PROFILE
  • Craig Silverman
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Craig Silverman

CEO Antuit AI
Craig Silverman is the CEO of Antuit AI, leading Antuit in its mission to deliver business results at scale for clients by leveraging advanced analytics and AI-powered solutions. With over twenty years of experience leading teams in analytics and AI, Craig has been committed to helping retailers, consumer brands, and manufacturing companies drive transformational programs across marketing, merchandising and the supply chain. Before Antuit, Craig served as Senior Vice President at Qlik Global Services. Previously, Craig was Global Managing Director at Accenture and led the firm’s largest analytics practice. He served as an IBM Partner and as the Global Leader for Retail Analytics & eCommerce.
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  • Posted on: 08/14/2020

    Build vs. buy: Is that still a question in retail IT?

    In today’s world, no retail organization can fully build software internally. For a retailer, it is very difficult to keep pace not only with the changes on the tech side with cloud and AI/ML but also with core transformation in their business models with omnichannel and its impact across the organization’s process and IT. What retail organizations need to seek are not just software solutions but true partnerships that integrate and evolve as they do. Many forward thinking organizations have shown outside partnerships are extremely strategic to their business, so much so that there’s a new trend in acquiring those capabilities outright e.g. Nike’s acquisition of Celect or McDonald’s acquisition of Dynamic Yield.
  • Posted on: 08/06/2020

    Will shortages shortchange soft goods recovery?

    To be sure, there will be BOTH excess inventory and shortages. In the seasonal and fashion space, disruption to consumer seasonal buying patterns as well as shifts in mix put a lot of inventory in the wrong place at the wrong time. Successful merchandising is driven by a well-managed flow of inventory. Leading retailers look at their inventory the way banks look at their loan portfolios: Some products are low risk (albeit lower returns) and other products are high risk/high reward. Reaction, especially in a time of disruption, cannot be one size fits all. Already we see strong indicators on products that maintain or grow share: basics, wear at home, wear now, comfort purchases. Other luxury, status or social categories have no demand at any price. Negotiating these inventory commitments is especially tricky in this time period and may take new tools and skills.
  • Posted on: 07/22/2020

    Why does it take a crisis for retailers to get innovative?

    "Digital First" in its true sense needs an overhaul in the retail organization culture. While many retailers will perhaps think of BOPIS and other engagement models as a transformation into "digital first," the true change comes when you leverage "data driven" experimentation and innovation in every aspect of the retail business. As the market transforms, a lot of new questions around the role of the store, design of new customer engagement models such as subscription, and re-imagining the supply chain is all going to come out of earned, owned and paid data, along with advanced AI models. It is time to let AI allow retailers to "fail fast" at finding the eventual winning ideas in the new "digital first" world.
  • Posted on: 05/22/2020

    New marketing analytics for a new COVID-19 reality

    I agree that the latency of insights and top-down view of traditional media mix models does not support the types of insights needed by marketeers in this level of market disruption. Instead, marketing organizations need more real time "bottom-up" insights which are possible with predictive models based on attribution modeling, Bayesian approaches, and experimentation. In fact, advances in AI/ML now enable a family of ensemble models to forecast ROI and uplift with high rates of accuracy across hundreds of tactics with stability and at lower levels of granularity at brand/week/store, even during the current pandemic event. This level of granularity enables marketing teams to leverage both "art" and "science" to better understand hyper-localized execution, consumption pattern shifts locally, and an integrated view of next best action of dollars spent by forecasting similar events going forward.
  • Posted on: 04/14/2020

    Has COVID-19 turned fashion into an endangered retail species?

    The combination of closed stores due to COVID-19, along with the economic recession, will most definitely have an impact on fashion. One of the leading indicators is that as China has started to come out of the pandemic, they’ve seen fashion demand pick back up – by as much as 80% of pre-pandemic estimates. Although there are many differences between China and the rest of the world, it provides hope, and most importantly data points and measurements. But retailers are going to need to be smarter than they were before, and will need to use more varied, and sometimes external data sources, and sophisticated and advanced tools to help them anticipate and react quicker to demand shifts. For those that use this time as an opportunity, they will be the ones to come out on top.
  • Posted on: 04/09/2020

    Will old-time retailing skills fix the supply chain mess created by COVID-19?

    Retailers shouldn’t be thinking that they must decide between humans or machines. It’s true that systems that simply rely on historical data are not going to perform well right now, but that doesn’t mean retailers should revert entirely back to human intuition alone. Rather, retailers should be looking at other data sources – other countries or regions, pandemic statistics, etc. – to start building new, advanced analytic models to better anticipate demand in the short term. And once they understand demand, retailers can make more informed buying, replenishment and allocation decisions, as well as leverage it to make pricing and markdown decisions to maximize margin and sell-through of existing inventory.
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