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You’ve built a product and found a user segment for which you have product/market fit. If users from this segment learn about your product and experience its value for themselves, they will choose it for getting the job done.

This is when you start planning how to get the word out to potential users about your product’s value. But what happens if you simply say that you have some new way of solving their problem? Odds are that their behavior won’t change.

Generally speaking, people want to go with the flow and are reluctant to try new things.

Data drives product management. Product managers rely on data for everything from creating an easy buying experience to determining if a product should even be developed. And while data is used to inform all aspects of managing a product, are there different considerations for using data for long-term strategy vs. daily decisions? 

It turns out that the answer is yes. While there are many similarities, like needing to ensure success is clearly defined, for strategic decisions more context, expertise, and qualitative data is required. Data used for strategic decisions tends to be higher quality, take longer to collect, and be more expensive than data used for everyday decisions. Data mistakes, such as bias or incorrect benchmarking, are also more costly to the organization when they happen in the context of creating a strategy.

For a thoughtful approach to product growth and development, it’s critical to know the tasks and contexts that create the jobs-to-be-done (JTBDs) handled by your product.

We began this series with how product habits get made and why the neurotransmitter dopamine is so important for this process. Then we looked at the Hook Model, which Nir Eyal created to explain habit formation. Here in our concluding article, we will look at which products by definition cannot be habit-forming, what user habits can be confused with, and alternative ways to encourage users to interact with a product more often.

Activation refers to more than just onboarding and the initial in-product experience. For most products, activation starts long before. It’s important to prime potential users in advance, especially for products with extended time to value or a long sales cycle.

Regular use of a product can become a habit. In the previous article we zoomed in on dopamine’s role in this process. This time we will look at a way of thinking about habit formation called the Hook Model, proposed by Nir Eyal.

Last month we asked our product management experts about the transition from working at a startup to working at an enterprise. While each expert took a different path to enterprise product management, there were similarities. They told us that both startups and enterprises have intelligent, talented, and passionate people and that you’ll learn a lot in both places.

However, most of our experts made the switch from startup to enterprise because they wanted to deepen their product management skills and broaden their scope. They also ended up improving their communication skills because enterprises have many more stakeholders that must be heard and brought on board. Teamwork becomes more important than moving as fast as possible. The experts also stressed to get clear on your career goals and do a lot of research into company culture if you’re thinking about making the move to enterprise.

There was another question we asked them: ”What useful information sources helped you to move more smoothly through this transition?” The number and quality of resources they came back with were impressive. Based on their answers, we put together this selection of books and podcasts for product managers looking for inspiration and knowledge for their careers.

Teams usually design onboarding from the start of the funnel: acquisition channels, followed by a landing page, main features, and then the paid version. But this can lead to a clumsy and ineffective activation flow. Users get lost, conversions stay low, and the unit economics fail to turn positive.

In this article, Ilia Krasinskii and Oleg Ya will share the story of a real product that had this problem, which was solved by designing activation in reverse: by starting with added value and only then moving toward acquisition channels.

User habits can have a big impact on a product’s long-term success. We will kick off our discussion of habits with how people develop them and the ways in which popular products nudge users to keep coming back.

A quantitative data-driven culture is generally seen as very positive. It’s great for understanding performance and tweaking strategy. Quantitative data is useful for reducing risk and can be used for decisions that need a high degree of certainty. These situations are usually high enough of a priority that adequate time is allotted to use data to verify various experiments before the decision is made. 

But there can be very real downsides. Data alone isn’t particularly useful for big transformations or concepts that don’t exist in the market. Henry Ford, founder of Ford Motor Company, famously said, “If I had asked my customers what they wanted they would have said a faster horse.” Ford’s customers actually wanted a faster way to travel, but lacked the language and vision to describe an automobile. Ford had to make the leap from “faster horse” to “car.” Data cannot do that.