Multiple data issues face direct marketers in 2020, starting with data privacy. While many of our U.S. clients are not affected directly by the European Union's General Data Protection Act (GDPR), U.S.-based consumer-data privacy efforts have now resulted in the California Consumer Privacy Act (CCPA), with more legislation on the horizon. Meanwhile, omnichannel data personalization has become essential for targeted response and ROI. Companies face complicated decisions when combining first-party data collection, user-level data from the big digital platforms (Google, Facebook and Amazon) as well as second- and third-party data in ways that balance consumer privacy with smart (and customer-demanded) personalization. A post in AdExchanger by Briggs Davidson, a senior manager at Deloitte Consulting, outlined some key steps for coping. He advises starting with a focus on the customer in collecting, organizing, storing, and activating data across all silos that may need to meet data-privacy compliance. When it comes to first-party data, prepare to shift marketing strategies to ensure consumers have a reason to share their data, delivering value to build trust. Davidson predicts creation of data clean rooms, or a separate analysis space for combining first-party data with platform-level customer data under strict privacy controls. Regardless, marketers will need multidisciplinary teams as well as partner collaboration. Meanwhile, prepare for hyper-personalizaton to drive marketing, according to European digital platform firm Qualifio, which found that 83% of marketers say creating personalized content is one of their biggest challenges. Why? Because personalization now requires: 1) new tools to collect and analyze first-party data for compliance with data privacy regulations like GDPR and CCPA; 2) an omnichannel purchasing journey and analytics for a single customer view; 3) incorporation of new technologies such as voice search (50% of Google searches are expected to be voice searches in 2020); and 4) meeting rising customer standards for personalized promotion and service. In fact, 70% of the customers surveyed want an immediate response to their questions or complaints, which is fueling artificial intelligence (AI) and machine learning (ML) initiatives. This means data quality will be even more key. A Forrester Consulting July 2019 report revealed that while 82% of companies place a high priority on refining data quality, more than a quarter of all marketing campaigns were hurt by substandard data in the last 12 months. Plus, a majority of marketers launching artificial intelligence (AI)/machine learning (ML) initiatives (78%) say these projects have stalled—with data quality as one of the culprits for 96%—according to a new study from Dimensional Research. CMO Kristin Hambelton, of Marketing Evolution, urges marketers in a recent Forbes magazine post to take these basic steps for improved data quality: 1) prioritize data quality and create a comprehensive initiative on data verification, collection and cleansing policies; 2) define and verify high-quality data in terms timeliness, completeness, consistency, relevance, transparency, accuracy, and representativeness; 3) organize disparate data sources with unified marketing measurement for a holistic customer view. For more, see https://www.acculist.com/personalization-and-privacy-trends-highlight-need-for-data-strategy/
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