Tell us about your role and the team/technology you handle at ViralGains.
I joined ViralGains in 2017 as Principal Data Scientist, where I not only create Machine Learning models to help grow the business but also build and lead the Data Science team. Regarding technology, we use Amazon S3 and Snowflake as our primary data warehouses, R and Python to build our models, and Microsoft PowerPoint and Tableau to communicate results, insights and recommendations to the executives.
How are AI, NLP and Voice Search transforming our lives?
Over the past five years, big names like Amazon, Google, Facebook and LinkedIn have used AI and NLP to interpret and classify information requests into personalized and relevant recommendations, creating a more impactful user experience that also drives further engagement. We’ll continue to see companies use these technologies to drive deeper personalization and added convenience to our lives.
How do you leverage your expertise in AI and Machine Learning to build marketing products?
Marketing and advertising are fundamentally about reaching the right person at the right time, with the right message in the right environment, to encourage that person to take a particular action—like purchase a product or sign-up for rewards—and drive business outcomes. AI helps us accurately identify—at scale and in real-time—these opportunities and capitalize on them.
What makes ViralGains different from other AI-driven video companies?
What differentiates ViralGains is the way that we help marketers incorporate the voice of the customer into their ad journeys by collecting declared behavioral (how a person engages with the video ad) and attitudinal (how customers feel about the video ad) feedback from video viewers. Our Engagement Experiences help marketers collect a multitude of signals that provide them with the ability to create greater relevance and impact than ever before.
How can MarTech customers benefit from leveraging this platform?
How do you see Retail platforms evolving with better AI adoption?
There is a reason companies like Walmart and Wayfair are quickly becoming giants in the AI field. Few industries have as much AI potential as retail, due to the volume of customers and the variety of data that are collected online or in-store across hundreds and thousands of different product categories. Retail platforms will likely evolve to incorporate increased personalization that truly put the customer—who they are and what they want—at the heart of their shopping experience.
What are the biggest challenges in measuring the ROI of AI products and services?
The biggest challenge in measuring the ROI of AI products and services is articulating success metrics. Without well-defined success metrics and KPIs, one cannot capture or measure impact. Marketers should tie success metrics to real business outcomes that move the needle on their business.
What is your prediction on the disruptive application of mobile video apps on Personalization and Usage Analytics?
There’s been a steep trend over the last five to 10 years in the number of hours a day the average person spends on a mobile device. With an increase in time spent on mobile, opportunities for capturing more behavioral and attitudinal data will open up, allowing companies that employ AI to maximize their reach and further drive business outcomes on mobile devices.
Justin Fortier is an accomplished Artificial Intelligence, Machine Learning and Data Science executive with more than 20 years expertise developing actionable insights and recommendations for leading companies like Thermo Fisher Scientific, Constant Contact and Staples. At ViralGains, he serves as Principal Data Scientist, where he has built an AI strategic road map for the company and developed Machine Learning models to support real-time bidding decisions at scale.
This piece originally appeared on MarTech Series.