DIGITAL MARKETING | Building Customer Data Knowledge

<p>The Visionary Chronicles Podcast</p> <p>CHRONICLE # 81: May 5th, 2022</p> <p> </p> <p>"Data is not information, and information is not knowledge, knowledge is not understanding, understanding is not wisdom.”</p> <p>                                                                                                                                 Knowledge from Clifford Stoll</p> <p>PODCAST: DIGITAL MARKETING | Building Customer Data Knowledge</p> <p> </p> <p>Digital marketing has been moving at the speed of light, and most brands will be left in the dust. But unfortunately, they continue to manage their digital marketing strategy as if it was 1999, not 2022.</p> <p>It is challenging to jump and stay on this fast-moving train without getting run over, but you must have a digital strategy that allows for knowledge learning.</p> <p>Knowledge is the king of digital marketing, anticipating consumer needs, offering recommendations, and being proactive with products that match immediate needs.</p> <p>Companies like Amazon are a model of how to anticipate consumer needs and continually adapt to changing conditions. Amazon is at the pinnacle of digital AI, and this has taken them decades to perfect. They sell over 4,000 products every minute, with over 55% recommended through their AI database. With a database of over 350 million items, they reset their algorithms within seconds. These recommendations are relative to Amazon assets; Prime, Prime Video, Amazon Fresh, and Whole Foods.</p> <p>Google is another brand with an endless amount of consumer data and Shopping analysis algorithms. In addition, the interconnectivity of Google is ongoing, with over 25 billion data points connecting products with consumers.</p> <p>Both Amazon and Google, along with many other brands, capture how individuals exercise, work, play, interact, vacation, and other activities which define specific recommendations.</p> <p>The intent is to learn their customer's preferences and offer what they “may” need before they know it or when they are lookin