The term predictive analysis has been around for decades. And while enterprises understand its importance in the ever-competitive marketplaces across industries, there are still some brilliant use cases when it comes to customer experience that need to be talked more about. Predictive analytics models can empower businesses by enabling them to leverage vast enterprise datasets and improve CX. In simple words, AI-powered data and analytics can help predict customer behavior and interests using historical data, allowing businesses to proactively adapt their CX strategies to anticipated customer and market trends.
However, the benefits of predictive analytics are not just limited to analyzing customer portfolios and improving engagement efforts; it can be a powerful tool even for non-customer-facing processes that are crucial for completely streamlined CX operations.
Let’s understand how predictive analytics technology can help enterprises and even growing businesses gain an edge and stay competitive consistently.
Streamlining and Optimizing Supply Chain Management
CX is highly influenced by how timely and efficiently businesses can cater to customers and clients. Challenges like spending millions of dollars on resource maintenance and, at times, overstocking the resources with severe losses are not unheard of. However, with predictive analysis, the losses and damages can be impressively reversed. Taking an example of improved inventory management, predictive analysis can help correctly estimate demand for resources by analyzing previous sales patterns and trends, reducing overstocking or shortages.
AI-powered predictive analysis can further prove to be superior with its analytics-driven insights. With suggestions like task automation, process optimization, and others, enterprises can save on costs tremendously. The power to see into the future better prepares them for supply chain challenges and continues to provide exceptional customer experiences.
Dealing with Customer Churn Rate
Since obtaining a new client is far less expensive than retaining a current client/customer, organizations must keep their customer turnover rate as low as possible. Predictive analysis makes this possible by identifying trends and behaviors that indicate customer unhappiness or prospective churn. Businesses may identify and solve variables associated with customer attrition by analyzing historical customer data. Predictive models can be used to anticipate which customers are more likely to churn, allowing for more focused retention measures. The capacity to predict and act before consumers decide to leave can bring dramatic improvements in customer retention efforts, building loyalty, lowering churn rates, and creating brand advocates for long-term business success.
Achieving New CX Standards
The most popular use case of predictive analytics is to improve customer engagement. By studying customer data, businesses can acquire the knowledge of customer inclination, reshape their marketing efforts, and personalize strategies for separate customer segments to keep them consistently engaged. Humans can take years to do something like this and still may fail to predict accurate customer behavior. AI-based predictive analysis can do this job rather quickly and more accurately. It can analyze entire customer lifecycles and engagement touchpoints thoroughly to give businesses an improved understanding of their customers’ behaviors and demands.
For example, in an e-commerce or online business, predictive analysis can help track website user activity and past behavior to adjust products, services, and marketing efforts to customer preferences. Similarly, in the BFSI industry, the use of analytics can help understand customer portfolios better, enabling banks and financial service providers to build improved and personalized products. In a nutshell, predictive analysis technology can empower brands to leverage customer activity data to build better engagement, tailored marketing strategies, improved experiences, and overall customer loyalty.
Bringing About Analytics-Driven Transformation in Businesses
At Tech Mahindra, we have realized the power of enterprise data and built innovative solutions to help enterprises navigate CX, businesses, and operational challenges. Our AI-powered frameworks and capabilities cover the entire spectrum of data management allowing us to accelerate digital adaption while improving customer experiences. The idea is to modernize and utilize not just customer data platforms but enterprise-wide data so businesses can transform at operational levels and be in a better position to achieve exemplary CX standards. We cater to over 55 countries across industries, including manufacturing, media, and communication, BFSI, retail and CPG, healthcare and life sciences, logistics, and travel.
In all our solutions, we follow a data-driven approach and enable the same for our clients at every step from consulting to execution. Using our reliable base of data assets with intelligence and insights, we power 360 views in organizations from customers to employees, assets, suppliers, and products.
For more details, you can visit our website or write to us at bpsmarketing@techmahindra.com.
About the Author
Prabhjinder Bedi
Chief Growth Officer - Tech Mahindra Business Process Services
Bedi has over two decades of experience involving launching start-up ecosystems, scaling-up businesses, and successfully taking products and services to market across industry verticals, spanning telecom and media, hi-tech/new economy, financial services, retail and consumer goods, manufacturing, and life sciences. Having spent over 16 years at Tech Mahindra, Bedi is currently responsible for taking our existing and new-age service offerings to global markets and adding meaning to our shareholders, partners, and customers. Bedi is a bachelor’s in engineering from IIT, Benares and a Master of Business Administration (MBA) from IIM Calcutta.
