Our esteemed client is a pioneering B2B commerce firm that thrives on the use of cutting-edge technologies to facilitate business processes and client engagement.
Recognizing the ever-increasing significance of data in shaping business futures, they possess a deep-seated commitment to incorporating a holistic view of their clients, ensuring transparency, and maximizing engagement efficiency.
In today's digital landscape, businesses grapple with synthesizing data from myriad sources into cohesive insights. Recognizing this, our client, a leading B2B commerce entity, sought a solution to amalgamate diverse data streams, aiming for a comprehensive understanding of their clientele. This case study explores the journey of the codvo.ai team in actualizing a B2B Commerce Unified Database, designed to offer a holistic customer view, drive engagement strategies, and ensure operational efficiency. Through this endeavor, the client aspired not only to refine operational workflows but also to elevate the overall customer experience.
Our client, a leader in the B2B commerce sector, confronted a multifaceted challenge. They aspired to craft an Integrated, streamlined database that not only amalgamated data from various client interactions and third-party sources but also yielded actionable insights. The envisioned system needed to provide an in-depth view into client scores, predict potential client engagement probabilities, and maintain stringent governance standards. Additionally, the client was keen on deriving trusted analytics from a singular, quality-assured data pool, achieving a complete 360° customer perspective, delivering personalized experiences through detailed data segmentation, elevating operational efficiency with automation, and ensuring the platform was adaptable to future growth and diversifications.
Our Approach and Solution
Taking these challenges head-on, our rightfit team laid out a systematic approach:
Data Ingestion: We began by enabling data ingestion from a plethora of sources like CSV files, different types of databases, web hooks, and more, ensuring a seamless flow of information into the system.
Pre-processing & Standardization: With the data in place, we set up flexible pre-processing pipelines. Standardization was of utmost importance to ensure data uniformity across diverse sources.
Metadata Tracking & Data Governance: Data integrity is essential. Our approach incorporated robust metadata tracking mechanisms that supported data governance, ensuring compliance and quality control.
Entity-specific Processing: Different data types require varied processing approaches. Our solution tailored processing techniques based on data types for accuracy.
AI-Driven Core Data Enrichment: Leveraging the power of AI, we enriched the core data using external sources and resolved customer identities into golden records.
Structuring for Self-service: Finally, keeping the client's need for operational efficiency in mind, we structured the data in a manner that promotes business user self-service analytics.