The digital economy is fast becoming one of the most prolific growth stories the business world has seen in history. Buoyed by the COVID-19 pandemic, most organizations have ramped up and accelerated the pace of adoption of digital transformation to meet the constantly evolving and dynamic aspirations of digital-savvy customers.
From customer experience to product excellence, the measures of success in the digital economy lie predominantly in the way businesses can leverage data floating around in their operational landscape. By drilling deep into datasets, businesses must uncover insights that can help them drastically improve their relationship with customers, partners, regulatory and government bodies, and in fact, any entity that connects them to market trends.
This data-driven technology landscape offers the most fertile opportunity for enterprises to integrate predictive analytics into their strategic roadmap for growth. With a slew of new and emerging technologies in the field of AI, machine learning, IoT, Blockchain, etc. making its impact felt in the business environment, enterprises have more data than ever before to subject to study and insight generation.
Predictive analytics is the primary solution that helps businesses to understand the inner meaning and perspective of different data sets collected from across the length and breadth of the organization.
This is why studies estimate that the global market size for predictive analytics will be worth a staggering USD 28.1 billion by 2026.
Let us explore four reasons why predictive analytics is a key pillar for enterprises in a highly data-driven and digital-first business landscape:
We have seen how disruptive events like the pandemic threw life out of gear for customers and made things even more miserable for businesses. At times like these, it is important for businesses to be able to handle risks considerably by being aware of potential roadblocks and disruptions well ahead. Through predictive analytics, the possibilities of revenue hits or workforce restrictions, supply disruptions, etc. can be predicted through modeling historic data and brands can adjust their operational routines to help cope with market dynamics and new norms of working. This helps minimize or eliminate risks such as being understaffed when demand from customers is sure to peak or set supplier expectations to match delivery commitments ahead of possible market disruptions, etc.
Better Customer Experience
At the end of the day, the customer is still the King for any business, irrespective of how good a product or service they are providing. Ensuring that their needs are fulfilled in a personalized and unbiased fashion is critical in fostering trust and loyalty. Studies point out that nearly 80% of customers buy something from a brand when they are treated to a personalized experience. It could be smart recommendations, the subtle user experience of apps or websites that customers interact with, personalized pricing or offers, intuitive marketing campaigns, and much more. Predictive analytics helps businesses to understand what a customer would expect every time she interacts with a digital channel of the business. Fulfilling their expectations can result in winning the unwavering trust and possible word-of-mouth publicity for the business which is often one of the biggest factors influencing new customer acquisitions.
Secure from Threats
With data diversity and scale, there also comes an added risk of security threats looming around cyberspace. Fraudsters and hackers see the massive digital economy as a key opportunity to exploit vulnerabilities in customer behavior and trick them to reveal sensitive information which can further cause irrevocable damage. Additionally, vulnerabilities at customer touchpoints can create even bigger liability and challenge for businesses as they could face lawsuits and regulatory penalties if sensitive customer data lands in the wrong hands courtesy of their lapses. Predictive analytics can chip in and turn around the situation favorably for businesses and customers. By rapidly observing transactional behavioral data and usage patterns of digital channels, predictive analytics systems can pick up suspicious data patterns that have the potential to be vulnerabilities slated for exploitation. It can prevent fraudulent activities by supplying actionable insights to security frameworks deployed, based on historical analysis of the threat landscape.
Staying Ahead of the Competition
With competition rising, businesses need to move one step ahead every time to ensure that they attract customers better. This would require a comprehensive analysis of how competitors are faring in the market, the trends shaping demand from customers, and the productivity levels within the organization that influences their time to market and innovation. By leveraging predictive analytics across a wide range of organizational facets like competitor analysis, workforce, resources and machine utilization, sales and marketing metrics, etc. businesses can obtain strategic inputs that help them make better decisions to stay ahead of the competition every single time.
Cultivating a data-driven operational style is essential for businesses to sustain growth and survive in the digital economy. Predictive analytics can be a key differentiator in this regard by enabling businesses to remain alert of what happens when they execute a given strategy through predictive data modeling. This helps to eliminate risks and improve operational efficiency and ultimately contribute to improving bottom line profits.
Get in touch with us to know more about how predictive analytics can help your business achieve rapid and sustainable growth even in challenging times.