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Predict Your Audience's Preferences

Howard Fiderer
Predict Your Audience's Preferences Howard Fiderer

In today's competitive environment, consumers are overwhelmed with choices. There can be dozens of options available for even the most specialized of products. The pressure to capture consumers' attention is made even greater given the availability of online purchasing.


Given consumers' ability to visit many sites in a relatively short time frame, it becomes even more important to keep them engaged and on your site. To do so, the site must be sufficiently interesting to speak to their individual needs, wants and personalities.


Marketers have long known that a one-size-fits-all approach to marketing cannot address individual tastes. Direct marketing techniques, for example, take advantage of consumer data allowing for more targeted mailings based on characteristics such as demographic information. By utilizing data such as life cycle, income and age, marketers can tailor their messaging to prospects, improving their overall conversion rate. The need for this type of approach is just as great on the internet where users often disengage before the webpage is fully rendered.


The good news is that there is a wealth of information available about internet users as part of the browser session, including basic user data such as their connection speed, the time and the day of the week. We can even derive geographic location down to the zip code level. By combining this information with offline market data such as their life style segmentation, it is possible to create a fairly accurate profile of every user. Best of all, this information does not rely on user-provided data and is completely anonymous. The use of anonymous user data not only makes profiling easier but also protects user privacy.


It is possible to capture data across many visitors and see which user characteristics lead to the desired outcome. The trick is to make this information actionable so that you can tailor the user experience on their very first visit.


In its simplest form, you can imagine that during the winter months users from the north are more likely to be interested in down jackets than their southern counterparts. Now imagine that we can explore dozens of such attributes and determine which ones are truly predictive of user behavior.


More importantly, you can see which marketing messages and creative executions drive individuals toward conversion. And, since this data is not tied to site interaction, it is possible to tailor the messaging and creative immediately and not wait for multiple site visits.


When compared with techniques that require the user to provide personal information or needs to build a user profile across multiple visits, the advantages of a predictive approach become obvious.


Of course, additional information can and should be gathered as users interact with the site. This information will allow for the continual fine tuning of messages presented to users. The more relevant the messaging, the better the user experience and the more likely prospects will be to convert to customers. But, if the messaging is not right on the first visit, you may not have a second chance. After all, you only get one chance to make a first impression.


Howard Fiderer is VP, product management for [x+1]. .


 

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