Unify Data to Amplify its Value through the Connected Data Framework
Datamatics, as the Data to Intelligence (D2I) expert, enables brands to optimize the use of their data through data unification and insights amplification for data monetization. It uses the brand’s enterprise-level data that may be in different multi-structured formats and broadens its use through interconnectedness across unique parameters. Datamatics systematically extends the data usability by preparing/curating, integrating and unifying it by using different tools, and runs it through advanced analytics and data visualization tools. It helps create a high-quality, unified data structure and amplifies its value through its Connected Data ecosystem which makes it the ‘Single Source of Truth’ for mining customer and brand-related insights.
Identify CX blind spots and place the power of data directly into the hands of every business user in the organization
Engage frameworks for data-driven decision-making, plug CX gaps in real-time, and improve responsiveness toward customer requirements
Monitor different customer touchpoints by using different methodologies, including surveys, on-camera interviews, and mystery audit/mystery shopping, to improve processes
Institutionalize compliance management solutions and systems to monitor the on-ground scenarios at remote stores and contact centers at pre-defined frequencies
Link disparate datasets, comprising multi-structured data, derived from internal and external sources, surveys, and audits to derive intelligence on the customer’s path to purchase
Map data insights to the unique customer ids or create customer personas to derive persona-specific insights for better data monetization
Mine actionable insights from this unified and ever-evolving Connected Data ecosystem on an ongoing basis
Perform 360-degree analysis of customer or brand-related data by using Advanced Analytics across the Connected Data.
Use digital solutions, such as omnichannel voice-of-the-customer generation, speech-to-text solutions, social media analytics, customer lifetime value analysis, churn/customer acquisition models, etc.
Research & Analytics involves gathering, studying, and understanding the consumer voice and their perception of the product and the brand. Aggregating and unifying the sentiment at scale amplifies the voice of the customer and allows the researcher to generate a report for the management for taking market decisions.
What is a brand?
A brand is a particular product manufactured by a company under a particular name. The word “brand” is interchangeably used to denote the user perception of the product and the company.
What is a research & analytics agency?
A research & analytics agency undertakes a study about the users’ perception of the different products of a particular company and submits actionable insights for market penetration.
Some large companies have in-house research and analytics groups, which engage in periodic research and analysis of the company’s different products or brands.
How is Research & Analytics benefited from data unification and amplification?
Research & Analytics agencies and in-house groups gather the users’ or market perception about a product or products through different modes, such as questionnaires, interviews, video graphs, etc. Aggregating and unifying these inputs over a large section of users, amplifies the voice of the customer across different demographics. This true voice of the customer allows the Research & Analytics agencies and groups to submit a report about the improvements or attenuations in the product specifications to be undertaken for a particular product for increased market penetration.
How does Research & Analytics benefit from data visualization?
Research & Analytics agencies and in-house groups gather a large amount of data while analysing the market perception of a particular product. Technology-enabled data aggregation and data visualization allows the agencies and in-house groups to generate a 360 degree comprehensive conclusion from the research in a shorter period of time as compared to the manual activity.
How does Research & Analytics leverage Advanced Data Modelling?
Research & Analytics agencies and in-house groups leverage different Advanced Data Modelling techniques, such as Diagnostic Analytics, Prescriptive Analytics, Predictive Analytics, Descriptive Analytics, and Deep Analytics to provide Advanced Analytics Models and Visualizations. Ready visuals, graphs, and automation solutions allow the agencies and in-house groups to undertake quick analysis and take faster business decisions.
