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RichRelevance and Manthan Software have completed a merger resulting in a new entity christened Algonomy. This merged company will apply machine learning algorithms within a customer data platform (CDP) to personalize online and in-store shopping experiences.

Manthan Software previously provided a prescriptive analytics application infused with machine learning algorithms primarily used to determine in real time what a consumer is most likely to buy while shopping in a store. RichRelevance provides analytics software used to personalize shopping experiences both online and in the store.

Current Manthan Software CEO Atul Jalan will head up the new company, while RichRelevance CEO Sarath Jarugula will become Algonomy’s chief product officer.

As the online and in-store shopping experience continues to converge, it became apparent both companies were heading in the same product direction, Jarugula said in an interview. Algonomy will be able to compete more effectively against rivals such as Salesforce and Adobe that are also building CDP platforms infused with AI, Jarugula added.

Other providers of CDP platforms include Oracle, IBM, and SAP, but Jarugula said general-purpose CDP offerings are not optimized for the retail sector. The combined company already has more than 400 organizations using its software to one degree or another, including HP, L’Oreal, REI, Burberry, Walmart Canada, KFC Canada, and Pizza Hut UK.

Regardless of whether purchases are made online or in a store, retailers are looking to apply AI to better predict when they will need additional merchandise, Jarugula said. Alognomy is the only provider of a CDP platform training AI algorithms to address that requirement, he added.

In the wake of the pandemic, more consumer shopping has clearly shifted online. However, as the COVID-19 vaccine becomes more widely available, Jarugula said retailers are going to better integrate the online and in-store shopping experiences. As customers opt into loyalty programs, for example, retailers will surface highly personalized recommendations in real time via mobile computing devices while they are still shopping online or in a store.

At the core of the Algonomy CDP are technologies such as the open source Apache Spark in-memory computing framework curated by Databricks that has been layered on top of an event-driven architecture. That approach makes it possible for Algonomy to apply algorithms to data as it streams into the platform without having to first store that data.

“The revolution has started,” Jarugula said. “Everything that happens on the platform is an event.”

The Algonomy platform is also designed to be integrated with third-party customer relationship management (CRM) and backend supply chain software, Jarugula added. That makes it possible to apply algorithms to enable retailers to share insights with suppliers and better optimize the overall supply chain, he added. In contrast, rival CDP platforms today are primarily focused on streamlining marketing functions, Jarugula said.

The capability within a CDP will allow retailers to own the point of interaction with the customer at the time of purchase, Algonomy chief marketing officer Raj Badarinath said.

“Algorithms are becoming the foundation for analytics,” Badarinath said. “Any company that owns the algorithms will dominate the future of interactions.”

Regardless of the platform employed to achieve that goal, it’s apparent that legacy batch-oriented processes for processing data over a 24-hour window are giving way to real-time data processing.
Organizations that embrace digital business transformation need to differentiate themselves by continuously engaging with customers, which means processing data in isolated silos will no longer be viable. The customer expectation is going to be that all applications are synchronized in real time to reflect their latest interactions, regardless of whether those occurred online or in a store.

Achieving that goal after relying on batch-oriented processing for the better part of five decades will not be a simple feat, which means organizations that have already started down the digital business transformation path are more likely to be around in a few years.

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