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

Three Retail Inventory Management Challenges for the 2018 Holiday Season

As the sugar high from Halloween subsides, retailers are shifting their focus to the next holiday spending rush this season: Black Friday. The dangerous combination of pumpkin-spiced lattes, a strong economy, and product deals and discounts will fuel consumers into the eagerly awaited shopping period for retail.

The outlook on holiday spending this year is optimistic. Retailers are getting holiday ready and pulling out all the stops, such as Target and Walmart's free two-day holiday shipping rollout and Wayfair's holiday pop-ups

However, the difficulties in achieving success during the holidays always fall back on how effectively a retailer can manage their inventory. Are you providing the right product, in the right amount, at the right time and place? Here are some of the biggest inventory management challenges retailers must overcome this holiday season:

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Topics: brick-and-mortar retail, merchandise planning, merchandise assortment, product assortment, data, inventory, e-commerce, holiday shopping, holidays, demand prediction, order fulfillment, advanced analytics

Lessons from Amazon's 4-Star Store, GH Lab, & Fashion Pop-Up Boutique

It’s easy to gloss over the timeworn Amazon headlines, but media coverage of the e-commerce titan’s recent physical retail strategies incited us to dig a little deeper to share some key learnings for you today:

1). First, Amazon’s partnership with Good Housekeeping magazine to create a new pop-up shop and digital boutique, GH Lab, at the Mall of America beckons a unique approach to the physical shopping experience using technology and a thoughtfully crafted, limited assortment.

2). Secondly, the opening of Amazon 4-Star — a new physical store where everything for sale is rated 4 stars and above, is a top seller, or is new and trending on Amazon.com— signals a new level of data-driven curation and transparency that only seemed possible online. 

3). Lastly, the introduction of Amazon’s first fashion-focused pop-up shop in London further affirms the 'brick-to-clicks' phenomenon driving many digitally-native brands to embrace offline despite the 1,773 store closures so far in 2018. 

Amazon has been dabbling in physical retail since its acquisition of Whole Foods in 2017, but its bold experimentation with these new store models clearly reveal the company’s ambitions across multiple physical retail verticals – from fashion to furniture to wellness and more.

These moves signal a future in retail where the power of data drives curated assortments, transparency, and more pleasant, stress-free shopping experiences.

Retailers, take note!

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Topics: brick-and-mortar retail, merchandise planning, merchandise assortment, product assortment, amazon, data, inventory, e-commerce

Why the Biggest Problem with AI is Human

Every brand in retail is talking about AI. We’ve read the reports, the articles, and the survey results about all the different pain points AI can solve for retailers. From all the chatter around groundbreaking innovations and the changing retail industry, brands understand this need for technology in order to adapt. 

And there isn’t a shortage of technology solutions out there either—retailers have a ton of options. 

Understanding this need, the need for tech, then why is it so difficult to actually adopt? Why are retailers still struggling to keep margins afloat and adapt to the digital consumer? 

What’s the biggest problem with AI in retail?

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Topics: inventory optimization, data, advanced analytics, digital transformation, artificial intelligence, machine learning

Why It's So Difficult to Introduce New Products to Your Assortment

“One of the biggest challenges that companies face is predicting demand for new products over time. Overestimate it, and risk warehouses full of excess inventory. Underestimate it, and your customers could leave empty handed—or you might be left with a hefty bill for expedited delivery.”Kellogg School of Management, Northwestern University 

Innovate or die trying. 

The phrase is almost as overused as “retail apocalypse,” yet a concise depiction of what retailers face constantly when we think about the video-gone-viral level of speed behind the changing retail landscape and unpredictable nature of demand. 

As if determining the optimal assortment wasn’t already difficult enough, introducing new products to your strategy when some fashion trends barely last is a risk merchants must take. 

When it comes to new products, retailers are getting burned (more often than not) when a quick pivot or adjustment to changing demand is unmet. Today, these losses hurt big time, especially considering retailers are clenching onto their purse strings more tightly than ever.

Why is it so difficult to accurately predict consumer demand for a new product? And, more importantly, how can we overcome these difficulties? 

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Topics: inventory optimization, data, consumer trends, consumer habits, demand prediction, advanced analytics

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