Name: Digital Marketing Analytics
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Publisher	Pearson Education
Language	English
Book type	Paperback
Utgiven	2018-07-30
Edition	2
Pages	272
ISBN	9780789759603
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Description

Distill Maximum Value from Your Digital Data! Do It Now!

Why hasn’t all that data delivered a whopping competitive advantage? Because you’ve barely begun to use it, that’s why! Good news: neither have your competitors. It’s hard! But digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you. Chuck Hemann and Ken Burbary will help you chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results! Scope it out, pick your tools, learn to listen, get the metrics right, and then distill your digital data for maximum value for everything from R&D to customer service to social media marketing!

Prioritize—because you can’t measure and analyze everything
Use analysis to craft experiences that profoundly reflect each customer’s needs, expectations, and behaviors
Measure real digital media ROI: sales, leads, and customer satisfaction
Track the performance of all paid, earned, and owned digital channels
Leverage digital data way beyond PR and marketing: for strategic planning, product development, and HR
Start optimizing digital content in real time
Implement advanced tools, processes, and algorithms for accurately measuring influence
Make the most of surveys, focus groups, and offline research synergies
Focus new marketing investments where they’ll deliver the most value • Identify and understand your most important audiences across the digital ecosystem

“Chuck and Ken lead marketers clearly and efficiently through the minefield of digital marketing measurement. And they do so with a lightness of touch and absence of jargon so rare in this overhyped, much-misunderstood ecosystem.”

—Sam Knowles, Founder & MD of Insight Agents; author of Narrative by Numbers: How to Tell Powerful & Purposeful Stories with Data

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