The DAM ROI metrics that matter for brand teams

Last month I spent a morning with the marketing team at a large automotive manufacturer. Thousands of dealerships, local market operators across most of the world, and a DAM that was never designed to be an IT system and instead what delivered their brand to local markets.

The meeting was all about how to drive adoption of the platform and their reasoning was sound. More usage meant better brand consistency, a lower cost per asset, and a slower climb in agency spend, which had been heading in one direction for a while.

Where it got interesting was measurement. Their reporting produced maybe a dozen numbers, all of them true, none of them ranked, and most of them built to answer a question about infrastructure rather than a question about brand.

So someone asked the one that mattered: which of these should we actually watch, to know whether the things we’re about to try are working?

Three metrics came out of that conversation. They’re the DAM ROI metrics I’d argue matter most to a brand team, and the order is about as important as the metrics themselves.

Why DAM ROI changes when marketing owns the platform

Most DAM ROI models were built for infrastructure. Storage consolidated, licenses retired, hours saved hunting for files, duplicate shoots avoided. All real, all worth counting, and all fundamentally questions about cost of ownership.

That model holds while IT owns the platform. It stops being sufficient the moment a Digital Asset Management (DAM) system starts doing brand management work: serving guidelines to distributed markets, feeding templates, governing what dealers and local teams are allowed to publish.

Infrastructure metrics can’t see that. A perfectly consolidated library nobody in Spain or Singapore ever opens has excellent storage economics and no brand value whatsoever.

Most organizations are further back than their dashboards suggest. Across Papirfly’s discovery conversations, 84% of organizations sit at stage one of the brand management maturity model (Source: Papirfly brand management maturity model, 2026), where the assets exist somewhere but nobody is governing or measuring how they get used.

This is the distinction I’d want any marketing team to draw before they build a business case. The infrastructure numbers are what get a DAM approved. They are not what tells you it’s working.

Why the order of your DAM ROI metrics matters

A DAM creates brand value through a chain of behaviors: people show up, they reuse what’s already there, and eventually they adapt it for their own market.

Let’s consider download volume. A genuinely useful figure, right up until you find out it came from eleven people in the central team.

When we spoke to Rabobank about their teams’ annual usage, they reported over 23,000 assets were produced in a single year through their portal. Whilst this is clearly impressive, it’s also uninterpretable until you know whether that came from a team of twenty or from thousands of people across fourteen markets, because those are two completely different companies.

The ratio is the argument, and it’s the version that survives a board meeting. Total volume proves the platform gets used. Volume set against the size of the user base proves the brand has reached the markets where the reputational risk actually sits.

DAM metric 1: Logins

Logins come first because they tell you whether the platform has entered anyone’s working habits. If people aren’t showing up, they’re getting brand materials somewhere else: an agency, a colleague’s drive, whatever design tool was already open on their laptop.

Two figures are worth pulling out separately. The first is active users as a share of total licensed users, which tells you how much of the population you paid to provision has ever engaged, and which markets the rollout never really reached. The second is average logins per user over time, which tells you whether people keep coming back to the platform or just make an annual drop in.

Rabobank’s portal is accessed by more than 22,000 people a year, around 2,500 of whom are regular users activating the brand. Both numbers are true and neither is enough on its own.

Wide reach with low frequency usually means a rollout that touched a lot of people without changing how any of them work. A small core logging in constantly while whole markets stay silent is a different problem with a different fix. You need both readings to know which one you’re holding.

DAM metric 2: Asset downloads

Once people are reliably showing up, the question becomes whether they’re using what’s already there. Downloads answer that directly, which makes them a measure of reuse rather than a measure of activity.

Reuse is where the first hard saving sits. Every download of an approved asset is a shoot not commissioned, a brief not raised, or an afternoon of internal design time spent on something more useful.

Total download volume has the same denominator problem as total output, so the number to track is average downloads per user across twelve months. It normalizes for headcount and stays comparable year on year and market by market.

The automotive manufacturer above averages 158 downloads per user per year. Another organization on the same platform averaged 34 over the same window (Source: Papirfly customer data, 2026). Both had people logging in. Only one had made the library the first place anyone looks.

This is why downloads belong above content creation in the order. Reuse is cheaper and it happens earlier, so a business creating heavily while downloading lightly is building from scratch at higher cost, further from the approved set every time.

When the download rate lags, it’s nearly always findability rather than willingness. People arrive, don’t find what they need fast enough, and go back to whatever they were doing before.

DAM metric 3: New content created

The third metric picks up what local teams do once the first two are healthy. New content created is the read on localized campaign adaptation: markets taking approved material and making it land with their own audience, in their own language.

It’s worth being precise about what gets counted here. Templates built and documents produced from those templates are two different numbers, and the second one is where the end user value sits.

Templates are infrastructure. Documents are the evidence that someone in a market picked the infrastructure up and used it.

It’s also the metric closest to commercial performance, because locally relevant content tends to outperform central material dropped into a market unchanged. And it’s the clearest evidence that a brand has scaled rather than simply been stored somewhere tidy.

XXL’s teams generate more than 4,000 assets a year across 84 stores in four Nordic countries, with campaign production down from weeks to minutes. That second figure is a time to value measure as much as a volume one, and the volume only works because access and reuse came first.

Taken together, the three read less like a report and more like a diagnostic:

1. Logins low -> Adoption hasn’t started, and nothing further down the chain is worth interpreting yet. The work is rollout, training, and getting the platform into people’s daily routine.
2. Logins healthy, downloads low -> People are arriving and leaving empty-handed. The work is findability: search, taxonomy, and how assets get surfaced.
3. Logins and downloads healthy, new content low -> Local teams are consuming without adapting. The work is templates, and usually whether the right local formats exist at all. Check the document count rather than the template count here, since a healthy template library that nobody builds from looks identical to no library at all.

Building the DAM business case

The team I met had the right instinct. They were never short of data. What they lacked was a view on which number should move first, and what a healthy figure on one metric implied about the next.

Logins, downloads, and new content each measure a different behavior, and each becomes readable in light of the one before it. Take them in that order and the reporting starts answering a question rather than listing facts, which is a considerably easier thing to walk into a budget conversation with.

None of this replaces the infrastructure case. Storage consolidation and retired licenses still belong in the business case, and they’re usually what gets a DAM approved in the first place. They’re just not what keeps it funded once marketing is the team living in it.

All three sit in Prove, Papirfly’s analytics module, where they can be visualized on a single dashboard and broken down by region, team, and asset.

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