5 Types of Product Pivots, and When to Make Them

In the process of finding product-market fit with a new product or feature, it’s challenging to know precisely when to pivot and when to persevere. Making product pivots too early, or without enough evidence, can lead you away from a valuable opportunity. Making a pivot decision too slowly, on the other hand, can lead you to spend time and resources on a product that doesn’t deliver customer value.

Product pivot decisions are challenging because they are not a perfect science. Even when you’re operating with a rigorous, data-driven process, the choice of when, how, and where to pivot requires judgment, intuition, and risk. 

In this article, I’d like to explore a few different pivot types. My hypothesis is that we make better decisions when we are aware of the options we can choose. We can diagnose the problem with better precision and can be more adaptive to new realities. Studying pivot types can help us pinpoint the layer of the product that is failing, and what we need to change to get our products back on track. 

If you are experiencing a slew of bad results, or friction in bringing a product to market, read on! Here are 5 pivot types you should consider when making a pivot.

#1 The Customer Mental Model Pivot

A customer mental model pivot happens when we need to adapt our product, strategy, or roadmap because we have new data that changes our understanding of customers. 

One of my favorite customer mental model pivot examples comes from The Lean Startup. Eric Ries describes how his company, IMVU, believed that customers would want to create avatars as themselves so they could socialize with their friends online. They learned, however, that customers actually wanted to use avatars to create new, imagined selves, so they could form new friends without giving up their real identities. He writes: 

“Our customers intuitively grasped something that we were slow to realize. All the existing social products online were centered on customers’ real-life identities. However, IMVU’s avatar technology was uniquely well suited to help people get to know each other online without compromising safety or opening themselves up to identity theft. Once we formed this hypothesis, our experiments became much more likely to produce positive results.” 

Customer mental model pivots are high-leverage pivots. Not only can they improve the outcome of a new product, but they also help create better outcomes for future product development. And while they are often made in response to a series of failed tests, they can also be made before, or independently of, feature deployment. By interviewing users on a consistent basis with prototypes, for example, teams have the opportunity to pivot and refine customer mental models without building out expensive, fully loaded features. 

#2 The Execution Pivot

The execution pivot occurs when you have the right value hypothesis, but the execution prevents users from realizing its value. You are still finding the right way to shape your product in order to solve your customers’ problems.  

Perhaps the problem you’re trying to solve is so novel that you need to trial a few different approaches before you find something that works. It also could be due to flaws in the design. For example, you have validated a tutorial during a user test. It’s effective at driving product engagement in your test, but, after launching it live, users don’t discover the survey because it’s below the fold. 

The trick with the execution pivot is that it can masquerade as a mental model problem. It might appear that your assumptions about customer value are incorrect if your test launch was unsuccessful. 

To avoid doing this, it’s important to have a strong customer mental model as a foundation. It’s also helpful to accompany product launches and tests with ample contextual data: funnel analysis, screen recordings, and user conversations. These types of analyses can reveal whether unsuccessful features are failing because you haven’t found the right execution, or because your customer assumptions are flawed. 

#3 Strategy Pivot

A strategy is an underlying policy that results in a series of product decisions. Strategies inform what types of features we build, when – which areas of the product to focus on, and in what sequence. 

In a strategy pivot, the principles that are governing the product execution need tweaking. Perhaps you decide that the best way to win the market is to introduce a future-forward solution. You then discover that no users are buying. You might re-shuffle your strategy to start selling a version of the product with less feature adoption friction, so that customers start using your product, and, eventually, adopt your future-forward technology.  

One of my favorite strategy pivot examples comes from George Rommel’s “Good Strategy, Bad Strategy.” Rommel tells the story of Steve Jobs returning as CEO of an almost-bankrupt Apple in 1998. At the time, the company had a wide range of product lines – several desktop computers, handhelds, printers, and so forth. The current strategy left Apple over-extended, unfocused, and hemorrhaging cash. Jobs’ new strategy was to pair down product lines to a minimum, focus on cash efficiency, and plan ahead for “the next big thing.” And instead of producing a wide array of products, Jobs built an interconnected ecosystem around a few pivotal products (the iMac, iPod, iTunes Store, and later, the iPhone) that Apple’s competitors didn’t focus on. This strategy allowed Apple to move from a dying niche computer company to the most valuable company on the planet. 

#4 Business Model Pivot

A business model pivot is less about “is this the right product for users” and more about finding the right way to monetize that maximizes user success and business success. In this scenario, a team might find that the product idea is correct, but the path to monetization is not scaling; or that a product is generating revenue, but at the cost of its users. 

Finding the right fit is not easy. Google search, for example, originally set out to monetize by offering SEO consulting services. They pivoted away from the idea because it would allow big companies – that could afford to partner with Google – artificial priority in the search results. Instead, Google a way to maximize search integrity and profitability by displaying ads that matched keyword intent. 

#5 Vision Pivot

This pivot is something I discovered from Marty Cagan, who, in an SVPG article, describes the vision pivot as altering “the big picture of what you are trying to achieve, typically over a 2-5 year timeframe.” (The article sparked my interest in pivot types. If you want to learn more about pivots, it’s a must-read.) 

A vision pivot happens when a company alters its existential focus. The company doesn’t just change its business model, but its view of itself and its place in the market.  

Cagan argues that visions are hard to achieve, and require a great deal of sustained iteration to bring to reality. Visions, therefore, should only happen after a company or team has exhausted many other kinds of pivots, and is still not gaining traction or success. 

Vision pivots can also happen when companies realize that their current product is nearing the end of the s-curve, and a pivot towards new technology is necessary for future growth. Netflix bet that the future of entertainment would be streaming, instead of mail-ordering DVDs. Meta recently pivoted their vision beyond social media platforms, towards the metaverse. 

Pivot types in action

Pivot decisions are tough, but we can make better decisions by classifying and studying different ways products, businesses, and companies pivot. As product managers, we don’t usually make pivots with the same magnitude as company CEOs, but we can apply the same reasoning to our own areas within larger organizations. 

If you are confronted with a situation that requires a change in direction, stop and diagnose the situation fully. Make sure you figure out what aspect of your product is failing. If revenue is down, ask whether the business model is failing, or whether the business model makes sense but the strategy is flawed. If your latest feature isn’t taking off, make sure to rule out an execution pivot before making a customer mental model pivot. 

Once I started reasoning this way, I started making more informed, precise, and effective product pivots. I hope this helps you do the same. 

If you found this article helpful, check out David Prentice‘s other article on product pivots.

About the speaker
David Prentice CollegeVine, Product Manager Contributor

David Prentice is a Product Manager who is happiest when actualizing ambitious visions, fine-tuning high-quality user experiences, streamlining complex interfaces into simple interfaces, learning by talking with customers, binge-building dashboards, collaborating with cross-functional teams, and shipping products that make a meaningful improvement in the lives of their users. He currently works at CollegeVine, an education startup dedicated to bringing high-quality college guidance to every family, and has led the creation of a new app to help students optimize their college choices. Prior to CollegeVine, he managed brand, platform, and research teams at two of the world’s largest online travel companies. PM-life aside, David is a music, art, and history nerd, who lives in Boston with his girlfriend and three cats.

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