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The Subtle Art (and Science) to Successful Retail Allocation

Knowing how and where to allocate products to the right stores can make or break a retailer. We live in a consumer-centered world. For better or worse, thanks to companies like Amazon, customer delivery expectations have changed so that they expect to get what they want and when they want it at the single click of a button. Often, this product can arrive on their doorstep the very next day.

Not wanting to be left in the dust, many brick-and-mortar stores are utilizing tools enhanced with artificial intelligence to master the subtle art of retail allocation. In today’s retail landscape, companies who do not utilize advanced analytics to allocate their products will be left behind or even fail completely. 

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Topics: data overload, allocation, artificial intelligence, inventory optimization, ecommerce, brick-and-mortar retail, data, cross-channel demand, advanced analytics, technology adoption, customer preference, accuracy, demand prediction, markdowns

The Biggest Takeaway from NRF 2019? Optimize Everything.

The word “optimize” was littered across the expo floor at NRF 2019.

From shelf space to e-commerce basket sizes to your in-store workforce – every process across the retail value chain seems to be begging for optimization. “Frictionless,” “efficient,” and “seamless” were the all-encompassing descriptors used to entice interest and engagement among attendees perusing the aisles for technology solutions, ideas, or (let’s be real) free giveaway swag. 

The need for optimization is unequivocal as retail organizations are tasked with executing costly decisions on a daily basis at a tremendous scale. Yet how to approach this problem is less than certain when there are numerous opportunities to improve decisions at each stage of the retail process. Whether your current struggle hinges on production, inventory, store operations, or last mile fulfillment — whatever the challenge may be — the technology available today will enable retailers to glean insights into the mountainous amount of data they have. 

Based on our observations at the big show in NYC, it’s apparent retailers must prioritize investments in tools like artificial intelligence (AI) and advanced analytics to make the optimal decisions to meet the ever-evolving needs of their customers.

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Topics: allocation, retail technology, retail trends, artificial intelligence, inventory optimization, brick-and-mortar retail, fulfillment optimization, advanced analytics, demand prediction, NRF2019

3 Practical Reasons Retailers Should Adopt AI in 2019

In the world of retail, the goal is simple: sell product. 

However, reaching that goal is a completely different story. When you throw competition, customer expectations, stores, inventory, logistics, and fulfillment into the mix, things reach a whole new level of complexity. The challenge is really two-fold:

  1. ) First, demand is seemingly unpredictable, with a multitude of factors influencing a consumer’s desire to want to buy something. 
  2. ) Secondly, there’s the issue of optimization – how can retailers leverage their inventory more productively? 

Overcoming these challenges requires retailers to better predict demand and optimize their inventory decisions more effectively to ultimately maximize every opportunity for a sale. Artificial intelligence and advanced analytics technologies are growing to be the tools of choice for retailers when it comes to optimizing inventories as customer expectations force retailers to invest heavily in digital capabilities.

Many retailers, according to Gartner, are “simply not optimizing their most significant assets.” What asset is more important than a retailer’s inventory? Here are three reasons retailers should adopt AI for inventory optimization in 2019:

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Topics: allocation, merchandise planning, inventory, e-commerce, artificial intelligence, brick-and-mortar retail, data, advanced analytics, order fulfillment, demand prediction, markdowns

The Flux Capacitor of Retail

What if you could travel into the future?

In the 1980s sci-fi classic trilogy, Back to the Future, Marty McFly brings back from the future the Sport's Almanac, a compilation of sports statistics and scores, with the intention of gambling his fortune on games with a 100% accuracy. 

What if you could fast-forward to next season? What would you bring?

If I had to guess, as a merchant, you’d probably gather all of the transactions across each store. With that knowledge, you could make the best use of inventory by knowing exactly where each product was going to sell.  

If only it were as easy as time travel. While nothing will be as easy as time travel, it can get pretty close with advanced analytics.

Here's why advanced analytics is the flux capacitor of retail. 

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Topics: allocation, merchandise planning, fulfillment, brick-and-mortar retail, machine learning, advanced analytics, merchandise buy, demand prediction

The Challenges of Sequential Allocation

It’s almost that time of the year – Amazon Prime Day’s a-looming. The midsummer, Black Friday equivalent and annual reminder to retailers of one of the most wildly successful loyalty campaigns ever created. 

This four-year-old online shopping “holiday” is also a clear reminder to retailers of this:

It’s time to step up your game.

Beyond the Prime Day phenomenon, Amazon’s success stems from understanding what their customers want. 

In essence, understanding what your customer wants means the ability to offer the right product in the right place at the right time: the ultimate challenge retailers face today.

Perhaps not surprisingly, a huge part of this challenge can be traced back to a retailer’s allocations. You can have the best assortment plan in place, the perfect quantities purchased—and yet, you continue to see unsold product, day after day, that should have sold well at store A or out-of-stock situations at the supposedly-low-demand store D.

It’s not easy to know ahead of time that you should have stocked 30 more pairs of faux fur slide sandals in a size seven at Houston’s Galleria store. While hindsight’s 20/20, it’s also freakin’ costly. 

Here are some of biggest allocation challenges retailers need to quash ASAP:

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Topics: allocation, localization, advanced analytics, customer preference

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