07
The open ground
Baseline functionality is widely covered. Personalization and innovation are the next step, and no category has owned either yet.
Most apps now cover baseline functionality. The open ground is the layer above them: products that recognize who is using them, anticipate what comes next, and adapt accordingly. This chapter examines the fourth driver, Feature richness, through three dimensions: completeness, personalization, and innovation. Together they define how much work the product does for the user.
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Baseline functionality is widely covered. Personalization and innovation are not
Most apps cover the features users need. Far fewer personalize or anticipate what comes next. 47 percent score below 3.5 on personalization, 61 percent on innovation. Apps have the features; the product does not yet recognize who is using it or what they need next.
Strong on features, weak on intelligence
Baseline functionality is widely covered. The market shipped the features. The next layer is the intelligence around them: products that adapt to the user, anticipate the next step, and do work the user did not have to ask for.
Personalizes, but does not innovate
A product that personalizes but does not innovate reads as mature and trusted, sometimes conservative.
Innovates, but does not personalize
A product that innovates but does not personalize feels exciting but generic.
Strong on both
Strong on both is where expectations are moving. Weak on both is still where most of the market sits today.
In practice that looks like a banking app that knows which account a recurring transfer should come from, a music app that surfaces the playlist matching the time of day, or a grocery app that completes the weekly basket before the user opens it. None of these requires new features. They require the product to know who is using it.
Feature completeness is also a moving target. AI tools can now build a small feature on the spot, tailored to one user’s situation. A travel app handing an LLM a booking and getting back a screen built for that specific trip is no longer hypothetical. As the cost of building new features drops, the bar for “complete” keeps moving up.
For product teams, this is the clearest open ground in the report. The bar for personalization remains low across categories, and no category has yet defined what good looks like. The first product to consistently personalize and anticipate will reset expectations for the rest of the market.
Where the feature opportunity actually lives
Per-app weighted score on each Feature richness statement: feature completeness, personalization, and innovation. Bands at 3.0, 3.5, 4.0 split the 1–5 scale into poor / mid / good / excellent.
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Are you building features, or building the intelligence around them?
Some products clear Pulse 4.0 without personalizing
Some products are loved without personalizing. 33 apps clear Pulse 4.0 while scoring below 3.5 on personalization. Almost all of them are Danish or Dutch. MobilePay in Denmark, the Danish payments app, and NOS in the Netherlands, the Dutch public broadcaster, are representative: technically excellent, widely loved products. They are loved because of what they do consistently well (feature completeness and trust), not despite a weak personalization layer.
The pattern is concentrated in Denmark and parts of the Netherlands, not universally across markets. In Sweden, products clearing Pulse 4.0 also tend to personalize.
This matters because context and memory are becoming baseline expectations. Users who live with a product that remembers them notice when another product does not. Today the pattern is defensible, especially where trust concentration is high (see Denmark’s dominance on data responsibility in Chapter 5.1). Under AI-era expectations, it will not hold. The window in which personalization is optional is closing, and it closes faster in markets that already expect it.
App Pulse vs. personalization, all apps
33 apps sit in the upper-left quadrant. 25 are Danish, 8 are Dutch, 0 are Swedish. Swedish apps that clear Pulse 4.0 also tend to personalize.
Every (app, country) pair in the study, plotted by personalization (x) against App Pulse (y). Reference lines mark Pulse 4.0 and personalization 3.5. The upper-left quadrant carries the ‘good but not smart’ apps.
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Is your product still defensible without personalization, or has the AI baseline already moved past it?
No category owns innovation yet
Innovation averages 3.4 across the market and tops out below 3.6 in the strongest category. Finance leads, carried by neobanks more than by the category as a whole; the rest of the categories sit close behind. No product yet defines what innovation looks like in its sub-category.
Innovation means solving a friction users live with today, in a way they did not expect. AI is one amplifier, not the only one. The market has yet to claim this ground. The bar is low. The first product to remove a real friction, whether through AI or through better design, sets the bar for the whole category.
In practice, the products closest to claiming it are ones like Tibber, which reimagined the user’s relationship with energy costs, or neobanks that automated savings without asking. Each solved a friction the category lived with. Neither required AI.
For a product team, the question is what innovation looks like inside their product. Innovation that solves the user’s real friction, in ways the user could not do before, is what users will recommend.
Innovation score by category
Weighted average of the innovative-features statement per category. Score on a 1 to 5 scale.
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Who is defining innovation in your category, and what are they teaching users?
Innovation perception cuts between mindsets, not ages
The same product looks different to different mindsets.
Innovators rate “Innovative features” at 3.8
Late Majority users rate it at 3.4
A 55-year-old Innovator and a 25-year-old Late Majority user read the same interface through opposite lenses. When product calibration assumes one mindset and the user base lives in another, the output is a product that looks progressive in the building room and generic in the field.
Recruit research participants by adoption type, not by age. The age cut hides the gap that moves perception. A product team that tests its innovation with innovator-mindset colleagues risks missing half of the user base.
Innovation and modern design by adoption type
The largest demographic gap in the entire dataset, wider than any age, gender, or income effect.
Weighted driver score per adoption-type segment.
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Which mindset is your product designed for, and which mindset is using it?
What this means
Finding
Baseline functionality is widely covered. Personalization and innovation are the next step, and no category has owned either yet.
Evidence
48 percent of apps score below 3.5 on personalization. 63 percent on innovation. No category averages above 3.7 on either dimension.
Implication
The first product in any category to deliver real personalization and anticipation defines what users will expect from the rest.
What we did not expect
We ran this chapter as a temperature check. Personalization sits on most roadmaps. The smart, intelligent version of it rarely ships. 47 percent of apps score below the bar. Only 2 percent of users name personalization in spontaneous feature requests. The roadmap intent and the release notes are not the same thing.