WOW! Your Customers
Manish Limaye, Revanate’s Chief Data Officer, shares his “Five-Pillar Playbook” to manage Data and WOW! your customers. Data is a living, breathing beast that demands constant taming to drive business wins.
AIs have evolved from number-crunching to a generative powerhouse, empowering even small businesses to jump in without building tech empires, thanks to cloud tools and open-source magic.
Limaye’s five-pillar approach screams: know your problem, keep your data clean but not obsessively perfect, and make your digital assets—like websites—production superstars.
The big takeaway? Don’t chase unicorns or throw AI at everything; focus on real problems to deliver Customer Wow! and stay ahead of the game.
Data as a Living Organism:
Data is dynamic and constantly evolving, requiring continuous management rather than a one-time cleanup. It’s likened to a living organism because it changes with consumer behavior and business needs, necessitating ongoing data hygiene and adaptation to maintain relevance.
Strategic Use of Data for Business Value:
Data management should focus on solving specific business problems, such as improving customer experiences or optimizing internal processes. Businesses must identify what differentiates them and ensure their data strategy aligns with those goals to drive value, particularly in enhancing customer engagement and operational efficiency.
AI's Evolution and Impact:
The definition of AI has shifted from traditional machine learning (predictive analytics based on past data) to generative AI, which creates content and enables reasoning-like capabilities. This evolution allows businesses to make faster, more informed decisions and deliver personalized customer experiences.
Data Management Challenges and Strategies:
Businesses face decisions about handling legacy data (whether to clean or start fresh) based on its relevance and lifespan. The discussion emphasizes not discarding data unless required by legal retention rules and highlights the importance of a modern data management framework, such as the five-pillar approach outlined by Lemay, starting with understanding the problem and ensuring reliable foundational data.
Customer Experience as a Differentiator:
In industries like hospitality, data and AI enable tailored customer experiences, such as personalized marketing campaigns. The shift from back-office data crunching to front-end production systems (e.g., websites and digital assets) underscores the importance of seamless, data-driven customer interactions as a competitive advantage.
Accessibility of Data and AI for All Businesses:
Advances in technology (e.g., cloud platforms, auto-ML, open-source tools) have lowered barriers, allowing small and mid-sized companies to leverage data and AI without building everything from scratch. This democratization enables businesses to focus on problem-solving and incremental improvements rather than heavy infrastructure investment.
Production Systems and Digital Assets:
Data systems are now critical "production systems," akin to physical stores, especially for tech-driven companies. For example, a website failure is equivalent to a store closure, highlighting the importance of reliable digital infrastructure in delivering customer value.
Avoiding Common Pitfalls:
A key mistake in data modernization is pursuing perfection in data cleaning, which is unrealistic due to its dynamic nature. Another is implementing AI without a clear business purpose, which can lead to wasted resources or poor customer experiences, especially in regulated industries where accuracy is critical.
Ready to be WOWed?! Connect with Tony
