Simply knowing the numbers in your Google Analytics eCommerce report isn’t going to help you. It’s what you do with them that counts.

We mentioned earlier that Google Analytics eCommerce tracking is a powerful tool, but today we’re diving into that mysterious middle step, the transition between acquiring data and applying it. You already have all the facts and figures, but now what do you do with them?

One of the reasons Google Analytics Enhanced eCommerce is so effective is the magnitude of data it collects, including some areas the standard Google Analytics ignores. This data can reveal many of the elusive factors you need to make informed business decisions:

  • How to design the site to appeal to your visitors
  • The areas of your site that are most/least effective, and what that means
  • Raw components for a SWOT analysis
  • Behavioral patterns that signify problematic areas

This behavioral data, and using it in these four areas, is the focus of our piece today. The numbers aren’t going to do any good just lying there on the page. Let’s explore what you can do with them.

How to Apply Data for Visitors

All retailers should cater the shopping experience on the preferences of their specific customers. For eCommerce, that means a lot more than product lines and prices; online stores also have to account for site design and the user experience.

At the basic level, you have general demographics, which you can view these directly in Audience > Demographics. This broad data informs broad strategy decisions, such as the navigation system or style of writing.

Coupled with other marketing studies, the behavioral data from Google Analytics eCommerce tracking becomes invaluable. If you match the customer data from your site with the preexisting customer data from marketing research for that group, you’re able to hone in on your visitors’ preferences with pinpoint precision.

Google Analytics eCommerce - Age

Age

Let’s start with age. Behavioral data for different age groups is well-established, so you can easily make sweeping design changes if you know how old your average visitors are. The following come from the research of the Nielsen Norman Group, one of the most trusted names in online studies and marketing data:

  • The younger a person is, the less text they prefer. For teenagers, copy like product descriptions and blog posts should be as short as possible. The older your shoppers are, the more words they tolerate, so you can expand commensurately.
  • Young adults (18-25) are the most sensitive to the tone of the text, especially if it seems condescending, or if it’s trying too hard to sound “cool.”
  • Young adults are also the most skeptical. They tend to trust social media and peer reviews more than advertisements and on-site text. To reach them, a brand should move their attention more on their social media presence and less on advertising through influencer channels.
  • Teens enjoy interactive elements like games or quizzes. As the age progresses, this attitude shifts, and older customers only enjoy interactivity when it serves a purpose.
  • Younger shoppers tend to experiment more with navigation and tread off the beaten path. Give them this choice with multiple navigation options and easy return routes. Older shoppers are more compliant, and will more often follow whatever navigation guidelines you provide. That puts extra pressure on the design team to optimize their central navigation.
  • Older shoppers blame themselves for errors, younger shoppers blame the site. Either way, the UX is damaged. You can tailor your error screens accordingly, accepting the blame if sites are predominantly older shoppers, or gently guiding younger shoppers back on course without having them lose face.
  • Ironically, younger shoppers are more accident prone, with a mentality that the NNg calls “click first and ask questions later.” A site targeting young customers should spend more time on error control and prevention.

Google Analytics eCommerce - Gender

Gender

Gender, too, should influence site design, although the documented gender differences are more blurred and mercurial than age groups. First you need to understand the fundamental difference between how men and women think, and the biological reasons, before we get into the strategy. Both are reviewed in this article from Guided Selling.

Logic dominates the left hemisphere of the brain, while emotions dominate the right. Because women have a more developed corpus callosum connecting the hemispheres, they’re able to use both sides in decision-making activities such as shopping, whereas men tend to stick only the left side’s logic.

This suggests that men are more task-oriented shoppers, aiming to “complete the job” as quickly and effectively as possible. Women, however, are much more open to a drawn-out shopping experience that take longer but are more enjoyable. Here are some direct applications we can take away from these studies (please excuse our gender generalizations — we’re the first to admit these are not always applicable; they are just loose guidelines, not black-and-white rules):

  • Women are more suggestible to veering from their set paths, making promotional windows like product recommendations and sales adverts more potent.
  • Men prefer a straightforward navigation layout right from the start of their landing page. Women are more open to browsing new or unexpected sections, especially if they appeal to the emotional aspects of the shopping experience. For example, home page features for “extra” sections like shopping guides or the brand’s ecological policies perform better with women than men.
  • Men prefer imagery that revolves around the product itself, such a direct product photo against a plain background. Women prefer imagery that suggests how the product will make them feel, for example, how clothing looks on them or how a gadget will improve their lives. Product photos for women can be more contextual and tell a story.
  • Women are more responsive to email marketing. The email establishes a more personal connection, and you can speak directly to the customer and explain your value.
  • Men are more responsive to paid advertising. If your ad hits them during their shopping process (and your product/promotion is good enough), then men will see the ad as a shortcut to accomplishing their shopping goals faster.

Google Analytics eCommerce - Interest

Interests

Directly below demographics (Audience > Interests) is the Interests section, which takes the user data from a macro scale to a micro scale. Here you can really see what your visitors want, with more precise data on customer types and coalescent markets.

The Affinity Categories are pretty straightforward, and show you concretely what interests your visitors have, and more pertinent what types of products they’re looking to buy. This can have a direct effect on your marketing campaigns and which products you promote, and can even shift your entire business strategy into an entirely new industry.

Think of the In-Market Segments section as a smarter way to expand your advertising campaigns, especially when re-marketing, according to Word Stream. This allows you to observe specific user groups of your own design, best used when determining where to place ads. According to Google, in-market segment advertises to more than the eager shoppers, but also to people on the fence.

Google Analytics eCommerce - Location

Geo

Last, don’t forget to check the Geo section (Audience > Geo) for more macro-level customer data. Here you can learn the broad basics of Language and Location. Language will, of course, tell you which language/translation options you need — or don’t need — on your site. Location can be a bit more telling.

Location is most important in eCommerce for determining shipping options. You may have more customers from abroad than you think, in which this data might inspire orchestrating better international shipping options. Domestically, you can track which cities are most popular for purchases to restructure the logistics of your national shipping operations, particularly where to seat your fulfillment warehouses.

You can also use the location section cross-reference with cart abandonment. If you’re noticed a lot of cart abandonment on the shipping page of your checkout, it might because your shipping options are lacking in a popular area.

Just as important are payment options. Certain countries have their own payment preferences or systems, so make you incorporate the payment options to make your customers feel most comfortable.

Related posts:  Juicy New LemonStand Features, Tutorial Video, Theme Updates and More

More creative eCommerce managers can use location to stimulate new ideas or promotional campaigns. If your popular geographic regions are cold, you could advertise more products for keeping warn, for example. If there are regional celebrations, you could have a special sale just for them. Even distinguishing between rural and urban areas can have its advantages, even on specific products, for example a range of gardening equipment.

Think outside the box — everything you know about your shoppers, even where they live, offers you the potential to strengthen your relationship.

How to Apply Data for Products

Google Analytics eCommerce - Product Performance

Google Analytics eCommerce Tracking monitors product performance just as meticulously as it does with customer behavior. Go to Conversions > eCommerce > Product Performance to see a list of data for each and every product you offer, including statistics on:

  • Total product revenue
  • Percentage of total revenue
  • Unique purchases
  • Average quantity bought per purchase
  • Amount for product refunds
  • Views of the product page
  • Views of the details on the product page
  • Adds/Removes from carts
  • Percentage of cart adds after viewing the details
  • Percentage of buys after viewing the details

Applying product data requires a little bit of deduction on your part; it’s not so clear-cut what the figures on their own mean.

Obviously, you can separate your successful products from your lacking ones, good to know when deciding which products to feature over others. At the very least, you know which products to keep your eye on to make sure they don’t go out of stock.

However, you can’t always define success by which products make the most money. You’ll want to factor in all the data, not just the completed purchases metric.

Many Views, Few Purchases

For example, you may have a product that has a high rate of views, but a low rate of purchase. Google Analytics eCommerce tracking is specifically designed to sniff out this exact kind of situation, because it reveals a great business opportunity.

In this case, you can cross-reference other data points to see what blocks an otherwise popular product from being purchased. How are the rates on the detail views? Is the product a novelty that people are just curious about, or were visitors sincerely considering purchasing it? How far along on the checkout did they abandon their cart? It could be an issue with pricing, shipping, or payment options.

Google Analytics eCommerce - Behavioral Flow

You’ll also want to check out the report in Behavior > Behavioral Flow, one of the most important for eCommerce site design. It graphs out your typical customer journeys so you can visibly see your individual page performance. Here, you can see where customers go after the product page — perhaps they spot another product they want more and leave the first product for the second.

If the same problem exists with multiple products, maybe it’s your product page layout. If only a few products have this issue, you can focus on these products individually.

Few Views, Many Purchases

Likewise, watch out for products with a small rate of views but a high rate of purchases. These are a big opportunity; more often than not, it suggests that a product is inherently high value, but under-publicized.

In this case, again look at your behavioral flow report to see where most of your traffic is coming and going. Promote the product in high-traffic areas for the exposure it needs. If you have the Interests and Affinity Categories set up, you can even recommend the product on the pages of similar products.

Products Bought Together

And speaking of similar products, check to see if certain products are often bought together. This could signal an opportunity for promoting the products on the other’s pages, or perhaps a special promotion for buying the products together.

Few Detail Views

If the product has low rates for its detail views, there’s either a problem with the details display, or the product itself. The former calls for a rewrite or perhaps changing the entire product page layout (if the problem happens often); the latter calls for re-evaluating if you want the product in your line.

Average Order Value

Another important product performance statistic is the Average Order Value, found in Conversions > eCommerce > Overview.

Google Analytics eCommerce - Average Order Value

If this number is below your liking, you can raise it with one of these commonly used tactics:

  • try cross-selling and/or upselling related products
  • offer discounts and price breaks when customers purchase higher quantities
  • offer free shipping on purchases over a certain amount.

The above are just a few of the more popular tactics, check out this post for 15 growth hacks to increase average order size.

SWOT Analysis with Google Analytics eCommerce Data

Improving site performance doesn’t have to be a one-time thing. Conducting a SWOT analysis periodically helps you guide the direction you site goes in and keeps performance at peak levels. But instead of shooting in the dark, the Google Analytics eCommerce data keep your observations accurate and remove most if not all of the guesswork.

In case you’re new to the concept, a SWOT analysis means accessing the Strengths, Weaknesses, Opportunities, and Threats of a business model, product, concept, etc. It can be done as a group discussion with the team, or alone by a single decision maker.

The Google Analytics eCommerce data reveals each of these areas, if you know where to look. If you’re going to reevaluate your eCommerce store’s business model or strategy, consider these data points:

Product Performance. This is one of the pages you’ll be spending a lot of your time on. In Conversions > eCommerce > Product Performance, you see a list of all your products and their related statistics, ranked from best to worst by whichever metric you choose. These are your obvious Strengths and Weaknesses.

Behavioral Flow. This chart reveals your most and least successful pages (Strengths and Weaknesses). Consider pages with a large drop-off rate as Threats, and popular intermediary navigational hubs as Opportunities for promotion.

Demographic and Interests. Most often, this area shows you new opportunities. Are you delivering enough options to Movie Lovers (for example)? If shoppers with certain characteristics/affinities are already visiting your site, take the opportunity to market to them.

Acquisitions. We’ll discuss acquisitions in a later article in this series, but it’s worth mentioning here as either a Strength or a Weakness.

Bounce Rates. The MVP of Google Analytics eCommerce data for SWOT analysis. Your bounce rates (Behavior > Site Content) are even more accurate than revenue for determining how effective certain areas of your site are. The golden rule for bounce rates are “the squeaky wheel gets the grease.” Pages with high bounce rates are obvious entries for Weaknesses, Threats, and Opportunities.

Google Analytics eCommerce - Bounce Rate

You’ll want to redesign or eliminate completely these pages/products, although some digging may be required to find the root of the problem. Try A/B testing different layouts of the problematic pages to see if that unveils the troublemaker.

Keep in mind, however, that bounce rates are not always the fault of the page itself: sometimes they’re the result of a faulty navigation system. If a user lands on a page in error, of course they’ll leave it quickly. You may need to implement a more comprehensive navigation system to fix the problem.

Takeaway

We hope this article gave you some good ideas of how to approach and apply your own Google Analytics eCommerce data. There’s a lot of information there, and a lot you can do with it, so our goal was to help you stay focused on achieving what you want out of these statistics. Stay tuned for our next piece, where we’ll examine data for referrals, content, and social media.

Do you have any tips or techniques for Google Analytics eCommerce tracking? Do you have any questions? Let us know in the comments section now.