Google Analytics helps us identify conversion uplift opportunities. Traffic is precious, and we don’t want to waste it on tests that don’t result in learning or uplifts.
That’s why we want good data for:
- Which pages have uplift opportunities;
- Specific page issues.
Google Analytics won’t tell us what the problems are—we need to interpret the data ourselves. That said, Google Analytics can give us strong hints as to what the problems may be, making it easier to conduct further investigations.
Proper conversion analysis uses multiple methods, data points, and tools congruently. Heuristic analysis, user testing, and technical testing (i.e. whether stuff works) goes hand-in-hand with Google Analytics analysis.
Always keep in mind that looking at only average numbers in your analysis will lead you astray. There are no average visitors—you must segment ruthlessly.
Look at new vs. returning visitors, check performance across different devices and browsers, and buyers vs. non-buyers. What’s working for one segment might not work for another, and personalization could make you a ton of money.
1. The first thing I check in Google Analytics
I’ll start with one of my favorite reports for identifying where to start optimization efforts. I learned this from Craig Sullivan, and this is how I kick off pretty much every optimization project.
It’s a standard report: Behavior > Site Content > All pages.
What I do with this is two-fold:
- Map traffic flow by layer of the site (and see where the flow is stuck).
- Double check if the Goal funnel has been configured properly.
Here’s the flow:
- Start with a manual walk-through of the site.
- Map out the URL structure. If the URL structure is not specific about the type of the page (e.g., */product/*, */category/*, etc.), we’ll start tracking virtual pageviews for the same types of pages.
- Go to Behavior > Site Content > All pages report and type on the URL identifier of the layer (e.g., “/products/”, “/cart/”, “/checkout/step2/”)
- Count the unique pageviews per layer.
I’m constructing a funnel—manually. If you run an ecommerce site, the layers might look something like this:
- Category + Search;
- Checkout step 1;
- Checkout step 2;
- Checkout step 3;
- Checkout completed.
The Behavior > Site Content > All pages report gives you unique pageviews for each layer. Once you have them, check the numbers against what you see in Conversions > Goals > Funnel Visualization. If you see discrepancies, odds are that the funnel has been set up incorrectly.
You can look at the funnel as just numbers, or you can visualize it if that helps you see the big picture. Something like this:
If you had 300,000 product pageviews, 5,000 adds, and 1,000 checkouts, where would your problem be? Cart adds! If you had 300,000 product page views, 100,000 adds, and 1,000 checkouts, your problem is somewhere else.
Optimization experts’ favorite Google Analytics reports
I reached out to fellow experts in the field and asked them for their go-to reports when digging for conversion uplift opportunities. This is what they told me.
2. Chris Goward, WiderFunnel
The most useful report depends on the type of website and goals, but some are handy to pull out for a large swath of companies.
Here’s one from one of WiderFunnel’s awesome strategists, Alhan.
- It filters out mobile. (You can create separate report for mobile traffic.)
- It splits the report by New vs. Returning. (It also gives an idea of the amount of new vs. returning traffic and whether most visitors convert on the first visit or not.)
- It goes into landing pages, sorted by entrance counts, and shows conversion rates for each as well as behavioral metrics, which are more/less useful depending on the website.
Here’s an example of what it looks like for one of our clients:
As Alhan says, “It gives a nice snapshot when looking at a website for the first time to identify some of the big opportunities in terms of traffic-to-performance ratio.”
You can easily swap in metrics that are more important to your website. Just click “Edit” after importing it.
(Goward’s book You Should Test That would make a fine gift for any optimizer.)
3. Tim Leighton-Boyce, Government Digital Service
One of my favorite reports is a standard report that most people ignore: the Conversions > Goals > Reverse Goal Path. I use it for error reporting.
This requires being able to configure a Goal for errors, which is not always possible. But if you can set up such a goal, then Reverse Goal Path becomes very powerful.
Reverse Goal Path works really well in situations for which you can’t predict the steps leading up to a Goal (unlike a checkout funnel). In fact, the steps that lead up to the Goal, in this case, are exactly what we’re trying to uncover.
On rare occasions, you may spot one of those “bug” scenarios—if you do “this,” then “this,” then “this,” you get an error.
But the most common thing I see on ecommerce sites is the existing email account variations that people enter into the “new account” or “guest” email field—they’ve been confused by the design or language of the site.
Another example is when people fail to notice mandatory size, color (or quantity, don’t get me started) selection when adding to cart. Using error reporting in this way is a great tool to spot opportunities to reduce friction.
A useful technique is to use a generic Goal to get an overview and monitor for new variants. (Intelligence Alerts are good for this.) Then, configure a specific Goal, if possible, to target the big errors. You can use that Goal in tests you design as a solution and to measure the long-term change.
It’s hard to produce a screenshot that gives any idea of how the report looks in action without also showing data that might breach client confidentiality. Here’s an attempt that might give you an idea of what your report could look like:
4. Craig Sullivan, Optimal Visit
My favorite report is the conversion rate split by device category and browser. (Segment it by Desktop Only, Tablet Only, and Mobile Only, and edit the report Goals as needed.)
The report helps you identify technical or UX issues for specific browsers and devices. If your website doesn’t work properly with the device and browser a visitor uses, they won’t buy.
Any issues identified here are low-hanging fruit.
5. Justin Rondeau, DigitalMarketer
I have two reports that I really like to use. They’re nearly identical except for my dimension drill down (i.e. the metric groups are identical).
I have two report tabs that differentiate at the dimension level, which give me detailed insight into which marketing campaigns are working.
It also provides valuable information to our marketing and biz dev team when they’re doing marketing barters with prospective partners. Any report that gets you revenue information is going to be very valuable.
Whenever I speak about optimization and reporting, it’s best to speak in the language of the HiPPO—and that language is money.
Whenever I develop content, this report gives me insight into what free content produced the most leads. We also run new ads on the site from time to time, and this helps me figure out how effective those ads were.
I have another report that goes into more detail, but this one gives me a heuristic sense of which content increases buyer behavior and which traffic channels produce the most sales.
6. Theresa Baiocco Farr, Conversion Max
One of the first reports I look at is top landing pages; using the comparison button, I look at their bounce rates compared to the site average.
Top landing pages with bounce rates that are higher than the site’s average go on the list of problem pages to look at in more depth.
It’s simple but good.
7. Sean Ellis, Turazo
One of my favorite ways to use Google Analytics is to look at visitor behavior by initial landing page.
For example, on GrowthHackers.com, we know that visitors who first come to one of our company profiles behave very differently than those who first visit the homepage feed.
Our goal with company profiles was to use them as a customer acquisition engine. While they’ve been great for driving tens of thousands of new visitors to the site, Google Analytics showed us that these first-time visitors rarely click over to our main feed.
This spawned several test ideas to better drive a flow of traffic from the company profiles to the feed. It also revealed an unexpected value from the company profiles, which are a great way to re-engage our primary members (who spend most of their time in the feed).
This alone is justification to keep doing them, but the value will increase significantly when we can drive new visitors from the company profiles to the main feed, which I’m sure we’ll be able to test our way into.
It’s an advanced segment (link here) that’s set up as follows:
- Behavior: Visits > 1
- Advanced Conditions: Landing Page contains /companies/
8. Yehoshua Coren, Analytics Ninja
One report that I like to go to looks at the conversion funnel in a “horizontal” manner, with each step toward the macroconversion a separate goal.
I then evaluate different dimensions, especially the more “technical” ones, such as browser or screen resolution. Often, one can find a cross-browser issue and identify the stage in the funnel where users get stuck.
I also make sure that the report includes some behavioral measures, like bounce rate and page depth—not just abandonment rates between funnel steps.
Here’s the report configuration:
9. Judah Phillips, Squark
Within Conversions reports, I like Multi-Channel Funnels > Assisted Conversions.
The MCF Channel Grouping dimension and metrics (a ranked histogram) enable me to view a set of acquisition, behavior, and conversion metrics adjacent in space to each other.
That, in turn, enables easy scanning both numerically, using ratios/rates, and visually.
I find it easy to scan for conversion trends by channel and by using custom segments, such as Converters vs. Non-Converters.
Proper interpretation of these reports is possible only if the analyst understands attribution and how different attribution models can be interpreted differently by various stakeholders, such as your CMO.
Last-click conversion is default in GA, but certain channels are “top of funnel” or “bottom of funnel,” so it may be improper to assess their conversion efficacy by looking only at last-click attribution. For example, affiliate traffic is more likely to be bottom of funnel; display advertising is more likely to be top of funnel.
And while only one channel may lead to a conversion in a short purchase cycle, it’s more likely that the customer had multiple media exposures. The Assisted Conversions report enables an analyst to understand the role of other channels and media.
10. John Ekman, Conversionista
Everyone knows that quality site search is important for conversions. But they know it only on a general level—as they do with site speed or high-quality images.
So how important is it? One of the first things we do with a new client is to use the segment “Visits with site search.” This includes visitors who, at some point, used the internal site search.
We can then compare the conversion rate for visits with and without a site search. On an average, I would say that the conversion rate for visits with site search is usually twice that of visits without a site search.
When our clients see this number they realize the potential value of improving site search: “What if I could make the search field even more prominent?” They understand—quantitatively—how important site search is.
Word of caution: You need to subtract “bounced visits” from the comparison. Bounced visits have a conversion rate of 0.00%, by definition, so if you include them in visits without site search, you’ll make the visits with site searches look too good in comparison.
You can see what I mean in the sketch.
If you want to dig deeper, mine your internal site search data for misspellings that are unmatched in your results or products that visitors look for but you don’t have in stock.
Internal site search queries are the best tools for finding new business opportunities with your existing customers.
These guys know what they’re doing. Add these reports to your analysis process and reap the benefits.