Houseware Analytics: Powerful ways to get signal from your Product

Businesses today are gathering a ton of first-party data including data on user actions, attributes, behaviours and so on. With ambitious growth goals and a customer-first approach, there is a lot of emphasis on optimising and making the most of this data. And it makes total sense, this data in addition often reveals hidden preferences, priorities, as well as frustrations that customers face with your products.

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Over the past few years, to manage this treasure trove of data more effectively, we see teams moving to a central data warehouse like Snowflake or BigQuery. On top of this data, we see teams delve into product data analytics to make better decisions. Some of the most common ways to do this is by analysing user behaviour, measuring the key performance indicators (KPIs), and optimising your digital strategy.

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However, there is a challenge: you need to connect your data warehouse with your product analytics platform to gain these product analytics insights. The way traditional analytical tools have been solving for this is rather tedious: relying on SDKs or ETL processes to copy this product data into their product analytics tool to generate fragmented insights. This is a long and unreliable process that could take weeks to complete, can be incredibly expensive, and can hurt data security especially if you are in a security-first environment.

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That's where Houseware comes in — a warehouse-native product analytics platform, with the power of AI, and an advanced data modelling technique.

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Instead of copying customers' data from their existing data warehouse, Houseware simply works on top of your data warehouse. You do not have to do any ETL to transfer your data into Houseware. In addition to this the Terra model of analytics helps you find revenue-impacting insights, create omni-channel visibility, and simplify your analysis with AI.

Houseware Analytics: The 3rd Gen of Product Analytics

Houseware offers impressive features that help you analyze your event data, attributes, and aggregates from a host of touchpoints, channels, tools, and teams.

Funnels

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Funnel analysis helps you understand how your users get through each step required to reach a particular outcome. It maps out the flow and steps your users need to take to carry out specific actions and where they drop out of the funnel. It helps you identify the potential areas of friction and take action to make it easier for your customers.

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For example, you can utilize funnels to visualize how many users complete onboarding post signup and understand if they face any issues. You can then modify the workflow, simplify the messaging, or remove a few steps to improve the onboarding experience.

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Houseware Funnels breaks down the user journey into sequential steps and helps you identify:

• Where your users drop out of the funnel.
• What is their experience while navigating through your product?
• How you can simplify the user journey to build positive experiences.

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Flows

User path analysis or flow analysis helps you determine how users navigate your product, interact with the on-screen elements, and reveal the routes they frequently use to carry out specific actions. Like Funnels, flow analysis helps you identify the pain points that might prevent users from completing certain actions in your product. It also enables you to understand how your product's UI supports users with product usage.

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For example, using the Flows tool, you can check how a UX change in your product pages affects user behavior.

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Houseware Flows helps you build a frictionless customer experience by identifying:

• Where your users are dropping off.
• If there is any problem with the workflows you created.
• How many users are completing the different steps of the workflow?

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Trends

Trend analysis examines your current and historical user data to identify patterns or patterns in their behavior over time. It provides valuable insights into users' actions, allowing you to predict future trends or events and make better product decisions. It helps you gauge the users' interest in your products and predicts future outcomes.

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Houseware Trends sifts through large volumes of user data and analyzes it to spot trends at a glance. It helps you analyze and compare:

• User data from different geographical locations can be used to customize your product offerings for each region.
• Feature usage should be used over time to observe how the users perceive it.
• How users on different subscription plans engage with your product features.

Retention

Retention analysis provides intelligent insights into your user data to understand customer retention and your product's long-term viability. It helps you learn why your users are churning so that you can optimize your product experience accordingly and encourage them to stay.

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The retention feature gives you valuable insights into keeping your users and preventing them from switching to competitors. It answers questions such as:

• Why is your churn rate so high?
• Why has your retention rate suddenly observed an upward trend?
• Which user cohorts are more likely to opt for a paid plan?
• Which type of users typically churn?

Stickiness

Product stickiness measures the tendency of users to continue engaging with your product, thus increasing the customer's lifetime value. It helps you identify users who find the most value in your product and understand the areas that need improvement to attract more users.

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Tracking stickiness helps you find avenues to strengthen your relationship with your users. When users know your product's value to their business, they engage with it daily and are more likely to renew their subscriptions or make additional purchases.

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Houseware Stickiness feature helps you identify:

• Which users are actively using your product?
• Which users are at the risk of churning
• How your product is performing over time.

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Cohorts

Understanding your users, their pain points, and product usage behavior is essential to build successful products. Build behavioral cohorts by grouping users based on their shared characteristics. Observe these cohorts closely to find common behavior patterns and understand how you can improve your product for them.

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For example, you can utilize cohort analysis to track users who uninstalled your mobile app after using it for a month.

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The Houseware Cohorts feature helps you analyze user behavioral data to answer questions like:

• Which users are engaging with your product?
• Which users are at risk of churning?
• When are users churning? When is the best time to re-engage these users?

What’s Currently Broken in Product Analytics?

The traditional product analytics tools fail to understand the influence of product experiences on the users. These tools focus primarily on a single channel, which is in-product experiences. Hence, the data they collect and process is incomplete. As customers interact with brands through various channels like customer support, social media, marketing, and so on, relying on such a tool that does not support multichannel analysis offers little data insights.

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Further, these tools work on rigid data models that follow a one-size-fits-all canned analytics offering pre-defined reports. If you need insights beyond those standard reporting templates, you must rely on additional data engineering (or another tool) to derive those insights. This adds to extra costs and hours of effort, creating fragmented analytics and performance degradation.

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Another astonishing observation is data purging to maintain system performance at all times. These tools are not designed to scale and support large-scale raw data businesses generate today. As a result, there is a massive loss of high-fidelity data that could share valuable insights for answering critical business questions.

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Enter Next-Gen Product Analytics Solution - Warehouse Native Application Like Houseware

To address these challenges of traditional product analytics tools, the modern data stack - warehouse native applications are introduced. The primary objective of this advanced data stack was to encourage centralized data storage in a cloud-based location like Snowflake. This common central data repository ensured consistency in data, stopped data duplication, and eliminated the need for ETL (extract, transform, load) data pipelines.

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Our warehouse-native product analytics tool directly sits on your data platform and runs natively as a self-service platform. Thus eliminating the need for tedious data transfers and lengthy configurations to generate best-in-class product insights.

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Further, Houseware leverages artificial intelligence (AI) technologies like predictive analytics and machine learning engines to identify gaps in your product data. Rather than reporting on simple product metrics, you can gain thorough insights into the cross-channel behavioral patterns of your users and make data-driven decisions.

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Houseware Analytics enables this by unlocking incredible analytics capabilities.

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• Access, analyze, and visualize data - events, behavior, or user paths from any source in your data warehouse.
• Enables self-guided data exploration by tracking higher-order metrics that go beyond product usage.
• Offers real-time event data processing capabilities to keep up with potential issues and opportunities.

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When using Houseware, you do not need multiple analytics platforms to gather different types of product insights. It is a one-tech-stack solution for your product analytics.

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Testimonials from Houseware Users

Do not just take our word for it. Check out these reviews Houseware has received from its customers on G2Crowd.

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Siddharth S, a founding team member, switched from Amplitude to Houseware to tackle their concerns related to data residency, security, and compliance. In his review, he highlights the product’s warehouse-native nature. Houseware runs on top of their existing data warehouses on Snowflake, so they have complete control over their data. Since adopting Houseware, they have cut their product analytics costs by almost 50%.

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Anjan has all praises for our Flows and Trends feature. He calls Houseware an excellent visualization tool for monitoring user events. This especially holds when observing real-time trends and identifying patterns in user behavior.

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Santanu K calls Houseware a game-changing product analytics product. He talks about how Houseware's low-code environment has helped him and his team to create and analyze funnels for contextual product insights. He mentions the fast and reliable support the Houseware team offers customers to help them get started with product analytics in no time.

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Note from the Founders

Houseware is not just another product analytics platform. It goes beyond tracking user engagement and retention and offering top-level visibility into product usage. Houseware analytics digs deeper into user data, both in-product and outside, to provide a deep understanding of how your user's behavioral patterns can drive growth.

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Every team, whether Product, Customer Success, or Marketing, can leverage Houseware to gain insights into behavioral analytics to understand patterns in user behavior across all touchpoints. We offer a host of features like behavioral cohorts, retention, flows, or funnels for you to understand user behavior and its outcomes quickly. You can dice your user data across any dimension to refine your understanding of their behavior.

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Further, as Houseware is a warehouse-native platform, it leverages your existing data infrastructure and requires minimal time for integration. Your data never gets copied onto our systems, thereby eliminating the challenges related to data transfers and residency.

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Houseware Analytics is the best choice for you if:

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• You are tired of one-size-fits-all analytical solutions.
• Your product analytics data is spread across multiple platforms.
• You are looking for a centralized analytics tool that accurately models your entire user data.

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Book a demo of Houseware today, and let us discuss how we can maximize the value of product analytics for your business.