It was in the mid-1990s when I had my first taste of actionable web analytics. I was working for a telecommunications company that offered a Voice over IP solution (VoIP) and I was part of the team that tracked banner placements on websites like Excite, Yahoo, and AltaVista. I will never forget the cartoonish banner that consistently beat out every other banner ever produced. It was counterintuitive, but that alone isn’t what excited me. Here we were in the mid-90s and this company’s web team was able to tell you exactly how many minutes of phone calls were made to Guatemala as a result of banners placed on a particular keyword. They were even able to predict how many people would call Russia after they downloaded the VoIP software from the sports pages on Yahoo. These were the metrics that drove the media buys and placement decisions week after week. This was my web analytics reality and so it set my expectations.

After that, I started working with a startup, a specialty retailer. When I began working with them, I was shocked at how little people were tracking. Not that they didn’t have metrics but they weren’t the type of metrics you could make decisions and take action on. This is still, sadly, the reality for far too many companies today. While today so many companies have sophisticated analytics installed to measure web activity, the organization and planning of their measurement is still poor and the ability to take action on that data is still minimal.

I would like to share just some of what just a handful of companies are doing with their insights today in the hope it will inspire you to analytics greatness.

One of the companies I know, a multi-channel retailer, provides regular reports to their physical store managers of the browsing history from visitors who are geographically located near the store. The reports are not so impressive; it’s the action they drive that impresses me. These store managers often rearrange in-store displays to promote the items visitors are viewing the most online.

You can do a similar thing even if you are an online-only retailer. You could easily change home page, search results, and category promotions based on geo-location data and visitor browsing history. Imagine you are a home goods and hardware retailer and you begin to see an increase in searches for shovels and snow blowers from the Boston area because the weather forecast shows a winter storm coming. If you were a multi-channel retailer, your Boston store would put shovels, melting salt, and snow blowers on prominent display, while your Miami store might still be showing garden hoses prominently. Online you can use segmentation and personalization tools like BTBuckets (which is free) to swap out your promotions for geo-targeted traffic from Boston to see your winter storm promotion. Enterprise tools like Monetate can even leverage built-in capabilities to target geo-location traffic based on local weather or weather forecasts.

Another similar multi-channel retailer collects and analyzes in-store scans of their product shelf tags by cellphones and uses that data to change end-cap displays based on scanning popularity. They can also take that same scanning data and change website promotions to mirror the popular products in those locations for website visitors.

I know several other companies that are monitoring product reviews and changing their local inventory based on how positive and negative reviews are. Again, you can use business rules to change your website behavior and target visitors based on all of these fantastic data points.

Another simple geo-personalization tactic you can use is custom messaging international visitors. It can be as simple as displaying the fact that you ship to the visitors’ countries to changing tag lines or promotions to be localized. Monetate has found that across its significant client base when it personalized experiences based on international visitors’ geo-location, it improved conversion rates by as much as 100 percent.

Are you already using geo-location data to your advantage? If you are, please share how you are using the data with our readers. If not, then can you afford not to take advantage of the geo-personalization opportunity?