How Generative AI is Reshaping Data & MarTech in India
The emergence of generative AI (gen AI) is fundamentally reshaping the landscape of data and marketing technology in India, compelling leaders in these fields to reevaluate and revamp their existing platforms. This transformative technology is not just an incremental improvement but a paradigm shift that promises to revolutionize how Indian businesses interact with data, engage […]
Zero Party Data vs Customer Single View: What Marketers Need to Know
In the evolving landscape of data-driven marketing, understanding the nuances between diverse types of data and their applications is crucial. Two important concepts in this realm are zero-party data and the customer single view (CSV)/single customer view (SCV). While both are valuable for creating personalized and effective marketing strategies, they serve different purposes and are […]
Zero-Party Data Explained: Your Tool for Privacy-First, Personalized Marketing
In today’s digital landscape, where data privacy concerns are paramount and third-party cookies are on their way out, marketers are increasingly turning to zero-party data as a valuable resource for understanding and engaging their customers. This article explores the concept of zero-party data, its importance for marketers, and effective strategies for collecting and leveraging this […]
How to Use AI in Marketing: The Ultimate Guide for Marketers
In the latest Meta earnings call, the word AI was mentioned a record 47 times! Meta, over the past two years, has shifted their investor messaging to focus on ways AI in marketing can bolster engagement and monetization, helping the company make more money. Frankly, the AI hype cycle is at its peak. Every big […]
CEO Guide: Data-Driven Marketing Optimization Strategies
In today’s digital landscape, the marketing and advertising technology ecosystem has evolved into a sophisticated framework that enables businesses to leverage data-driven marketing and effectively manage marketing optimization. This ecosystem is segmented into three interrelated layers: data, intelligence, and activation. Together, these layers provide an integrated approach to accessing and moving data across various solutions, channels, and customer […]
LLM in AI & Gen AI in Marketing: Key Factors for Cost & Implementation
Generative Artificial Intelligence (AI) has gained significant attention for its potential to transform various industries. Some of the ways that an organisation can use generative AI are – Personalising customer experiences, streamlining operations and efficiency, enhancing decision-making, preserving privacy and security, fraud detection and cybersecurity. However, most organisations are encountering challenges when implementing generative AI […]
Why Customer Single View? Insights, Challenges, Solutions
It’s been a long time since we have been discussing a customer single view or a 360-customer view. A plethora of marketing technologies, a promise of hyper-personalization like never before, and the use of artificial intelligence and analytics has helped build momentum towards achieving this. Marketers today understand that there is a need to continuously […]
Why Data Clean Rooms are Essential for 2024?
In the era of data-driven decision making, data clean rooms have emerged as a critical component of the digital marketing landscape. As we step into 2024, the role of data clean rooms is expected to evolve and expand, driven by advancements in technology and changing data privacy regulations. Understanding Data Clean Rooms Data clean rooms are secure […]
How Gen AI Can Enhance, Not Replace, Human Creativity?
Generative AI (gen ai) is a rapidly evolving field that has the potential to revolutionize the way we interact with technology. However, as with any innovative technology, there are concerns about how it will impact society. One of the biggest concerns is that generative AI will be used to replace human creativity and intuition. To […]
How to Build a Data Pipeline That Delivers Real Results?
Today, organizations deal with massive amounts of data. To analyze all this data, organizations need a single view of the entire data set. The problem is that data more often than not resides in multiple systems. It needs to be brought together meaningfully and purposefully through a data pipeline so that it can be effectively […]