SaaS Analytics: The Best Tools for Analyzing Your Data (2020 Update)

When it comes to SaaS analytics tools, you have hundreds of options to choose from.

There’s a tool for everything: tracking marketing spending, measuring app engagement, heatmaps and more. Unless your full-time job is to research the best tools for your business, this can be a daunting task.

I wrote this post to help you sort through all the noise by giving you 3-4 options for each the different use cases that I see all the time with our clients.

The goal here isn’t to choose the perfect tool (which doesn’t exist) but to choose something that is good enough and starts giving you actionable insights.

To help you navigate this post, I broke it apart into two sections: best tools for specific jobs and the complete stacks that I recommend to companies based on their size, product maturity, and internal resources.

These are still some of the best tools that you can use in 2020. Dominant players get better and make it more sticky to keep using them. The trend of 2020 would definitely be consolidate as much as possible and ensure that you data can flow freely between all your tools.

Let’s dive right in…

I’m interested in tools for specific jobs such as:

Marketing Attribution

Product and User Behavior

Engage Users Through Email, SMS, Push or In-App Notifications

A/B Testing

User Experience & Qualitative Data

Revenue Analysis

Dashboards and Reporting

Customer Data Platforms & Data Piping Tools

Ruben’s Favorite Saas Tools

I’m interested in complete stacks for my company:

Startup Stack (and How it Compares to Returnly)

Growing Company Stack (and How it Compares to Wistia)

Enterprise Stack (and How it Compares to Slack)


Marketing Attribution

Marketing attribution tools will help you understand what campaigns are driving the most conversions (signups, installs, downloads, paid subscribers) and how you should optimize your marketing dollars.

I should also note that your options will differ depending on if you need to do attribution of web traffic (ecommerce sites, SaaS products, etc) and mobile traffic (mobile app, mobile games, etc).

Google Analytics for Web Attribution ($0)

Google Analytics is a great option for companies who are just starting to measure the attribution of their campaigns. GA is relatively easy to set up and will let you even start exploring multi-touch attribution modeling.

GA is a great fit for those companies who drive mostly web traffic and have under 1M monthly visits.

Google Analytics Attribution Report

Website: https://marketingplatform.google.com/about/analytics/

Google Analytics 360 for Web Attribution ($150,000/year+)

Google Analytics 360 is the enterprise version of Google Analytics. You get access to more advanced reports including a more powerful funnel and attribution report.

If you’re spending significant money through Google Ads and Youtube, GA 360 will integrate nicely with these sources and give you better insights into your campaigns.

Like GA, this is suited for companies who are driving primarily web traffic and can easily justify the annual expense.

Google Analytics 360 Attribution Report

Website: https://marketingplatform.google.com/about/analytics-360/

AppsFlyer for Mobile Attribution ($0 – $100,000+/year)

Appsflyer is our first introduction into the world of mobile app attribution. Unlike web traffic, mobile apps have certain restrictions (i.e. app stores) that will limit how much data you can get.

Tools like Appsflyer were created to get around these limitations and give you granular data around what marketing campaigns are driving the most app installs or downloads.

User acquisition trend Appsflyer

Website: https://www.appsflyer.com

Kochava for Mobile Attribution ($0 – $100,000+/year)

Kochava is a second option in the mobile attribution world. They have flexible plans (from free to Enterprise) and offer a very robust platform to better understand your mobile app campaigns.

Kochava Attribution

Website: https://www.kochava.com

Funnel.io for Attribution Dashboards ($5,000 – $50,000+/year)

Funnel.io is will connect to all your advertising data (Google Ads, Facebook Ads) and your conversion data (Google Analytics, Shopify, Stripe) and connect all the dots for you.

This can be a great option for some companies who already have all the data they need but no way of bringing it together. However, keep in mind that you still need a way of capturing conversion data such as mobile installs.

Funnel.io Dashboard

Website: https://funnel.io

Attribution App for Attribution Dashboards ($5,000 – $50,000+/year)

Attribution App is a competitor to funnel.io with the same idea: connect all of your data in a single dashboard. Like funnel.io, you need to ensure that your data is properly structured for this work as expected.

AttributionApp Report

Website: https://www.attributionapp.com

Product and User Behavior

In this category, we are interested in tools that will help us better understand our product and how users behave within the product.

The need for these tools will depend on how complex your product is and what questions you need to answer.

Mixpanel ($3,000 – $100,000+/year)

Mixpanel is an event-driven analytics tool which means that you can send data in almost any format and then easily analyze it. Mixpanel is known for having a great funnel analysis and user retention report.

Their focus has been primarily on software products but their platform is flexible enough to handle other types of products (ecommerce, media sites, etc).

Mixpanel Funnels

Website: https://mixpanel.com

Amplitude ($0 – $100,000+/year)

Amplitude is another event-driven analytics tool that will let you easily analyze your data across almost any product.

Like Mixpanel, they are known for having a great funnel analysis and user retention report though they have also developed other advanced reports.

Amplitude Lifecycle Report

Website: https://amplitude.com

Heap Analytics ($0 – $100,000+/year)

Heap Analytics is similar to Mixpanel and Amplitude but they have a different philosophy.

They believe in automatically capturing all user interactions (page views, transactions, clicks) and then letting you easily create reports off this data.

If your company is wary of heavy implementations, Heap can make the initial setup a breeze.

Heap Analytics Report

Website: https://heapanalytics.com

Pendo ($0 – $100,000+/year)

Pendo also offers built it analytics reports but they are better known for the user qualitative features such as the tracking of NPS and the ability to add guided tour pop-ups throughout your product.

This is a great choice for product teams who lean heavily on qualitative data and metrics like NPS.

Pendo Report

Website: https://www.pendo.io

Engage Users Through Email, SMS, Push or In-App Notifications

Being able to easily engage your users can be an easy win as you try to improve your product. The tools in this category will make it dead simple to set up automated messages across channels like email, SMS, push or in-app notifications.

Mixpanel ($0 – $100,000+/year)

Mixpanel was covered in the Product and User Behavior section but they also allow you to easily send notifications to your users based on your Mixpanel data.

Activity on these notifications will be automatically tracked and store alongside your other data.

Mixpanel Insights Report

Website: https://mixpanel.com

Intercom ($1,500 – $30,000+/year)

Intercom offers a product that will allow you to communicate with your users across most of the common channels (email, SMS, push and in-app notifications). They have other features built in for customer support teams such as help articles.

Intercom User Profiles

Website: https://www.intercom.com

Customer.io ($1,800 – $20,000+/year)

Customer.io will make it easy for you to automate your marketing messages across all the channels that your customers might be using (email, SMS, push notifications).

They also offer an extensive API to handle any other edge cases that you might run into.

Customer.io Report

Website: https://customer.io

A/B Testing

A/B testing is a critical part of running a SaaS company and in this category, we’ll be looking at the tools you can use to design and deploy your experiments.

All the tools in this category will allow you to run experiments across web and mobile apps.

Optimizely ($5,000 – $50,000+/year)

Optimizely will make it easy to run A/B tests across your website and mobile apps. They have been around for a long time and have a proven and stable product.

You’ll also be able to easily send your experiment data to other analytics tools like Google Analytics.

Optimizely Report

Website: https://www.optimizely.com

VWO ($5,000 – $50,000+/year)

VWO is another long term player in the A/B testing space. They have also expanded their product to include other aspects of conversion rate optimization. Like Optimizely, you’ll be able to run A/B tests across web and mobile apps.

WVO Report

Website: https://vwo.com

User Experience & Qualitative Data

In this category, we are interested in collecting qualitative data about our product such as heatmaps, visitor recordings, and surveys.

Hotjar ($1,000 – $20,000+/year)

Hotjar gives you multiple tools or reports in one platform. You can easily run heatmaps, surveys, polls and visitor recordings.

Setting up Hotjar is also really easy (just add the snippet and you’re done). I also like that you can repurpose features like feedback polls to get metrics like NPS.

Hotjar Heatmaps

Website: https://hotjar.com

FullStory ($0 – $20,000+/year)

FullStory is another all-in-one tool that will allow you to easily capture heatmaps and visitor recordings.

You can’t run surveys through this tool but it will collect quite a bit of information about user interactions.

As a side note, I think this is one of the most beautifully designed products that I have ever seen.

FullStory Report

Website: https://www.fullstory.com

Revenue Analysis

SaaS companies are special when it comes to revenue metrics. They have a well-defined list of metrics that they should be looking at on a regular basis such as MRR, ARR and revenue churn.

This means that there are quite a bit of tools that will quickly calculate these metrics for your business.

ProfitWell ($0 – $20,000+/year)

ProfitWell will help you understand your subscription metrics after integrating with a payment processor such as Stripe or Recurly.

They have also built other products to tackle problems like failed credit cards and more advanced revenue analysis.

ProfitWell Dashboard

Website: https://www.profitwell.com

Baremetrics ($500 – $10,000+/year)

Baremetrics is another option that will quickly give you dashboards around the most important SaaS metrics for your business.

They have also built features to help you understand why things are happening e.g. cancellation and trial insights.

Baremetrics Dashboard

Website: https://baremetrics.com

ChartMogul ($0 – $15,000+/year)

ChartMogul is yet another option for quickly visualizing your subscription data. Like Baremetrics and ProfitWell, you can easily integrate your payment processor and track trends in subscription metrics.

Chartmogul Dashboard

Website: https://chartmogul.com

Dashboards and Reporting

Regardless of your company size, you will likely end up with different sources of data that you want to bring together into a central dashboard. Tools in these categories will help you tackle this problem.

Databox ($0 – $5,000+/year)

Databox can integrate to over 60+ data sources including advertising data (Facebook Ads, Google Ads), analytics tools (Google Analytics, Mixpanel, etc) and other tools.

You can then combine these data sources into custom metrics and dashboards.

Databox Dashboard

Website: https://databox.com

Klipfolio ($350 – $5,000+/year)

Klipfolio supports over 300 data sources and is one of the most established tools in this category. They also let you run custom calculations on your data similar to what you could do inside Excel.

Klipfolio Dashboards

Website: https://www.klipfolio.com

Google Data Studio ($0 year)

Google Data Studio supports over 150 data sources and plays quite nicely with Google products (as expected).

Most of their data sources are marketing related (advertising data, marketing tools, etc) and they also offer pre-built templates you can easily replicate.

Google Data Studio Dashboard

Website: https://marketingplatform.google.com/about/data-studio/

Domo ($1,000 – $25,000 year)

Domo supports over 500 data sources and is incredibly flexible in how you can process the data before visualizing it.

They support all kinds of businesses but are better suited for larger organizations who need quite a bit of flexibility in their data processing.

Google Data Studio Dashboard

Website: https://www.domo.com

Customer Data Platforms & Data Piping Tools

Customer Data Platforms (CDPs) were created to help you simplify your data collection across multiple integrations.

You will likely need to send the same data to a bunch of different tools and CDPs can make this a breeze.

Segment.com ($0 – $25,000 year)

Segment.com can integrate with 200+ tools and they have lots of SDK options for collecting data from the web, mobile apps and server libraries.

They have also built other products such as Protocols for data governance and Personas for advanced identity management.

Segment.com Connections

Website: https://segment.com

Hull.io ($450 – $25,000 year)

Hull.io focuses on the B2B market and has built a CDP around the most common tools such as Salesforce, Intercom, and MailChimp.

I particularly love the playbooks they offer since those can show you exactly what you can do with their product.

They also integrate with Segment.com which lets you access tools they don’t directly support.

Hull.io Product

Website: https://www.hull.io

mParticle ($1,000 – $25,000 year)

mParticle integrates with 150+ tools and also have wide-ranging support of SDKs across all platforms. They are focused much more on the enterprise market which is reflected in their pricing model.

mParticle Product

Website: https://www.mparticle.com

Ruben’s Favorite SaaS Tools

I get asked all the time about my favorite tools across the categories listed above. I personally like tools that can do multiple jobs since this avoids the issue of having to implement and maintain too many tools.

Startup Stack (and How it Compares to Returnly)

If you’re starting from scratch, it can be helpful to think about your entire analytics stack and not just individual tools.

This is the stack that I would recommend to a startup which is just getting started with data and doesn’t have a lot of internal resources to implement tools.

  • Segment.com: this will let you easily send your data to different integrations.
  • Google Analytics/Appsflyer: this will give critical marketing attribution data.
  • Heap Analytics: Heap can automatically collect data from your app and let you analyze what is going on with your product.
  • Hotjar: collect qualitative data such as heatmaps and session recordings.
  • Databox: quickly create dashboards of all your existing data.

I also thought it would be interested to see how this stack compares to an existing company. In this case, I chose a company called Returnly which fits my criteria of “startup”.

Growing Company Stack (and How it Compares to Wistia)

Just like in the Startup Stack, these are the tools that I would reccomend to a growing company who is past the startup stage.

Companies in this stage are collecting quite a bit of data (millions of data points per month) and have more internal resources for managing all of this data.

  • Segment.com: having a data piping tool is quite helpful especially since you will be experimenting with different tools and implementation speed is of the essence.
  • Google Analytics/Appsflyer: you will still need a tool for collecting attribution conversions and GA or Appsflyer can help here.
  • Attribution App: this will make it easier to run complex marketing attribution reports across multiple data sources.
  • Amplitude/Mixpanel: both of these options can give you access to more advanced product reports that will help you understand usage and retention.
  • Domo: this will let you visualize your data from different sources plus give you access to more advanced ETL functionality.

Let’s now compare this stack to an existing company called Wistia. They offer business hosting and are growing quite quickly.

Enterprise Stack (and How it Compares to Slack)

Finally, let’s look at what an enterprise stack might look like. At this stage, your company has quite a bit of internal resources for managing your data and this lets you choose tools that are very flexible but not as user-friendly to non-technical people.

  • Custom data piping: using a data wrapper still makes sense but you will be better off writing a custom internal solution instead of selecting a third-party tool.
  • Google Analytics 360: Google Analytics can still be quite helpful here but you will need the enterprise solution to get around sampling issues and get access to advanced attribution reports.
  • Data warehouse + SQL: for any product analysis, SQL plus raw data will be the most flexible option here.
  • Tableau/Domo: to visualize data, Tableau or Domo will help you bring multiple data sources into a single dashboard.

Let’s now compare this stack to Slack, a company with lots of data and resources for managing this data.

Conclusion & Next Steps

Hope you found this post useful! I would also love to hear what you thought about this post. Let me know in the comments below.


One more thing before you go! Do you know how to get more insights out of your data? 

All companies are sitting on a goldmine of data that they haven't fully explored. It's not about technology or capturing more data. The key is to learn how to make the most of your current data and convert it into actionable insights. This is the main idea behind my first book, The Data Miage: Why Companies Fail to Actually Use Their Data

I'm excited to announce the release of the book through all major retailers. If you're interested, you can download the first chapter for free using the form below. You'll learn what the best data-driven companies do differently and how to make sure you're playing the right data game.

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