DCxM is an open source platform encompassing various modules including - Linguistics (NLP, text analytics), Automation (OCR, Information Extraction and Machine Learning capabilities), Analytics (BIG Data, social analytics, lead generation, search relevancy) and loyalty management. Some of the business benefits of DCxM are:
Increased Revenues. Better lead generation by targeting relevant customers and improving online conversions.
Product Innovation. Build better customer intelligence by aggregating and understanding social media sentiment to improve product design, pricing, and promotions.
Personalized Customer Experiences. Offer personalized campaigns across digital channels, resulting in improved loyalty and quality referrals.
Process Digitization. Digitize manual operations to streamline processes.
MongoDB is the backbone of the DCxM platform and MongoDB’s flexible schema, aggregation pipeline, and expressive query language provide many key benefits for the DCxM platform:
Schema less design allows users to inject any type of data from any channel.
Aggregation pipeline helps filter and process through large amounts of data, while also providing real-time analytics.
Expressive query language provides rich query capabilities, as well as advanced search functionality such as geospatial, text search, map-reduce.
With MongoDB, DCxM is able to aggregate, process, and derive fast insights from multi-channel information to generate a deeper understanding of their customer audience and then personalize engagement, resulting in a truly transformative customer experience.
MongoDB is the backbone of the DCxM platform and MongoDB’s flexible schema, aggregation pipeline, and expressive query language provide many key benefits for the DCxM platform:
A leading automotive manufacturer leveraged MongoDB to store unstructured social data and capture sentiment analysis of new product features, leading to more targeted marketing campaigns and a deeper understanding of its key customer audience.
One of the largest European banks digitized and streamlined its whole loan approval process by using MongoDB to store the document taxonomy. This led to less manual intervention and faster turnaround time for loan approval processes.
A leading US pharmaceutical company had a large number of documents with different drug specification formats. Processing these documents was manual, error prone, and repetitive. DCxM was able to digitize the documents and use MongoDB to store the different formats, resulting in more applications processed annually and an 82% reduction in work.
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