Privacy
Many consumers are concerned about marketers’ access to their data (as shown in ARF studies with a new report being released soon). Read more »
Many consumers are concerned about marketers’ access to their data (as shown in ARF studies with a new report being released soon). Read more »
Like “Better Measurement” issues, since the early days of marketing, this has been a topic that always requires a fresh look. Given the fast changes in all relevant factors, this is true now more than ever.
The intention behind recent privacy regulations is to protect consumers from unauthorized use of their data. However, this Marketing Research Institute (MSI) working paper finds unintended consequences that are not good for the consumer or the marketplace. Researchers found such regulations reduce satisfaction with search results and increase search costs. The personalization in products and services is thus degraded, as many smaller and midsize firms are no longer able to provide the level of efficiency and personalization they once could. Larger firms, however, benefit from increased search activity which leads to increased purchase activity. As a result, such regulation leads to unintended market concentration.
Member Only AccessThe Attribution & Analytics Accelerator returned for its eighth year as the only event focused exclusively on attribution, marketing mix models, in-market testing and the science of marketing performance measurement. The boldest and brightest minds took the stage to share their latest innovations and case studies. Modelers, marketers, researchers and data scientists gathered in NYC to quicken the pace of innovation, fortify the science and galvanize the industry toward best practices and improved solutions. Content is available to event attendees and ARF members.
Member Only AccessIn addition to the insights in the recently released Attention Measurement Validation Initiative Phase 1 Report, there will be several new findings from other ARF, CIMM, and MSI projects. Here is a sample:
Modern digital privacy laws, while well-intentioned, carry significant unintended consequences. On September 12, industry experts joined us for a virtual Town Hall and discussed the unintended consequences of privacy regulations on marketers, consumers, the industry and society—as well as shared actionable strategies that can be used to mitigate their impacts.
On July 26, measurement practitioners discussed how to adapt to this new era of privacy with tools for measuring ad performance effectiveness. Panelists explored new considerations for existing methods, such as marketing mix modeling (MMMs) and multi-touch attribution (MTAs), and discussed the pros and cons of various privacy enhancing technologies (PETs), including multi-party computation, clean rooms, and more.
Buying online display ads in bulk through online exchanges makes it difficult to ascertain the effectiveness of such ads, a situation that’s less than ideal. This is especially true for new websites. One proposed solution is to pool data across advertisers and publishers. Doing so while running matching simulations can substantially improve the welfare of such ads for advertisers, publishers and networks, too.
Member Only AccessThe practice of marketing mixed modeling (MMM) is increasing, research finds, partially because of the implementation of privacy restrictions. Today, finding appropriate providers to optimize marketing investments remains challenging. This was the impetus behind the Marketing Science Institute (MSI)’s Blue Ribbon Report on MMM. This free preview of the full white paper outlines what best practices to employ in a rapidly changing landscape. It identifies challenges for MMM veterans and ways to meet them. It also introduces executives to the opportunities that exist when introducing MMM into their firm. The report preview provides a brief overview of the top-level findings found in the full report, which is only available to MSI members.
Member Only AccessThis new MSI report explores the challenges of modern MMM, MMM use-cases and recommendations for successful MMM implementation.