AI Tools Are As Good as the Data They Process – Meltwater CTO

AI Tools Are As Good as the Data They Process – Meltwater CTO

Interview by Nikola Djuric
Published: December 04, 2023

Generative AI is reshaping the landscape of technology and data analysis. To discuss this trend, DesignRush interviewed Aditya Jami, the Chief Technology Officer of the world's first media monitoring tool Meltwater.

Join us as we delve into the world of AI-driven marketing strategies, discuss practical steps for integrating your favorite AI tool into your business operations, and discuss the critical balance between the capabilities and ethical use of generative AI.


Who Is Aditya Jami?

Aditya Jami is Meltwater's CTO who has been with the company since 2016. He's an experienced tech leader with a demonstrated history in executing complex engineering systems, developing product strategy and creating high-velocity engineering cultures at tech giants such as Netflix and Yahoo. Jami holds an M.S. in Computer Science from Stanford University, while he also served as a visiting scientist at Cornell University.

DesignRush: What are the most significant ways AI has transformed traditional marketing practices in recent years?

AI has become a fundamental pillar of marketing research, strategy and execution, ensuring every stage is data-informed and efficiency-driven.

Here are a few examples of how AI has transformed traditional marketing:

  • Strategy & Market Research

AI engines can sift through vast amounts of data to identify market trends and customer preferences, which is crucial for marketing teams looking to develop effective strategies and tactics. Pattern recognition and predictive analytics are key in this phase, allowing marketers to anticipate and strategize based on consumer behavior trends.

  • Content Creation

Generative AI can produce diverse content formats, including blog posts and social media updates, representing a leap in scaling personalized content. AI's ability to generate and optimize copy with numerous variations saves teams time and effort and enhances both engagement and relevance.

  • Campaign Execution

AI's predictive capabilities can be leveraged to personalize marketing campaigns at a granular level. By analyzing customer data, AI-powered tools can predict which messaging will resonate best with different segments, enabling marketers to tailor their campaigns precisely and automate their execution.

  • Performance Measurement

Teams need real-time insights on key performance indicators (KPIs), which AI technology can automate and distill into clear and actionable metrics. This allows for real-time optimization of campaigns and more nuanced performance analysis that might be beyond human detection.

  • Customer Intelligence

Generative AI is instrumental in parsing through customer feedback and social media posts to offer deep insights into customer sentiments and pain points. This analysis feeds back into the marketing strategy, creating a feedback loop that continually refines and improves the marketing approach.

With such a vast amount of data available, how does Meltwater discern between what's relevant and what's considered "clutter"?

We know that data overload is a common challenge for marketers and communication professionals — and that it’s vital that they can access, synthesize and analyze data quickly and effectively. At Meltwater, we want to make those millions of data points easier to understand, without the need for sophisticated resources or skills.

Our use of generative AI is already making advanced media and social insights accessible to organizations of all sizes and users with varied skill levels.

Meltwater's AI engine turns billions of data points into actionable insights to solve our customers’ real-world challenges — saving them time, unlocking deeper insights and enabling them to take action.

We are automating the previously manual analysis needed to highlight critical trends and explain spikes in conversations, ensuring a focus on statistically significant data shifts. Our AI-driven discovery tools also detect key changes within large datasets, spotlighting the most impactful content for strategic decision-making.

Combining these features, Meltwater's AI engine filters the relevant from the "clutter" enabling our customers to navigate the vastness of data with precision and insight.

Can you tell us more about the role of customer feedback in refining Meltwater's capabilities and strategies?

Customer feedback is essential for our product development and investment, and our AI engine is needed for refining models like sentiment analysis, trend prediction and summarization.

Feedback helps to calibrate these models more accurately, ensuring they understand the nuances of language, context and industry-specific jargon.

Given the varied and global customer base of Meltwater, this feedback is vital for training the AI to handle a vast range of scenarios, enhancing the models' performance across different markets and languages.

Can you share some practical steps businesses should consider before integrating AI into their marketing efforts?

Integrating AI into marketing is a strategic move that demands a nuanced approach. Businesses should:

  • Identify specific marketing challenges by understanding which aspects of their marketing strategy could most benefit from AI, such as customer segmentation, content personalization or predictive analytics
  • Assess data readiness by ensuring they have the necessary data infrastructure. AI tools are only as good as the data they process
  • Choose the right AI solution that aligns with their identified challenges and integrates well with their existing systems
  • Train the team to effectively leverage these AI-powered tools
  • Implement gradually through a pilot project, and scale as they gain confidence and understanding of the AI's impact and functionality
  • Regularly review by continuously evaluating AI's performance and impact on their marketing goals

The logo of media monitoring tool Meltwater on a white background

Can you provide an AI-enhanced strategy that marketers can implement to see immediate improvements?

A quick win would be to use AI to enhance social strategy.

Social media marketers can use AI to optimize social posts and more accurately target and publish by using AI tools to analyze historical engagement data and audience insights. This analysis can guide the scheduling of posts for optimal times, targeting specific audience segments and creating social media content that resonates well with their audiences.

AI can also help identify key influencers for potential social campaigns and partnerships. Through these measures, marketers will see a noticeable improvement in engagement, reach, and overall campaign performance on social media.

Which misconceptions about AI in marketing do you feel need addressing in this industry?

Addressing misconceptions about AI in marketing requires understanding its role as an enhancer, not a replacement for human talent.

AI in marketing is often misunderstood as a threat to jobs, when in fact it reallocates human focus towards more strategic and creative tasks.

It's pivotal to communicate that AI assists with data analysis, content personalization and operational efficiency, which can empower marketers to devise more insightful, customer-centric strategies.

What kind of ethical considerations should marketers keep in mind when using generative AI?

We define ethical AI as a harmonious blend of trust, responsibility, transparency and empowerment — and that starts with us as an information provider.

It's about ensuring those algorithms are robust, aligned with human values and free from harmful biases. Ethical AI for Meltwater means making safety, privacy and security first-class citizens in the development process.

We treat bias and drift as defects that fail both the business and our customers.

Our guiding light is a set of ethical AI principles, which lay the foundation for how we conduct research and development in this space. By adhering to these principles and leveraging innovations in Human in The Loop techniques, interpretability and real-time monitoring, we aim to set a gold standard in ethical AI practices.

It's about taking a leadership role in fostering a culture where AI augments our capabilities in a manner that aligns with society's most deeply held values.

For marketers and communication professionals using AI, it’s important to remember that the human touch remains a vital component despite AI’s ability to automate much of these efforts.

For example, acknowledge potential bias by regularly reviewing content recommendations through a critical lens and be transparent about the use of AI in your content.

Where do you see the intersection of AI, ethics and the human element heading in the upcoming years?

Looking ahead, this intersection is heading toward a more symbiotic relationship.

AI will increasingly act as an extension of human capabilities, not a replacement. Ethical frameworks will evolve to be more comprehensive, mandating that AI systems are transparent, fair and privacy-conscious. The human element will remain central, with AI serving to enhance human decision-making and creativity.

Continuous dialogue and partnership between technologists, ethicists and the broader public will shape this trajectory, ensuring that AI development is guided by a moral compass that aligns with societal values and enhances the human experience.

We thank Meltwater for this conversation. If you enjoyed it too, be sure to stay tuned for more of our interviews with industry experts!

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