Welcome back to our 5-part introductory course to product management! We hope you enjoyed the first part of the course, and we’re excited to take the next step with you 😀
In the first tutorial, we introduced the role of the product manager and explored some typical tasks and responsibilities. In this tutorial, we’ll take a closer look at the product management process. First, we'll discuss the general approach and mindset of a product manager, and then we'll look at the seven steps of the product management process in detail.
- Why we need to do research
- Why we need to define the problem
- The product management process
- How product managers can leverage AI
Let’s make a start!
If you have questions or feedback about this short course along the way, you can simply reply to any of the course emails you receive to share your thoughts with us. We’d love to hear from you! 😊
Why we need to do research
So here you are. You've just started as a product manager at a company, and your head of product has discussed the product strategy with you. You know where the ship is supposed to go; now you need to work out how to get there 🚢
You decide to tap into the experience of those around you who have been with the company for a while. You start interviewing members of the team. Very quickly, you find yourself with a whole bunch of great ideas for what could be done.
However, great ideas can be risky. We tend to overvalue the importance of our own issues and experiences, while at the same time overestimating how representative we are.
For example: Using a mobile phone may be easy to you and your friends, but there’s a whole bunch of people to whom it really isn't!
It might help to think about it this way: Most companies and products got started with a great idea, but most great ideas did not turn into successful companies or products. We always hear about the Facebooks and the Amazons of this world… but for every success story, there’s a hundred that failed along the way.
So how do we make sure that our “great idea” isn’t one of those that will fail? We conduct research.
Why we need to define the problem
When we have a great idea, the first thing we should do is consider why we think it’s such a great idea (or ask the person whose idea it was). What is the problem we’re actually solving? What is the great opportunity? Why now? Who for?
You’d be surprised how often a great idea starts falling apart while trying to answer these questions. In fact, starting with the problem (or opportunity) and then coming up with a matching solution will often lead to much better ideas than going straight to the solution and then scrambling for a problem statement afterwards.
Here are some examples of realistic problem statements:
- Going to a brick-and-mortar store to purchase books takes a long time and is inconvenient.
- Taxicabs are very expensive but getting a ride with strangers is not easy and may not be safe.
- Filing your taxes is difficult and getting an accountant is expensive.
And here are some examples of opportunities:
- The installation rate of broadband in households in the US is now high enough to stream video at a high quality.
- Capacity per weight and volume in lithium-ion batteries has improved so much that a car could go for hours on battery power alone with a battery that fits into the floor of the vehicle.
You can probably think of the companies that have solved some of these problems and capitalized on these opportunities when they arose.
Do you have a good idea that you’ve been thinking about? 💡 It doesn’t have to be in software—it can be anything. Think of the problems and opportunities that underlie your idea—there could be several. Can you think of other solutions that might solve your problems? (Keep this in mind! You'll need it for the practical task at the end, and for the remaining tutorials!)
Now that we are aware of what problem we're trying to solve, we should do some research before we start investing a lot of money into making our solution.
At established companies, a product manager (PM) will often collaborate with UX specialists and data analysts on conducting their research. In a smaller organisation, it may be up to the PM to conduct their own research.
Here are some common research methods that will help establish confidence in both your problem and solution:
- User interviews: Have users experienced this problem? How important is it to them?
- Surveys: How high is the share of people doing X? Do people prefer Y over Z?
- Analytics: Does the data suggest people use the product as intended? Is there a drop-off in usage where the problem is suspected?
- Competitor research: How do others in the market deal with the problem?
- Customer care: Have users been reporting the problem? Have they suggested their own solutions?
While conducting your research, you'll start to develop an understanding of whether the problem you're focusing on is actually the right one. Perhaps you’ll discover that people are actually experiencing a different problem to the one you’ve identified. Let's take a look at Apple.
When the arrival of the Mp3 format made it possible to share your entire music library over the internet, piracy started booming. At the time, people were convinced there was no way to beat piracy, because it was "free", so they focused on selling Mp3 players.
Apple, however, having captured a large part of the hardware market with their iPod, recognized that it was more the process of buying a CD legally and then manually turning it into Mp3s to listen to on your player that was terrible. So they created iTunes, where people could legally purchase and download their music straight to their iPod. iTunes became the number one music distribution service in the world 💫
Stories like Apple's remind us that it's important to conduct research to understand the markets we're in. If Apple hadn't recognized that the real problem with peer-to-peer music sharing was convenience, not price, then iTunes might never have taken off in the way it did.
The product management process in 7 steps
Now that we've discussed how a product manager approaches product development, let's take a look at how this can be systematized in a product management process.
This process outlines the typical product journey from conception to development, launch, and iteration. While the process will differ from company to company, the following steps will almost always feature.
1. Gathering ideas
A crucial part of the product management process is to gather the constant stream of ideas coming from the Product Team and wider company. This includes capturing them in a central location—typically a product backlog—organizing them, and evaluating whether or not they’re worth acting on.
In maintaining the product backlog, product managers must provide transparency and clarity for stakeholders with regards to how ideas are managed. This allows those outside of the product management team to see the status of their suggestions, requests, or ideas, and to get an overview of what else is currently in the product backlog.
2. Determining product specifications
The next step in the product management process is to flesh out the ideas you’ve captured and figure out some of the finer details. At this stage, the product manager works collaboratively with various stakeholders to create what’s known in the industry as ‘product specifications.’
Product specifications (or specs) are brief technical documents which detail what should be built and why, what the new product/feature should achieve, and how success will be measured.
This analysis and documentation enables the product management team to estimate how much time and effort will be involved, as well as what resources are required. From there, they can factor it into the product roadmap in a way that’s both realistic and feasible.
3. Creating a product roadmap
A product roadmap is a strategic plan of action for the product you’re building, usually presented as a visual summary. It lays out the product vision and the direction it will take over time, and provides a high-level plan for how the vision will be realized.
The purpose of the roadmap is to focus on the bigger picture, rather than on specific details or tasks. It’s all about mapping out the overarching goals and milestones for the product, keeping the focus on strategic objectives and outcomes 🎯
The product roadmap serves as a single source of truth within the organization, giving everybody a clear overview of where the product is headed, how it will get there, and the reasons behind the product strategy. Essentially, it keeps everybody aligned and in the loop with regards the product’s development.
4. Prioritizing
Prioritization is a balancing act. During this stage in the process, product managers must prioritize those ideas that will best contribute to the overall product strategy and help to achieve goals and KPIs. At the same time, they must also factor in requests from stakeholders.
This can be the toughest part of a product manager’s job as it often means saying no to certain requests or ideas (and facing pushback from the people requesting them). It’s therefore crucial that product managers are able to explain the reasoning behind their prioritization and share how decisions are made.
When it comes to prioritization, product managers often use what’s known as prioritization frameworks. Prioritization frameworks set out certain criteria which each idea should be compared against, giving product managers a consistent set of guidelines on which to base their decisions.
5. Developing the product
The next step in the product management process is to actually bring the product to life. In other words, to develop and build it! 🏗️
With digital products, the development phase largely falls to the engineering team. Developers will write the code for the product (or feature) based on the requirements set out by the product manager and the designers.
The product development phase can vary greatly from company to company depending on which methodology is in place:
- Startups (especially those in the tech industry) tend to take an agileapproach, building and shipping the product iteratively in short cycles known as sprints.
- Larger, more traditional corporations may follow the waterfall model, which is a more linear, sequential approach.
6. Running analytics and experiments
As you know, product managers are responsible for the entire product life cycle. So, even once the product has been built and launched, the product manager’s work continues…
With the help of product analytics tools, product managers can capture data to see how users interact with the product and, in particular, to identify user behaviors that are related to product success metrics. Based on these insights, they can adapt the product to further experiment with and optimize the user experience 📈
7. Gathering user feedback
The final step in the product management process is capturing feedback from customers. This data is invaluable as it gives you clear, first-hand insights into whether or not the product is meeting your target users’ needs and where it’s falling short.
Having captured feedback (or even suggestions, requests, and complaints) from real users, the product manager must organize it, analyze it, and use it to adapt the product roadmap and improve the product.
As you may have noticed, this step loops us right back to the very start of the product management process: capturing and managing ideas.
And so the process continues…
How product managers can leverage AI
Before we get to the practical task, it would be remiss not to mention AI when talking about the product management process. 🪄 As is the case in countless other industries, artificial intelligence is transforming many aspects of how product managers work.
Note that we said transforming how product managers work—not “replacing them altogether.” In the context of product management, AI is more of an opportunity than a threat. It’s empowering product managers to optimize their workflows, perform accurate market research and generate insights using predictive analysis, and segment customers and generate feedback and deep insights.
Most importantly, AI is increasingly working its way into the product manager’s toolkit, with many industry-standard tools now incorporating all kinds of handy AI features 🤩
Some of the most useful AI tools for product management include:
- ChatGPT, the incredibly popular AI-powered language model developed by OpenAI can be a great help throughout the product management process. You can prompt ChatGPT to assist you with research, generate user personas, predict user behavior, come up with product and feature ideas—and much, much more!
- Bard—a Google product that is quite similar to ChatGPT. Described as a creative and helpful collaborator, it’s excellent for creating design briefs and exporting them to Google Docs without much effort. You can also use it to brainstorm various product features and share them with your team members. Most importantly, you can use Bard to create product roadmaps that result in successful feature improvements.
- Canva, a popular image generator and editor, is one of those tools you might have used already. It’s super popular for quickly creating banners, posters, and resumes without previous design knowledge. It’s recently upped its game by branding itself as one of the AI tools for PMs, as it now helps you to generate ideas relevant to product feature improvement and management. You can use it to generate images based on text (also known as text-to-image generation), collaborate with teams to create images necessary for market research, and much more.
- Notion is another tool you might be familiar with already. You can use it to create complex workflows necessary for product roadmaps while ensuring excellent collaboration with everyone involved. And its advanced AI features can identify patterns in your notes, create company wikis to help employees understand different product features better, and allow PMs to reduce the time spent on repetitive tasks.
- Otter.ai—an AI-enabled tool that accurately records and transcribes different meetings and discussions. As product managers, meetings are a regular affair. Recording and transcribing these for storing and sharing can take a lot of time. But Otter.ai can record and transcribe different product-related discussions and meetings, and create high-precision transcripts that eliminate mistakes and misunderstandings. It also integrates into Google Meet, Microsoft Teams, and Zoom to ensure that the most popular video conferencing tools are covered.
Wow, those are some pretty exciting opportunities right there! 🪄And it really is just the tip of the iceberg. Check out this article for more great AI tools for product managers, and this handy cheet sheet for PMs using ChatGPT.
As with all tools, it’s important to bear in mind that AI is there to assist you, not replace you. Above all else, product managers must always rely on their own creativity, expertise, and emotional intelligence. They’re designing products for humans, after all—and no one can understand humans better than, well, other humans! 🧑🤝🧑
Critical thinking is very important when product managers are using AI tools—meaning it’s important to know how these tools can elevate your work, but it’s also important to know when not to use an AI tool. As these tools and technologies become more integrated into our lives, it’s essential for product managers to ensure the ethical use of these technologies, and always prioritize the user’s best interests.
Ethical AI principles act as a framework for transparent, fair, and respectful development and deployment of AI technologies. Read more about ethics in AI in this article.
🧐 Your task
We're just about done for this tutorial, so here's a small task for you to work on:
Think back to your idea from earlier. Have a look to see if there are similar products out there already. Search the internet for apps or products that seek to solve your problem. 👀 Don't be discouraged if there's lots of competition out there! Being the first to market rarely means being the best! Download one or two of them and check out how they’ve approached the problem.
Give it a go—the results might surprise you!
Coming up
In the next tutorial, we'll take a closer look at how to talk to users and how to interpret some basic data. Looking forward to it!
