Understanding Consumers with Google Analytics

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Understanding Consumers with Google Analytics

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Post by Max Crowe, Developer with insights from Caterina Merenda, Marketing Specialist, Content

To understand consumer intent and motivation to purchase, brands must learn about consumer actions and patterns on their sites, as well what consumers do before reaching their sites.  With tools like Google Analytics, brands have the opportunity to do just this.

GOAL TRACKING

Within Google Analytics, brands can leverage a specific feature, Goals, to track how often visitors perform specific actions on a website. Goals also allows brands to track conversions (e.g. orders placed, newsletter sign-ups, PDF downloads, etc.) and engagement (e.g. amount of minutes user spends browsing a site, amount of pages a visitor views, etc.).

By gathering consumer information on conversions and engagement through Goals, brands can begin to uncover specific types of interactions that users have with a website. So, what types of Goals can brands set up? There are four main categories:

  • Destination: Destination Goals are triggered when a user visits a certain URL. The filters can be toggled to provide results for exact match URLs, broad match URLs, complex matching, case sensitivity and more.
  • Duration: Duration Goals are triggered whenever a user’s session lasts longer than the minimum threshold
  • Pages per Session: Pages per session Goals are triggered whenever a user views more than a certain number of pages in a session. In Google Analytics, a session is a related group of interactions a user has with a single website; it ends when a certain amount of time (typically 30 minutes) elapses since the user’s last action on the site, or when a user re-enters the site from a new marketing channel and thus begins a new session.
  • Event: Event Goals are triggered the first time a user triggers a certain event during a session

Each of these Goals allow brands to identify something new, and possibly eye-opening, about their customer base and visitor retention.

ADVANCED SEGMENTATION

It’s important to understand the value of an organic click, a paid click, an email sign-up and so on. But, it’s impossible to leverage these metrics without knowing what visitors who do these things will do in the future. With Google Analytics’ Advanced Segmentation, this becomes possible.

Within Advanced Segmentation, there are two different types of segments: (1) condition-based segments, which indicates that the order in which users participated in an event (e.g. clicking through to an ad/an organic listing) is unimportant and (2) sequence-based segments, which is the opposite—the order in which the user participated is significant (e.g. clicking on an ad that leads to a video view).

With both of these segmenting options, brands can set up specific dimensions to narrow down their results. Because condition-based segments indicate that the order is insignificant, the filtering capabilities are more along the lines of metrics, whereas the sequence-based segments offer filters that are more relationship-based.

EVENT TRACKING

For most websites, simple page view tracking (e.g. interactions with forms, file downloads, video views, etc.) aren’t enough. Fortunately, Google Analytics’ Event Tracking feature allows measurement of actions that may be specific to a given site and can be configured to track practically anything. Unlike Goals and Segments, Event Tracking requires JavaScript code changes to a site.

By leveraging the DOM (Document Object Model), developers can plug-in JavaScript code that runs instead of, or in addition to, what the browser would normally do. Before setting up Event Tracking, it’s crucial to understand and determine exactly how users complete the action that will be tracked. Do they click a specific button? Do they submit a form? If the event is conditional on something, what is it? Once a brand has completed this discovery process, a JavaScript developer will understand how to map the action to the appropriate DOM event and begin sending tracking data to Google Analytics.


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