<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=2006193252832260&amp;ev=PageView&amp;noscript=1">

3 Min Read

Human in the Loop for Marketing Analysts [Video]

Featured Image

Wondering how to get started with AI? Take our on-demand Piloting AI for Marketers Series.

Learn More

As marketers, we have access to a plethora of data—social insights, sales data, customer information, and more—and completely manual analysis can be tedious and time-consuming.

In this interactive presentation at MAICON 2022, our annual Marketing AI Conference, Yash Gad overviews how custom machine-learning tools can augment the work done by marketing analysts, helping them do their jobs faster and more efficiently by automating, scaling and improving the manual insights your company already generates.

Gad, CEO of Ringer Sciences, a healthcare and behavioral data science and strategy consulting services firm, also discussed the evolving role of the marketing analyst—and the types of human-in-the-loop solutions he has found to be the most successful.

Attendees left this session with a better understanding of how marketing analytics can work hand in hand with data science to ensure you're telling the right story with your data.

 

“The idea long term, I think, will be to find better and better AI solutions, better technology solutions, to plug into this process that will help scale all of these tools but will still not eliminate the fundamental kind of dependence on analysts and data scientists to guide and shepherd this process.” ~ Yash Gad, CEO, Ringer Sciences

Yash Gad started his career as a computational neuroscientist…specifically neural networks and AI deeply rooted in making biologically-realistic models of the cerebellum. An unusual path to marketing AI, isn’t it? 

Similar to Paul Roetzer’s journey as an agency owner, Gad looked at AI and neural networks and thought, “What else could I do with [AI]? 

Through a chance introduction while working on pharma signaling and pathways, Gad was introduced to and started working with marketing and communications agency Real Chemistry. He worked to apply his AI learnings to marketing, not fully understanding the marketing world and context. 

After three months and a chance meeting with an analyst, a use case was clear. The analyst asked, “I have this marketing data I’m trying to clean in Excel. I do these same 10 things every day. It’s just data cleaning. It’s just counting stuff. It’s just automating a bunch of those things. Can you help me with that?”

Gad easily wrote up three lines of code, then a Python script to solve her problems. However, as a marketer, we aren’t all well-versed in Python and coding. 

The next step was creating a simple web application to drop into an Excel file. It will “do its business” and out will come a new Excel file, cleaned, containing everything that the analyst needed.

Problem solved! Except, once Gad realized the power of artificial intelligence, the analyst came back a week later with ten more needs/use cases: parsing out keywords, topics, and more. Over the course of the next few months, the tool was implemented systemwide.

Then once the other analysts saw this technology in action, more use cases and problems surfaced, and an amazing collaborative environment was born.

Marketers and analysts understood what was possible, and Gad was able to help identify:

  • What are your requirements?
  • What kinds of files are you working with?
  • When you access this tool, what do you want from it?
  • What do you want it to look like?

This collaboration helped uncover two very important steps that needed to be addressed before a project could get off the ground:

  • What does a marketing analyst need to be telling the data scientist for them to be understanding the problem?
  • What does the data scientist need to be asking to understand the problem? 

When communications tie back to these two important questions, rapport is built, and repeatability is built. 

This leads to tackling larger problems, being innovative, chaining together processes, and creating “products” the company can leverage internally and externally. 

As the machines and artificial intelligence support us in our roles, marketers and business leaders are able to think critically about the business, scale processes, and motivate teams.

It was a great session, and one that showed the true value of Marketer + Machine.

Become a next-gen marketer by checking out the resources at the Marketing AI Institute. Read our blog posts, take our Intro to AI for Marketers class, attend webinars, join our community, download reports, guides, and templates (all free), read Marketing Artificial Intelligence, look into AI Academy for Marketers and Piloting AI Bundle, and our annual MAICON—Marketing AI Conference.

Get access to all MAICON main stage keynotes, sessions, and panels with the MAICON 2022 On-Demand Bundle.

Related Posts

Vision AI and the Future of Video and Design [Video]

Cathy McPhillips | October 31, 2022

Shutterstock, Viralspace and AnyClip experts joined MAICON 2022 to discuss the future of vision AI.

How AI + Predictive Analytics Drive Marketing Strategy [Video]

Cathy McPhillips | October 4, 2022

Learn more about how AI + predictive analytics drive marketings strategy in Atalia Horenshtien’s MAICON 2022 keynote.

Meet Christopher Penn: Marketing AI Conference (MAICON) 2021 Speaker

Cathy McPhillips | August 18, 2021

Christopher Penn is Chief Data Scientist at Trust Insights, and a MAICON 2021 speaker. Learn more about Christopher's work in this post.