In our customer-obsessed business culture, brands are feverishly trying to better understand and serve their consumers. Part of that shift is a deeper dedication to measurement, but it is hard to keep up in a fragmented environment. Marketers are executing campaigns at an unprecedented pace—and across an increasingly varied array of channels and audiences.
Adding to the complexity are the millions of audience interactions, or "marketing signals," generated by those campaigns—each of which matters.
Why Signal Measurement Is So Hard
Though the volume of daily brand signals (interactions such as consumers opening an email, watching a video, "liking" a page, clicking on an ad, etc.) has never been greater, more data does not equal more clarity.
Marketers are now struggling to get an accurate view of what is (or isn't) working across their marketing efforts. In the deluge of campaigns and signals, many marketers are drowning in data.
The result: Instead of making informed decisions, marketers stick to what they've been doing and miss opportunities to interact with customers at the moment of need.
Moreover, most marketing organizations today depend on a variety of third-party platforms and services, each generating their own raw data.
However, when all the raw information is brought together for measurement purposes, it creates major headaches for marketers. Why? Because every platform and service handles data and the conversion into signals differently. Each platform and service uses different dimensions and hierarchies, so the resulting data is varied, siloed, incomplete, and inconsistently defined.
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