{"id":9766,"date":"2020-11-19T13:52:31","date_gmt":"2020-11-19T08:22:31","guid":{"rendered":"https:\/\/www.vue.ai\/blog\/?p=9766"},"modified":"2024-01-10T19:58:17","modified_gmt":"2024-01-10T14:28:17","slug":"the-making-of-vue-ai-personalization","status":"publish","type":"post","link":"https:\/\/www.vue.ai\/blog\/ai-in-retail\/the-making-of-vue-ai-personalization\/","title":{"rendered":"The Making of Vue.ai\u2019s Personalization Solution"},"content":{"rendered":"Reading Time: <\/span> 3<\/span> minutes<\/span><\/span>\n

Back in 2016 when Vue.ai was launched, not many retailers had heard of AI-based personalization engine<\/a>. Even retailers like Starbucks had just begun conversations about the possibility of AI  Being innovators in this space, this meant that we had to work as extensions of retail companies, helping them tap into the power of AI to demonstrate significant business impact. Today we are 200+ people across 4 continents and we still work this way! <\/p>\n\n\n\n

Vue.ai\u2019s Personalization solution is a distillation of everything we\u2019ve learned over the last 4 years of working with over a 100 retailers across the globe, helping them build personalized customer experiences that move the needle.<\/h4>\n\n\n\n

Here are some of our biggest lessons:<\/h2>\n\n\n\n
  1. Too many conversations about personalization are really about segmentation. <\/strong>At the end of the day, a shopper wants to see content that is relevant to them and that they love. Segmentation as a strategy is just not enough. Clustering people based on some shared behavior or characteristic is convenient but often has no impact. 
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  2. Data is a problem, everywhere. <\/strong>Retailers found themselves at the right end of a powerplay between them and the CPG industry as a result of data. Yet most organizations we worked with, irrespective of their size, had broken data and data in silos.  
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  3. A solution to one retailer’s problem is not a solution to another’s. <\/strong>Just as we kept telling our customers that their shoppers are all different and they need to understand their individual preferences and intent, retailers too came in various shades. A single, one-size-fits-all solution simply won’t cut it. The inventory a retailer carries, whether they have an in-house label, their brand strategy- all have a big impact on how a personalization engine<\/a> should be designed. 
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  4. eCommerce teams are increasingly expected to function at superhuman levels and be experts in marketing, merchandising and technology. <\/strong>They end up using a dozen tools to manage customer experiences and these tools don’t ‘talk’ to each other. This adds to their work load and leads to more broken data. <\/li><\/ol>\n\n\n\n

    Vue.ai\u2019s Personalization solution addresses many of these challenges. At its core, its mission is to help eCommerce teams move beyond transactions and build customer experiences that are so remarkable, they define the brand. But while it keeps it simple for eCommerce teams, behind doors it does a lot of heavy lifting. <\/h4>\n\n\n\n