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How Marketers can use AI
Last week, I wrote about how Data Scientist should use AI and had a few marketers reach out about my thoughts on how Marketers could use it, so here we are.
To explain this, I’m going to revisit a concept from finance called Alpha and Beta that I used last week.
Example: You buy Apple shares and it’s up 25% this year.
Beta → The beta of a portfolio is how much of your returns are related to the broader market. Example : The S&P 500 is up 10% this year. That would generally be considered “the market” and so that’s the Beta
Alpha → The alpha of a portfolio is how much of your returns are related to your decisions. You chose to only buy Apple instead of the broader market and so you’ve created a 15% Alpha.
10% (Beta) + 15% (Alpha) = 25%.
So, how does this work with Marketing? The Beta will essentially be the expected and the average performance. The Alpha is what you can layer on top to create better performance than your average peer. Using this concept, we’re going to explore how Marketers should use AI and how you can find Alpha and Beta.
But first, let’s examine the job of a marketer.
The job of a Marketer
Regardless of the type of marketer you are, there are some overlaps on what your job is. Lucky for us it’s quite simple:
Understand your customers
Build creatives that cut through
Optimize budgets to maximize ROI
No big deal. Easy enough.
Understand your customers
Understanding your customers is one of the toughest jobs for marketers because:
It’s complex
It requires an analytical skillset
There’s either too much data or not enough
So, let’s now revisit the Alpha + Beta concept.
If you’re below the Beta (aka below the average) about understanding your customers then you can use AI to help analyze the data set that you have.
For example, run all of your reviews (internal + external) through GenAI to create a wordmap or a synthesis of the biggest pain points
If you don’t have a data science team then another great use of AI is to run your data through AI. For example, a few questions you could ask it to analyze:
What’s the average time from signup to 1st conversion
Are there any attributes of people likely to convert (mobile vs web, iOS vs Android etc.)
Now, here’s where it gets good. If you don’t know what to analyze then ask AI. Again, AI is built to produce the best average using all the data it has so if you’re below the average then use it to catch up.
