One of the key things Google Analytics helps us do when optimizing a website is identify conversion uplift opportunities. Traffic is precious, and we don’t want to waste any of it on tests that don’t result in learning or uplifts. That’s why we want to have good data for:
- A) which pages have uplift opportunities and
- B) specific page issues.
Google Analytics won’t tell us what the problems are, we need to interpret the data ourselves. That being said,Google Analytics can give us strong hints as to what the problems may be, making it easier for us to pinpoint and look deeper into the issues and to conduct further investigations. Proper conversion analysis is always done using multiple methods, data points, and tools congruently. Heuristic analysis, user testing, and technical testing (whether stuff works) goes hand-in-hand with Google Analytics analysis.
Always keep in mind that only looking at 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.
The first thing I check in Google Analytics
I’ll start off with one of my own favorite reports that I use for identifying where to start my 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 out traffic flow per 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, and map out the URL structure. If the URL structure is not specific about the type of the page (e.g. */product/*, */category/* etc), I’ll make sure we’ll start track virtual pageviews for the same types of pages.
- I go to Behavior -> Site Content -> All pages report, and type on the URL identifier of the layer, i.e. “/products/”, or “/cart/”, or “/checkout/step2/” or whatever they may be, and I count the unique pageviews per layer.
Basically, what I’m doing here is constructing a funnel – manually! If you run an eCommerce site, the layers might be something like this:
Category + Search
Checkout step 1
Checkout step 2
Checkout step 3
So you’re using Behavior -> Site Content -> All pages report to get unique pageviews for each of those layers. Once you have them, you need to check the numbers against what you see in Conversions -> Goals -> Funnel Visualization. If you see discrepancies, odds are that the GA funnel has been set up incorrectly.
You can look at the funnel as just numbers, or you can visualize it if it helps you see the big picture better. Something like this:
If you had 300k product page views, 5k adds and 1k checkouts where would your problem be? Cart adds! If you had 300k product page views, 100k adds and 1k checkouts your problem is in a different place!
Optimization and analytics experts share their favorite reports
I reached out to various fellow experts on the field and asked them for their go-to reports when digging for conversion uplift opportunities. This is what they told me.
Chris Goward, WiderFunnel
The most useful report will depend 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, he uses part of our Kaizen Plan process.
Here’s the Shareable Report Link: https://www.google.com/
- It filters out mobile (a separate one can be created for mobile traffic)
- It first splits the report by New vs. Returning (also gives an idea of the amount of new vs. returning traffic and whether most visitors convert on the first visit or not)
- It then goes into landing pages sorted by entrance counts and shows conversion rates for each, as well as behavioral metrics, which will be more or less useful depending on the website.
Alhan says, “It gives a nice snapshot upon looking at a website for the first time to identify some of the big opportunities in terms of traffic-to-performance ratio. It’s called ‘High Trafficked/Low Converting LPs (non-Mobile).”
You can easily swap in metrics that are more important to your website. Just click “Edit” after importing it.
Chris’s book “You Should Test That” would make a fine gift for any optimizer.
Tim Leighton-Boyce, CXFocus
One of my favourite reports when looking for opportunities is a standard report which 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 on a site. But IF you can set up such a goal then the Reverse Goal Path becomes very powerful.
The Reverse Goal Path works really well in situations where you cannot predict what the steps leading up to the goal are, unlike a checkout funnel. In fact, the steps which lead up to the goal in this use case are exactly what we’re trying to find out.
On rare occasions you may spot one of those ‘bug’ scenarios where if you do ‘this’, then ‘this’, then ‘this’ specific sequence you will get an error. But the most common thing I see on eCommerce sites are the existing email account variations people enter into the ‘new account’ or ‘guest’ email field because they’ve been confused by the design or language of the site.
Another example is people not noticing the mandatory size, colour (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), and then configure a specific goal, if possible, to target the big errors. You can then use the specific goal in the tests you design when coming up with a solution and to measure the overall change in the long term.
It’s very hard to produce a screenshot which gives any idea of how the report looks in action without also showing data which might breach client confidentiality. Here’s an attempt that might give you an idea of what your report might look like:
Tim is speaking on this subject at Superweek on Wednesday, January 22nd 2014.
Craig Sullivan, Optimal Visit
Custom report link: https://www.google.com/analytics/web/template?uid=QVznrqOgTaOGgQ_HPnnPtw (make sure you segment it by Desktop Only, Tablet Only and Mobile Only). Edit report goals as needed.
Peep’s comment: this helps you identify any technical or UX issues for specific browser and/or devices. If your website doesn’t work properly with the device/browser a visitor uses, they won’t buy! Any issues identified here are low-hanging fruits.
Justin Rondeau, WhichTestWon
I have two reports that I really like to use, they are nearly identical except for my dimension drill down, i.e., the metric groups are identical. I have two total Report tabs that differentiate at the dimension level.
This gives me detailed insight into which of my marketing campaigns are working. I think what is most interesting about this report is that at WhichTestWon we do a lot of content marketing (e.g., guest appearances on blogs, webinars, podcasts, etc), and this gives me some information to report back to my boss about how effective these campaigns actually were.
This also provides valuable information to our marketing and biz dev team for them to use when they are 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 is best to speak in the language of the HIPPO – and that language is in $$$.
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 these ads were. I have another report that goes into more detail, but this gives me a heuristic to work with.
As a publication that uses free content to promote our paid content, shows, and sponsor offers; these two reports help me understand what content increases buyer behavior and which traffic channels are producing the most sales.
Theresa Baiocco, ConversionMax
One of the first reports I look at is top landing pages; using the comparison button, I look at their bounce rates compared to site average. So 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.
Sean Ellis, Qualaroo
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 that first visit the home page feed. Our goal with company profiles was to use them as a customer acquisition engine. While they’ve been great for driving 10s of thousands of new visitors to the site, GA showed us that these first-time visits rarely click over to our main feed on GrowthHackers.com.
So this has spawned several test ideas to better drive a flow of traffic from the company profiles to the feed. On the other hand, GA revealed an unexpected value from the company profiles. Turns out that the company profiles are a great way to re-engage our primary members who generally 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 that is setup as follows:
Behavior: Visits > 1
Advanced Conditions: Landing Page contains /companies/
Here’s a link to the segment configuration, but it doesn’t show traffic data: https://www.google.com/analytics/web/template?uid=Wze7JiQpSJWHbZhydxKJZw
Yehoshua Coren, Analytics Ninja
One report that I like to go to is one that looks at the conversion funnel in a “horizontal” manner, with each of the key steps towards the macroconversion being a separate goal. I then evaluate different dimensions, especially the more “technical” ones such as browser or screen resolution. Oftentimes, one can find a cross browser issue in this way and identify at which stage in the funnel users are getting stuck.
I also make sure the report includes some behavioral measures like bounce rate and page depth—not just looking at abandonment rates between funnel steps.
Judah Phillips, Digital Analytics Thursdays and KarmaLoop
I like the indexes of “first interaction conversion” and “assisted conversions” on the Multi-channel funnels > assisted conversion report.
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, which enables easy scanning both numerically, using ratios/rates, and visually. I find it easy to scan for conversion trends by channel overall and by using custom segments, such as Converters and Non-Converters.
The tabs for “first interaction conversion” and “assisted conversions” on the Multichannel Funnel report are available by default in GA with no custom download necessary. Proper interpretation of these reports is only possible 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 can be improper to assess their conversion efficacy by only looking at “last click” attribution. For example, affiliate traffic is more likely to be bottom of the funnel whereas display advertising is more likely to be top of the funnel. It may not make sense to evaluate a media plan or predict performance from using conversion inputs to your model that are only last click based. Thus, indices of first/last click conversion, or linear/last click conversion (available in GA’s attribution modeling tool) can help the savvy analyst understand conversion in the context of the multichannel path to conversion in order to provide analysis and insight for improving the allocation of media spend.
Related, while it can be the case that only one channel leads to a conversion in a short path to purchase cycle, it is more likely the customer had multiple media exposures. The “assisted conversion” report enables an analyst to understand what other channels and media have assisted conversion such that these ‘assists’ can be considered and not omitted when planning and evaluating a media strategy to drive conversion, revenue, profit, and economic value.
John Ekman, Conversionista
One of the Favorite reports: Conversion rate for visits with site search.
Internal (site ) search is important for conversion. Everyone knows that. But they know it only on a general level. Like – “Site speed is important”, “High quality images are important”, and “Good search is important”. The question is – How important is it?
Therefore, one of the first things we do with a new client is to use the segment “Visits with site search”. This means visitors which at some point in their visit used the internal site search.
Then we compare the conversion rate for visits with and without site search.
On an average, I would say that the conversion rate for visits with site search is usually TWICE AS HIGH as visits without site search.
When our clients see this number they start going – “Mmm , Ahh – What if I could improve site search even more. What if I could make the search field even more prominent?” They understand, for real, 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%, by definition, so if you include them in visits without site search, you will make the visits with site searches look too good in the comparison.
You can see what I mean in the sketch.
If you want to dig deeper, start mining your internal site search data for misspellings which are unmatched in your results or products which visitors look for but you currently don’t have in stock. Internal site search queries are the best tools for finding new business opportunities with your existing customers.
Here’s what it looks like in GA:
Custom report link: https://www.google.com/analytics/web/template?uid=63zLMp5pQyGQIYsrxsnX4g (remember to adjust goals as needed and segment for non-bounce visits).
These guys know what they’re doing. Add these reports to your analysis process, and reap the benefits.
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