Heap vs. Google Analytics 4

Heap was built to provide best-in-class data so users can generate deep insights into how people use your website or product. Heap tells you why things happen, shows you what’s working and what isn’t, and directs you to the root causes of key customer behaviors.

Heap’s data science features guide your analytics in real time by highlighting behaviors you may have missed and making suggestions about where to focus your analyses.

With features like funnels, journeys, influence of touchpoints and time-based analytics, Heap can set up automatic queries to answer questions like the following:

ㅤ• Did a feature change after a specific date? 

ㅤ• Which accounts have the best per-user conversion rate for a particular feature?

ㅤ• How does the use of a particular feature influence conversion and drop-off rates?  ⠀

ㅤ• What are the most common paths that users take after landing or before purchasing?  

ㅤ• How does my experiment affect the conversion rate?  

ㅤ• How has my purchase funnel changed since last month? 

ㅤ• Do users returning after a break convert at a higher rate than new users?

Because GA4 is web-based and has a more limited data set, GA4 users get a narrow focus on high-level metrics that tell you what happened on your site or product, but not why those things happened. GA4 offers automated insights, but they are quite limited.

Here are some examples of the types of automated insights and depth of analysis you can take advantage of with GA4:

ㅤ• How many users did I have last week? 

ㅤ• What are my top cities? 

ㅤ• How many users from organic search in the last 30 days? 

ㅤ• What are my top pages and screens by views?

ㅤ• How many new users visited this year?

To investigate deeper, GA4 users need to pull data into BigQuery and have knowledge of SQL.

Heap’s complete data foundation and analytics features let users paint a complete picture of the customer experience, and guides teams to understand what components of their digital experience are keeping users engaged, improving retention or causing churn.

Heap’s data science layer automatically scans your dataset to show you missed steps, alternate paths to conversion, and areas with significant friction.

Heap offers Session Replay integrated into our analytics suite. For any user event you’re interested in, Heap can pull up endless sessions cued to that exact event. This is a significant advance over stand-alone session replay tools, which require you to search through hundreds of recordings to find what you're looking for.

Heap’s new Journeys feature lets you analyze multi-funnel nonlinear user experiences, with multiple branches and optional steps. Heap also offers traditional funnels, path analysis, advanced retention, time based usage analysis and influence analysis.

Google Analytics provides high-level web marketing analytics that focus on advertising spend and revenue. GA4 is not intended to be a product analytics tool. It lacks functionality that is generally required for analytics and PM teams, like the ability to ask iterative behavioral questions that uncover the root cause of user behaviors.

Though GA4 offers analysis like funnels and retention, because it only offers surface-level metrics, it cannot uncover the drivers of what is causing users to complete a funnel step or be retained. 

For example, in GA4 you can see where there was drop off in a funnel, but you won't have the data to see what interactions between those funnel steps are causing the friction or drop off.

GA4 offers no ability to watch session replays to confirm your hypotheses and see quickly what the right improvement should be.

Heap provides the most complete data capture on the market. Our Autocapture snippet and SDK which automatically capture every user view, click, swipe, and form fill with a single snippet of code.

This is achieved without maintaining manual tags and without forcing teams to expend hundreds of hours managing data dictionaries, writing code, and reacting to endless tagging changes.

Forrester found that Autocapture alone produced a 40% labor reduction per product innovation.

To this autocaptured dataset Heap adds  custom tracking and server-side events, which gives customers the most complete and manageable data set available on the market.

Heap collects all this data from the moment teams install the snippet. This gives teams the power to analyze data retroactively, and see all every behavior from every user from the moment of installation forward.

Google Analytics 4 offers the Google Tag, which can automatically detect a few event types, including page views, scrolls, and outbound clicks. Manual tagging is still required when wanting to track basic click events and add additional data at the event level.

Though these features improve upon past iterations of the Google Tag, teams will still need to build an implementation plan, work with technical teams for the initial implementation, and then constantly revise their tags as websites or apps change over time. This requires significant time investment and can easily create a disconnect in ownership across analytics consumers and data engineering teams.

In addition, changes to captured events have to be manually managed through Google Tag Manager. This makes things difficult for less technical users, who aren’t able to easily define anything they want without code.

Read more about the differences in GA4 and Heap data capture.

With Heap, you get fast and easy instrumentation for mobile so you can get the insights you need quickly. Easily capture a complete data foundation from every platform and device with Heap’s autocapture and mobile SDKs.

By eliminating the risk of broken tracking and inconsistent tagging schemas, you’re guaranteed quality data. Plus, you can easily combine data from different platforms into a single event or property, so nothing gets counted twice. 

Get a complete view of your customer journey with retroactive data for everything in your product, regardless of when it was released. 

Unlock answers to impossible questions by building reliable clean segments and user cohorts that capture user preferences on different platforms.

While GA4 does offer automatic capture for mobile through Google Tag, manual tracking is still required to track basic click events and to add additional data at the event level. That means teams will need to build an implementation plan for tagging, and then constantly revise their tags as things change over time.

For mobile, any manual tracking becomes increasingly more complicated because of the different mobile development frameworks for Android vs iOS. Multiple tagging schemas will not only need to be created and maintained for each mobile operating system, but each app version. 

These cumbersome tagging schemas and tracking plans open up many opportunities for disconnected events and complete data gaps. You’ll spend more time monitoring data quality while having reduced visibility into user behavior.

Heap was designed with collaboration in mind. Anyone can define an event, add a description to it, perform an analysis and pin it to a dashboard, and add notes on dashboard panels for better visibility into what an analysis means.

Heap offers automated templates and playbooks, and the ability to share any query or dashboard with other users via a unique URL, so other users can edit without changing the original query.

GA4 offers collaboration features like sharing chart links or sharing via email. However, it lacks many key features like notes in dashboards, event descriptions, and customizable playbooks and templates.

GA4 does not give users the ability to create a custom report, save it as a template and import it to a new property. This reduces a team’s ability to easily share information.

Heap lets any user create behavioral segments based on real actions taken on your site or app. This ensures that teams can segment users according to what they do, not just who they are.

Segments in Heap can be brought into any analysis to understand how different groups navigate your user experience, and how you can personalize communications to them.

Segments defined in Heap can also be pushed out into other tools, where they can drive a multitude of marketing and product related use cases, like personalization and targeted advertising.

GA4 allows users to create user cohorts for advertising segments and define simple behavioral segments. These are predominantly focused on who users are, not necessarily what they do in your product or experience.

To build more specific or advanced cohorts relative to time or specific behaviors, teams need a more technical analyst with SQL knowledge.

Heap provides a network of over 40 integrations, providing both data-in and data-out connections to products like Snowflake, AWS S3, Redshift, Salesforce, Optimizely, Hubspot, Marketo, Shopify and many more.

Heap’s autocaptured data provides teams the data they need to perfect use cases spanning A/B testing, personalization, ad targeting, NPS surveys, marketing campaigns and more.

Many Heap customers push Heap’s gapless data set into data warehouses like Snowflake, Redshift, and AWS S3 to drive more complex data science use cases and personalization.

Google Analytics 4 allows users to connect and integrate with other tools inside of the Google ecosystem like Google Ads, Google Cloud, Google Ad Manager and more.  However, the only external integration available is Salesforce Marketing Cloud.

Google Analytics 4 allows users to send data out to Google Big Query, which requires users to have a paid account if they want to store more than 60 days of data at a rate of $0.05 per gigabyte of data, which is roughly 600,000 GA4 events. There are also many latency and table timing factors to take into account.

In addition, the event schema only includes a raw event table. Users will have to use SQL in BigQuery to recreate any analyses or cohorts they built in the GA4 UI which can be a limiting factor for non technical users.

Because Heap was built on a more expansive data collection foundation, we had to create a data governance suite capable of managing data at scale.

Users can use point and click, no-code visual labeling to identify elements on a page and immediately define them.

Heap’s governance features include enforced naming conventions to keep events organized and event verification which ensures that less technical users are analyzing the right things.

Users can also monitor their events via a live data feed, where they can watch as events are generated in real time, and immediately take action by defining events that are undefined.

Google Analytics 4 requires users to still manually define, tag, and manage their events. Aside from the associated cost, and known issues associated with manually tagged events (which is why Google is taking a first pass at auto-tagging), GA4 has other known data quality management issues as well.

Data quality management is limited to an out of the box DebugView report, which shows data as it is collected and helps troubleshoot issues. However it has been known to run into issues where it will show “No devices available.” DebugView can also be a limiting factor for untrained users, limiting the level of involvement and control less technical teams can have over their data governance.

There have also been reported data quality and consistency issues with GA4, among a host of other bugs.

Heap offers 4 different pricing tiers with different offerings for each.  Heaps free tier offers analytics for 1 product/website, unlimited user licenses, automatic data collection and management, 1 year retroactive data, 2 enrichment sources and our data science layer, Heap Illuminate.  For more information check out our pricing page. 

GA4 has a free tier that offers all of its standard analytics, data collection, and data management features. For more information on audience, conversion, sampling, and retention limits see their feature limits matrix here.

Heap offers paid tiers that include additional features and data volumes that include what our free tier offers and more. For more information check out our pricing page.

GA4 has a paid version that includes all of the standard analytics, tagging, and data management features included in the free version. Where they differ is in data retention, number of allowed dimensions, audiences, and more.  For more information see their comparison matrix.