360-Degree Customer Intelligence

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One of the largest retailers in the US is engaged in ecommerce, retail (e-tail) and wholesale business through the multiple channels of distribution to end-users. The firm intends is to provide the best value merchandise for their customers. They focus on using digital channels as complements to differentiate themselves and drive better customer engagement. Due to technological evolution and variety of user behavior, the customer were facing new challenges in their business and looking for software to improve their internal processes and go through digital transformation and innovation in the interest of maximizing user experience. As a result, they planned to shift their operations from “digital-first” to “data first” to fully maximize the benefit of using real-time data insights to directly affect customer engagement and create a 360-degree customer view across all channels.



In order to understand a 360-degree view, the client first had to ingest data streams from across various supply chain, inventory, multiple customer touchpoints and digital sources such as social media to predict and analyze user behavior. All of these data comes in through many varieties ranging from structured data to files to unstructured data and SQL based databases with relational properties. Information from different sources is stored in respective systems and applications, often that aren’t compatible with one another. This adds an integration challenge into the mix and consolidation. They were unable to link records from one source to another without and Data Governance strategy along with processes for data quality ,cleansing and master data management. Only when done, can the customer be able to track a customer who walks in the store to the same customer purchasing online and providing the continuum of user experience to the highest level. Also interesting the customers channel preference also dictated the behavior and the expectation of the treatment plus a track and audit trail for performing shopping basket analysis and surface personalized recommendations in real-time. After understanding and failed strategies, initiatives due to unreliable data, the retailer made data quality and MDM a top priority.

To meet the above challenges, we successfully implemented DQLabs an AI-augmented data management platform to help organization such as this to handles issues around data quality, data curation, data governance, and master data management effectively.



The out of the box connectors helped the customer to ingest a variety of sources at ease such as CRM, POS, Customer behavior and interaction history across all channels, Campaign activities, and process history to develop a single view of the customer to improve engagement and transform data to make it usable, accurate, and trustworthy. The platform also helped them manage ingestion and consumption over a period of time with profiling and curation all automated in matter of minutes. Further the data governance and steward team including analysts were provided instant information on those measures and had opportunity to interact and see the actual data behind those data quality issues. This sort of data quality lineage helped understand the issues on the source system and fix to help improve the data quality of the overall system. Upon profiling, cleansing plus creating a single view of the consumers, the platform also provided option to push data out to visualization platform for reporting, visualization and deliver real-time information with few clicks using out-of-the-box-connectors. This enabled analysts and reporting users to understand well and help decision makers in creating an unified and customizable experience platform across every customer touchpoint, whether in-store, online or on a mobile device . Also, the platform helped the company transform digital data into predictive, customer-focused insight to guide and shape real-time customer interactions to make contextual decisions. With the help of our data quality and MDM platform, the customer was able to combine online and offline customer data, recent behaviors and real-time actions into a cohesive 360-degree view.

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