Data-Driven Decision-Making in B2B Marketing and Sales with Kunal Mangal

The Role of Data-Driven Decisioning at Verizon

• 🎯 Kunal Mangal leads the Pega Decisioning Platform team at Verizon Business Group, focusing on creating data-driven "next best actions" for customers.
• 💡 His role blends technology, data science, and marketing to implement intelligence in marketing flows and drive value.
• 🚀 The Pega Customer Decision Hub is used to centralize data, business rules, and machine learning models for automated decisioning strategies.

B2B vs. B2C Marketing Similarities and Differences

• 🤝 Concepts like personalization and customer experience are equally crucial in both B2B and B2C, though B2B personalization can be more complex due to multiple stakeholders.
• 📈 Content marketing and customer nurturing are significantly more sophisticated and longer in B2B due to the need to demonstrate value and address pain points.
• 💬 B2B requires tailoring messages to different roles within a client organization, such as a CTO versus an HR head.

Shifting to a Data-Driven Mindset

• 🔑 A mindset shift is the biggest challenge, requiring leadership to demonstrate data usage and encourage cross-functional collaboration and data sharing.
• 🧠 Fostering a culture of continuous learning and curiosity is essential, as data models require feedback and adaptation to changing environments.
• ⚠️ Employees must be encouraged to question assumptions and embrace data-driven conclusions, even when they challenge intuition.

Customer Experience and Data-Driven Initiatives

• ✨ Customer experience (CX) remains paramount; data-driven insights must be communicated effectively at the right time, in the right context, and through the right channel.
• 📈 Many efforts at Verizon are geared towards improving CX, measured by metrics like Net Promoter Score (NPS).
• 💡 Data-driven initiatives are crucial for identifying gaps and improving customer satisfaction.

Implementing Data-Driven Strategies Iteratively

• 🧩 Starting small with specific, solvable problems is more effective than attempting to "boil the ocean" in large organizations.
• 📊 Pilot projects allow for measuring outcomes, demonstrating value, and building stakeholder confidence before scaling.
• 🛠️ Productionalizing AI and data-driven insights by embedding them directly into B2B marketing processes is critical for adoption and success.

Generative AI in B2B Marketing and Sales

• 💡 Generative AI (GenAI) is being explored for making tools like Pega easier to use, such as generating reports or creating customer personas in plain English.
• ✍️ Key use cases include automated content creation for offers, tailoring tone and persuasive principles, and improving chatbots and IVR transitions.
• ⚡ GenAI also offers efficiency plays, like reducing time spent on repetitive tasks such as writing prospecting emails, and analyzing unstructured data from conversations and emails.