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Using AI/ML And Real-Time Data At Scale To Help Retailers Improve On-Shelf Availability And Ecommerce Profitability

  • aster.cloud
  • February 14, 2022
  • 4 minute read

Editor’s note: We’re inviting partners from across our retail ecosystem to share stories, best practices, and tips and tricks on how they are helping retailers transform during a time that has seen tremendous change. The original version of this blog was published by Trax Retail in October 2021. Please enjoy this updated entry from our partner.

Image source: Trax Retail

 


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In 2020, we saw a massive leap in online grocery. Within a few weeks, the industry reached numbers that were unexpected for at least four more years. In a snap, what seemed like a relatively insignificant channel became one that grocery retailers simply couldn’t ignore and, what’s more, is likely to remain a norm.

Retailers trying to stay ahead of the curve have already started experimenting with methods like building warehouses and installing robots to fulfill the growing demand, but in-store picking has been and will continue to remain one of the primary methods of fulfilling online orders as it offers several advantages. First, it allows the use of existing infrastructure – large retailers already have geographically well-located outlets in major cities, which enables shorter lead time to delivery. Secondly, it allows retailers to stay flexible and move swiftly between in-store and online order fulfillment. And finally, it fits perfectly with the omnichannel approach to allow customers to shop wherever and however they want – click and collect, curbside pick-up, or inside brick-and-mortar stores.

How improving on-shelf availability helps ecommerce profitability

Image source: Trax Retail

 

Despite its many advantages, in-store picking is expensive and affects profitability in an already competitive space since the cost of picking is directly tied with hourly labor fees. Moreover, with labor being a major challenge to obtain and retain, every minute spent picking counts. However, there is an easy way to keep costs down – optimizing the picking process by ensuring product availability and reducing the need for substitution.

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An average of 8% of products are not available on-shelf in stores at any given time. As a result, pickers waste much of their time hunting for products that simply aren’t on the shelf or are misplaced, or spend time looking for substitutes, further increasing the time and cost for picking. In fact, grocery pickers often claim that out-of-stock (OOS) occurrences are the main reason that slows down the picking process. Without these factors, pick rates could be two times faster. Since picking accounts for 50% of the fulfillment cost, it has a substantial impact on the order’s bottom line and often makes the difference between a loss-making and a profitable basket.

Maintaining on-shelf availability for the thousands of products in every store has always been a significant problem to solve. The shift to online ordering has made the availability issue even more significant as the shelf is also now the fulfillment center for the majority of online orders. For e-commerce, out of stocks present two major issues for retailers. First, the impact of out-of-stock items is even more noticeable for online shoppers as they do not select their own substitutions. Additionally, out-of-stocks cause inefficiencies in the item fulfillment process, which is already a costly and margin-diluting practice for retailers. The good news is that through a partnership between Trax and Google Cloud, and the power of Google Cloud’s AI/ML capabilities, these challenges are addressed. The granular, real-time data at scale to enable picking efficiency and the data transparency to unlock a better shopping experience are now a reality which benefits both shoppers and store associates.

Read More  Introducing Firehose: An Open Source Tool From Gojek For Seamless Data Ingestion To BigQuery And Cloud Storage

Trax and Google Cloud technology helps the bottom line

Trax and Google Cloud offer solutions that can help retailers improve on-shelf availability (OSA). Trax Retail Watch powered by Google Cloud uses computer vision (CV) and AI to create a digital version of the physical store in real-time and informs out-of-stocks so that retailers always have full visibility of items that are running low and can replenish them quickly. In turn, pickers are more likely to find everything they need quickly without facing the problem of missing products or having to look for substitutes. Trax Retail Watch also allows store associates to quickly spot any issues arising on shelves without having to physically walk down each aisle. From misplaced products to low stock, having full visibility means that shelf managers make more informed decisions, so that pickers face fewer obstacles, are aware of the true inventory, and significantly improve their pick rates. Faster picking means lower costs and ultimately, higher margins for online grocery orders.

With more e-commerce retailers crowding the online space, competition is tough. Want to know how frustrated e-commerce shoppers are about on-shelf availability? Trax uncovered this problem through an in-depth consumer study. Learn how to address shopper happiness while driving more profitable fulfillment and stay on the leaderboard with this Trax and Google Cloud whitepaper: Winning the online grocery race.

 

 

By: Ariel Sternfine (Director of Product Marketing, Retail Solutions, Trax Retail) and Paul Tepfenhart (Director of Global Retail Solutions, Google Cloud)
Source: Google Cloud Blog


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