Google Analytics vs. Customer Analytics: What’s the Difference?

Written by Bjorn Sigurdsson

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Data is known to be the world’s most valuable resource. But companies struggle to make use of the information they’re collecting.

The challenge, according to Deloitte, Duke University, and the American Marketing Association is a lack of alignment between data and decision-making. For this reason, it can be challenging for an individual within an organization to make informed, in-the-moment judgment calls. So how do you get your product and marketing teams on the same page, with a shared perspective?

To answer this question, you need an analytics solution that captures and visualizes user journeys.

If your analytics capabilities are limited to Google Analytics, you won’t be able to answer these business-critical questions.

One question that people ask us is what’s the difference between Google Analytics and Indicative? First and foremost, the two platforms are noncompetitive: one solution is not a substitute for the other. But some people use Google Analytics to answer business questions for which the platform was not built. 

That’s because Google Analytics is, in essence, a platform for marketers to analyze the performance of website traffic acquisition sources. What Indicative does is integrate product and marketing data across business units. Enter Customer Analytics.

In this article, we’ll walk you through the difference between Google Analytics and Customer Analytics — to help you invest in the right tools to get the data-driven insights that you need.

Google Analytics vs. Customer Analytics: an Overview

The core difference is the analytics interface between the two platforms. 

With Google Analytics, you’ll see metrics that help you understand your web traffic better.  

The goal of Indicative is to help you gain insight into individual-level user journeys from marketing through core product experiences. In this section, we’ll explore this idea in more depth.

Dashboard home view of Google Analytics platform

Google Analytics and Analytics 360 

Google Analytics is the most widely used analytics platform in the world. There are two versions of it, at two pricing tiers — Google Analytics Standard (free) and Google Analytics 360 (paid). 

Google has also created two newer solutions that some companies are using instead of Analytics: App + Web and Google Analytics Firebase (both free). It is unclear what the trajectory of what this product suite looks like, relative to the core Google Analytics platform. So we’ll leave this topic to another discussion while we focus on Google Analytics, in more depth.

The purpose of Google Analytics is to allow for analysis of the visitors on your website. This could include understanding where someone first discovered your website (Acquisition reports), the demographic and geographic make-up of your audience (Audience reports), surface-level behavior such as bounce rate, average time on page (Behavior reports), and finally goal tracking (Conversion reports).

Website Usage Analytics

When you install Google Analytics on your website, you gain access to a basic data-dashboard in exchange for sharing insights with Google. With this perspective, you can easily see:

  • Top-level views of visitor accounts, referral traffic sources, and popular sections of your website
  • Comprehensive and accurate marketing attribution based on paid channel campaigns that you might be running
  • Insight into what actions people are taking on your website

Because of this, the platform is limited to accompanying metrics:

  • Sessions
  • Pageviews
  • Time on site
  • Conversion milestones

Google Analytics Acquisition Channel Report View

The goal of these metrics is to help you understand engagement with your content pages. With Indicative, the goal is to create a comprehensive picture of your digital experience interface. Both platforms have different ways of showing stories at the user (or person) level, which may consist of experiences across multiple devices. 

Google Analytics assembles this perspective through event and e-commerce tracking. Event tracking allows capture of nearly any user behavior via interpretation of markup in Google Tag Manager (GTM) and dataLayer specification. Enhanced Ecommerce provides the shopping and checkout journey, and is also best implemented via GTM and dataLayer specification.

Indicative uses a technique called aliasing to build a comprehensive customer picture. When an unknown user comes to your site, they are tracked through cookies. Once a user is logged in, they can be identified by a known user ID. Indicative has the ability to pair multiple unknown user cookie IDs, or unauthenticated IDs, to one known user ID. With this pairing in place, it is easy to unify a user’s behavior across multiple platforms and devices, giving you a holistic view of a user’s activity.

Google Analytics associates persistent IDs for single users to monitor their engagement. You would need to build this User-ID system (or host it in a platform called Indicative). 

Google Analytics Costs

There are tiers of Google Analytics: Free and Premium and four versions.

With the free version, the analyses you run are often based on sampled data. With the pro version, you work with your complete dataset across website properties.

Google Analytics Audience Device Report View

If you want to upgrade your perspective, you’ll also need to upgrade your subscription to an annual Google Analytics 360 license that begins at about $150K/year. With this price point, you’ll get:

  • A service-level agreement that guarantees 99.9% uptime and customer support
  • Data freshness limits of 12-48 hours
  • Unsampled reporting
  • Free extract to BigQuery
  • Support for integrations
  • 200 Custom Dimensions (Free offers 20)
  • 200 Custom Metrics

You can learn more about Google Analytics Free and GA 360 here.

Customer Analytics

With Customer Analytics, you are implementing business intelligence that adapts to the unique constraints of your business.

You define and control your data infrastructure across product and marketing initiatives from the ground-up. You implement the naming, categorization, and tagging infrastructure that is right for your business.

As a result, you gain clear and comprehensive insights into customer journeys for your business

Advanced Analytics

Using customer analytics, you can ask and answer complex questions in an interactive, intuitive way. For instance, here are some analyses that you’re able to run using Indicative’s Customer Analytics platform:

  • Conversion analytics. Understand variability in marketing campaigns using Indicative’s funnel tool. Gain insight into how subsequent product usage ebbs and flows, so you can reach audiences with the right message, at the right time and place. You can also visualize conversion paths towards a specific goal, which means that you can build more targeted analyses than what is possible with Google Analytics. With Customer Analytics, marketing teams can answer common questions such as “How did the audience from campaign A behave differently from the audience acquired in campaign B?”, and “Once we spent money to acquire them, did they end up taking the same path to conversion, or were there obvious trends different between the two journeys of each group?”

Conversion analytics funnel build using Indicative

  • Cohort trend analyses. Organize customers into groups, based on intelligently defined segments. These cohorts can help you identify — and optimize experiences for — your most engaged users. With well-defined groups, you can target experiences, messaging, visuals, and more that help increase retention.

Cohort trend analyses using Indicative Customer Analytics platform

  • User path analysis. Indicative tracks experiences at the individual level, making it possible to conduct analyses of anonymous users. If you notice a specific issue — sign-up flow churn, for instance — you can drill down to the individual actions that the person has taken through activity timelines. This granular perspective can help you pinpoint exactly where a valuable user has fallen through the cracks before they became a customer, and immediately devise a solution to prevent it from happening again. 

User path analysis using Indicative Customer Analytics platform

  • A/B testing. Run routine A/B tests, across your marketing and core product experiences, to determine what is “most right” for your audience. With Customer Analytics, you can create a series of experiments to test your hypothesis, while trusting the data along the way.

g game download campaigns using Indicative Customer Analytics

 

Technical Snapshot: Google Analytics vs Customer Analytics

Here’s a look under the hood:

Chart of a technology comparison google analytics vs customer analytics

Data Warehouse Integrations

One of the key differences between Google Analytics and a Customer Analytics platform like Indicative is the ability to weave together data into a cohesive story across more areas of our business. 

With Customer Analytics, it’s possible to synthesize data from various sources into one platform for analysis. Indicative, for instance, connects to several data warehouses. You can also integrate with a CDP and any other software that you’re using to generate insights about your business.

Both technical and non-technical teams benefit from a data warehouse to synthesize data from multiple different sources. You won’t be able to connect to these warehouses to conduct analyses with Google Analytics. With Indicative, you can. That means non-technical teams can perform sophisticated analyses in processing large volumes of custom data. With this vantage point, anyone at a company can participate in data-driven decision-making.

Google Ecosystem Integrations

If you opt for a Customer Analytics solution, for deeper insights into your overall business, you can still tap into Google’s portfolio of tools. 

  • For instance, Google BigQuery provides a serverless and low-cost enterprise data warehouse solution with limitless elastic scalability. That means BigQuery allows technical users to directly query datasets using SQL. By connecting Indicative to your BigQuery dataset, you can empower your non-technical users to achieve the same results without the use of SQL. App + Web can automatically (and for free) extract into BigQuery every day.
  • Another important integration to consider is Google Tag Manager (GTM). With this tag management system (TMS), you can add or update your own tags for conversion tracking, site analytics, remarketing, and more across websites and apps. Within Indicative, you can see this conversion tracking from the perspective of an individual user journey.

GTM is an industry-standard. Websites, Apps, Web View apps that are not implemented in GTM lack supportability, scalability, suffer increased development costs and time needed to implement the always flowing waters of tracking needs. Sites without GTM implementation also do not benefit from the performance increases as well as supported auto-event variables and provided tag types that are provided from Google.

Sites implemented without GTM or some TMS may fall behind.

Measure Product Impact

Rather than conforming to pre-defined templates as you would in Google Analytics, you have the freedom to run ad-hoc analyses and build queries with Customer Analytics platforms like Indicative. You can then save these queries, to support collaboration with teammates across your organization. 

With Customer Analytics, you can more easily visualize conversions towards a certain goal, for targeted analysis.

Think: What is the quickest path users are taking from the time they first discover us to the time they convert as a customer? From there, the game becomes a rinse and repeat.

With Google Analytics, you still won’t have a comprehensive view of user behavior because the Free Plan does not enable you to integrate data sources, nor does it support tracking within mobile apps.

As a result, you won’t be able to see what your audience is doing beyond browsing your website. You’ll only be able to see data from your website, which means that you won’t see how the dots connect between your website, app, CRM software, and endless other sources.

Google Analytics is marketer focused. Indicative is not only designed for marketers but also product people and data analysts. It was built with the goal to bring data to your entire company, even among those who are not inherently technical-savvy.

With this shared, democratized view, everyone on your team — no matter their experience levels with data   can make decisions in alignment with overall revenue goals. 

Data Freshness and Data Retention (History)

Data freshness is defined by Google “as the time it takes for Analytics to collect and process a hit from your property.” Google Analytics has the following intervals of data freshness: 

Data freshness info chart in Google Analytics support docs

With Indicative, it’s possible to see user behavior in real-time. You can use a third-party partner like Segment or Snowplow or track data using Indicative’s SDK. Data warehouse integrations can be processed as quickly as you need. 

Data history is how long your analytics software holds on to your data.

In Google Analytics, that time period is determined by whether you want to track a web property-only or an app + web property. Indicative offers a few different thresholds: 6 months for Free users, 1 year for Pro users, and a custom time period for Enterprise users.

Having this history may be necessary for various data privacy and compliance processes — or simply for record-keeping and looking into historic analyses such as trends in month over month, year over year, and so forth — what best fits your company’s individual needs.

Business Impact

To make an impact on your business, data needs to be intuitive.

While Google Analytics can help you form a partial story of user behavior, you need a Customer Analytics platform to gain a deeper perspective into actions that coalesce into an overall picture for your business. 

Here’s how Customer Analytics can help you maximize the business impact of your data.

Democratize Data: Make Data More Usable

Indicative built its product with the philosophy that its user experience should be simple and not require technical capabilities, such as writing SQL queries.

As a result, the learning curve to getting up and running with the platform is minimal. New users can get up and running with a series of small steps — meaning that anyone can participate in the data-driven decision-making process at your company.

In Indicative, you can collaborate in multiple ways. Create scheduled reports, create public dashboards, and share any query or dashboard by simply copying and pasting the URL.

Indicative dashboard views

Google Analytics is person-centric. Reports take several steps to share between users, and users may not have the same data picture due to different settings.

Both perspectives are valuable but meet different use cases.

In most companies, data is free-flowing and widely available, but it is not integrated into a clear, centralized, or strategic picture. For this reason, it can be challenging for an individual within an organization to make informed, in-the-moment decisions. Marketing and product teams have been feeling the pain of fragmented and disjointed information silos, for years.

Google Analytics does not resolve this pain point. Indicative does.

Learning Curve

With Google Analytics, there is a learning curve to get up and running with the platform, especially if you plan to use it for advanced analysis – you might even need engineering help to support proper data collection and goal tracking. For this reason, consultancies are often involved with the implementation of Google Analytics. If you want to become proficient in using the platform, there is an online academy and certification program available. Even with this information at hand, it may take some time for teams within an organization to take action on data that your company is amassing.

With Google Analytics, you’ll work with pre-defined templates. Indicative is set up to help you run analysis on the fly.

Customer Support

In the realm of technology, things can break. In some cases, you might not even realize that your reporting is inaccurate. 

If you run into an issue with Google Analytics, it may be very difficult for you to get the support that you need from Google. Only self-serve options are available for free Google Analytics users, as account management is only an option for paying 360 customers.

In order to ensure that Google Analytics is implemented in a way that quickly and accurately informs your business, is sustainable, and you do not want to invest the time and budget into internal resources, you will need to hire an analytics consultancy to assist you. The support that Google provides is often limited.

For this reason, a “free” analytics solution has the potential to create an opportunity cost in your business. With a Customer Analytics solution like Indicative, you have access to the support that you need, when you need it. This rings true even among our Free Plan by asking for help via our in-app support widget.

If more is needed from support, Indicative offers a dedicated Customer Success Manager for your account for paying customers, while still remaining cheaper than the alternative offered by Google Analytics 360.

Final Thoughts

With Customer Analytics, you can capture comprehensive user journeys. Google Analytics can help you monitor top-level views on the number of visitors, where they are coming from, and popular subdomains. With Customer Analytics, you can answer the questions “why” and “how.” With Google Analytics, the question that you’re asking, primarily, is “what.”

If your business wants to run a very simple out-of-box analytics implementation without customizations to capture user actions, without a userId tied to a backend database, and needs only basic site metrics, then Google Analytics Standard edition without consulting assistance may be the ticket.

If you want powerful analysis tools that help you understand your complete customer journey, then you need a Customer Analytics platform. Here’s a quick compare/contrast with takeaways for each platform, to help you make your best decision for your organization:

Summary chart of the difference between Google Analytics vs Customer Analytics

It’s critical that business leaders invest in tools that empower their workforces to make their best judgment calls.

Google Analytics can only take you so far. Indicative helps you continue on that journey, to help you fully understand your customers.

Contributors Statement

This blog post was a collaboration among the Indicative Team and Christopher Bridges. While Bjorn Sigurdsson was lead author, Marc LiebmannEsmeralda Martinez, and Tara McQuaide also contributed to the narrative.