Optimize Omnichannel Fulfillment for the Holiday Season

We’re just a quick block and jingle bell ring away from the holiday season — a high stakes, strategically coordinated shopping season retailers strive to perfect each and every year. 

At this point, inventory assortment plans and buys have been squared away.

However, once the frantic shopping frenzy ensues, the scale of orders coming through (from any and all channels) becomes increasingly difficult to manage. When an e-commerce purchase is made, retailers are bending over backwards to meet customer expectations even at the expense of a more profitable sale.

“[O]nline sales are growing at a respectable rate for many omnichannel retailers in large part because they continue to bear nearly all the associated costs of attracting and accommodating online shoppers, while their store-based sales often languish.” - WWD

Read More

Topics: holidays, ecommerce, holiday shopping, fulfillment optimization, cross-channel demand, advanced analytics, customer preference, order fulfillment, demand prediction

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?

Read More

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

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? 

Read More

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

An Interview with Aldo’s Sr. Director of E-Commerce on Predictive Analytics

If you’re familiar with Celect, then you know how excited we are about our latest press release, which announces our recent partnership with multinational footwear retailer, ALDO Group.

For those of you who haven’t heard—here’s the lowdown on the announcement:

By leveraging predictive analytics, Celect is providing Aldo with unique insights on customer demand to help optimize the fulfillment of online orders across its global network of stores.

Which brings me to my next point:  

Total Retail just released an exclusive interview with ALDO Group's Director of E-commerce Operations, Marc Chretien, to talk about his experience with Celect and Aldo’s omnichannel fulfillment efforts: 

“Customers have become very flexible in their purchasing patterns and have embraced omnichannel, leading them to expect these options from retailers. […] A strategy that ALDO Group has adopted is placing the most possible inventory in-store (vs. distribution centers) where both the walk-in and the digital customer can access it. The Celect technology is a great compliment to that strategy and allows ALDO Group to more accurately predict customers’ demands in real time and, subsequently, determine which stores have inventory opportunities.“Marc Chretien, Sr. Director of E-commerce Operations at ALDO Group

The Q&A provides some additional insights into how Aldo is adapting to the changing consumer and leaning on predictive analytics to make better, faster and more profitable order fulfillment decisions.

Read More

Topics: predictive analytics, fulfillment, ship-from-store, fulfillment optimization, advanced analytics, order fulfillment

What Retailers Can Learn From H&M’s $4B Worth of Unsold Inventory

“In the world of fashion retailing, where shopping is fast moving online and stores try to keep inventories closely matched to sales, even a small stack of unsold clothes can be a bad sign.”  The New York Times 

The news circulating about H&M’s colossal pile of unsold merchandise simply reminds us of the risks fast-fashion retailers face to deliver trends at quicker-than-lightning speed consumers demand.

Although at the unfortunate expense of H&M’s affected profits, here are three invaluable lessons retailers can take away from the big, pile of unsold inventory getting so much press lately:

Read More

Topics: convenience, inventory optimization, data, advanced analytics, fast fashion, speed, accuracy

Ready for more?

Request a Demo