{"id":454,"date":"2018-06-14T18:49:37","date_gmt":"2018-06-14T18:49:37","guid":{"rendered":"http:\/\/recommendationinsights.com\/?p=454"},"modified":"2018-06-26T01:25:31","modified_gmt":"2018-06-26T01:25:31","slug":"the-promise-and-pitfalls-of-current-recommendation-engines","status":"publish","type":"post","link":"http:\/\/recommendationinsights.com\/?p=454","title":{"rendered":"The promise (and pitfalls) of current recommendation engines"},"content":{"rendered":"

NOTE: You can right-click all images to view a larger version. Left-click to go to data source.
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\u00a0Value<\/h1>\n

As arbitrary as they often seem,<\/span> “35 percent of what consumers purchase on Amazon come from recommendations”<\/span> —\u00a0 McKinsey<\/a><\/h3>\n

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The big disconnect<\/h1>\n

While people value good recommendations, most (7%) rarely click on one from a site because 93% find them irrelevant.<\/p>\n

Yet, those 7% who do click on a recommendation amount to 24% of orders and 35% of Amazon’s revenues.<\/p>\n

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The very small percentage of site visits (7%) that resulted in a click on a recommendation is testament to the irrelevance of most recommendations.<\/p>\n

It is probably NOT a coincidence that a Digital Marketing study published in 2015<\/a> –3 years before the graphic, above — found that 93% of users say that offers are NOT relevant regularly or all the time.<\/p>\n

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Suboptimal: Even Amazon mostly fails<\/h1>\n

\u201cThere\u2019s a collective belief within the e-commerce industry that Amazon\u2019s recommendation engine is a suboptimal solution,\u201d<\/strong><\/a>\u00a0 — Trisha Dill Fisher, Wells Fargo analyst.<\/p>\n

Dill Fisher: ‘”it\u2019s hard to fault Amazon for their recommendations,’ but she also says the company has a lot of work to do in offering users items more relevant to them. As an example, she points to a targeted email she received pushing a chainsaw carrying case. (She doesn\u2019t own a chainsaw.)”<\/span><\/p>\n

\"Screen<\/a>Optimizing via big data personalizations<\/h1>\n

Consumers Find Personalized Ads \u2018Creepy,\u2019 But Still Want Meaningful Interactions<\/a><\/em> — [a]list<\/h3>\n

\"Screen<\/a>Creepy personalizations<\/h1>\n

\u00a0“75% of consumers find most forms of personalization at least somewhat creepy”<\/em>— In Moment: 2018 CX Trends Report<\/a><\/h3>\n

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More Personalization Perils – The $756 Billion Penalty<\/h1>\n

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Personal Data- Personalization Perils – Legal and Regulatory<\/h1>\n

Beware \u201cSon of GDPR!\u201d EU privacy czars are crafting something even stricter!<\/h3>\n

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Needed: A new paradigm<\/h1>\n

Recommendation Insights is in touch with a Canadian development company which has developed a completely new paradigm that dramatically raises accuracy and relevance far above current methods using collaborative filtering, clustering techniques and other “state of the art” technologies. According to the company, the new algorithm reduces the reliance on big data and is GDPR compliant.<\/p>\n

More information will be forthcoming. To make contact with this “stealth mode” company, email Lewis Perdue<\/a><\/p>\n

Some background reading<\/h1>\n