Google Analytics can do what? 3 examples of advanced data upload for ecommerce

by Jim Cain

While Google Analytics (GA) has millions of enthusiastic users, there is still an unfortunate opinion in large businesses that it isn’t ‘ready for prime time’ in the enterprise.

This is no longer the case. GA is much easier to implement, more cost effective and in many ways way more powerful (I’m looking at you attribution) than comparable tools.  One of the most overlooked areas of GA is currently the functionality around data upload, which isn’t surprising, given that it can be difficult to take advantage of.

Once you get comfortable with how data uploads work however, you quickly realize that with a little bit of effort you can evolve Google Analytics from a clickstream measurement tool to a marketing intelligence platform. I have at least one conversation a week with someone about what Google Analytics is capable of with data uploads that changes the way they look at the tool. Instead of a bicycle with training wheels, Google Analytics is a supercar (some assembly required).

Our friends at Babbage Systems have been writing a lot of great blog posts recently on how to take advantage of data uploads with their Analysis Engine product for Google Analytics. Below are links to the most recent ones, and how each of them could move your Google Analytics deployment from “a quality free tool” to “the cutting edge of measurement”.

1. Refunds in Google Analytics

One of the things that GA is great at is accurate traffic/campaign tracking. For Adwords you can even get cost analysis out of the box (and get it for everything else with cost data upload). Even with all this great data it can be hard to get executive buy in around action.  How come?  Web analytics numbers from any tool (Revenue, ROAS, Attribution, etc.) are exclusively tied to the bookings of the reporting period. Any business with a decent transaction volume has people who cancel, change, or even grow their order – on the site, in the call centre, or in store. Want to tie ‘actual’ revenue to your site performance? Upload the order change data. Not only will the data be much more business-relevant, but imagine the additional analysis you can do.

2. Cost Data Import and Return on Ad Spend (ROAS)

Almost every user of Google Analytics with an AdWords account knows what cost data looks like — but just for AdWords. Most of those same users are equally frustrated that they see zeros behind all their other paid marketing channels. Imagine the analysis you could do if you could see cost data for everything, tied into GA’s advanced attribution and segmentation functionality.  Few organizations are able to ask the question “how much did it cost to get a sale” and answer it accurately. With Google Analytics you can. Not only does full adoption of cost data imports open up better and more accurate analysis, it will make the web analyst the most popular person in the company when budget time rolls around.

3. Gross Margin and Cost of Goods Sold (COGS)

Companies that want to make actionable decisions with their web analytics data, especially ones with large merchandising organizations, tend to not ask their friendly neighborhood digital analyst for reports. Why you ask? Because businesses need a lot more than conversion rates, transactions and top line revenue to keep the lights on. Are we selling the high margin products?  Transactions went up, but did we keep more of the money?  By injecting product cost data into GA at the product level, you move the analytics tool from clickstream/behavior into merchandising/online product mix.

Any eCommerce business that takes advantage of all three of these advanced data upload features will not only have a cutting edge, world-class web analytics deployment (regardless of price), but will also have access to some of the most actionable retail performance data in the market.

In a future post I’ll talk about the same thing for SaaS companies and Lead Generation sites, but in short, take off the training wheels with Google Analytics and strap on the rockets.  Your employer will thank you.



Jim Cain

Founder and CEO, Napkyn Analytics

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