Without the Right Tools, Marketers Can't Get Personal
Low adoption of advanced personalization tactics, technology
Personalization is hot right now, and marketers are turning to data to create a single customer viewpoint—but that doesn’t mean they’ve got it down pat. In fact, a May 2014 study by Forrester Consulting, commissioned by ExactTarget Marketing Cloud, found that, despite all the buzz about ramping up personalization efforts, just 18% of US digital marketing decision-makers considered creating a personalized customer experience across multiple digital touchpoints as one of their top three goals.
Respondents also weren’t getting down to the nitty-gritty when using personalization, with 86% agreeing that they used broad segmentation techniques to execute campaigns in individual digital channels and 83% turning to simple business rules for targeting across digital. More advanced tactics, such as real-time, self-learning analytics and machine learning and artificial intelligence algorithms, were less common for driving personalization across digital channels.
The research noted that the technologies used for personalization execution weren’t the best for real-time targeting and predictive decisioning—thus preventing marketers from implementing these more advanced tactics.
Web analytics and email marketing were the most-used targeting tools. Meanwhile, more advanced technologies—such as real-time interaction management, predictive algorithms, A/B and multivariate testing tools, and next-best offer technology—all trailed in adoption, which Forrester explained could hold back successful personalization efforts.
Results from June 2014 polling by Experian Data Quality supported the idea that technology issues presented challenges to the creation of a single customer view—an aggregated, consistent and holistic representation of the data known by an organization about its customers. Among the 24% of US data management professionals surveyed who said their companies had a single customer view, the inability to link different technologies was the top challenge, cited by 40%. Poor data quality ranked second, with 34% of respondents, and a lack of relevant technology came in a close third at 32%.
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