Maximizing Productivity: A Practical Guide to ChatGPT Product Management
We are living in exciting times — the area of the rise of AI tools. Product Management is a challenging and dynamic field that requires constant adaptation to new technological developments on the one hand and changing customer and market demands on the other hand. In recent months a significant evolution happened in one of the most powerful technologies that impacted the product management space — the emergence of artificial intelligence (AI) tools.
You probably heard about chatGPT and the daily changes in the field. Let’s define chatGPT (his response by the way): “An artificial intelligence (AI) tool that uses natural language processing (NLP) to understand and respond to text-based queries. It is designed to communicate and interact with humans similarly to how we communicate with each other.”
For the past several weeks, I have used it in my daily product work to the point that it has become my go-to tool whenever I start a new task. As Director of Product, it has helped me leverage my time (and my team’s time) X10 or more. A word of caution before we begin — AI responses are not bulletproof and should be considered as a template++ to start from. Be skeptical and use your judgment on the generated answers.
This article will explore how product managers can use AI (specifically chatGPT) to enhance their work and deliver better products to their customers, achieving better business results. We will go throw several product activities that consist of the daily routine of the product person and ill show examples of prompts that I use to leverage chatGPT for that task. One of the primary ways to use AI is in the field of efficiency by automating repetitive tasks. For example, AI-powered software can analyze large data sets and generate reports that provide insight into customer behavior and product usage patterns. This information can then be used to identify areas for improvement and prioritize product development efforts. By automating these tasks, product managers can save time and focus on more strategic activities that require human creativity and decision-making.
We will begin with business questions, let’s dive into two examples and specific prompts:
“Generate a business canvas model table for an e-commerce platform that helps SMBs increase sales”
“Analyze the user behavior in Medium; what are the recent trends for product managers’ content?”
AI can also be used to analyze customer feedback and sentiment data. Traditionally, product managers have relied on surveys, focus groups, and product discovery calls to gather customer feedback, which can be time-consuming and costly. With AI-powered tools, product managers can analyze large volumes of customer feedback from various sources, such as social media, online reviews, and customer service interactions (those notes on Salesforce/any other CRM platform are a mine of gold! Think about all the content you have in your organization or online that consist of customers feedback).
Using natural language processing (NLP) algorithms, AI-powered tools can identify patterns and trends in the data that might otherwise be missed or hard to discover. This can help product managers better understand customer needs and preferences and develop products more closely aligned with customer expectations.
Let’s dive into an example and specific prompts to do so:
“You are the product manager of Facebook; create a report to analyze customers’ sentiments toward the platform”
Another use of AI can be to optimize product pricing and packaging strategies. By analyzing customer purchase behavior and market trends, AI-powered tools can provide insights into pricing products for maximum profitability and customer appeal. This information can be used to design pricing and packaging strategies that are tailored to the unique needs of each product and market segment.
Let’s dive into an example and specific prompts to do so:
Another exciting application of AI for product managers is outsourcing to the AI the daily task of writing the tickets to the developers. Try this prompt, for example:
“You are the product manager of Facebook, write a Jira ticket with DOD to the login process for the platform”
You might be reading this and thinking it’s pretty naive, but using it in your team while perfecting the prompts will save time.
Another field chatGPT can help with is market research — as product managers, we constantly need to understand the personas and the business funnel. For example, you can use chatGPT to start that market research on a new persona and educate yourself on that market:
“You are a product manager; create an empathy map for CROs of middle-size companies in the e-commerce verticle.”
Again, this is a very basic answer, and just a place to begin from.
Collaboration is also a field that chatGPT can help with; you know your audience and the feeling you want to convey — chatGPT can help write the message with the style and tone you want. For example:
“Write an internal release email about the latest feature, “New login flow.” Write it in a happy tone, with excitement about the business goals it had already moved. “
Using AI effectively requires product managers to understand the technology and its capabilities. This means investing in training and development to ensure your product managers have the skills and knowledge to make informed decisions about AI-powered tools and strategies usage at your company. I would recommend doing some introductory courses in AI and language models to understand the scope of the capabilities; here are some of my favorites:
For beginners (no-code option): https://www.coursera.org/specializations/ai-foundations-for-everyone
For advanced product managers:
https://www.udacity.com/course/ai-product-manager-nanodegree--nd088
(this course aims at product managers that strive to become AI product managers and is a great way to understand this world of content).
In addition, as mentioned at the beginning of this article, product managers must be mindful of AI’s potential risks and limitations. As with any technology, there are ethical and privacy concerns that must be taken into account when using AI-powered tools. Product managers must proactively address these concerns and ensure that their use of AI aligns with their company’s values and objectives. Also, another point to be mindful of is that sometimes the AI tools are wrong and might mislead — you should always treat the answers with mild distrust and check them by yourself.
In conclusion, AI has the potential to revolutionize the way that product managers work (it had mine!) and deliver value to their customers. Automating repetitive tasks, analyzing customer feedback and sentiment data, optimizing pricing and packaging strategies, and using AI for collaboration can help product managers to make more informed decisions and develop better products, faster. However, it is essential for product managers to approach AI with caution and to invest in training and development to ensure that they can use this powerful technology effectively and responsibly.
