{"id":5495,"date":"2020-12-02T23:33:20","date_gmt":"2020-12-02T18:03:20","guid":{"rendered":"https:\/\/www.intelligencenode.com\/blog\/?p=5495"},"modified":"2026-03-17T14:57:04","modified_gmt":"2026-03-17T09:27:04","slug":"how-data-driven-assortment-optimization-empowers-retailers-to-grow","status":"publish","type":"post","link":"https:\/\/www.intelligencenode.com\/blog\/how-data-driven-assortment-optimization-empowers-retailers-to-grow\/","title":{"rendered":"How Data-Driven Assortment Optimization Empowers Online Retailers"},"content":{"rendered":"\n

What\u2019s the best way to position your products to effectively entice consumers on your eCommerce store and maximize your returns? That\u2019s a question that every company, on one level or another, comes face to face with. How you answer it, though, makes a world of difference: Do you rely on intuition, on long-held practices supported by status-quo thinking? Or do you utilize industry-leading analytic tools to build a multi-faceted assortment optimization strategy?<\/p>\n\n\n\n

Here at Intelligence Node<\/a>, we\u2019re firm proponents of the latter. Establishing a strong merchandising strategy is as important for online stores as it is for your traditional brick-and-mortar stores. With data-driven, AI-enabled assortment optimization, companies can thoroughly consider all the vital factors of a product\u2019s selling appeal: From inventory stocks and competitor analysis to product bundling and audience segmentation to customer preference and alternate product viability. <\/p>\n\n\n\n

Understanding each of these elements enables a company to make smarter decisions with respect to organizing their SKUs. More specifically, adopting assortment analytics can lead to growth in per-product margins, improved customer relations, and better performance for each product category<\/a>.<\/p>\n\n\n\n

With that big picture in mind, let\u2019s zoom in and explore what assortment optimization looks like from a practical perspective.<\/p>\n\n\n\n

First thing\u2019s first: Effective category management requires strategic inventory practices<\/h2>\n\n\n\n

Before you do anything else, use an assortment optimization software<\/a> to understand the lay of the land. Take a look at what your competitors are offering: Are there any product categories that are overrepresented? If so, heavily pursuing that direction may be an uphill battle. But what about the other side of the coin: Are there any categories that are even somewhat underrepresented? If yes, this could be your golden opportunity for growth.<\/p>\n\n\n\n

That being said, just because there is an opportunity doesn\u2019t mean it\u2019s the right opportunity for your brand. You also want to make sure that your categories reflect the desires<\/a> of your existing customers and target audience.<\/p>\n\n\n\n

Read more : Assortment Planning \u2013 The Holy Grail of Merchandising<\/a><\/pre>\n\n\n\n
Now, this begs the question of how<\/em> to know what your customers want \u2014 a difficult question, given that they may not know themselves. The infallible answer, as always, comes to us in the form of data: Taking a look at past SKU sales patterns is the most effective way to achieve assortment optimization. We\u2019ll dive deeper into this notion in the next section, but for now, suffice it to say that historic data and analytical evaluations of SKU trends can inform decisions<\/a> about which parts of your inventory to prioritize, which to keep as they are, and which to remove or replace.<\/p>\n\n\n\n
So: On the one hand we have market opportunity and on the other we have consumer interests. One of the keys to category management is finding the overlap between the two and shaping your inventory to match it.<\/p>\n\n\n\n
With the aid of smart, intuitive technology, this becomes an ongoing iterative process, on autopilot. Your software assesses the efficacy of various categories\u2019 performance \u2014 how profitable they are for you, how they\u2019re performing for competitors \u2014 and you adjust your offerings according to smart recommendations.<\/p>\n\n\n\n\"Compare<\/a><\/span>