Big data CRM (big data customer relationship management) refers to the practice of integrating big data into a company's CRM processes with the goals of improving customer service, calculating return on investment on various initiatives and predicting clientele behavior. Companies struggle, in general, to make sense of big data because of its sheer volume, the speed in which it is collected and the great variety of content it encompasses. Tools and procedures are evolving in order to help companies house and examine these large amounts of data and help companies move toward making data-driven decisions.
Big data CRM's goal is to combine internal CRM data with customer sentiment data that exists outside of the company's existing system, such as on social media networks. By finding patterns and trends in this data, sales opportunities and adjustments to product and service offerings can be made to boost profits.
Combining big data with other CRM data can improve customer analysis and lead to predictive modeling and other practices. Companies using big data in conjunction with CRM aim to have systems that can process data in real time and therefore connect with customers faster. Analytics is of paramount concern to companies looking to achieve big data CRM. The other key concern for companies is pulling together inbound and outbound interactions with customers across all channels so that analytics can be applied. Customer data silos and other inflexible architectures are factors in companies' inability or unwillingness to adopt systems using advanced algorithms or other machine-learning technology that can translate big data into actionable business information.
While big data technology is cheaper thanks to open source tools, main costs associated with big data CRM implementation have to do with hiring the necessary labor needed to work with such a complex and evolving category of systems. Big data CRM requires powerful data integration capabilities as well as data quality and cleaning that needs to be addressed before any value can be extracted from analysis.
Collecting and analyzing big data on their customers allows companies to augment service by examining customer sentiment. Big data can provide businesses with metrics on sales, marketing and other areas to gauge performance and quality. It can also help make better forecasting decisions by allowing for real-time decision-making as well as giving information on product inventories, customer segmentation and assist in the development of products and services.
When referring to customer data, big data refers to large amounts of either transactional data or analytical data. It can also be structured, or easily quantified in charts, graphs or other standard record-keeping applications, or unstructured and contain things like audio, video or other images.