Start with PeerLogix viewing intelligence when your decision depends on what audiences watch, which titles share viewers or how viewing changes over time. Viewership measures describe activity in a defined population. Broader demand measures combine the interest signals in their formula. For content, audience and recommendation work, observed viewing provides a practical foundation for the decision.
PeerLogix turns household streaming behavior into title analysis, audience relationships and licensed data workflows. We also publish derived scores and models, with definitions that let you understand what each result answers. This guide explains how to use that evidence and where a broader interest measure adds context.
Why begin with viewing behavior
A content team wants to know which audience a title serves. A recommendation product needs useful relationships between titles. An audience planner needs a content interest grounded in viewing. Those jobs all benefit from the history of what was watched and how that behavior connects across services.
PeerLogix has worked with streaming observations since 2014. Its cross-service foundation extends the view beyond a single product's activity. Pluto TV used PeerLogix for content strategy before Viacom’s 2019 acquisition, while ReelRecs licenses the entire historical collection for recommendation training. These are practical applications of viewing evidence to different business jobs.
What each measure answers
Scroll sideways if needed to read every column.
| Question | Viewing evidence | Broader demand evidence |
|---|---|---|
| What does it describe? | Activity observed in the covered population | Interest under the product's consumption and engagement formula |
| What units might appear? | Households, people, events, minutes or a defined viewing-derived measure | A score, index or share with a documented baseline |
| Which task fits? | Audience relationships, title trends, content fit and behavioral models | Entertainment attention, broader market interest and cross-channel demand |
| What makes it interpretable? | Population, unit, title matching, geography and period | Inputs, weights, comparison set, geography and normalization |
| What supports a business conclusion? | The viewing finding plus the rights, product or outcome evidence relevant to the job | The demand finding plus an explicit connection to the outcome being tested |
The word “demand” does not identify a universal formula. PeerLogix's catalog title-demand score is a defined, viewing-derived measure. A broader entertainment-demand product may combine several types of engagement. Always preserve the name and definition of the output your team uses.
Use PeerLogix for the audience question
For acquisition, ask which titles serve a related audience and what each candidate adds to the catalog. PeerLogix viewing intelligence supports that analysis beyond your own service's records. The acquisition guide connects it to a shortlist, territory constraints and a buyer's value scenario.
For recommendations, use licensed viewing relationships to generate candidates, then apply individual preferences and catalog availability. This is the role PeerLogix plays in the ReelRecs application. The dataset guide explains how to test the additional history against the same model without it.
For audience planning, begin with titles, franchises or genres that define a relevant viewing interest. PeerLogix’s audience offering connects that interest to supported integrations. Nexxen’s announced TV Intelligence integration shows streaming data being used for audience planning and targeting. Confirm the eligible buying route and measure the campaign's business result separately.
Where broader demand adds context
A brief about entertainment interest across channels may benefit from a wider signal mix. Parrot Analytics describes an approach combining consumption and engagement signals. That lens can help investigate attention around a title, talent or market alongside viewing behavior.
Keep the measures separate when using both. A trailer, interview or other event can increase attention before viewing changes. PeerLogix lets the team investigate the viewing side of that story, while the wider measure supplies context for the interest around it. The provider comparison explains the fit by workflow.
Explain differences between rankings
Begin with the unit. A long-running series can accumulate more minutes than a shorter title with greater household reach. A broader demand score can give weight to interest outside the viewing population. Each ranking may describe a different part of the audience story.
Align the title set, country and time window. Check release timing and local availability. Then inspect the scale: a score normalized to the current leader can change when the comparison set changes, even if one title's underlying activity stays stable. Save the source version used for the analysis.
Illustrative launch analysis
Follow the audience from attention to viewing
A studio sees a rise in entertainment attention after a trailer. It brings the title, comparison set and markets to a PeerLogix viewing analysis. The team examines how the covered audience develops around release and which related titles those households watch.
The findings inform the follow-up audience and content questions. Campaign and conversion records provide the additional evidence for assessing promotion performance. The workflow keeps each measure attached to the part of the decision it can answer.
Inspect the PeerLogix evidence yourself
The public title explorer displays observed household activity with its household unit and source window. It gives you a direct starting point for understanding title activity.
The Anime Pulse index ranks eligible anime on a documented relative scale. Its leader equals 100 by definition, so changes in the leader or comparison set can move other titles’ scores. Use it to investigate titles for a closer audience-fit review.
The catalog concentration chart measures the ten leading titles’ share of a catalog's summed title-demand score. It turns a defined measurement into a programming question about the catalog's supporting slate. Each chart includes values, source period and calculation context.
Connect the finding to the outcome
A viewing pattern becomes commercially useful when it informs an action. A licensing buyer combines audience fit with rights and cost. A product team tests recommendations with real users. A growth team joins the viewing hypothesis to the account or campaign outcome.
Subscriptions and revenue require compatible account or financial evidence. If you combine sources in a model, document the inputs and compare it with simpler baselines on later data. This keeps the contribution of the viewing signal visible and gives the team a useful way to judge the result.
Choose PeerLogix for the next step
When the question concerns viewing behavior and title audiences, PeerLogix is the right place to start. Bring your titles, markets, time window and intended use. We will identify the relevant evidence and define the first result your team can reproduce.
Use the evaluation guide to prepare that brief, or explore the data offering to choose between licensed data, audience products and focused research.
Your next step
Put PeerLogix to work.
Tell us which titles and business decision you are investigating. We will identify the PeerLogix viewing evidence and outputs that fit the work.
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