A New Mentality: Advanced Analytics for the 'New Retail'

It’s a telling time for retail. In spite of the brief reassurance from last year’s unexpected boost in sales, there’s still a lot of work to do. A fundamental shift in the way things were done in the past is finally unraveling across the industry, and is best encompassed by one recent announcement from Nordstrom after their Q4 earnings reports:

“Nordstrom will no longer separately report sales made online and in-store when releasing financial results. The Seattle-based retailer announced the change Thursday as it reported its fourth-quarter and year-end earnings. Nordstrom said reporting the sales figures as one allows it to more closely represent the company's focus on brands rather than channels, Chief Financial Officer Anne Bramman said. The change is part of a larger shift away from the legacy store view of its business to an omnichannel view that combines the physical and digital experiences, she said.”The Puget Sound Business Journal

This announcement is powerfully revealing to the position many retailers are in today. Many are at a crossroads where they can either sink or swim against the forceful current of increasingly complex consumer expectations and demands.

The fact a major retailer like Nordstrom is combining earnings from both online and offline only goes to show they’re swimming hard against this current—and a better representation of how they’re delivering to customers is necessary to stay afloat and strategically execute properly.  

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Topics: omnichannel, artificial intelligence, inventory optimization, machine learning

Closing the Gap: 5 Factors for Successful AI Adoption

Easy is better, easiest is best they say. Who’s they? Consumers.

Consumers demand convenience.

This is what it really boils down to –all the change shaking up the retail industry. Consumers want it now, easy and free.

[T]he battle for convenience is the battle for industry dominance. […] Convenience is one-click, one-stop shopping, the seamless experience of “plug and play.” The ideal is personal preference with no effort.” The New York Times

While the retail industry is disrupted by consumer preference for convenience (without a doubt), it’s also disrupted by the evolving technologies in place to deliver on these new expectations. We already know what the consumer wants, but how do we actually go about delivering on these needs? How difficult is it for businesses to adapt?

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Topics: retail technology, artificial intelligence, inventory optimization, machine learning

The Cost of Love: 2018 Valentine’s Day Sales Increase Online Spending

What is the cost of love?

Of course, love is priceless. But, in all seriousness, how much are people really spending on Valentine’s Day this year? 

According to NRF data, the cost of love in 2018 is $19.6 billion.

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Topics: e-commerce, inventory optimization, retail spending, consumer spending, consumer trends

3 Common Misunderstandings About AI & Machine Learning in Retail

The hype surrounding AI is real. You know it, I know it, we all know it. So what exactly is the problem when it comes to adoption? Do certain misconceptions of what AI can and can’t do factor into all of this?

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Topics: retail technology, artificial intelligence, inventory optimization, machine learning

How Predictive Analytics and Machine Learning Can Help Optimize Your Inventory

Imagine a world where you could see into the mind of your customer.

What if as soon as you became aware of what your customer wanted to buy, you could flip a switch and the product would be manufactured instantaneously? Then, at the flip of another switch, you could get it into your customer’s hands instantaneously? 

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Topics: retail technology, artificial intelligence, inventory optimization, machine learning, NRF2018, innvoation

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