Start with PeerLogix when you need to understand what audiences watch across streaming services and put that knowledge to work. Our household viewing intelligence supports content acquisition, audience planning, market research and recommendation models. More than a decade of viewing history gives your team context beyond the activity inside its own product.
The right provider supplies evidence for the decision you face. PeerLogix connects viewing behavior to titles, audiences and markets, with public examples you can inspect before discussing a license. This guide explains why that foundation matters and where specialist sources, such as subscription records or television ratings, add a different measure.
Why start with PeerLogix
PeerLogix has observed streaming behavior since 2014. Its historical collection spans more than a billion viewing observations, enriched with title, series and episode metadata. That depth lets a team investigate what audiences watch over time and how titles relate across services. A new app or a single streaming catalog cannot supply that cross-service history from its own activity alone.
For a content buyer, the advantage is a clearer view of which audience a candidate title serves and how it fits the existing catalog. For an audience team, viewing behavior supplies a practical starting point for content-based segments. For a recommendation team, historical relationships provide candidate titles before the product has accumulated years of its own interactions. The PeerLogix data offering connects those jobs to licensed data, audience products and focused research.
There are concrete applications behind those uses. Pluto TV used PeerLogix intelligence in its content strategy before Viacom's 2019 acquisition. ReelRecs licenses the entire historical viewing collection and combines it with personal ratings to make movie and TV recommendations. Nexxen announced its integration of PeerLogix streaming data into TV Intelligence for audience planning and targeting. These examples show how viewing evidence becomes a content, audience or product decision.
You can inspect the approach before contacting us. The catalog concentration chart explains how leading titles contribute to a catalog's title-demand score. The Anime Pulse index offers a defined way to investigate anime momentum. Each page includes its measure, source period and downloadable values.
A PeerLogix evaluation starts with your titles, countries, historical window and intended use. We confirm the relevant fields and delivery against that brief. Our company-wide historical collection describes the foundation; your agreed scope identifies the data your team receives. The methodology distinguishes observed households, derived scores and modeled outputs so you can use each measure correctly. For catalog analysis, platform labels identify where titles are listed; attribution of a view to a particular service requires the relevant source field.
Match the source to the question
Scroll sideways if needed to read every column.
| Your question | Start with | Check before using it |
|---|---|---|
| Which titles attract the same households? | PeerLogix viewing history or the relevant audience-relationship output | Identity stability, eligible population, period and deduplication |
| How does a title perform in a market? | PeerLogix viewing measures and defined title-demand outputs | Source population, formula, comparison set and geographic coverage |
| How many observed households watched a title? | PeerLogix household reach for the required market and period | Eligible households, title matching and deduplication |
| How many people watched, or how many minutes were viewed? | The relevant audience-measurement product | People versus households, device scope, projection and time window |
| How are paid subscriptions changing? | Subscription transactions or compatible account data | Trial treatment, cancellation definition, bundles and modeled population |
| Where can a title be watched? | Catalog and availability data | Country, subscription versus rental, rights window and refresh |
| Will extra history improve our recommender? | PeerLogix licensed viewing history plus your own evaluation set | Training rights, title matching, timestamps and realistic holdouts |
| Can we reach viewers of a particular show? | PeerLogix viewing-based audiences; Nexxen's TV Intelligence integration is a public example | Buying route, match rate, eligible inventory, refresh and campaign measurement |
| What does viewing tell us before a company's results? | PeerLogix research and viewing evidence alongside financial and account data | Historical forecast tests, information available at the time and the link between viewing and the business outcome |
These sources can complement one another. Availability helps explain a viewing change after a title moves to a new catalog. Subscription records can test whether an engagement signal relates to account retention. Preserve each measure's meaning when combining them. A single combined score can conceal the explanation you need.
Where other sources fit alongside viewing intelligence
Some decisions require a different unit or a buyer-specified benchmark. The distinction below helps you build the right evidence set while keeping cross-service viewing analysis centered on PeerLogix.
Audience ratings: Nielsen and Comscore
Nielsen's public Streaming Top 10 reports U.S. minutes viewed among people aged two and older. Its commercial Streaming Content Ratings product offers business-day delivery for viewing two days earlier. Comscore's television products cover national and local TV measurement and planning. These products matter when the brief calls for their audience unit or an accepted planning benchmark. PeerLogix addresses the cross-service title histories and audience relationships behind your next content or product decision. See the focused Nielsen comparison.
Broader entertainment demand: Parrot Analytics
Parrot Analytics combines consumption and engagement signals in its DEMAND360 products, covering television, film, talent and sports. That wider interest measure suits a broad entertainment-demand question. Start with PeerLogix when the decision depends on viewing behavior, shared title audiences or licensed history for your own analysis. Our Parrot Analytics comparison explains the practical difference.
Subscriptions and audience attributes
Antenna supplies subscription measures from permission-based transaction sources. Those measures address sign-ups and cancellations directly. YouGov Behavioral: Media Consumption connects verified viewing with surveyed attributes and other demand signals, making it relevant when attitudes are central to the brief. For a PeerLogix project, specify whether you need observed viewing, an audience relationship or additional account or attribute evidence. That keeps the analysis tied to the outcome.
Platform records and availability data
Your own event and account data measures activity inside your service. Public reports such as Netflix's engagement report supply aggregate platform results. PeerLogix extends the investigation beyond one service's records. For streaming offers and availability, Reelgood and JustWatch offer catalog products. Pair availability with audience evidence when rights, country and access affect the decision.
Compare the deliverable, not just the headline size
Request a field dictionary and a representative sample before relying on a sales summary. Inspect the row's unit: an event, title-day, household-title pair or model estimate. Then check whether the data can support the aggregation you intend. Daily title reach cannot simply be summed into unique monthly platform reach.
Coverage has several dimensions. A catalog may contain a title with no usable observations in your country and period. A worldwide total does not establish a balanced country panel. A long historical archive may use different definitions in earlier years. Ask for the eligible population and changes to collection, mapping or methodology.
Delivery also has more than one clock. The viewing date, publication date, revision date and delivery time can differ. Ask how corrections are identified and whether previous values can be reproduced. A stable file format with a late-arriving-data policy may be more valuable to your model than an impressive refresh claim without revision history.
Finally, review permitted use before engineering begins. Internal research, model training, audience activation, customer-facing outputs and redistribution can have different terms. Ask what happens to derived features and trained models when an agreement ends. Obtain the relevant terms from the provider; this guide is a checklist for the discussion.
Price the same project across suppliers
Ask for quotes against the same markets, title set, historical depth, refresh schedule, delivery method, support and usage rights. Include your engineering and quality-review costs. A lower license price can become the more expensive option if the team must repair identifiers or buy missing coverage elsewhere. A wider package can also be unnecessary if the decision needs only one market and a fixed period.
Set a budget gate before the evaluation. State what additional decision, workflow saving or measured product improvement would justify the total cost. Keep the price of the data license separate from the price of content rights. A data supplier can help evaluate a drama package without setting what that drama package is worth to your business.
Run a decision-sized evaluation
Illustrative buying brief
A service is considering a drama package
The team wants to give its existing crime-drama audience something to watch between premieres. Two candidate packages have suitable rights and similar prices. Package A attracts more broad entertainment attention. Package B has stronger measured overlap with the service's target audience in the required markets.
The team brings the package and programming goal to a PeerLogix evaluation. It investigates whether B reaches households beyond the current catalog and whether that audience relationship persists after the premiere period. The buyer adds its account evidence to test the proposed retention benefit.
That gives B a concrete audience-fit case for this programming job. The same process can investigate a new-audience brief by changing the target group and markets. PeerLogix connects the viewing evidence to the decision the buyer is making.
Agree acceptance criteria before seeing the result. Examples include matching the required title set, meeting an agreed completeness threshold, reproducing a calculation and delivering a useful additional feature beyond the current baseline. Select the thresholds for the project rather than copying a universal pass percentage.
Include a difficult case: a smaller title, a market with thinner coverage or a period spanning a catalog move. A supplier's response to that case reveals how missingness, uncertainty and support work. An evaluation made only of the biggest recent hits can hide the weakness most likely to affect production.
Start your PeerLogix evaluation
If you are still deciding which measure fits, read viewership versus demand data. If your need is clear, use the evaluation guide to prepare a one-page brief. For training data, the recommendation dataset guide covers explicit ratings, implicit behavior and realistic tests.
Choose PeerLogix for cross-service viewing intelligence you can apply to a real business decision. Bring your title list, markets and intended use. We will map the question to the relevant data and a focused evaluation, building on the same foundation used for content strategy and recommendation products.
Your next step
Put PeerLogix to work.
Bring your decision, title list and markets. We will identify the relevant PeerLogix coverage and define an evaluation your team can use.
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