What is the difference between Google Analytics and the Zoovy Business Intelligence Desktop application? A lot of people think they basically do the same thing - which is sort of true - they both help users visualize data.
First we're going to spend a moment explaining what GA does, and how much we like it. The Zoovy Business Intelligence desktop application definitely has some functionality overlap with Google Analytics, in fact Zoovy clients will still use Google Analytics to measure website traffic, visitors (the BI app cannot analyze traffic data since Zoovy does not record/store that in a user accessible format) - so most clients will probably want to keep using Google Analytics to be able to study traffic behavior on each of their sites. GA is a great tool for analyzing web traffic - especially with the amount of data amending that Google does such as country of origin, browser type, etc.
GA could be considered an entry level business intelligence application for web data, however it lacks the ability to create adhoc queries or do robust data/import export (so it's all non-actionable data) - which is fine, because Google wants it to be an Analytics tool - which is only one facet of a real BI tool.
* Hint
Even though the traffic data for the BI tool is not exportable from Google Analytics, Zoovy does maintain traffic logs and can send those files for clients who want to use the BI tool to manipulate data. GA is a great tool, so it's typically not necessary.
The Zoovy Business Intelligence Desktop application has access to data that is not available in Google Analytics (GA) because GA does not have the rich data such as product cost, product tagging (categorization), manufacturer, supplier, product type, origin, shipping class, etc. GA does not know which orders were from repeat clients, and which orders were for pre-orders, or back orders, or had more than one supplier, it does know which suppliers an order went to, if the order was edited, and which employee worked with it, or it if was subsequently returned. Further more - google analytics can only track web sales, so other sources like ebay, amazon, buy.com, sears, newegg, bidz.com etc can't be tracked and compared against web traffic. It can't look at phone orders, or point of sale orders either. GA is limited to the web sales data, and it's further limited to it's list of internal tracked variables and a handful of user definable variables that are SAFE to expose to the public (supplier and cost generally aren't considered "safe"). That's because everything GA does with data collection is public and is transmitted via the customers browser using javascript. For that reason it must be lightweight, and public.
Google Analytics is limited to running within a web interface, and is limited by the speed of the javascript engine. Specifically the developers at Google are restricted to the "nominal performance" of the slowest JS engine (IE) since they can't assume everybody is running the latest version of the chrome browser and at this time Google doesn't offer a Chrome vs. Non-Chrome version of GA. These constraints force the GA developers to limit the size of the data sets, and how a user can interact with them, not to mention they are having to work through the browser windowing model which adds substantial overhead for functions like drag and drop, sorting, right click, etc.
Since the BI component is a desktop application, and it runs under the Microsoft .NET framework as a native 32 or 64 bit application accessing a local database usually over a 100mb or 1gb network interface - it's much faster, and the difference between a native application is the difference between running Microsoft Office, and Google Apps. (We love Google Apps, but lets just say most sane people wouldn't want to publish a manuscript on it!). That native vs. web application is even more important the more intensive the demand of the application is, and this type of interactive data mining is without a doubt the most intensive application any business will run - so speed/capabilities and overhead really matters to the overall user experience and capabilities of the application.
Finally it's also worth mentioning that the bi component can be used to analyze more than just sales/traffic - it can be used to analyze customer behavior (for remarketing campaigns), and product inventory (to optimize warehouse & supplier efficiency), any piece of data that is tracked can ultimately be populated into a cube and then worked with. Since Zoovy has a meta-data database with infinite support for custom fields, it means anything you can dream, you can track, and ultimately report on.
The BI application can export data into CSV files, and in the future we hope to let clients take direct action within the software itself. Currently the BI tool can answer questions like: how many customers have purchased three times over the past year with a 90 day or less frequency, with an average order of $100 or more, but who haven't purchased in the last 60 days -- that's something that a person familiar with the BI tool could extract in a minute or less. Then they could export that data - and use the promotional capabilities within the Zoovy platform to send a $5 giftcard with a 30 day expiration, and a coupon code for free shipping on one item -- and by the time they finish with that task the barrista at starbucks should just be finishing up with the foam on their latte. So the BI tool really puts an incredible power at the fingertips of the data analyst with it's ability to create the ad-hoc variables, and manipulate them up/down or sideways and instantly visualize what happens to the data in realtime. In that capacity - it's nothing like GA, or any other application on the market for that matter.