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.

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

3 Takeaways from Cowen’s Re-Think Retail: The Store Must Do More

Customers require an easy shopping experience, a focused product assortment, and an experience which connects them to the brand, retailer, or other people. – Cowen Research, Re-Think Retail: The Store Must Do More 

How are you breaking into the new world of retail?

Obviously, times have changed. Consumers have changed. How we do business has changed.

Technology has really changed. 

With all this change going on in our world, it’s inevitable retailers must change too. But how can retailers ensure they’re adapting to survive? To succeed? To thrive? 

In a recent retail manifesto, Cowen and Company gives their two cents on how retailers are “rethinking retail” as profound shifts in customer expectations continue to force traditional retail business models to innovate and change. 

From Cowen’s perspective, it’s all about the store.

Just like the title of the report illustrates, the store must do more to “maximize a customer’s experience” and “minimize tasks” as their purpose has fundamentally shifted. In today’s new world of retail, stores must act as customer acquisition points where convenience, curation, and culture trump all other factors.

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Topics: customer experience, predictive analytics, in-store assortment, convenience, inventory optimization, in-store experience, data

The ROI of Optimization: A Case for the Board

In a retailer’s perfect world, knowledge of what your consumer wants to buy (along with when and where they want to buy) would be instantaneous and inventory lead times would be nonexistent.

A retail utopia.

Unfortunately, this isn’t how it works. Instead, merchants are tasked with predicting enormous (sometimes erroneous) investments to: 

  • Determine the optimal assortment/mix of product to sell
  • Determine the optimal store location to allocate each product
  • Determine the optimal fulfillment path for online orders

As a merchandiser, you’re on a perpetual quest to provide the right product your consumer base demands.

So many variables come into play as you try to accomplish this.

Furthermore, it can be very difficult to make the best merchandising decision when the data required to make future decisions isn’t accessible or, best case, spread out across various systems.

As a result, retail professionals globally are looking to invest in advanced analytics optimization technologies. Whether your organization is searching for ways to buy less inventory or improve fulfillment efficiency for online orders—the case for AI-driven inventory optimization is a no-brainer for many once they gain a clear understanding of its ROI.

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Topics: allocation, predictive analytics, merchandise planning, fulfillment, inventory optimization, data, advanced analytics

Part Four: Q&A with Aéropostale’s SVP of Planning & Allocation (Bonus Questions!)

“Emerging technologies driving disruptive innovation, many yielding transformational benefits, must be prioritized for investigation, even though the ‘buzz’ and expectations for them are just on the rise.” – Gartner, Use Cases Harness Emerging Technologies to Deliver Delightfully Disruptive Customer Experiences 

How are you keeping up with disruption in the industry?

This question resonates with merchants globally—from luxury to fast fashion to off-price—as most are challenged to meet consumer expectations, anticipate future demand, and make the right investments and decisions throughout the merchandising cycle.

Given the circumstances retail is in today, the technology available to help businesses become digitally enabled provider[s] of unified retail commerce is, as Gartner so accurately highlighted, “yielding transformational benefits.”

As an example, retailers are expected to use AI to hone the accuracy and speed of human decision making well beyond current levels by 2020. 

And 2020 is RIGHT around the corner.

As such, we wanted to share some final insights from our recent Q&A with Aéropostale’s SVP of Planning & Allocation, Karen Walter, who shared plenty on how her team is incorporating emerging technologies (like advanced analytics!), as well as:

  • A new approach to the Merchandise, Planning, and Allocation process (Part One)
  • How new technologies are blended with existing business process (Part Two)
  • Why and how Aéropostale adopted analytics in today’s retail environment (Part Three

At the end of the Q&A, we gave retailers a chance to submit their own questions to Karen, which we outlined below! We hope her responses help provide some clarity on any looming questions you may have on Aéropostale's newly AI-enabled merchandising process or strategies you may be considering at the moment.

Also, feel free to access to full webcast Q&A video here for more context! 

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Topics: allocation, predictive analytics, merchandise planning, inventory optimization, data, advanced analytics

Part Three: Q&A with Aéropostale’s SVP of Planning & Allocation on AI

"AI, which is forecast to grow to $36.8 billion by 2025, could bring a new way of transformation to retail." - Deborah Weinswig, CEO of Coresight Research   

Everyday you make really difficult inventory decisions. 

The impact of AI on retail is clearly a major topic of discussion for many merchandisers on the hunt for new tech to help make their job of managing inventory and forecasting demand better, faster and much more accurate than ever before. 

At the end of the day, your goals revolve around improving revenue — and yet, so much of it is tied up in unsold product, inefficient processes, or bad merchandising decisions. 

If a technology existed with the sole purpose of helping you meet these goals, why wouldn't you use it? Many retailers are in a dire position because of this failure to adapt and evolve with the tools available to meet the customer-centric demand driving the market today.

And, at the moment, machine learning and advanced analytics are the tools making it possible to do just that. Retailers like Aéropostale are taking steps to make better investments in the right products with their customer in mind by incorporating advanced analytics into their merchandising process.

Check out what Karen Walter, Aéropostale's SVP of Planning & Allocation, has to say in our latest webcast Q&A (transcript below!) about how and why her team adopted analytics in today's retail environment.

(Also, feel free to access Part 1 and Part 2 of the Q&A transcript for more insights from Aéro!)

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Topics: allocation, predictive analytics, merchandise planning, inventory optimization, data, advanced analytics

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