How can PMs improve their intuition? (+ 6 CustomGPT ideas for PMMs)
How can PMs improve their intuition? (+ 6 CustomGPT ideas for PMMs)
Can product folks improve intuition over time or is it all innate? Also, learn about 6 Custom GPTs PMMs should consider in 2024.
Hey BPL fam,
After a few long-haul flights and a refreshing break back home, Behind Product Lines is back in business.
The past 90 days were very insightful, to say the least. I got an opportunity to meet several community members whose feedback has inspired me to work on a more refined direction for the newsletter. More on that in a few weeks.
Till then, let’s dive into this edition. Here’s what’s in store:
Lines of 5 > hand-picked content pieces of the week.
For PMs > Can Product Managers build intuition?
For PMMs > 6 Customer GPT ideas for Product Marketers.
Lines of 5: Hand-picked faves
Here are my top 5 favorite content picks from the past couple of weeks:
Is Gemini really a ChatGPT killer?
If Google’s latest Gemini rollout is giving you FOMO, this video comparison will help you understand why it still has some way to go.
PMs: John Cutler shares key signs when you’re on your way to becoming a real PM.
Can you relate?
https://www.linkedin.com/posts/johnpcutler_signs-youre-becoming-a-real-pm-you-activity-7160862697314553856-whkWCompelling Use Cases for Apple Vision Pro at Home
Although I don’t see the masses coughing up $3K for Apple’s latest brainchild, I have to admit that this demo does a good job on showing why AR and VR are here to stay:
PMMs: Stop trying to tell customers ALL you do in the first interaction.
Robert tells us why you’re messaging is probably too big for customers to fathom:
PMMs: April observed that positioning dies in the chasm between marketing and sales. She shares a few ways to overcome that - superb read:
Can Product Managers build intuition?
Or is it just an innate attribute that some are good at?
Spoiler alert: Intuition ≠ gut feeling.
Just so that everyone is on the same page, I take intuition “as the ability to understand or deduce something immediately, without the need for conscious reasoning.”
Thus, intuition is more like a capacitor that's charged and discharged over time. It’s subliminally informed by our observations, societal upbringing, personal learning, and constant exposure to "evidence".
By evidence, I’m referring to any relevant observation in the product's ecosystem of operation e.g. customer qualitative feedback, usage data, market insights, or global trends.
Smart founders & CEOs tend to have better intuition NOT because they are necessarily "smarter", but rather because of sheer exposure to high-signal evidence.
And while "instinct" is part of the equation, I see intuition is largely influenced by how we interpret "evidence".
Interestingly, a Product Manager’s societal upbringing and values can play a big part in this. After all, a lot of product decisions aim to influence user habits which is closely linked with human behaviour.
Here’s an example:
I was raised in Pakistan where most of my inter-personal skills got developed.
In my late 20s, I moved to Dubai to work for Bayt.com.
During my early days there, I was tasked to work on an email-based retention campaign to bring inactive customers in the Saudi Arabian market back to the recruitment platform I was leading (Talentera).
My intuition was that a warm email packed with bulleted reasons for what they were missing would do the trick. I chose to craft an email campaign with the subject line “We miss you.”
As it happened, that email backfired.
It was poorly received by people in the Saudi market by people who had a conservative stance. Surprisingly, it turned into a major PR issue for certain government-based customers and I had to come forward to own the mistake.
But now, I know better.
Thus, I’m here to tell you that "intuition" isn't all innate. It can be honed over time.
Product Managers working on 0-to-1 ventures who are suitably empowered need a strong intuition “muscle” as product usage data in those early stages is sparse and a precedent may or may not be available.
So, how can PMs & PMMs position themselves to improve their intuition?
Some ideas:
[1] Regularly tap into a broad set of evidence pools.
Brian Chesky attributes Airbnb’s early success to actively engaging with different stakeholders - hosts, guests, competitors, industry reports - to form a holistic understanding of the market. That exposure fuelled his intuition.
Look into the evidence pools available to you namely:
[2] Learn to ask better questions from customers, prospects, churned accounts, and internal stakeholders.
Heard of the Mom Test?
It’s a book that teaches you how to validate solutions by asking the right set of questions.
Rather than asking leading questions, learn to frame “revealing” questions that help you understand honest opinions from your customer base and stakeholders.
[3] Improve their "interpretation lens" by recognizing cognitive biases and fallacies.
"Data doesn't lie, but analysts sometimes do." - William Edwards
Product Managers often fall prey to biases and fallacies when they process data and information. Not everyone deduces the right conclusions.
Some resources that can help with this:
Mind the Product’s article on dealing with cognitive biases
Daniel Kahneman’s book: “Thinking, Fast and Slow” teaches critical thinking.
Some products bake in processes to deflect biases. For example, Netflix has a very strong culture of experimentation. It uses A/B testing extensively to combat confirmation bias. They don't rely on assumptions about what users want, rather they test different initiatives to see what truly drives engagement.
I’m not saying you should A/B test everything now. However, you need to be aware of common fallacies that we become victim to.
[4] Question data. Learn how it's recorded, the biases it may possess, and how it correlates with your target hypothesis.
Young PMs take GA4 data as the ultimate truth without understanding concepts like data sampling.
Just because a tool serves you numbers, doesn’t mean they are accurately compiled. Use tech docs to be aware of how those numbers come out to be.
"Bad data just leads to bad decisions later on. Data analysis is important work." - Suhail Doshi, CEO Mixpanel
[5] Unlearn. Be ready to let go of assumptions and challenge narratives that lean on "that's how we've always done it".
Customer behavior, business context, and market dynamics are always in flux. There are a few constants that mandate product folk to update their perspectives.
Ex: Slack originally thought it needed to compete with email on features.
The email was thought to be Slack’s nemesis. The initial positioning kept contrasting Slack’s strengths with email’s limitations.
However, over the years, Slack updated its narrative. Why?
User feedback and data analysis revealed the true value was real-time communication and collaboration, leading to a shift in product focus.
That mindset shift requires a little unlearning of the core value proposition. Although Slack still showcases content to prove that it’s a better alternative to email, that’s no longer the de facto messaging.
[6] Collaborate to learn, not lead. Leverage the collective intelligence of the team, especially engineering and design. They can uncover your blind spots.
"None of us is as smart as all of us." - Ken Blanchard, Author & Management Consultant
Ex: Intuit leverages internal "design sprints" where cross-functional teams rapidly prototype and test ideas. This diverse expertise fuels product intuition beyond any single role.
Similarly, Asana's founders Dustin Moskovitz and Justin Rosenstein designed the system to enable greater transparency and input from engineers on product priorities.
Teams working closely together can sharpen each other’s intuition over time.
[7] Shadow subject matter experts and active practitioners to pick up on how they reason before they reach conclusions.
I’ve been lucky to have worked with some great mentors. The biggest advantage of shadowing one is that you can always inquire about the thought process behind a key product decision. That journey helps you reverse engineer what considerations they actively mull upon and hence adds valuable dimensions to how you arrive at conclusions.
All in all, with some conscious efforts, product folks can level up their intuition sense over time instead of overly relying on self-made qualitative opinions or vanity metrics. This honed intuition, complemented by evidence, can put the product on a path of growth.
6 Custom GPTs PMMs should consider building
ChatGPT’s Custom GPTs are a massive unlock for productivity.
As product practitioners, we have so much data to synthesize and deduce insights from that it becomes hard to do that by scanning spreadsheets and digital notes.
With Custom GPTs, you can “train” a chatbot with plain CSVs and PDFs to bring it up to speed on key domain knowledge, market context, and company-specific ingredients in your mind. Then, you (and your team) can start querying it for highly tailored and informed responses.
Here are 6 Custom GPTs Product Marketers should consider investing in this year:
1. Feedback analyzer
A GPT that looks at text-based customer feedback and summarizes likes/dislikes and sentiments. I posted a step-by-step tutorial about this here: https://lnkd.in/edTi9G2G
2. Competitive Intel bot
Train a custom bot on competitive feedback found on sites like G2, Capterra, and Software Reviews. Let the bot summarize where competitors lag.
3. Product knowledge bot
Think of a chatbot that knows your product inside out. Instead of sales peppering Slack with questions about product capabilities, this bot would answer sales/CSMs directly and even reveal what's on the roadmap. (tip: instruct the bot to always mention the quote from the reference doc to prevent hallucinations)
4. Pitch Tailor
Feed your messaging/positioning stance to the bot and then have it customize sales pitches, presentation content, and outreach emails colored with the critical value propositions you've laid out. Yes, it starts pretty pathetic. However, it gets better over time and starts to shine.
5. Data Muncher
Analyze large volumes of marketing data (e.g. transactional data with attribution) or product usage data (e.g. feature utilization or cohort data). Get some interesting insights and generate visualizations. Super helpful if you want to dive into a rabbit hole.
6. Asset Critiquer
Train your bot on your best collateral, your branding guidelines, and the core messaging. Then, let it analyze deliverables like emails, creatives, and landing pages to suggest improvements and corrections. I often take snapshots of mockups and let them do a teardown of both aesthetics and written content.
FAQ: Do you need separate chatbots?
In my experience, Custom GPTs perform better when they're trained and configured to do one specific task category well. As soon as you try to convert it into a Swiss Knife of capabilities, it breaks down.
Two notes:
[1] the bot will only be as good as the quality and quantity of data you train it on. Ex: It would be ill-advised to glean insights from a handful of reviews.
[2] Product Marketers need to be judicious about how much they want to rely on ChatGPT's responses. It doesn't always get it right and some human intervention is always required.
These bots don't just save time. They uncover blind spots and interesting ideas that may have not been considered before.
When done right, Custom GPTs can be just the sparring partner you need.
Till next time,
Aatir
Nice. Apart from GPTs, are there any other tools you would recommend for building a bot? I'm looking for a tool that allows me to train the bot using newsletters and articles, around 100 articles or so, that I find relevant and insightful. Then, I want the bot to answer my questions based on those readings.