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The 2016 CRM Market Rising Stars: NGDATA Optimizes Customers' Experiences with Timely, Relevant Offers
For the rest of the August 2016 issue of CRM magazine please click here

Compiling a single view of the customer to deliver timely, relevant, contextually aware, and personalized offers can be a challenge for any business. NGDATA aims to assist in this endeavor with its Lily Enterprise platform, which aggregates customer data from all available data sources, including data warehouses, CRM systems, and social media activity.

After gathering customer data from various sources, Lily uses it to establish Customer DNA Metrics, which reflect customer information such as socio-demographic, behavioral, value, and risk data. These metrics are calculated in real time and updated with new customer interactions, and Lily also enables users to compare individual customer profiles with sets of metrics representing groups of customers. NGDATA identifies two key data types that Lily draws customer information from: interaction-based data and entity-based data. According to the company, interaction-based data comes from transactional behavior including payments, IVR, and online tracking; entity-based data is housed in CRM systems.

“NGDATA Lily translates customer and customer behavioral data into actionable ‘Customer DNA’ that supports data-driven actions to continuously optimize the customer experience based on real-time and traditional data sources that were previously left untapped, or processed in siloed fashion using complex and inefficient batch data flows,” says Steven Noels, chief technology officer of NGDATA, via email.

In March 2016, NGDATA announced a partnership with predictive analytics specialist Zementis with the goal of boosting organizations’ real-time predictive analytic capabilities. The partnership enables Lily users to add real-time insight into customer profiles from the predictive technologies they already have in place, enabling integration with all predictive solutions, including offerings from SAS and IBM. By harnessing the capabilities of multiple systems, the partnership helps companies garner more insight from their customer information.

“Our customers are seeking both real-time scoring capabilities as well as a flexible and open way to create (train) predictive scoring models,” Noels says via email. “The partnership represents a unique solution combining these two key capabilities.”

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