To hate, despite, loathe, be sick of, and feel sickened by

Many businesses love data analysis, comprised of the big, little, and even tiny actions customers take. This is great for making cool-looking reports. But now we can layer in words analysis, thanks to generative AI. It’s something like sentiment analysis but bigger and more fluid. Take for example the words that often come before actions: complaints. I hear you can find them on the Internet. We hate, despite, loathe, are sick of, feel sickened by, or annoyed by. We feel agony and pain, we laugh with disgust of disbelief, and we regret that our time, our day, or even our life was wasted by such a stupid company. While our trust was abused, our intelligence insulted, and our money was taken. Like with this Kaggle-dataset customer-support chat: “Just wanted to warn people not to waste your time with Delta’s “Best Fare Guarantee” that they supposedly offer. I went through all the steps, had a perfectly valid claim, on the same day, and was denied. This was their response…” In marketing, you scan for genuine, emotionally-charged complaints like the above and echo them back near verbatim: “Sick of perfectly valid claims being denied – and your time wasted?” “Sick of trying to manage 1,000 processes in spreadsheets?”. Sidebar: an product that uses your account to log into the Slack or Discord channels of competitors, to proverbially scrape the bitterness of their customers. Speaking of products, we love actions analysis – analytics and product metrics like CTA, CPCs, page scroll depth, usage time, day-of-month churn trends. And I admit, there’s valuable insight there. But there’s also value in words analysis – a task that a product can now perform as well as a marketing consultant, with the right training.

Art of message – subscribe

To hate, despite, loathe, be sick of, and feel sickened by

June 8, 2023

Many businesses love data analysis, comprised of the big, little, and even tiny actions customers take. This is great for making cool-looking reports.

But now we can layer in words analysis, thanks to generative AI. It’s something like sentiment analysis but bigger and more fluid.

Take for example the words that often come before actions: complaints. I hear you can find them on the Internet.

We hate, despite, loathe, are sick of, feel sickened by, or annoyed by. We feel agony and pain, we laugh with disgust of disbelief, and we regret that our time, our day, or even our life was wasted by such a stupid company. While our trust was abused, our intelligence insulted, and our money was taken.

Like with this Kaggle-dataset customer-support chat: “Just wanted to warn people not to waste your time with Delta’s “Best Fare Guarantee” that they supposedly offer. I went through all the steps, had a perfectly valid claim, on the same day, and was denied. This was their response…”

In marketing, you scan for genuine, emotionally-charged complaints like the above and echo them back near verbatim:

“Sick of perfectly valid claims being denied – and your time wasted?”

“Sick of trying to manage 1,000 processes in spreadsheets?”.

Sidebar: an product that uses your account to log into the Slack or Discord channels of competitors, to proverbially scrape the bitterness of their customers.

Speaking of products, we love actions analysis – analytics and product metrics like CTA, CPCs, page scroll depth, usage time, day-of-month churn trends. And I admit, there’s valuable insight there.

But there’s also value in words analysis – a task that a product can now perform as well as a marketing consultant, with the right training.

(This was originally published on Art of Message – subscribe here)