Social platforms create a brutal math problem for rights teams: the volume of potential infringements grows faster than headcount, and “treat every use the same” quickly becomes a recipe for slow recoveries, inconsistent outcomes, and missed revenue.

To accelerate IP recovery, you need a prioritization method that treats infringement like a pipeline, not a pile of fires. That means scoring each use by recoverable value, choosing the right play (license, enforce, or monitor), and setting SLAs that keep high-value cases moving.

Why “value-based” triage beats “infringement-based” triage

Most catalogs are not under-enforced because teams do not care. They are under-enforced because triage is often driven by whatever is most visible in the moment:

• A stakeholder forwards a viral clip.

• A platform report surfaces partial data.

• A brand is “famous,” even if the use is not actually monetizable.

Value-based triage flips the workflow. Instead of asking, “Is this unauthorized?” (important, but binary), you ask, “Is this worth acting on now, and what action maximizes recovery?”

That reframing matters because the economics of recovery depend on:

• Commerciality (ads and whitelisted/boosted posts often matter more than organic UGC)

• Proof and attribution quality (can you win the facts quickly?)

• Counterparty clarity (can you reach the right decision maker?)

• Time to cash (some wins are real but slow)

Define the unit you are prioritizing: “use,” “campaign,” or “account?”

Before you score anything, decide what an “item” is in your pipeline:

• Use-level: each post/video is a separate case. Best for evidence precision, but can overcount when the same ad is duplicated.

• Campaign-level: group multiple creatives that share the same brand, objective, landing page, or ad account behavior. Best for monetization and settlement conversations.

• Account-level: prioritize by advertiser/agency account, then resolve multiple uses under one negotiation.

For most labels, publishers, and catalog investors, campaign-level prioritization tends to accelerate recovery because it aligns with how brands buy media and approve licenses.

The Value Scorecard: a practical way to rank infringements

A strong scorecard does two things:

1. It makes prioritization repeatable (not dependent on who triages that day).

2. It makes prioritization defensible (to executives, partners, and counsel).

Here is a scorecard structure many rights teams can adapt. You can start with a simple 1 to 5 scoring model, then apply weights.

Add one simple formula: Expected Recovery Value

To keep teams aligned, translate the score into an “expected value” estimate. You do not need perfect precision, you need consistent decisioning.

A useful model:

Expected Recovery Value = (Estimated License Value) x (Probability of Recovery) x (Time-to-Cash Factor)

• Estimated License Value: based on your internal rate card, precedent deals, or counsel guidance.

• Probability of Recovery: how likely this counterparty will pay or settle given evidence, jurisdiction, and identity clarity.

• Time-to-Cash Factor: discount slow-moving cases so you do not starve quick wins.

This helps prevent a common failure mode: teams spending weeks on a “big brand” case that is actually low probability, while dozens of medium-value, high-probability cases sit untouched.

A value-first workflow that scales

1) Normalize intake, dedupe, and enrich

Your prioritization is only as good as your inputs. The goal is to turn messy detections into decision-ready records.

At minimum, each item should have:

• Asset identifiers (where applicable): ISRC/ISWC, writer/publisher info, recording owner

• Platform context: TikTok/Instagram/X/Facebook/YouTube, post URL or ad reference

• Creative capture and timestamp

• Engagement metrics (views, likes, comments, shares, saves, remixes, sound uses)

• A first-pass classification (commercial, sponsored, organic, unclear)

This is where monitoring tooling matters. For example, Third Chair’s approach of measuring engagement across major social platforms in one view, plus preserving evidence at detection time, is designed specifically to reduce “triage friction” and rework.

2) Classify the use in a way that predicts leverage

Classification is not just taxonomy. It predicts what path will work:

• Paid ad: often the cleanest licensing leverage (especially if it is clearly promoting a product).

• Brand post: usually licensable, sometimes resolved quickly through brand legal or marketing ops.

• Influencer sponsored content: can require disentangling brand, agency, influencer, and whitelisting.

• Organic UGC: may be better suited for monitoring, selective outreach, or platform-specific actions depending on goals.

If you need a deeper licensing-versus-enforcement decision framework, Third Chair’s guide on Licensing vs Takedowns is a useful companion. (This article focuses on prioritizing by value, not re-litigating every decision branch.)

3) Prioritize by “highest value per unit of effort”

Rights teams often prioritize by absolute value. A better operational metric is value per hour.

Ask:

• Can we identify the counterparty in one step?

• Do we have preserved proof that would survive a dispute?

• Is the use clearly commercial?

• Can we bundle this into an account-level or campaign-level resolution?

This is also where understanding the advertiser’s incentives helps. Performance-focused teams respond to clarity and speed, because ads have flight dates and reporting cycles. If you want to see how modern advertisers structure acquisition across Meta and Google, it is helpful to understand how a digital marketing agency running Facebook and Google Ads thinks about creative iteration, budgets, and timelines.

4) Set SLAs and routes, then batch work

A scalable system uses routes (what you do next) with timelines (how fast you do it), based on score bands.

The key is batching. Instead of opening 200 separate threads, you resolve 20 high-value advertisers and clear 60 percent of meaningful value.

What data most improves prioritization accuracy

You do not need “all the data.” You need the data that changes the decision.

Evidence that survives pushback

Prioritization breaks down when you cannot support your claim later. Strong records typically include:

• Proof of use captured immediately (before deletion or edits)

• Context showing commercial intent (CTA, product page, brand handle, ad labeling where present)

• Clear mapping between the audio used and the claimed asset (high-confidence attribution)

Contacts that reach the decision maker

A high-value case can still be low-probability if it is routed to a generic inbox. Enrichment that identifies the right person, plus verified email/phone/address data, increases probability of recovery and reduces cycle time.

Cross-platform aggregation

Brands rarely run one platform. If you only see a single TikTok, you may underestimate a campaign that is also live on Instagram Reels and YouTube Shorts.

Aggregating usage and engagement across platforms lets you:

• Detect campaign breadth

• Justify commercial value with unified metrics

• Negotiate once, rather than platform-by-platform

Portfolio metrics that tell you if you are truly accelerating

If leadership asks, “Is enforcement working?” your answer should not be anecdotal. Use a small set of pipeline KPIs.

If you are not seeing improvements within one or two cycles, do not assume the strategy failed. Most teams simply need to adjust weights (for example, increasing weight on counterparty traceability or evidence strength).

Common prioritization mistakes (and how to avoid them)

Treating engagement as the only “value” signal

Virality can matter, but it is not the same as recoverability. A low-engagement paid ad from a real advertiser can outperform a million-view organic post in expected recovery.

Opening too many threads without a bundling strategy

If an advertiser has 40 uses, you usually want one negotiation and one paper trail, not 40 separate chases. Campaign-level and account-level grouping is one of the fastest ways to reduce workload.

Letting uncertainty stall the pipeline

Not every case needs perfect information upfront. A scorecard should support “progress with guardrails,” such as:

• Act immediately when commerciality and evidence are strong

• Time-box research when rights clarity is the only missing piece

• Monitor and aggregate when the use is currently low value

Putting it into practice: a 2-week pilot

If you want to implement this quickly without a re-org:

• Pick one catalog segment (for example, top 200 tracks by historical revenue).

• Run monitoring and intake, then score the first 200 to 500 detected uses.

• Work only the top band for two weeks.

• Review outcomes, then adjust weights and SLAs.

Value-based prioritization does not just make enforcement “more efficient.” It turns your recovery work into a repeatable revenue motion, one that can withstand platform changes, catalog growth, and shifting deal priorities.

When you can consistently identify the uses that matter most, preserve proof early, and reach the right counterparties quickly, you do not just handle infringement. You accelerate IP recovery.