Getting Closer to Your Customers with AI: Q&A with Rubikloud

Machine learning and artificial intelligence, while complex, offer retailers the chance to get closer to their customers, sell more, and outflank powerful competitors like Amazon and Walmart, if used correctly. Here, Waleed Ayoub (pictured below), CTO, Rubikloud, tells RetailTechNews how his business is helping their retail partners get to grips with this technology, leverage their data science capabilities, and gain a competitive edge on the rest of the market. 

RetailTechNews: Can you explain who Rubikloud is and how your technology works?

Waleed Ayoub: Rubikloud is the world’s leading artificial intelligence (AI) and machine learning (ML) platform for retail, helping leading omnichannel retailers around the world solve some of their most complex challenges. Our full-stack, cloud-native platform and two flagship applications automate and improve price and promotional planning and loyalty-driven marketing for multi-billion dollar retailers. Our patented big-data architecture gathers retailer data from both legacy and new, online and offline systems. This data is then used to help retailers make tangible actions that grow their loyalty revenue, forecast accuracy, and merchandising profitability.

How do your solutions help retailers better engage their customers?

Large enterprise retailers around the world consume huge amounts of data from their customers with no way to truly leverage it, because their cloud solutions aren’t compatible with their legacy systems. Rubikloud’s AI solutions are unique and help retailers break free from legacy in-house systems so they can leverage their data to make meaningful business decisions quickly and effectively. The result is higher customer engagement, increased conversation and longer, more profitable lifetime customer value.

Waleed Ayoub, CTO, Rubikloud

Are retailers making the most of the opportunities afforded to them by data science?

Most retailers have yet to discover the capabilities data science can unlock for their core business systems. There is still a learning curve when it comes to teaching the retail C-Suite that AI/ML technology is quickly becoming, if not already, the only way to function in today’s enterprise market. As a market leader, Rubikloud hopes to show traditional retailers there is a more effective way to engage customers, ensure correct inventory levels, execute the most effective promotion strategy, and more – and it’s through the application of data science.

How can AI and machine learning help retailers compete against the might of giants like Amazon?

While it’s clear Amazon has been outpacing the growth and margins of its brick-and-mortar retail competitors, the retail industry is using this as motivation to disrupt their current systems, fight back, and prevent a monopoly. As more retailers implement AI-first strategies, they are gearing up to complete with Amazon. More specifically, implementing AI can offset existing debt and transform their business into an automated decision-making machine by predicting demand forecasting to avoid stockouts, surplus inventory, spoilage, and help traditional retailers grow their valuable loyalty base.

What is the future of AI and machine learning in retail?

Retailers, responding to much of the hype around artificial intelligence, have rightly focused on its impact on the consumer experience. And while new capabilities that improve the consumer experience will continue to evolve, they are creating new pressures on the supply chain systems that enable the ultimate fulfilment of products to consumers. It is this area where Rubikloud, and others, have started to focus their AI and are developing capabilities to bring greater accuracy into the inventory forecasting, planning, and replenishment processes for retailers. Broadly speaking, these advances will become available when the focus shifts towards rapidly productising and commercialising these AI applications for business consumption. That is, the future of AI will be vertically focused, productised, and commercialised.