Home > SaaS Tools > Product Analytics

Published on Dec 1, 2022

If you're reading this article, you maybe looking for a product analytics tool to help you track usage behavior and derive insights to help you prioritise the features to build. The solutions compared below maybe relevant to a varying degree depending on the stage of your organisation:

• Early pre-product market fit - Probably, not yet relevant.

• Early post-product market fit - Soon becoming relevant, probably your GTM strategy is dictating your product feature roadmap. Good time to invest in such a tool before things go crazy!

• Mid-growth with established go-to-market strategy - Super relevant.

• Late growth  / Scale-up - Relevant, however you may prefer to setup your DWH if you have your own data analytics team.

*Disclaimer: Please note that the author has selected the below mentioned criteria for ranking based on their prevalence among the product analysts interviewed during his research. However, it is possible that some of these criteria may be more or less important depending on your specific business case, or that there may be additional criteria to consider. The author has attempted to compare these tools to the SaaS business use cases for mid-sized businesses, aiming to strike a balance between customisation and ease-of-use. However, please keep in mind that the rankings and descriptions may vary for businesses in different stages, whether they are in the early or late stages of development. The descriptions below provide additional context regarding the ranking. 

As a product analyst, you may consider the following criteria when comparing these product analytics tools:

1. Data Collection - How easy is it to set up data tracking and collect data with the tool? Is it customizable and flexible enough to capture the events and attributes you need?

2. Data Quality - How accurate and reliable is the data collected by the tool? Does it provide mechanisms to ensure data consistency and completeness?

3. Data Visualization - How easy is it to analyze and visualize data with the tool? Does it provide customizable dashboards and reports that allow you to quickly identify insights and trends?

4. User Behavior Analysis - How well does the tool enable you to understand user behavior and identify user segments? Does it provide features such as cohort analysis, funnel analysis, and user segmentation?

5. Experimentation and Testing - How well does the tool enable you to test and optimize product features and user experiences? Does it provide A/B testing and experimentation features?

6. Integrations - How well does the tool integrate with other tools and platforms? Does it allow you to export data to data warehouses, BI tools, and marketing automation platforms? And how is the interoperability?

7. Accessibility to raw data - for a late stage or scale up, it maybe important to have a live access to download your real time data for analysis or ETL purposes. 

Tools Compared For Data Collection:

1. Snowplow: Snowplow offers a highly customizable data pipeline that can collect data from a wide range of sources, including web and mobile apps, IoT devices, and server logs. Snowplow is particularly well-suited for collecting large volumes of event data from complex environments.

2. Heap: Heap provides automatic event tracking for web and mobile apps, making it easy to get started with collecting data. Heap also offers retroactive event tracking, which allows users to track events retroactively and gain insights into historical data.

3. Mixpanel: Mixpanel provides a range of tools for event tracking, including custom event tracking and event funnels. Mixpanel also provides real-time event tracking, allowing users to track user behavior as it happens. There are 3 tracking setup or SDK implementation options: client side, client-side with proxy and server side.

4. Amplitude: Amplitude provides automatic event tracking for web, mobile apps and even http API for C++ native apps. Amplitude also offers custom event tracking and funnels, as well as real-time event tracking - both client side and server side.

5. PostHog: PostHog provides automatic event tracking for web and mobile apps, and also offers custom event tracking, session recording and funnels. PostHog is particularly well-suited for teams who need to capture and store all user event data, as it offers quite generous event data storage (Free up to first 1 million events/mo, then $0.00045/event) in the paid plan.

Tools Compared For Data Quality:

1. Snowplow: Snowplow provides a highly customizable data pipeline that allows for fine-grained control over data quality. Users can define data schemas and validation rules to ensure that data is clean and accurate. Snowplow also provides a range of data governance tools to help ensure data privacy and compliance.

2. Mixpanel: Mixpanel has a strong focus on data quality and provides a range of tools to help ensure that data is accurate and consistent. Mixpanel provides real-time error monitoring to detect and fix data issues, and allows users to create custom event tracking rules to ensure that data is being collected correctly.

3. Amplitude: Amplitude provides a range of tools to help ensure data quality, including data validation and auditing features. It also offers data governance tools to help ensure that data is being used in compliance with regulations like GDPR and CCPA. It's Identity Resolution features ensure an accurate count of unique users using a combination of device IDs, user IDs, and Amplitude IDs. 

4. Heap: Heap provides a range of data quality tools, including real-time error tracking and data validation. Heap also offers data governance tools to help ensure compliance with regulations like GDPR and CCPA.

5. PostHog: PostHog provides a range of data quality tools, including error tracking and data validation. PostHog also offers data governance tools to help ensure compliance with regulations like GDPR and CCPA. One unique feature of PostHog is its ability to capture and store all user event data, which can be useful for debugging and troubleshooting data quality issues.

Tools Compared For Data Visualization:

1. Mixpanel: Mixpanel offers Insights, Funnels, Flows and Retention. Flows are the most popular visualization that is highly interactive and deep-dive friendly. It offers funnel analysis, retention analysis, and cohort analysis, and allows users to create custom dashboards and reports. Mixpanel's charts are highly polished and easy to interpret, making it a great choice for teams who need to share insights with non-technical stakeholders.

2. Amplitude: Amplitude's visualizations are one of the most powerful that allows to you quickly dive for deep insights. Amplitude offers all the usual visualisation: funnel analysis, retention analysis, and cohort analysis. One powerful feature of Amplitude is its Behavioral Cohorts, which allow users to segment their user base based on behavior and track changes over time, and further slice and analyse it much deeper after you've identified a potential target audience in the cohort.

3. Heap: Heap's visualizations are designed to be easy-to-use without much technical or analytical expertise, for example allowing users to easily create custom group relevant charts that are tailored to their custom needs. Heap's Event Visualizer, allows easily to find, name, and manage a complete set of user events, without touching your codebase. Additionally the 'Visual Labeling' feature allows easy tagging or clubbing of similar events. 

4. Snowplow: Same as its peers, Snowplow offers a range of visualizations, including funnel analysis, retention analysis, and cohort analysis, as well as custom charts and dashboards. However one unique feature of Snowplow is its event modeling capabilities, which allow users to create custom data models that can be used to analyze complex event data.

5. PostHog: PostHog's visualizations are designed to be simple and easy to use, making it a good choice for teams who are new to product analytics. PostHog as well offers funnel analysis, retention analysis, and cohort analysis, as well as custom charts and dashboards like rest of its peers. 

Tools Compared For Analytical Depth for Usage Behavior:

Here, users' feedback varied quite a lot depending on individual team size, business type, data type etc. It also varied based on the stage of implementation i.e. whether they've just implemented recently or using it for a few years and the data integration flow is streamlined with satisfactory data quality or not.

1. Snowplow: Snowplow is highly customizable and provides deep analytical capabilities, allowing users to track a wide range of metrics and events. Its flexible data schema allows for complex analysis, and its data pipeline supports real-time streaming and batch processing. However, these advanced capabilities also come with a steeper learning curve, which may make it less intuitive for less technical users.

2. Mixpanel: Mixpanel provides a range of analytical capabilities, including funnel analysis, retention analysis, and segmentation. Its interface is user-friendly and provides a variety of visualizations that make it easy to create and share reports. Their 'Group Analytics' feature lets you calculate metrics at the account or company level, like product adoption, active usage, and retention (popular in the context of B2B SaaS companies looking to understand their customers’ usage patterns to drive upsell and prevent churn).

3. Amplitude: Amplitude offers wide analytics possibilities for not just product, but also for marketing and engineering. The combination of product usage with the customer lifecycle is quite synergic for cross-functional insights. It also offers Amplitude Recommend, a personalization engine powered by machine learning that allows teams to create custom experiences, such as product recommendations or priority ordering, based on machine learning predictions. It also uses machine learning for 'predictive analytics', which estimates future outcomes, for example: future conversion rate, based on current and historical data.

4. Heap: Heap provides a range of analytical capabilities, including funnel analysis, retention analysis, and segmentation. However, some users have reported limitations in terms of the depth and complexity of analysis that can be performed.

5. PostHog: PostHog provides basic analytical capabilities, including funnel analysis and segmentation. It does not offer predictive analytics. 

Tools Compared For Testing:

1. Amplitude: Amplitude's Experiments feature is the most powerful as it allows to plan the experiment by starting from a hypothesis in existing behavioral analytics to decide what you want to change. It also allows flexibility to either leverage their feature delivery system to deliver your experiment or bring your own feature flags and send us the A/B data.

2. Mixpanel: Mixpanel supports A/B testing and multivariate testing as well. It also allows to create cohorts of the resulting audience from the experimentation  create follow on experiments and analysis.

3. Heap: While Heap offers very intuitive A/B testing and multivariate testing features, some users reported customization possibilities to be limited. 

4. PostHog: PostHog's two key features are: 1) 'Experimentation' is used to test changes to your product where you want to maximize a specific metric 2) Feature Flags are used for phased roll-outs or as a way to control feature access.

5. Snowplow: Snowplow does not provide built-in testing features, although it can integrate with third-party testing tools. As a result, Snowplow may not be the best choice for organizations looking for a comprehensive testing solution within their product analytics tool.

Tools Compared For Integrations

1. Mixpanel: Mixpanel is known for its ease of integration, for example with popular platforms such as Salesforce, Marketo, and Slack. It also has a comprehensive API that makes custom integrations straightforward.

2. Amplitude: Amplitude provides the widest range of integrations however it maybe slightly more technical to implement than the rest due to variety of parameters. 

3. Heap: Heap provides a comprehensive API that makes custom integrations relatively easy with popular marketing and CRM tools.

4. PostHog: PostHog provides a range of integrations, including with popular marketing and CRM platforms. It also supports custom integrations through its API. However, some users have reported difficulty with integration, particularly with mobile apps.

5. Snowplow: Snowplow provides a range of integrations, including with popular marketing and analytics platforms. However, it has a steeper learning curve than the other tools on this list, and its API requires a deeper technical understanding to use effectively. As a result, integrating Snowplow may require more time and resources.

Tools Compared For Accessibility to Raw Data

1. Amplitude - Data governance and management is a USP  of Amplitude. And the raw data export functionalities of Amplitude seems to be most structured - You can read more here.

2. Mixpanel - Every data point sent to Mixpanel is stored as JSON in our data store. The raw export API allows you to download your event data as it is received and stored within Mixpanel. You can read more here.

3. Snowplow - Snowplow allows custom modeling on your raw data and according to a blog back in 2012 is directly accessible in Apache Hive or Infobright.

4. Posthog - The PostgreSQL Export app enables you to export events from PostHog to a PostgreSQL instance on ingestion.

5. Heap - It offers a one-time data export in JSON format.

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