Multichannel merchants know how important their Websites and landing pages are for selling products to customers. You also know that the more you understand online customer behavior, the more your marketing efforts pay off in the e-commerce arena.
There’s also value in taking what we’ve learned in one channel and applying it to other channels. Let’s take a look at a few sources of data from the online channel—such as search engines, Web analytics, and multivariate testing—and consider what insights we can glean as we strive to improve offline marketing efforts.
Starting with search engine data, the research estimates that nearly 80% of all online purchases start at a major search engine (ComScore Networks). Search engine/pay-per-click (PPC) advertising systems from the likes of Google, Yahoo, and Bing provide marketers with a window to observe the conception of these purchase intents.
For example, consider a search engine advertising campaign for the keywords “winter coat.” By analyzing Google AdWords, we can determine the search trends (demand) and advertiser competition for the keyword over time, illustrating how often Internet users are looking for information about this product.
We can also analyze more specific terms such as “down winter coat” or “skiing winter coat,” and use that as a measure of the number of potential buyers trending over time.
Search engines also let you segment keyword queries by geographic area, which can help you with offline marketing efforts. For instance, geographic online search data can answer the question, “How is the blizzard in Denver affecting purchase-intent for winter coats in upstate New York?”
Are searches in upstate New York also on the rise, as consumers realize that they’ve avoided heavy winter weather for now, but probably not for long? Exploring the data to answer these sorts of questions helps marketers keep a finger not only on emerging online trends, but the pulse of consumer demand in response to what’s happening in the world, such as weather, current events, and so on.
Continuing to follow users from search into the site, we turn to site-side Web analytics as yet another source for marketing data. Exploring site analytics data to find hot products, successful promotions, and frequent cross-sells lends insights to offline print and radio promotions.
For example, what brands and product models are online users buying? Which are they browsing but not buying? What products or brands did users search for within your site that you don’t carry?
Take a look at these online insights and incorporate them as an input to merchandising decisions and demand forecasting in other channels.
Always keep in mind that any data exploration effort should be sliced into meaningful user segments. Are site visits from certain geographic areas trending up or down, and is this in line with historical activity as well as recent offline marketing efforts?
When viewed this way, Website data can be an early indicator that specific offline marketing efforts that mention a URL are either succeeding or askew.
Finally, let’s look at a way to turn your Website into a lab for marketing experiments. One of the best ways to understand and influence online consumer behavior is through multivariate testing, which enables you to test many changes to your Website simultaneously. These testing practices enable you to experiment with alternate promotions, copy and merchandising strategies on your site’s visitors and gauge response.
Evaluating the impact of combinations of these changes often reveals significant interaction effects that can have a dramatic improvement on your conversions, such as clicking the Buy button.
Online content can be tested transparently on actual site visitors—often tens of thousands of visitors per week—and for little to no incremental cost. Not only is this an efficient method for optimizing online behavior, it enables marketers to gauge consumer response to promotions and messaging before their more costly introduction into the print, radio, and TV mediums.
Once you’ve got a handle on basic testing, one of the best ways to glean additional insights is to segment your tests. The logic behind this is clear: why optimize your site for everyone when you can focus your optimization efforts on those types of visitors who have already demonstrated value to your business?
There are two ways to conduct a segmented test: ad hoc and post hoc. The former method requires that you are able to identify segment members in real-time so that the testing engine can assign people appropriately.
As an example, you may be targeting “first time visitors” or “visitors referred from Google organic search results.” The latter method for segmenting is post hoc—after the fact—which is more an analysis technique than a testing strategy. In this case you will mine test results for segment members and compare these results across control and test groups.
As audiences continue to move online, our collective understanding of visitor behavior in the Web channel needs to become more sophisticated as well. The use of testing technology is already a best practice from the perspective of a data-driven organization.
Even more important, the opportunity to take the output from testing and further analyze the data for otherwise inaccessible insights will undoubtedly be one of the trademark techniques of analytic competitors of the future.
Eric J. Hansen is the founder/CEO of SiteSpect, a multivariate testing and behavioral targeting platform for Websites and the mobile Web.