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ARF DASH

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ARF DASH Study Use Cases

USE CASE DESCRIPTION EXAMPLE
Assign digital devices and accounts to persons and households Media is predominantly digital, and digital devices and accounts are routinely shared, creating significant enumeration challenges. DASH respondents provide detailed, device-by-device and account-by-account usage and sharing, allowing licensees to resolve digital IDs reliably at the person or household level. An online retailer could use DASH data to develop an accurate projection of market share among young adults, many of whom “piggyback” on their parents’ or friends’ accounts.
De-duplicate HH and person-level impressions Media measurement is no longer bound by historical standards or ratings currencies. Advertisers, media companies and ratings services need to be able to reconcile HH- and person-level audience counts. An advertising technology company could use DASH data to roll up its person-level impressions into HH impressions, to enable direct comparisons across ratings schemes.
Fill gaps and control for bias in datasets Even large, census-level datasets can suffer from non-representativeness on important profiling and usage dimensions. A comprehensive, single source cross-section of US media and ecommerce consumers, DASH can serve as an independent and reliable “true north.” An advanced TV measurement service could use respondent-level DASH data to develop projections that correct for overrepresentation of older suburban households in its STB dataset.
Enrich customer databases and target-segment profiles Cookie deprecation and privacy regulations make marketers and media companies increasingly reliant on first-party and non-PII third-party data. Respondent-level DASH data can enhance consumer profiles for better research, strategy and activation. A telecom provider could use DASH data to improve volume forecasts and media targeting for a new SMB services package.
Project samples to broader universes A single-source study that covers a broad range of media and ecommerce behavior, DASH produces many useful “hooks” for projection of samples to known universes. An ecommerce panel could use DASH data to help scale up and refine sales projections for a new video game title.
Train algorithms and machine learning sequences for advanced measurement and activation The vast streams of passive data produced by digital media promise superior programmatic measurement and execution. One key to unlocking that potential is a “calibration set” like DASH. DASH contains rich signals of behavior on every device in the household and by whom. A developer of passive media measurement technology could use DASH data to improve the accuracy and interoperability of a core machine learning scheme.
Enhance identity graphs The DASH survey covers individual and household device ownership and usage, yielding its own identity graph among 10,000 representative respondents. This graph can serve as a seed to enhance much larger graphs and to verify the distribution of profiles and segments. An identity company could use the DASH graph to model persons’ usage by time of day across a set of household device bundles.
Contextualize digital media usage Strategists and product developers need to understand how their services fit into the “big picture.” DASH respondents complete a comprehensive survey that covers most aspects of their digital media usage. The data can be analyzed at an aggregated or respondent level, depending on the needs of the licensee. A streaming media service could take advantage of the holistic view the DASH data provides to identify and develop strategies for a high-potential, new prospect segment.

 

To learn more, contact Paul Donato, ARF Chief Research Officer, or Jim Meyer at DASH@thearf.org or by clicking the link below. by clicking the link below.

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