The Value Layer of Time: The Longer a User Stays in the Product, Why Should the Value They Receive Grow Exponentially?

When I ask people who have used the same software for years why they're still there, I get the same answer surprisingly often: “Switching is too much hassle. But honestly, I hate it a little more every year.”

That sentence holds both good and bad news for a product. The good news: the user is still there. The bad news: what keeps them isn't the value the product gives them. It's the cost of leaving. And on a retention chart, those two things look identical. Until someone comes along and makes switching easy.

In this article I want to talk about how a product should become more valuable over time, and why that is a completely different thing from trapping the user.

Time accumulates either value or fatigue

Every month a user spends in a product accumulates one of two things. Either the value the product offers them grows, or their patience with the product shrinks. There's rarely a neutral state.

Most products choose the second path without realizing it. Whatever they give the user on day one, they give roughly the same in year two. A few new features may have shipped, but the user's experience is essentially unchanged. Meanwhile the user's needs have grown, their expectations have shifted, competitors have shown new things. While the product stands still, perceived value quietly melts.

The ideal relationship is the opposite. The longer the user stays, the better the product should know them, the better it should fit their work, the less effort it should demand.

The longer a user stays in the product, the faster the value they get should grow. If the reward for staying doesn't grow, the appeal of leaving does.

The layers of accumulated value

Value that builds over time has several layers. You don't need to build them all at once, but you do need to know which one you're investing in.

The first layer is data. As the user uses the product, a history forms: records, documents, decisions, results. That history isn't value on its own; it's just an archive. It becomes value only when the product uses it. A finance tool that can compare against the same period last year is worth far more than a tool that merely stores five years of data.

The second layer is personalization. The product learns the user's preferences, rhythm and habits. It doesn't have to make the same settings every time, doesn't make them read the same explanations again. This is the natural result of the loops we discussed in the previous article; every turn makes the next one fit the user a little better.

The third layer is the network. As the user brings teammates, customers and partners into the product, it stops being just their tool and becomes the common ground of a web of relationships. At that point the product isn't one person's preference anymore. It's a community's shared language.

The fourth layer is settling into the workflow. The product starts talking to the user's other tools; integrations get set up, processes get defined through the product, reports get built on its data. The product is no longer an application. It's the infrastructure of the work.

The line between trapping and earning

This is where you need to be careful, because each of these layers can be built in two ways.

You can use data in a way that helps the user, or you can hold it hostage by making export impossible. You can build integrations to make the user's life easier, or to turn leaving the product into an infrastructure project. From the outside, both produce the same thing: high switching costs. Inside the user, they produce very different feelings.

The trapped user is the person who says the sentence at the top of this article. They stay, but they hate it a little more every year. Your product becomes your competitor's best sales argument. They leave at the first opportunity and tell everyone on the way out.

With earned loyalty, the user chooses to stay. They could leave, and leaving might not even be hard; but leaving means abandoning the value they've accumulated. Here the switching cost isn't a wall. It's a treasure. The user wants to protect it.

The simple test I use: if the user could export all their data in one click, would they still stay? If yes, what keeps them is value. If no, what you're holding is a hostage, and hostages run when they get the chance.

Designing the second-year experience

Most teams design day one. Weeks go into onboarding, the first five minutes get optimized to the millimeter. Very few teams design the second year.

Yet the second-year user is one of a company's most valuable assets. They know the product, have spread it across their team, have most likely recommended it to others. And very often they're using almost exactly the product they saw on day one.

There are a few questions worth asking here. What does a user who has been in the product for a year see that a newcomer can't? What does their history earn them? What does the product give back from everything they've accumulated over that year? If the answer is “nothing,” the user's loyalty is the work of inertia, not yours.

Even small touches make a big difference. An annual summary. A comparison that says “this time last year you were here, now you're here.” A recommendation that learns from the user's past decisions. An advanced capability reserved for long-time users. None of these are technically complex. Nobody just thought of them.

Time is the most honest metric

In the short term you can fake a lot. Launch excitement, a discount campaign, a well-designed onboarding. But sooner or later, time reveals what a product really gives. How a user feels in their third year is the most honest measurement of your product's value there is.

With this part of the series we've covered designing value: behaviors, loops, the organization and time. In the next part we move to a difficult subject: how do you turn this value into money, and how do you do it without losing the user's trust?