We talked last week about where to find beta testers, but there’s another important “where” when it comes to beta recruitment. Where do your testers live? Geographic location is an oft-neglected factor in beta testing, but it can be critically important. So today, we’re going to look at situations in which where your testers live matters just as much as other demographic characteristics.
Geographic location can make a huge difference in how a product performs, particularly for hardware. Just about everyone is familiar with how cell phones, GPS devices, and other radio-based technologies can vary from one area to the next, even on a scale as small as a city block. But there are other, less-obvious examples of how location can impact product performance. Environmental factors like temperature, humidity, and pollution can dramatically alter performance and customer experience, and they can vary wildly in common customer environments (e.g., Alaskan winter vs. Nevada summer).
You might be thinking these conditions can be tested in a lab, and they should, but lab tests rarely attempt to simulate the full spectrum of product use that you can get from beta testing. So, if there’s reason to think your product might perform differently in various environmental conditions, factor geographic location into your beta test recruitment.
Your product may be subject to special requirements or restrictions depending on where it’s being used. Whether due to trade compliance laws, specific safety requirements, or something else entirely, you might have to either deny applications from beta testers who live in specific areas or alter your product to comply. Perhaps the most common circumstance for dealing with this issue is the U.S. export restriction on cryptography. However, features that raise personal privacy concerns can also meet strong international resistance, as Facebook just experienced with the launch of its facial-recognition technology.
Localization and Language
This one may seem obvious. If you’re localizing your software, of course you’re going to branch out into the appropriate country for testing. The devil is in the details, however. Sometimes you need to drill down past location, as these two examples illustrate:
If you’re a U.S. company that doesn’t have the resources to fully localize into other languages, you might still decide to sell your product abroad. Many companies will distribute an English-language product in non-English speaking markets where English is commonly spoken as a second language. You still need to run a beta test in that situation, and you’ll want to recruit more than just individuals in that country who speak English well. You need to find testers with varying degrees of skill in speaking English, because that’s who you’ll encounter in the marketplace. This is one of the great examples where beta testing provides something that simply cannot be simulated in a lab.
The same principle applies when you are doing a full localization of your product, especially if you’re entering a melting-pot country like the U.S. Your target country’s inhabitants can come from all over the world and possess varying degrees of language fluency. If your beta process ignores those who don’t speak the language well, you may find that large portions of the market find your product unusable and your support costs (if not sales) will suffer from it.
People are a product of their environments. Testers from different neighborhoods, cities, provinces, states, regions, and countries may all perceive you and your product differently. This means that you can get different beta test data depending on not only how it is being used but who is using it. It’s smart to use this diversity to validate your product assumptions, and dangerous to ignore it. For example, if you envision your product as the next hot Web 2.0 property, but your beta testers are drawn exclusively from San Francisco and Silicon Valley, it would be unwise to extrapolate positive feedback and assume the product will be a global hit.
On the other hand, sometimes you really have to focus your beta tests on small, concentrated areas. Let’s say you’re developing a restaurant review web site and want to launch a beta test. The network effect tells us that the value of a site like this is going to correlate with the number of people using it. More specifically, in this case, the number of people using it in a given area. If you have 100 beta testers spread throughout the U.S., the density of your reviews won’t be sufficient to give people a meaningful product to test. You need your testers generating and consuming reviews in one geographic area, so they can assess the true value of your service.
As you can see, geography can become very significant to beta testing under certain circumstances. Sometimes it’s a trap for the unwary, but hopefully this blog post will help alert you to situations where you might need to give more thought to where your testers reside. Once you’re mindful of these situations, it’s often easy to reason out a solution.
In which situations do you really focus on where your beta testers live? Please leave a comment!
Image courtesy of Flickr user Tuppus.