Finding Product Culture Fit


Product managers most often reach out to me for advice when they are in the midst of contemplating their next role. In our discussions, we talk about all the usual things: their ultimate career aspirations; their understanding of their own strengths and weaknesses and the skill gaps they hope to fill; as well as the specifics of each role they are considering, including scope, responsibilities, title & compensation, and manager. But the one conversation that people often tell me they find uniquely insightful is our discussion on finding product culture fit. So I wanted to share my thoughts on this more broadly.

As an industry, we frequently talk about the reality that there is no single definition for the responsibilities of a product manager and that product management roles differ meaningfully across companies. The root of this comes from the fact that fairly unique product cultures often develop within each company. This typically stems directly from the personalities and proclivities of the founders & senior executives within the organization and ultimately permeates throughout the entire organization. The product culture ultimately informs how a product manager spends their time, how decisions are made, and the strengths and weaknesses of their product development approach relative to alternative cultures.

Before jumping into a new role, product managers should deeply understand the product culture of the organization they are considering joining and whether it's a fit for them. I find the best way to think about finding your own product culture fit is to think about it in terms of an explore and exploit algorithm. The idea here is that early in your career you should be looking to expose yourself to many different product cultures so you can learn to flex the various product muscles that each approach requires as well as learn the relative strengths and weakness of each approach. After you're exposed to many product cultures, you'll have gained a self-awareness of what type of product culture you thrive in and can begin picking future roles specifically on how well the company's product culture jives with your preferred approach.

Through my time in Silicon Valley, I've found four specific product cultures dominate tech companies: engineering-driven, data-driven, design-driven, and sales-driven product cultures. Individual companies typically have a dominant product culture, plus elements from a secondary product culture. Lets walk through exemplary companies in each category and the key facets of each culture.

Engineering-Driven
Engineering-driven product cultures often start with a unique technical insight that becomes the basis for their products. Larry Page and Sergey Brin's Page Rank algorithm, for example, was the unique insight that enabled them to build the world's most successful search engine. Given Google's early success in leveraging such technical prowess to build a market-leading product, a similar playbook was often used throughout the company. Google Maps, for example, was one of the very first apps to leverage AJAX functionality to create a buttery smooth scrolling experience across a map surface, something that had never been seen before when MapQuest was leading the market. Gmail initially launched by offering 1 GB of storage, which was unheard of relative to Hotmail's paltry 2MB. More recently, Google Photos is one of Google's best showcases of their artificial intelligence and facial recognition algorithms, allowing you to quickly search for people, pets, objects, holidays, and more. It's no surprise as well that Google is the leader in self-driving car technology.

Beyond Google, Microsoft, and Dropbox are also considered engineering-oriented product cultures. You also often see such a product culture inside developer product companies like Stripe.

Being successful as a product manager at these companies requires you to be quite technical. That stems mostly from needing to command the respect of the highly respected engineers you work with but also from needing to be able to determine how to leverage sophisticated technology to create unique product differentiation.

One of the challenges with an engineering-driven product culture can be that with engineering as your hammer, everything looks like a nail. You can sometimes find yourself searching for technology solutions to non-technology problems. It's no wonder Google struggled with building Google+, it's attempt at a social network, or a successful messaging app despite continuous attempts.

Data-Driven
Data-driven product cultures thrive off of the insights they can derive from product metrics. Zynga is the canonical example of a data-driven product culture. They truly pioneered the entire social gaming model, bringing an incredibly heavy focus on product metrics to the genre of gaming. They figured out how to reduce critical game mechanics to effectively equations that could be modeled in a spreadsheet and then optimized through rigorous A/B testing. This enabled them to significantly streamline their social invite flows to drive friends into games, tune the virtual economies to drive spend of virtual currency, and optimize appointment mechanics to drive retention. With such a deep modeling of user game behavior from acquisition to monetization to retention, they could bust out social gaming hit after social gaming hit, including FarmVille, Mafia Wars, Words with Friends, and more.

Beyond Zynga, Facebook, LinkedIn, and PayPal are all great examples of data-driven product cultures.

What's great about a data-driven product culture is that the definition of success for your product is very clear, so you always know how you are doing relative to the goals you set out for your team. At the same time, there is so much benefit in metrics being the ultimate decider of product decisions relative to the individual opinions of people within the four walls of your company. Product intuition is cleanly built through running hundreds of A/B tests and developing an ability to forecast future initiative gains.

The downsides of a data-driven culture stem from the fact that not everything is measurable through a metric, either because the time-scale you'd need to measure the right metric would be too long to make product decisions off of, or there are aspects that simply can't be easily captured through a metric. These limitations of metrics can sometimes result in a short-term focus or an over-optimization that deteriorates the user experience. Counter-measures as well as being more creative about the types of metrics you measure can certainly help to alleviate some of this, but the bias always exists.

Design-Driven
Design-driven product cultures obsess over every detail of the user experience. Apple is certainly the canonical example here. Look no further than the iPhone for how Apple entered the existing smartphone market filled with incumbents like Blackberry, Windows Mobile, and Palm, and still revolutionized the industry with superior user experience. You could technically browse the web with all these previous devices, yet the experience iPhone created was an absolute game changer purely from its speed and elegance and ultimately introducing a far superior app experience. By sweating every detail of the experience, Apple has proven it's ability to enter existing markets, like MP3 players, smart phones, smart watches, and wireless headphones, and blow up the sheer size of that market by bringing a broadly accessible solution to the world.

Beyond Apple, Airbnb, Snapchat, and Square are all great examples of design-driven product cultures.

The wonderful part of design-driven product cultures is that you are given the time and opportunity to deeply develop a perspective on every single detail the user experiences with your product. If you love spending your time as a PM in deep design discussions with your team, you'll truly enjoy this product culture. The downside of design-driven product cultures is that product taste can be very subjective, often leading to decision-making ultimately led by a trusted few taste makers within the organization. Since testing is rarely used as the basis of core product decisions, it's also hard to create conviction for your diverging perspective by simply trying it out with your users.

Sales-Driven
Sales-driven product cultures thrive off the insights garnered through the sales and customer success process. Salesforce is a great example of a sales-driven product culture. In an organization like Salesforce, each individual customer can be worth millions in annual contract value and with strong retention, will likely continue to generate that for years to come once acquired. Given this dynamic, it creates a strong incentive to deeply understand exactly what it's going to take to win each of the large customers in your sales pipeline, build your roadmap to satisfy their needs, and continually investigate and understand their future needs to upsell them to your new offerings.

Beyond Salesforce, Workday, Marketo, and Oracle are great examples of sales-driven product cultures. You tend to see sales-driven product cultures across many B2B enterprise sales products, typically with $100K+ ACVs.

In sales-driven product cultures, you can usually name the specific companies and decision makers within those companies that are ultimately going to make the purchasing decision and so have a clear idea of exactly who you need to satisfy to be successful. This is in stark contrast to consumer companies where you rarely have deep and direction interactions with your customers on a regular basis, instead choosing to leverage analytics and market research to understand their needs. The big challenge with sales-driven product cultures is that you could easily end up building one-off solutions for your largest customers that either don't apply to existing or future customers or stray you from the vision of where you ultimately wish to take the product.

I hope this helps convince you that the differences in the role of the product manager between companies stems from differing product cultures and finding product culture fit is an important part of finding your ideal product gig.
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