Set-Top Box Presentation

Purpose of the Study

• Provide holistic view of STB data from all aspects and users
• Understand challenges and opportunities
• Facilitate industry roadmap for a variety of potential STB data products – both for measurement and/or to support advanced advertising capabilities

Process

• Confidential interviews with media executives from all aspects of the STB landscape
• Across various job responsibilities
• Questions tailored by type of company
• All responses aggregated and anonymized
• Honest and detailed feedback
• Great support and wide participation

Company Types

• Data Originators (Multi-Channel Video Programming Distributors)
• Data Processors
• Software Vendors
• Programmers, Networks, Content Providers, Local Station Groups
• Agencies and Advertisers
• Hardware Manufacturers, Research Policy Accreditation Organizations

Interviewed 58 separate companies
and 85 policy and decision makers

	Companies	Interviewees
MVPDs	10	14
Data Processors	11	17
Software Vendors	11	16
Networks, Programmers	12	15
Agencies, Advertisers	14	23
	58	85

Questions Asked

• Aspects of optimal media measurement
• Challenges and opportunities of STB data
• Uses and capabilities of the data
• Long and short term goals for the data
• Privacy issues
• How to create representative samples
• Priorities and next steps

Questions varied slightly by Category of Company

Topline Results

STB Data Provides Value and New Insights and is a Game Changer for the TV Industry

No one company or source offers a full overview of the STB data industry. This results in disinformation because of conflicting agendas and business models.

Common Themes

• Frustration on progress of STB data rollout
• Need for edit rules and standards
• Need for representative, project-able samples – local and national
• Calculation of data value
• Need to apply value of data to respective business models
• Need for transparency and education

Divergent Attitudes

Depending upon the specific company's business model -

• Implementation runs gamut from ambivalent to enthusiastic.
• Some feel powerless to advance data. Others are deeply involved in the early stages to guide the process.
• What is a challenge or an advantage to one company can be a non-issue to another.
• Priorities vary, causing delays and giving appearance of stagnation.

Progress

• MRC initiative
• Local measurement and long tail networks
• Database matching for segmentation, ROI analyses and advanced advertising

The STB industry abounds in activity and creative innovation.

What's missing?

Evolving Landscape

• Technological changes on the horizon such as measurement apps or new boxes that could soon make STB data obsolete and irrelevant.
• But some of these technological advances could help address data shortcomings:
  • Set-Off/Set-On
  • Identification of Demographics

Industry Continuum

Overall Attitudes on STB Data

Wide Ranges of Opinion Across Categories and Within Categories

• Nielsen as a benchmark for STB data?
• Lack of demographics?
• Local market measurement?
• Data vetting and accreditation?
• Measurement of the long tail and niche networks?
• Development of a currency from STB data or ancillary value-added measurements?

Data Processors and Software Vendors

What They Said...

• Optimistic about the data
• Creating a viable business in processing, marketing and selling the data
• A great desire for more data

What it Means...

• More data improves their competitive position
• Highly competitive environment inhibits cooperation for standardization
• Creative applications of the data can yield revenue

Trade Organizations

What They Said...

• Enthusiastic about STB data

What it Means...

• STB data challenges can be overcome through industry initiatives
• Creative solutions are welcomed

Data Originators (MVPDs)

What They Said...

• Taking a careful and slow approach
• Citing privacy as one reason for caution
• Business model is based on subscriptions, not data
• Data used internally for customer satisfaction and carriage negotiations
• "Early adopter" MVPDs are using the data for subscriber and ad models

What it Means...

• Demonstrate data value to justify placing more resources against it

Agencies and Advertisers

What They Said...

• Wait and see approach … but there are outliers
• Three groups: Early, Middle and Late Adopters
• STB data must prove its value to advance the business and justify the added cost

What it Means...

• Need for transparency

Networks and Programmers

What They Said...

• Most pessimistic
• Some expressed frustration and impatience
• Data issues
• Some had no long tail networks that would benefit
• Smaller networks who initially used STB data have shifted to Nielsen
• Over-the-air or in downscale zip codes with low digital cable penetration

What it Means...

• Need for greater transparency as well as standards and project-ability

Challenges & Solutions

• Technical
• Privacy
• Data Standards
• Representative Samples
• Demographics
• Posting
• Business Models
• Fear of the Unknown

Strengths of STB Data

• Data Granularity, Larger Sample
• Improvement of Local Measurement
• No Minimum Sample
• Measurement of Long Tail and Unmeasured Networks
• More Stable Measurement of Niche Consumer Groups
• Larger Local Market Sub-Samples
• Ability to Measure Out-of-Home
• Ability to Measure Trick Play and DVR Use

Strengths of STB Data

• Ability to Measure VOD and ITV
• Potentially Lower Measurement Cost
• Passive Data Collection
• Potential to Link Cross-Platform Behavior
• Data Matching and Appending
• Addressable Advertising
• ommercials and Commercial Pod Measurement
• New Insights from Click Stream Data

Industry Next Steps: Overview

• Educate the Industry
• Transparency and Dialogue
• Common Language
• Define Foundational Data Standards
• Develop Guidelines for Project-able, Representative National and Local Samples
• Accreditation via the MRC

Industry Next Steps: Details

• Data delivery guarantees
• Find a solution for demographics
• As-run logs to match commercial occurrence and programs
• Inclusion of STB data within planning and buying systems
• Improve append-ability of outside datasets
• Model for missing elements such as OTA and co-viewing
• Addition of DVR usage and out of home
• Cross-Platform measurement

CIMM Roadmap POV

1. Local measurement
2. Granular analytics tool
3. National measurement currency
4. Database matching and advanced advertising

Questions?

Link to whitepaper:
http://www.cimm-us.org/whitepaper.htm

Link to presentation:
http://www.cimm-us.org/STBpresentation.htm