Category: Technology

If modern retailers know one thing, it’s that no matter how hard you plan, things almost always work out differently than expected. And nowhere is that more true than with your supply chain.

Suppliers, vessels, trucks, warehouses. Supply chains are complex and chaotic by nature. To solve the disconnects between your forecasts and what actually happens on the road, water, or factory floor, you need to be able to act and react as quickly as possible.

The good news is, there’s never been more data available to help you do that. With AI’s ability to crunch...

When it comes to AI, context is everything. But in the dynamic world of retail, there are countless movements across a range of products. AI can account for those intricacies for you, leading to a more nuanced and accurate forecast — but only if you have the right data to get the quality output you need.

The reality is, in a fast-paced retail environment, you won’t always have the full scope of data you need to get the accuracy you want out of your AI algorithms. 

The new world of retail isn’t for everyone. Less than 10% of emerging brands make it past the death valley curve of e-commerce. If you’re one of the few online retailers that has found success, you know you can’t afford to let your foot off the gas. From one or two top channels, you’re ready to expand.

According to research, for every three new sales channels you add, you could increase your revenue by up to 190%. The only catch? 

There’s a lot of talk about the role of AI in inventory. But with so many unknowns about how these tools are developed, how do you know whether your forecasting algorithm is really doing its job?

From just 4% in 2016, nearly a third of retailers are now using AI. But there’s a lot more to it than customer service bots and product recommendations. For retailers spending multiple hours per week on inventory, AI can help you make better replenishment decisions in less time.

Last week, we explored the top four use cases for AI in inventory. Today we’re taking a closer look at its current and future impact on what is arguably the most critical inventory task: forecasting.

After reaching the peak of the hype cycle last year, the AI fatigue is setting in. Modern retailers are done talking. They want practical ways to deliver value from AI.

The truth behind the buzz is that AI can help you achieve success with inventory as you scale — if you know how to use it.

With an unmatched ability to crunch vast amounts of data, AI can drastically improve your forecasting, save your team hours in manual data analysis, and help you make profitable business decisions in a fraction of the time.

Here are four ways modern brands and...

Tim Angel always wanted to build his own business. With a natural knack for problem solving, he loved coming up with new ideas to help make life easier.Today, he and the team at Zugu sell over $30M per year of their best-selling iPad cases. Tim and the team have expanded the brand’s footprint from three to 17 countries and are consistently leveling up its sales with each new launch.But it didn’t happen overnight. We sat down with Tim and his sister, Chief Operating Officer Jenn Angel, to get a glimpse into Zugu’s incredible story and learn how a highly...

The other day, I was chatting with a customer who said something that transformed my view on inventory. He said: “If I run out of stock on Amazon, I'm screwed. But I love running out of stock on Shopify.”

That’s right. He used the ‘L’ word to refer to stockouts. A problem known for contributing to nearly $2 trillion in inventory costs. Clearly, I needed to know more.

Managing inventory is arguably the hardest task of any retail brand. That is especially true for e-commerce, where sales, advertising, payments and even the customers are digital and can be managed with the click of a button, while inventory is still physical and needs real-world interactions to be produced, moved and stored. 

With the rise of generative AI like ChatGPT, Bard and Adobe Firefly, there is great potential for DTC brands to increase their productivity using the power of machine learning.