AI Academy Experts Discuss Marketing AI Attribution Modeling, Bias & Content [Ask Me Anything Session]
As part of the AI Academy for Marketers membership, we offer monthly Ask Me Anything (AMA) sessions with leading industry experts. We chat about everything from technology trends, use cases, lessons learned, and much more.
In this post, we’d like to give you an inside look into the latest, exclusive members-only session with Katie Robbert (@katierobbert), Co-Founder and CEO, Trust Insights, and Christopher S. Penn (@cspenn), Co-Founder and Chief Data Scientist. During the session, we discussed the importance and impact of bias, content, and attribution modeling in your marketing program—all questions stemming from their courses offered in the AI Academy for Marketers (listed below).
- Intelligent Attribution Modeling for Marketers [Certification Course]
- 5 Applications of AI for Content Marketers (Robbert)
- Assessing and Mitigating Bias in Marketing AI (Penn)
Below is a quick video from our chat, followed by top takeaways from the conversation.
What is the background of the person who is looking at the ethics of AI? What is the skillset needed?
(Katie): You cannot be shy about asking hard questions. A lot of times people want to accept what's given. You must have someone on your team to poke holes in everything. Ask if the data has a representative sample for everyone who has contributed to your data. There is a need for diversity in the creation of solutions.
What’s the fine line between fair bias and unfair bias?
(Christopher): There is statistical bias and human bias. Statistical bias happens when a metric deviates from the population sample. This just happens sometimes. The line is on the human side and generally around class (ethnically, gender, etc.) If the model disadvantages one class, you are in unfair territory.
What are some questions you should ask vendors to better understand what data they are using in their algorithms to make sure it’s not biased?
(Christopher): If they say they can't use the model they are using to gather data, it's a red flag. You should have nothing to hide. Just because you're sharing the information doesn't mean someone will go replicate it. They should also share the source of the data, but not necessarily the dataset.
What are the fundamental problems with last-touch and first-touch attribution?
(Katie): It's easy to understand these models so many use these. These models are very transactional, but human behavior is much more complicated than that. There are so many different channels that factor into a sale. You need more insight and understanding into the path to purchase (it might be 20 steps... or maybe it is only 3). But you would never get that information from a first or last-touch model. You need to understand how your channels are working together!
What are some of the key areas you focus on for applications of AI and content?
(Katie): A great place to start is to look at what already is working for you. Use technology to see which pages are working and determine your SEO or content strategy from there. Understand where your customers are throughout the journey and know what channels fall within which stages of the customer journey. Then, get the messaging right on each channel (i.e. email vs. social).
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