Product Management 101

We introduce the company Motive in this lecture - which will use as an example in the upcoming lectures - and we pose a question

In this lecture, we discuss customer analysis - and why a deep and intuitive understanding of our customers is the foundation of excellent product management.

The first rule of excellent product management is to interview customers early and often. We talk about the basics of customer interviews in this lecture - talking directly to real customers (in person or via Zoom), testing our new product concepts, avoiding all bias, and asking lots of open-ended questions.

In this lecture, we go through five steps for interviewing customers: 1) Recruit respondents, 2) Interview our customers, 3) Test our product concepts, 4) Analyze our data using AI tools to help us, and 5) Share and use what we have learned. We use Motive's driver safety product as our example.

Let's do a practice interview with office chairs (this time with a human!). We'll assume we are product managers at Steelcase.

Personas are a very useful way for us product managers to capture and share customer insight. Personas help us humanize a target customer - capturing their goals, a day-in-the-life, and what they care deeply about.

The Kano model is an excellent tool for analyzing customer needs.  In this lecture we discuss how to separate user needs into basic, performance, and attractive needs - using international flights as our example.

We look at the London-based publishing marketplace site Reedsy, and practice using the Kano model

The product teams at Motive and Steelcase do a nice job finding deep customer insight. In this lecture, we look at their work with electronic logging devices and office chairs.

In this lecture, we talk about market analysis and identifying market segments using needs-based segmentation. We use DNA testing as our example - with the companies Ancestry and 23 and Me.

Let's do a practice activity - identifying LinkedIn's needs-based segments.

In this lecture, we look at describing a market segment (needs-based segment) using a table format, and also a persona. Template attached.

As product managers, we should size our market segments - quantifying how big are our markets and how fast they are growing. This is tough for many markets, but rough sizing is better than no market sizing.

In this lecture, we discuss why we should analyze competition, and talk about direct competition and disruptive technology

In this lecture, we look at analyzing direct competition, with a focus on competitors' revenue, market share, and longer-term trends

In this lecture, we focus on analyzing our direct competitors' strategy, target market, strengths, weaknesses, and gaps, pricing, and go-to-market approaches. And we talk about how to find this competitive information - what are great sources and how to best use our AI tools.

We look at side-by-side product comparisons of our products vs. competitors and discuss competitive product teardowns.

In this lecture, we talk about competitive positioning, and using a competitive positioning matrix - with one of Motive's products as our example

In this lecture, we dive into disruptive technology and why companies (and product managers) get blindsided.  We use Kodak as an historical example - and autonomous trucks and generative AI as current examples.

We'll talk about product vision, product objectives, and product strategy - and why we do all this work.

We'll talk about how to craft a product vision and objectives in this lecture, with an example.

Create product objectives for an oyster technology mobile application in this practice activity.

We'll talk about four steps to create a product strategy: Reviewing our goals and insights, finding our best strategic options, evaluating and comparing our options, and picking 1-3 to take forward.

Let's track the success of our product strategy over time. Are we making progress toward our product vision and objectives?

Our development teams will never, ever, ever be big enough. We'll talk about the importance of prioritization and roadmapping in this lecture, and introduce the example of eBird

We'll look at the benefits - and dangers - of roadmaps in this lecture. If we keep roadmaps high-level and linked to a strategy, they can be a very effective communication and prioritization tool.

We'll look at various styles of roadmapping in this lecture, including:

• Roadmaps by product area

• Technology/product/market roadmaps

• Now, next, later roadmaps

• Theme-based roadmaps

Objectives and key results (OKRs) convert a longer-term strategy into this quarter's goals. We'll talk about how to create and use OKRs in this lecture, using eBird as our example.

Let's practice writing an objective and key result (OKR), using Ancestry's DNA testing and genealogy service as our example

Development buckets are a powerful tool to focus our engineering efforts on the most impactful areas - helping to push our products (and companies) forward.

Let's do a simple practice activity with development buckets. We'll use an example of an elder care robotics startup.

A value-effort matrix is a great tool for us product managers. It helps us prioritize our product development efforts at different levels, from strategic options to sprint priorities. It's a lean approach, it's not rocket science, and it's very useful.

User story mapping is an excellent tool to structure our thinking for new products and new capabilities. And it is a great collaboration and prioritization tool - helping us work better with product designers and our engineering teams, and guiding us what to build first, second, third...

We'll summarize our discussion on prioritization and roadmapping in this lecture.

We introduce this set of lectures on discovery and delivery in this video, and ask the question, "How we can delight our customers with innovative new products?"

Discovery and delivery is a fast, productive, iterative style of new product development. We start with deep customer insight and crisply define customer problems or opportunities in our product space. When then brainstorm ideas to answer these problems/opportunities with our products, and then select a small set to test. We then go through a discovery process, testing and refining our product concepts, trying to determine "what works?" and "what wows?". We then deliver these concepts to to the market with incremental releases. And our products are really never done - we continue to optimize them.

In this practice activity, backpackers are struggling with lighting inside their tent at night. Our engineering leader suggests adding an LED light string to the seams of the tent. It sounds like a great idea. Should we go back to our office and include this in our next generation tents? Is this a good idea? What are our best next steps?

Stage-gates is a commonly used new product development process. The "stages" are where the work gets done, and the "gates" are checkpoints where product development is reviewed, and go/kill decisions are made. We use the example of Canadarm in this lecture - the giant robotic arm used by the space shuttle. The company that developed this, Spar Aerospace, worked in conjunction with NASA, using an intense stage-gates process. We then compare "stage-gates" vs. "discovery and delivery" and talk about the cost to correct mistakes as the key element which might tip a company to use one new product development process or the other. For companies (and product managers) using a stage-gates process, we can still incorporate some of discovery and delivery's best practices.

During our product "discovery", we look for what works with our customers, and what wows them. A key part of discovery is testing and refining our product concepts. In this lecture, we use the company Too Good To Go as our example. If we are testing a concept like Too Good to Go, we might start with a simple printout, sharing this with potential customers, and getting feedback. We then progress to a screen capture video and a clickable prototype. We now have jaw-droppingly good AI tools to create prototype apps, and we show one of these in this lecture.

Testing hardware product concepts works a little differently than software/SaaS products, although the underlying principles are the same. Here we use the example of a robotic vacuum for cleaning hotel rooms, and step through how we would test this concept. With both hardware and software, it is important to test our product concepts, and not just assume we (or our executives) know what will work in the market. We should start simply, start fast, get feedback, refine our concepts, and test again (and again).

Product analytics give us data on how our customers engage with our products and services. We can do this with software and hardware, and in this lecture, we dive into analytics for software/SaaS products. We use the Envoy Desks product as our example. With product analytics we can discover all sorts of useful information to optimize our products and drive our metrics/KPIs: Daily active users, monthly active users; number of users by account type and location/geography; retention, churn, stickiness; most used / least used features; conversion funnels. We have great product analytics tools: Mixpanel, Pendo, Amplitude, Heap and others. And these tools now include embedded AI to speed our path to actionable insights.

Product analytics is easier with software products, but it is highly useful for hardware products. We can do this if we attach IOT (internet of things) devices to our hardware. In this lecture, we use the example of iMop floor scrubbers. With IOT-embedded hardware, we can understand product usage per day, location, on/off cycles, maintenance issues, and replacement timing. We can share all this data with our customers. While all of this helps us create better products, it also enables new revenue streams. For example, we can send preventative maintenance alerts to our customers and link these alerts to our spare parts online ordering sites.

Running product experiments can give us a powerful way to optimize our products and improve key metrics. With product experiments, we are testing like scientists, with an idea and a hypothesis. In this lecture, we use Envoy Desks as our example, and experiment with an idea to increase the number of users that reserve desks. We step through the full process, including our hypothesis and how we will know if this hypothesis is true (or not). Small changes - especially changes that accumulate over time - can often have a big impact on our revenue. Product experiments are easier for companies with lots of users, like large B2B or B2C SaaS companies. This type of experimentation is tougher with smaller B2B SaaS companies, and tougher with hardware or highly regulated products.

The current (and future) shape of product management is leaner, faster, more experimental, and accelerated by AI.  Our discovery and delivery processes allow us to find innovation, delight our customers, distance ourselves from competitors, and generate nice profitability. Product managers should lean heavily into this process, and aspiring product managers should do all they can to get as much experience as possible - interviewing customers, clarify customers' needs and opportunities, brainstorming ideas with development teams and product designers, and iteratively testing our concepts in the market. Our new AI tools - for prototyping and product analytics - are a great accelerant for us.

In this lecture, we look at the importance of impactful launches

In this lecture, we'll look at two companies who are very good at impactful launches.

We'll talk through positioning and communication for our products, and revisit personas.

Value propositions are simple statements that clarify our target customer, key benefits, and competitive differentiation.

We'll create a value proposition for Ancestry's DNA testing service in this practice activity.

In this lecture, we'll talk about how to create benefit trees - which are a useful way of mapping a hierarchy of product benefits.

In this lecture, we look at the importance of pricing - and its impact on profitability.

We look at the "3C's" of pricing in this lecture - cost of product, competitive environment, and customer value - and link these to three different pricing approaches.

Subscription prices for SaaS products can be a little tricky. We'll look at different options.

In this lecture, we look at the eight steps product managers go through to price a new product, or revise pricing for products in the market today.

Answer three questions about LinkedIn pricing in this practice activity.

In this lecture, we'll start the discussion on how we can best support a sales team.

In this activity, you'll read Rich Mironov's blog post on working with sales teams.

Excellent sales enablement tools can help win deals (and win friends)

In this lecture, we'll talk about on-going processes to support a sales team.

In this lecture, we will look at using sales channels as partners to co-create customer value.

We'll look at HP sales channels in this practice activity, asking three questions.

In this lecture, we'll look at adding new sales channels and editing your current channels.

In this lecture, we will talk about three "rules of the road" for managing product support issues.

We'll use two African transportation and logistics companies to discuss how to best manage product support issues.

Finding growth for our products is a fundamental role for us product managers. In this lecture, we introduce the topic and look at a typical lifecycle of successful products.

Growth strategies vary through the product lifecycle. We'll examine these strategies in this lecture, with examples from three companies (Bolt, Lytx, and HP)

Let's do a practice activity on finding growth. We'll use a product tool (and template) to spark creative ideas.

Product-led growth is one of our most powerful go-to-market models, with fast evolution and fast innovation. We introduce product-led growth in this lecture and compare two companies: Geotab and SafetyCulture.

Even if we can't fully use a product-led growth go-to-market model for our products, we can all incorporate product-led growth's best practices: 1) Get to value fast, 2) Make it easy for users to advocate our product, and 3) Integrate tightly with marketing, customers success, and sales teams.

We'll include four company examples: SafetyCulture, Calendly, OnX, and Guru.

In this lecture, we'll discuss the history of Udemy - and how the company found rapid growth.

In this lecture, we will look at obsoleting products, and freeing up time for more impactful parts of your work.

We'll talk about 7 big themes from the course in this lecture - 7 themes to help you become a more impactful product manager.

We'll talk about how to keep learning as you go forward.  Then we'll finish the course. Congratulations!