Hard Skills of Successful Product Marketers

Nov 25

Product marketing is the process of taking the right product to the right market with the right narrative at the right time.

Key stakeholders within an organization look for product marketing to help inform them on what market segments or industry verticals the business should prioritize. For example, they ask PMMs questions like:

What are the products they should be building and the audiences they should be targeting?
How much value can be extracted from potential buyers?
How will the organization raise awareness and bring products to market in the most effective way?
How will the business communicate with customers the unique value proposition of its products and solutions?
How are the products in your portfolio performing? What's their customer adoption rate?

These are the key hard skills PMM candidates are tested on:

1. Market Sizing - Total Addressable Market (TAM)

Product marketers are responsible for supporting the organization in identifying what segments or verticals the business should consider allocating resources. There are 3 ways to size a market: top-down, bottom-up or value-based.
Top-down extrapolates the size of the TAM from industry research. Top-down total addressable market calculations are often based on existing work by market-research firms, such as Gartner and Forrester.
However, to draw specific conclusions about particular markets, the broader research these firms have done often must be supplemented or refined by extra assessments, such as phone or email surveys, completed by third-party consultants or using your company's strategy and analytics team.
There are some pitfalls to keep in mind. This approach ignores the potential impact that a disruptive technology or product can have in the market. Innovations often expand the total market size!
The bottom-up approach uses data from your company's early sales to estimate the market. PMMs can calculate this number by extrapolating information from internal data based on current pricing and usage. PMMs can take that number and apply it to the larger customer base of the total potential target market.
For example, if you sell a B2B software solution that works best for small-medium firms with a certain number of employees (e.g., up to 500 employees), you can calculate the number of those firms in the target industry, the number of employees they have on average, and the number of those who will be likely to use your software. The TAM formula is = (Annual Contract Value) x (# of possible Accounts).
Lastly, the value-based approach relies on an estimate of the value provided to customers by the product or service and how much of that value can be reflected in the product pricing. Value-based TAM is mostly used for companies pioneering new markets where there is no innovation or market precedence.

🎯 Example: The TAM for Uber or ride-sharing companies was greatly under-estimated because it was primarily assumed to be a substitute for taxis. Bill Gurley, one of Uber's earliest investors, wrote a detailed post on why Uber was often undervalued in its early days due to TAM miscalculations.

2. Market Segmentation

Intimately understanding customers is core to effective product marketing. Great PMMs will seek out data (qualitative and quantitative) to determine all the different customer segments and help inform product development, product narrative and channel strategy. Therefore, it is important to understand the different types of teams PMMs can collaborate with and the different methods each team is potentially capable of deploying to uncover those insights.
It all starts with the product marketing research brief. Here the Product Marketer needs to clearly define the problem, objectives of the research and provide directional guidance to the each research team.
Data Science. At most modern tech companies, data science teams are responsible for data collection and analytics to uncover customer, product, and operational insights. They have access to all internal user data and are able to "slice and dice" the data to derive meaningful insights. Product marketers are key collaborators to these teams and provide directional guidance so that they can extract the right datasets to support the goal of the project.
User Research (UXR). User researchers are extremely useful partners to product and product marketing, too. They help define user maps, build customer journeys, collect product feedback and help test new product concepts. The methods they tend to employ can vary from focus groups, individual interviews and quantitative online surveys.
For example, at Uber, we used this team to interview several lookalike business travelers and help build out an entire customer journey: pre-trip, during trip and post-trip, outlining what they think, feel, want and need in each of those phases. This helps to uncover potential gaps in their journey that can be fulfilled with a new product or service. Not every user will think, feel, want or behave the same way in this customer journey. Product marketers use this information, captured by the UXR team, to create user profiles or customer personas. For example, during the business traveler project, PMM was able to use UXR data to develop four business traveler personas: The Jetsetters, The Road Warriors, The Locals and The Newbies. Each persona has different demographics, different pain points, different travel preferences, different use cases and each use different channels to communicate with. With this information, product marketing can start to develop content and channel marketing strategies.
Marketing Research. In some organizations, marketing research can also be referred to as Research and Insights. This team tends to sit within the marketing organization, unlike data science or UXR. Similarly to UXR, these teams can use a combination of 1-1 interviews, focus groups or omnibus surveys.
Product marketers can use marketing research to test narratives, value propositions, taglines, creative campaign visuals and assets. Using the previous example, through marketing research, we were able to validate our narrative, product positioning and test different campaign taglines. This ultimately allowed us to come up with the single-minded message:
"Let Uber take the work out of work-related Travel".

🎯 Example: At Uber, we wanted to understand how many users were likely business travelers. To do this, PMM, PM and the data science group collaborated to build a business lookalike model. The product teams provided guidance on the profile of existing business users like the frequency of trips to and from the airport, to and from hotels, international rides and type of payment method (e.g., corporate card vs. personal credit card). With this information, the data science team analyzed our internal data and provided PMM with a targeted list of users that fit the business traveler lookalike model.

3. Narrative Design

With user/customer research in mind, PMMs need to be able to understand how a product works, what makes it unique, what powers it and distill all that information into a compelling, memorable and reproducible narrative. There are 3 main elements to orchestrating a compelling narrative:
The WHY. Why should anyone care? Why should I listen to your brand or message? This is normally where PMMs identify the problem or pain point that the product is intended to address. For example, prior to ridesharing, people always had to walk to areas where they might be able to catch a taxi. To make things worse, pricing wasn't always transparent and some taxi drivers may refuse to take credit cards or even give out receipts.
The HOW. How are you solving customer problems? What is your value proposition? What makes your product unique and differentiated from the competition? This is where PMMs clearly articulate the solution to the problem highlighted before. Using the same example, Uber allows people for the first time to request a ride with a tap of a button.
The WHAT. What are the benefits you will provide customers? This is where PMMs identify the most important benefits from the solution to the problem. These are also often referred to as "reasons to believe". Ideally you shouldn't highlight more than three, to make it easier to remember and reproduce.

🎯 Example (using Uber):
Convenience: One tap and a car comes directly to you.
Reliability: Your driver knows exactly where to go.
Hassle-free: Payment is completely cashless and receipts are emailed.