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Customizing Megalytic: Traffic by Demographics Widget

Published December 30, 2015
Sure, you may start analyzing website data by looking at traffic volume and engagement to give yourself a general view of how many people are finding your site. But are you also taking the time to evaluate demographic data such as age, gender, and interests to learn more about the people who do find it?
Looking at traffic by demographics will tell you even more about your visitors, allowing you to identify if you’re actually reaching the audience you desire to target. In addition, you can also see if a particular unexpected demographic is taking interest in your site. For instance, you may currently target 18-24-year-olds, but find that you’re getting the most interest from people in the 35-44 age range. This level of insight can help you uncover new, more profitable opportunities for marketing.
To help businesses leverage these insights, Megalytic offers a Traffic by Demographics widget allowing you to show Google Analytics demographic data in your reports. In this article, we’ll review how to set up this widget in your reports, as well as how to customize it based on the information that you want to show. Of course, you’ll first want to make sure that you’ve enabled demographic data collection in Google Analytics. Once the data begins appearing in your reports, you can import it into the widget.

 

 

Choosing Demographic Dimensions

When you first add the Traffic by Demographics widget, you’ll choose a Google Analytics view to connect. You’ll then see a table graph breaking down Traffic by Age Group.

 

Traffic by Demographics

 

You can, of course, choose to show other data besides age here. Within the widget options, you have the option to break down data by one of five dimensions:

 

Selecting the Dimension

 

Age Group

Google Analytics breaks down age group into six buckets.

  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65+

Note that data about visitors under 18 years old will not appear in this report to keep data private for minors.

Gender

With this option, you’ll see data broken down by male vs. female. As with other demographic dimensions, this information comes from data tracked via the DoubleClick cookie (used for ad tracking) and mobile app advertising IDs. Information from Google profiles may also contribute here.

Affinity Category

Affinity categories describe the lifestyles of your visitors based on their web browsing behavior. If they frequent sites that fit a specific topic, you’ll see that category show up in the report. Note that the same users may be counted in multiple categories where they fit. Examples of categories include:

  • Art & Theater Aficionados
  • Auto Enthusiasts
  • Avid Investors
  • Foodies
  • Gamers
  • Green Living Enthusiasts
  • Health & Fitness Buffs
  • Movie Lovers
  • News Junkies & Avid Readers
  • Sports Fans
  • Technophiles
  • Travel Buffs

In-Market Segment

In-market segments include users who show intent to purchase goods or services based on their general online activity. Examples of segments include:

  • Apparel & Accessories
  • Autos & Vehicles
  • Beauty Products & Services
  • Consumer Electronics
  • Financial Services
  • Home & Garden
  • Real Estate
  • Travel

Other Category

This dimension includes highly-targeted categories that zero in on specific visitors’ interests within the broader Affinity Categories and In-Market Segments.

For example, Food & Drink breaks down into further categories, such as the following:

  • Cooking & Recipes
  • Food/Baked Goods
  • Restaurants/Fast Food
  • Beverages/Coffee & Tea

Changing Chart Types

You can portray demographic data in various ways by changing the type of chart used in this widget. For instance, if you want to compare how each age group segment has contributed to traffic over time, you can select an Area Chart. This is the second icon under “Chart Type” in the widget options.

 

Customizing the Area Chart

 

Once you’ve selected the chart type, you can then choose which categories to show in the actual widget. In this case, we want to choose the age group segments that will appear in the report. Use the “Series” dropdown to select your desired options, and click “Apply to Report” to update the widget’s appearance.

 

Area Chart with Customizations

 

In the final widget, you’ll be able to see how each age group compares to the others size-wise, as well as how changes have occurred over time.

Next, for visitor interests, you may want to simply show a list of the top categories. The Table View comes in handy here to show category names, along with metrics for each.

Here, we’ve selected the Table View icon and switched Dimension to In-Market Segment. We can see traffic and engagement performance for each segment, customizing the available metrics by using the “Columns” dropdown at the bottom of the widget options. In this case, we’ve added a Completions column to show how many people from each segment actually completed a Goal on the site (in this case, a free trial signup).

 

Table Graph in Megalytic

 

Now, we can see the top In-Market Segments in which people fit when visiting your site, along with how long people are spending on your site for each and how many result in Goal completions.

Filtering & Segmenting Demographic Data

You may want to show demographic data more specifically than the default widget options allow. For instance, you may want to break down visits by age group specifically for women who came to the site. Using Megalytic’s custom filtering option, you can apply a filter to the report using one or more metrics or dimensions.

 

Adding a Filter in Megalytic

 

Select “Add Filter” from the widget options, and then choose the parameters for your desired filter. In this case, we’ll choose to include any sessions in which Gender contains “female,” limiting our data to women who visit the site. We’ll also choose to show a dimension of Age Group with a bar graph for chart type.

Once we’ve applied the filter and our other options to the widget, we’ll see the final data. Now, we can clearly show that the majority of women visiting the site fall in the 25-34 age bucket, with each successive age range dwindling from that point on.

Imported Google Analytics Segments can also be applied as another way of showing more specific data. You can apply any Segments available via your currently synced Google Analytics view.

For instance, we may want to break down age groups of people who found the site via organic search. To do this, select the Segment section of widget options and click the current Segment name (default will be All Sessions) to see a list of available ones to apply.

 

Applying a Google Analytics Segment

 

In this case, we’ve chosen Organic Traffic, as well as selected New Users from the Metric dropdown above. The graph will now break down age groups for organic visitors tracked as coming to the site for the first time.

Conclusion

Megalytic’s Traffic by Demographics widget offers a number of ways to show data about age, gender, and interests for your website traffic. You can show information from beyond your website to data tracked via outside sources about people who came to your site.

By choosing from among several chart types and possible demographic information, you can portray specific data about who is coming to your site. Use segments and filters to drill down even more specifically to categories of individuals that you’d like to track.

ALSO IN THIS BLOG

When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:

 

 

It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.