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Category assortment: through image recognition

Category assortment: through image recognition

The retail business comes with a large managerial requirement. Presenting the right product at the right location to the right customer to organize stock availability, retail comes a long way of planning and executing. 

 In the retail industry, major attention is won by e-commerce, in-store experience, financial decisions and many more. Ignorance is paid to a significant factor in the retail business- “product assortment”.  The product assortment is often named product mix. It refers to the whole set of products and/or services offered by a firm; consists of product lines, which are associated items that consumers like to purchase. As we all know, it is impossible for all stores in a chain to require all lines. They are of different sizes, have different sales figures, and can have different customer profiles. Retailers need to give clear instructions to their buyers.

Planning assortment helps you to pave the path for breaking up spending among various product lines/products. It is never over as it is an ongoing process that requires a comprehensive and systematic approach that evolves the changing customer behaviour in-store. 

Retail space is costly and costlier the inventory costs. Consumer goods companies often look at unit sales volume or profit to identify their best products and optimize their category assortment. 

Several questions are answered through this process.  As vital it sounds for a business, as is neglected. Many retailers fail to analyse the trends of customers buying in certain time periods and thus avoiding the out-of-stock situation. 

Retailers are missing out on nearly $1 trillion in sales because they don’t have on hand what customers want to buy in their stores

 Companies do not invest in assortment planning.  Decades have gone by without major changes in the assortment. The initial stage of assortment requires time and energy which retailers do not put in. 

Planning assortment comes with 4 elements to be kept in mind. 

  1. Width

Width is also referred to as breadth, it means the number of product lines offered by a retailer to its customer. 

For example, HUL provides various product lines as food and beverage, self-care, laundry, home care, etc.

  1. Length 

The length refers to the total number of products in a product mix. For example, if a company has 2 product lines and within each, it has 2 products so the length would come out be 4.

  1. Depth

Depth refers to the number of variations in a product line. For example in a company, there is a self-care product line and within that, there is hair-care, oral-care, etc. So this is the depth.

  1. Consistency

Consistency refers to how closely related product lines are to each other. 

Introducing IR (image recognition) to you as the rescue. 

Image recognition is the ability of a system, combining IoT and AI, to process and interpret the visual content, like an image of a video. It is done to decode every image down to its pixels, and identify all objects, people, places and convert them into comprehensible data. The major elation in Image recognition technology has centred around augmented reality. However, there is much more potential in using image recognition to add services to what shoppers see in stores. 

Image Recognition and Object Detection techniques can help consumer brands to standardize store checks and get consistent results from all the sales channels allowing them to make business decisions based on shelf data confidently.

  1. Product placement  

Image recognition plays an important role in helping the consumer brands to standardize store checks and get consistent results from all the sales channels which allow them to make business shelf decisions in an improved manner. 

Object Detection, using a deep neural network, detects SKUs within images of shelves and classifies them at manufacturer, brand or SKU level.

  1. Detects Empty shelf

Retailers are missing out on nearly $1 trillion in sales because they fail to have the right stock available in the right place, at the right time. Thus, it becomes vital to stock the shelves with the right amount and type of products. You definitely do not want to do that, image recognition allows you to detect the empty space. The cameras can be installed in the store to keep track of when and what products are getting out of stock so as to avoid the situation of non-availability.

  1. Shelf occupancy

Shelf occupancy is a major issue. Examining the right place for products can be done via technology. The SKU-shelf data helps to understand how much space is devoted to which category of products. Comparing the share of space at the brand or single SKU level with its sales contribution helps to understand if brands are gaining a fair share of their space. A study was conducted where the fair share of space was evaluated by placing a product in different places to examine its sales. Later it was found out that the product was not placed in the right position and led to increased engagement and sales by a large margin.  

Pro tip: What requires manual labour can be done with a single click of a picture. Thereupon, we got it covered for you with Xtract which does-  space of the brand/SKU/category level within key customer segments, arrangement of diverse categories, a vacancy falling out

  1. Correlation 

Helps in analysing how closely two or more items are related to each other, which means how often a pair or more is bought together and the reason behind it. This helps in maintaining the right stock together and in the right proportions. Not having the complimentary item will lead to loss of sales and customers. 

  1. Research coverage ‘

Image recognition covers varied segments of the market that further allows to comprehend and analyse the market trends. It aids in estimating the market size and growth potential in technology, diversity, application, classification, region, deployment. Subsequently, it allows an in-depth knowledge of competitive analysis with their key products, company profiles and key observations related to its store. Assessing competition becomes easier and helps in getting a first-mover advantage. 

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