How To Use Google Analytics To Optimize Your Community Website | PCR Media Kit How To Use Google Analytics To Optimize Your Community Website – Private Communities Media Kit

How To Use Google Analytics To Optimize Your Community Website

Published on July 15, 2019

Do you recognize that logo? 

If you’re not seeing it at least once a week when you log in for your routine web traffic check-up, you’re missing out. 

Missing out on valuable (and free!) data that can measure the performance of your master-planned community website and educate you with insights to improve your marketing efforts.

By setting up Google Analytics (GA) for your community website, you can…

  • Discover how visitors are finding your site (Google search? Referral traffic? Direct?)
  • See how many visitors are being sent your way from partner sites like PCR 
  • Find out which of your pages are getting the most traffic and shares (Amenities? Home listings? Membership?) 
  • Examine what pages/sections on your site are driving the most lead conversions (General Contact Us? VIP Tour Request? Brochure Download?)

If you’re not familiar with the platform, it may seem intimidating. It’s really not. Intuitive and easy-to-navigate for the critical details that will help you validate and fine-tune the effectiveness of your website, here’s an overview of all the ways you can (and should) be using Google Analytics.

Monthly Google Analytics Report

Let’s start with your top, high-level GA report. When logged in, click Audience > Overview in the left-hand Reports menu, select the date range you want to isolate in the top right box, then…voilà. You’ll get a nice snapshot with traffic patterns and visitor behaviors.

 

NOTE: Images used throughout this article are to demonstrate general examples, and are for reference only.

Where Are Your Website Visitors Coming From?

We’ll get back to more detailed traffic reports in a moment…

But right now let’s take a look at how your users are finding your website.

Google Analytics Channel

Click on Acquisition > All Traffic > Channels. Then select your desired date range.

What you’ll see are broad categories showing how users found and accessed your site.

Types of channels include: 

  • Direct: These users came to your site directly by either clicking a bookmark in their browser or typing your URL into their address bar. There are a few nuances if you’re interested in a more in-depth read on direct traffic.
  • Organic Search: These users found your website organically, through a search engine. Whether it was a keyword or phrase, your lifestyle brand, real estate region, or community name, their search results displayed your website and compelled a click.
  • Referral: These users were referred to your website from another website. Real estate community sites get a fair amount of referrals from their listings on sites like PCR, for example.
  • Social: A social visit happens when a user clicks a URL to your site on Facebook, Twitter, LinkedIn, etc.
  • Email: If you’re running an email campaign and a user clicks through to your website from their inbox, they’ll show up as email traffic. Be sure to enable the Google Analytics integration if you’re using a platform like MailChimp or Constant Contact. 
  • Paid Search: Traffic shows up under paid search when a user clicks a Google Ad or Bing Ad you’re running.
  • Other: If a channel is not defined or set, it may show up as “other.”

Google Analytics Source/Medium

Drill down past channel and you’ll find the more detailed source/medium—the actual domains sending traffic to your website. So if organic was the channel, you now know Google was the specific source. A referral channel may have been from a mention and link to your community on a popular industry blog site, and so on.

GA will automatically fill these in, or you can create campaign-specific URLs with UTM tagging.

Detailed Traffic Patterns with Google Analytics

Now that we’ve seen how visitors are finding your site and where they’re coming from, let’s get back to more detailed volume traffic reporting.

The above graph shows the traffic of a specific website for each day of the month. This graph can be manipulated to display weekly or monthly traffic, as well as compare against a past period of equal length.

By looking at this graph on a regular basis, you can see trends in traffic. Is traffic gradually increasing? Were there any unusual spikes or dips? For example, a healthy new website in combination with a consistent display and/or SEM campaign is expected to have a steady growth in traffic every month. Spikes in traffic might be caused by a campaign, which brings a lot of traffic in a short period of time, like a mention in an email newsletter or Facebook ads.

With sufficient data we can compare days, weeks, months and even years of traffic. In the example above we are looking at a comparison between September (orange) and October (blue) traffic for a given business. We can observe that on September 8 and 9 the website had unusually high traffic. With GA, it’s easy to determine the cause of these traffic spikes. Just isolate the specific dates and look at where the traffic came from (back to Source/Medium):

Isolating the specific dates of September 8 and 9 and looking at the sources that generated the traffic, we can see that the majority of users came from Facebook, which would hint that on those two days there was a promotion running.

Analyze Visitor Behavior with Google Analytics

You recall the monthly traffic overview screenshot near the open of this article? Here we’ll break down what each user behavior category means for your website.

Sessions: A Visit, or Session, represents the full timespan that a Visitor/User spends on your site, starting when your site first loads in their browser and ending when the User either leaves the website, closes their browser, or the Visit times out after 30 minutes of inactivity. 

Users: Unique Visitors, or Users, represent the number of unique Web browsers that access your website during a specified time period. The presence of cookies in those browsers determines whether they have visited the site before. Ideally, each browser is counted as a Unique Visitor only once in a given time period.

Unique Pageviews: Unique Pageviews represent the number of Visits during which the specified page, or group of pages, was viewed at least once. Multiple views of the same page and page refreshes are not included in this metric.

Pageviews: A Pageview represents a web page being loaded in a web browser. Multiple views of the same page are counted in this metric. Files like Word or PDF documents are typically counted using a different metric, called Events, rather than Pageviews.

Pages / Session: Pages Per Session represents the average number of Pageviews during the course of a Session (Total Pageviews divided by Total Sessions).

Avg. Session Duration: Average Session Duration represents the average amount of time, in seconds, of a Session. Technically, it represents the time between the start time of the first Pageview and the start time of the last Pageview or Event.

Bounce: A Bounce represents a Session with only one Pageview (a User looked at one page only and left the site).

    • Whether a Bounce is negative or not depends entirely on the content of the Web page. Some Bounces occur because Users enter the site on the page that provides the content they want (in many cases that would be the landing page for a campaign).
    • However, you want to limit Bounces from pages that are meant only to direct Visitors to other pages on the website.

Bounce Rate: The Bounce Rate represents the percentage of single-page Sessions (Total Bounces divided by total Sessions).

New Sessions / Visitor: New Sessions represent the number of first-time Sessions during a specified time period. The presence of cookies in the Web browser determines whether it is a New or Return Visit.

% New Sessions: The percentage of New Sessions represent the number of first-time Sessions during a specified time period. (Total New Sessions divided by total Sessions)

Return Sessions / Visitors: Return Sessions represent the number of repeat Sessions during a specified time period. The presence of cookies in the Web browser determines whether it is a New or Return Visit.

Google Analytics Tracking Metrics

Google Analytics can undoubtedly move the needle and help you drive property sales in your community…if you properly track, adjust, and base key decisions on the data you uncover. 

Here’s a sample chart that can be used/customized to help manage and combine your GA reporting and marketing campaigns. 

Each business has unique needs and objectives, which require customized sets of metrics to be monitored on a regular basis.

And make no mistake, this has been a very general overview of Google Analytics. The level of granularity with which site admins can truly harness the power of GA is nothing short of head-spinning.

But for many master-planned and lifestyle community marketers, the basics are more than enough—or at least a great place to start. 

Using Google Analytics to track important metrics on a regular basis can provide insight that’s not only practical and valuable…but actionable. 

Being able to compare performance across different campaigns allows you to keep your goals on track, review and evaluate media effectiveness, and remain flexible in finding the best solutions for your diverse real estate marketing needs.

 

 

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