If your online shop analytics stops with the order, it is stopping short. Some product groups like Fashion tend to have high return rates, so looking at refunds can give you a different view of your shop and marketing performance. At siroop.ch, a new Swiss online marketplace, we tried to look at what happens after the order in both Google and Adobe Analytics. While Google’s imports may require a bit less setup time, they have major limitations. Adobe Analytics’ Transaction ID Data Sources gave us the full picture from Campaign to Cancellation.
For a Category Manager of an online shop with hundreds or thousands of products, it can get difficult to find those products that are performing poorly AND are worth optimizing.
You cannot simply work on all products that did not sell well last week, there are just too many. Focusing on only those products with high margins is not going to help much either.
Here are some helpful performance metrics you can create in Adobe Analytics (formerly SiteCatalyst) – and partially also in Google Analytics.
Technology software here, analytics tools there. It’s hard to get through a jungle of vendors, especially when youdon’t know in detail which requirements and future scope the Analytics or Business Intelligence road map has in your own company.
Luckily there are research companies out there providing an overview; besides the two giants Forrester and Gartner there are a only a handful of additional trustworthy research companies doing well researched studies and overviews. One of them is Third Door Media, now having published their latest Market Intelligence Report about “Enterprise Web Analytics Platforms 2015 – A Marketer`s Guide”.
German, French and English Visits, Internal and External Visits – all in one Report as neat, compact metrics. All this without having to spend a lot of time with tedious breakdowns and segments (and still not getting what you’d really like to). That’s what an Adobe Analytics client needed. The new “Unified Calculated Metrics” now make this possible – something that you can’t do in Google Analytics by the way.
The “breakdown” is something so essential to Adobe Analytics that you can hardly do any real analysis without breaking down. Breaking down is sort of a combination of what Google Analytics users know as Drilldowns and adding a second or third dimension to a report. When you break down with Adobe, you break down one dimension by another one, e.g. the Campaign Name by the Device and that by the Browser and that by the Browser Version and that by the Entry Page and so on… You can get as granular as you want and never have to fear sampling like in GA!
More Users than Sessions? Impossible! 172 Pageviews, but 0 Sessions? Probably an issue with the implementation. Unfortunately, it is the weird way in which Google Analytics, to this day, interprets Sessions, formerly known as Visits.
I was about to finish the second part of my Comparison of Custom Variables in Adobe, Webtrends and Google Analytics, but now this has to wait a bit. While writing about GA’s Custom Dimensions, I kept stumbling over the one reporting issue (besides sampling) that has been hounding and annoying me for years.
Since this issue is a bit complex, I decided to dedicate an entire article to it. I am talking about the weird Sessions metric in Google Analytics (formerly “Visits”, but with the same deficiencies).