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.
- Who are your best customers?
- What steps are they taking as they transition from marketing through your product?
- What are your most profitable conversion paths?
If your analytics capabilities are limited to Google Analytics, you won’t be able to answer these business-critical questions.
That’s because Google Analytics is, in essence, a platform for marketers to analyze the performance of traffic acquisition sources. What you need is a platform that integrates 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 power of your analytics solution is in the perspective that it is able to share.
With Google Analytics, you’ll see an aggregate level of web traffic, acquisition sources, on-site conversions, and website flow. With Customer Analytics, you’ll gain insight into individual-level user journeys from marketing through core product experiences.
In this section, we’ll explore this idea in more depth.
Google Analytics and Analytics 360
Google Analytics is the most widely used analytics platform in the world. There are two versions of it — a free version and Google Analytics 360, which is a paid offering.
For the last decade, Google Analytics has been the same core product. What’s important to consider about the platform is that it was never intended to function as a tool to provide end to end business intelligence.
Rather, 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:
- Time on site
- Conversion milestones
The process of aligning these metrics to company goals will not be intuitive. To create this framework, you will likely need to work with an analytics consultant and/or technical specialist.
While these metrics are valuable for understanding engagement with content pages, they share no insight into comprehensive customer journeys.
Because of cookie and data privacy laws, Google Analytics can only show you aggregate-level, session-based, traffic patterns. It is not possible to understand activity at the user level, nor is it possible to monitor actions performed by the same person, across multiple devices.
As a result of this tracking system, it is not possible to stitch together complete user behavior pictures across devices. Without a comprehensive picture of each user, you cannot monetize your analyses intuitively.
What you can do, instead, is to assign a dollar value forecast around actions and goals on your website. With this perspective, you’ll see general trends, at a high level, that can help inform decisions directionally.
Conversely, Indicative solves this problem using aliasing.
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 Limitations
Your Google Analytics Free Plan isn’t entirely free. It’s a limited picture of Google’s premium Analytics 360 product. Meaning, if you want to get more from the Free Plan, you will have to upgrade to a more costly alternative.
What happens if you want to start tracking variables that are important to your business?
With the Free Plan, you are limited to capturing 25 user properties. So you won’t be able to measure and track additional attributes that matter to your business.
Furthermore, you may be left with inaccurate reporting, even if you’re tracking all the properties that you want. That’s because Google Analytics exports are based on sample data rather than your complete dataset.
After all of this, you still won’t have a comprehensive view of your web traffic 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 simply browsing your website-only.
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 $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
- Support for integrations
You can learn more about Google Analytics Free and its premium 360 version, here.
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.
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?”
- 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.
- 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.
- 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.
Technical Snapshot: Google Analytics vs Customer Analytics
Your data is only as valuable as what’s possible to compute under the hood. Here’s a look at how Google Analytics and Indicative compare:
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.
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, CRM, 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.
- Another important integration to consider is Google Tag Manager. 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.
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:
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, itself. 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.
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.
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.
With Google Analytics; however, analytic collaboration is not easy. Reports take several steps to share between users, and users may not have the same data picture due to different settings.
The problem is that 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.
Google Analytics is meant for marketers. There’s 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 hard-code proper data collection and goal tracking.
If you want to become proficient in using the GA platform, there is an online academy and certification program available. But this education requires basic technical knowledge and requires people to take time away from already-busy days to learn. It may take some time for teams within an organization to take action on data that your company is amassing.
With a Customer Analytics platform, you are in control of your platform’s usability and accessibility.
Rather than conforming to pre-defined templates as you would in Google Analytics, you have the freedom to run analyses and build queries as you learn. You can then save these queries, to support collaboration with teammates across your organization. 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.
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. Only self-serve options are available for free Google Analytics users, as account management is only an option for paying 360 customers. If you don’t work with a consultant, you risk spending time on analytics that isn’t even working properly, to begin with.
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.
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 you’re looking for basic information about your website and are part of a small team, Google Analytics will be enough for you.
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:
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.
This blog post was a collaboration among the Indicative Team. While Bjorn Sigurdsson was lead author, Marc Liebmann, Esmeralda Martinez, and Tara McQuaide also contributed to the narrative. Ritika Puri was the writer.