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Behavioural Targeting: Rules Based versus Predictive Analytics: Part 1

The Internet has a “big data” problem – millions of website visitors with diverse interests means copious amounts of data. Rules based systems are crushing under the weight of big data. The only way to solve this problem is with predictive analytics that utilize organic intelligent algorithms.

With the massive, ever growing density of Internet competition, web industries vying for visitor traffic and e-commerce conversions have complications to face. Moving into the third decade of mainstream Internet use, visitors are more refined than ever with high expectations, demanding immediate access to pertinent content delivery under a well designed easy to navigate umbrella. Time is valuable and people lead busy lives, so website visitors want what they are looking for quickly and efficiently without having to siphon through large amounts of data. This is extremely important to online publishers with data rich sites, such as news and entertainment properties. Content heavy industries that understand these concerns have the edge, steering away from old standards and static website offerings to incorporate systems that use behavioural content targeting.

Traditional methods of driving web traffic to static websites through expensive ad campaigns and search engine optimization is no longer a viable primary strategy. Huge amounts of capital spent trying to bring visitors to websites using these methods alone is throwing money out the door, because there are no guarantees and it is a time consuming, ongoing process. However, a dynamic, more customized visitor experience applying behavioural content targeting alleviates this significantly by delivering targeted content to visitors based on who they are and what they are interested in.

With behavioural content targeting, website browsing data from visitors’ interactions is collected in order to determine what content and ads to display to visitors. Profiles are created about visitors based on values such as demographics, location, the amount of time spent on site, pages visited, activated links and the advertisements visitors interact with. When visitors come to the site, profiles are called up and content is delivered, supported by the appropriate profile. When treated this way, bounce rates drop, visitor retention is higher, ad campaigns are more accurate, conversion rates are greater and return on investment increases.

However, there are different systems of behavioural content targeting that need to be understood. These include simple rules based systems and predictive analytics algorithms. In the next blog I’ll discuss the two systems in more detail. But I wanted to make one point beforehand. Occasionally we run into the folks who hear the term behavioural targeting and think of simple rules based systems, with the idea that building such systems in-house is easy, and is a good enough solution. Youneeq is not a simple based rules system, but rather a complex set of algorithms that are constantly changing and evolving over time. Youneeq uses intelligent organic algorithms to match individual users with highly focused and targeted content – an intricate application to build. More soon.

Behavioural Targeting: Rules Based versus Predictive Analytics: Part 1 - Youneeq - Cookieless AI personalization engine

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