How Data and Analytics Bring Positive Business Outcomes
Today, organizations can collect data and information at every stage of the customer journey. This data might comprise mobile app usage, interactions on social media, digital clicks, and more, all contributing to a data fingerprint which is totally unique to its owner. Though some time ago, the thought of customers sharing information like what time they woke up, what they had for breakfast, or what time they left for office, would have been a highly unusual consideration to say the least.
Customer social norms have definitely changed and as an outcome, expectations have heightened. The following paragraphs will outline three benefits that organizations can reap from data and analytics in terms of drawing positive outcomes for their business and clients, while maintaining a high level of data protection.
- Proactivity & Anticipating Needs:
Organizations are under huge competitive pressure to not only get customers but also to understand their customers’ requirements to be able to enhance customer experience and build long-lasting relationships. By sharing their information and permitting relaxed privacy in its use, customers expect organizations to know them, create relevant interactions, and offer a seamless experience across all touch points.
Therefore, organizations need to capture and reconcile numerous customer identifiers like email and address, cell phone to one single customer ID. Customers are using numerous channels in their interactions with businesses, therefore both customary and digital data sources must be brought together to identify customers’ behaviors. Moreover, customers expect organizations to deliver contextually applicable, real-time experiences.
- Mitigating Risk & Fraud:
Security and fraud analytics intend to guard all financial, physical, and intellectual assets from misuse by external and internal threats. Efficient data and analytics competencies will deliver optimal levels of fraud prevention and complete organizational security: prevention requires mechanisms that allow businesses to rapidly detect fraudulent activity and forestall future activity, as well as recognizing and tracking perpetrators.
Use of statistical, path, network, and big data methods for predictive fraud propensity models leading to alerts will safeguard timely responses triggered by concurrent threat detection procedures and automated alerts and mitigation. Data management together with effective and transparent reporting of fraud events will result in better fraud risk management processes.
- Delivering Relevant Products:
Products are the life-blood of any business and often the biggest investment companies make. The role of product management team is to identify trends that drive calculated roadmap for innovation, different features, and services.
Effective data collection from 3rd party sources where people publicize their opinions, combined with analytics will help businesses stay competitive when new technology is developed or demand changes as well as enable expectation of what the market demands to offer the product before it is requested.
You can also optimize your business processes, by upskilling your workforce by organizing in-house corporate training in data analytics. There are numerous institutes in India that offer personalized corporate training programs to cater to the diverse business requirements of organizations from diverse industry verticals