batch jobs, only one single source of truth that enables self-service analytics via SQL.

Kubit offers integrations with many different cloud data warehouses, including:

  • Snowflake
  • Databricks
  • Google BigQuery
  • Amazon Redshift
  • Azure
  • Presto
  • Vertica
  • ClickHouse
  • Apache Hive

But we know that you need flexibility to get the maximum ROI from a combination of top-tier technologies. That’s why we created Kubit to align with all data architectures in an ever-evolving world of modern data stacks.

Kubit will meet you where you are on your journey, supporting you in getting the most out of your current data investments. At Kubit, we always say that the best time to start product analytics is now. You will benefit from access to actionable insights today that will enable downstream use cases tomorrow.

Technology partners that integrate with Kubit:

  • Snowplow
  • Eppo
  • Braze
  • Hightouch
  • Segment
  • mParticle
  • Rudderstack
  • Amperity
  • Amazon Web Services

Kubit’s warehouse-native approach to customer analytics provides a lower cost of ownership for businesses, frees up their engineering resources, and delivers more complete and accurate self-service insights. Our customers can rest assured that compliance requirements are met because data never leaves their cloud data warehouse. Total cost ownership of customer analytics is less than with other solutions, deployment is six times faster, and scaling is easy.

Customer intelligence involves gathering data about your customers from both internal and external sources that helps you better understand their wants, needs, and how they behave. Examples include their purchase history, their feedback, and their interactions with your brand on social channels. Customer intelligence uses insights from data provided by customer relationship management (CRM) systems.

Customer analytics dives deeper than customer intelligence, applying business intelligence to digital product use cases and enabling numerous teams within an organization (Product, Marketing, Growth) to understand how users are engaging within digital products. It collects data from your digital product, such as an app, streaming platform, website, online store, or connected device. This requires using a tool that is specific to product analytics to deliver insights, which focuses primarily on time series data and typically resorts in cohorts or user segments based on behavior.

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