Home PublicationsData Innovators 5 Q’s for Gerry McNicol, Founder of Distil.ai

5 Q’s for Gerry McNicol, Founder of Distil.ai

by Becca Trate
Gerry McNicol standing in front of a blue, green, and yellow geometric background

The Center for Data Innovation spoke to Gerry McNicol, founder of Distil.ai, a data management platform based in London. McNicol discusses how first-party customer data and external data sources, like geographic and seasonal information, can create a unified customer view for personalized communication and enhance sales. 

Becca Trate: Distil.ai is described as a customer data platform that helps boost online sales. Could you explain what data your platform uses to achieve this?

Gerry McNicol: Distil.ai utilizes a variety of customer data to enhance online sales. We use first-party data, which includes data from website content views, email interactions, purchases, and customer service engagements. This is tied all together into a single customer view that creates a cohesive profile of a customer’s relationship with a brand. Our synthesis of all this data helps companies to understand their customers as individuals so they can communicate with their audience in a personal, relevant, and timely way. Beyond this, we can feed in external data, from geographic locations, weather patterns and seasonal shifts—enabling our customers to understand not just their customer, but changes that can affect their patterns. This data goes way further than just selling a product, our AI can provide suggestions on what to move to a subscription model, what should be promoted for Black Friday. But it can also write your forecasts for the coming weeks, months, and at a pinch, years, too. 

Trate: Distil.ai caters to a wide range of businesses, including those that may not have in-house data. How does Distil.ai work with these businesses, and what data sources are used to bridge this gap?

McNicol: Distil.ai routinely provides services to enterprises which may not recognize the existence of in-house data. It is a challenge to identify a business that claims to be devoid of data; the truth is that all businesses possess data, though it may not be immediately recognized as such or deemed usable.

Our role is to assist these enterprises in consolidating their customer data into a coherent, singular view. Often, at the outset of our partnership, we reveal to them data that they have overlooked or undervalued, thereby creating a comprehensive picture that encompasses both their clientele and their internal data resources. This is the key, because data can appear daunting to businesses due to so many variables, data points, and measurements to understand. We are able to help them understand how all of it works together. Our process benefits various areas of a business, such as marketing, product development, and sales performance. One of the ways our AI adds instant value to a business is to segment their best, most valuable customers. It takes insight beyond the number of customers to the who’s who of the top cohort. All of this combines to make it easier for businesses to understand their customers and make data-driven decisions. 

Trate: What roles do AI and machine learning play in optimizing customer engagement?

McNicol: AI and machine learning are instrumental in enhancing customer engagement, given their capacity to meticulously analyze a multitude of customer data points, subsequently advising on optimal segmentation strategies. Distil.ai employs AI to discern demographic indicators, purchasing trends, and the lifetime value of customers, among other critical insights. Consequently, we empower businesses to engage with their customers more effectively and holistically, by providing tailored recommendations and devising strategic, targeted marketing initiatives.

Trate: What do you envision as the evolving role of data in consumer-focused industries?

McNicol: The role of data in consumer-focused industries is evolving towards more sophisticated and personalized customer insights. Businesses are likely to change their data use by employing advanced analytics tools to understand customer behaviour, preferences, and lifetime value more deeply. This shift will involve leveraging AI and machine learning to gain actionable insights, leading to more effective and rewarding business strategies for customers and business owners alike. 

Trate: What do you see as the biggest opportunities and challenges in the field of customer data analysis and management, especially in the context of e-commerce?

McNicol: The biggest opportunities in customer data analysis and management, especially in e-commerce, include the ability to drive acquisition, build loyalty, and understand customer demographics and buying patterns. However, challenges include managing large volumes of data, ensuring data accuracy, and effectively translating data insights into actionable strategies. Distil.ai addresses these challenges by providing tools for sophisticated customer insights, marketing ROI analytics, and channel attribution analytics.

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