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Why Rules Based Personalization Can’t Handle Big Data

Rules in a rules based personalization engine are pre-defined, static and have a limit on effectiveness. E.g. – all first time users who come to the site will be presented with a special coupon to save 10%. This would be part of a set of rules that govern the delivery of content, promotions etc. There are drawbacks to this approach. Creating, implementing and maintaining “rules” is labor intensive and thus very costly. Rules simply identify groups and categorize people; as such their intelligence is finite and ineffective when dealing with Big Data.

Rules categorize people; this is fine with small and narrowly focused websites.  Add Big Data to the picture and the drop in relevancy is proportionate with the increase in data. Aka – one goes up the other goes down.  Essentially you start to brush everyone with the same stroke and your results become less relevant.  So as your site grows your revenue decreases and you have to start working harder to make less money.

Algorithmic based personalization analyzes and creates a potentially limitless amount of machine generated micro segments. With the algorithm learning, adapting and evolving from these experiences.

With algorithmic based personalization an algorithm monitors user behavior patterns. A model is developed and personalized individual content is presented. The algorithm learns from these experiences and as the individual’s likes and dislikes change over time these changes are reflected, in real time, in the content displayed. The algorithm is constantly evolving, learning and adapting in real time. Content can take many forms; basically almost everything displayed on a page can be personalized via algorithm. This takes place all within the confines of your existing template and no adjustments are required.

Youneeq has a wide selection of first to market features that open up new business models and revenue streams. Some of these game changing features are the ability to react to social media hype cycles and real time predictive analytics and modeling. For content curation Youneeq offers the ability to track and learn directly from user behavior data to personalize the delivery of content. For search engine optimization practitioners, Youneeq provides information which allows the creation of personalized landing pages for specific individual users.

Moral of the story: if you have a large user base with diverse interests and a large (and growing) database of content, a real time algorithmic approach is the only way to go.

Why Rules Based Personalization Can't Handle Big Data - Youneeq - Cookieless AI personalization engine

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