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Cloud Marketing Analytics Snowflake Special Edition

by David Baum

These materials are © 2021 John Wiley & Sons, Inc. Any dissemination, distribution, or unauthorized use is strictly prohibited.

Cloud Marketing Analytics For Dummies®, Snowflake Special Edition Published by John Wiley & Sons, Inc. 111 River St. Hoboken, NJ 07030-5774

www.wiley.com Copyright © 2021 by John Wiley & Sons, Inc., Hoboken, New Jersey No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/ permissions. Trademarks: Wiley, For Dummies, the Dummies Man logo, Dummies.com, and related trade dress are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries, and may not be used without written permission. Snowflake and the Snowflake logo are trademarks or registered trademarks of Snowflake Inc. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc., is not associated with any product or vendor mentioned in this book.

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Publisher’s Acknowledgments We’re proud of this book and of the people who worked on it. Some of the people who helped bring this book to market include the following: Development Editor: Brian Walls Project Manager: Martin V.Minner Senior Managing Editor: Rev Mengle Acquisitions Editor: Ashley Coffey Business Development Representative: William Hull

Production Editor: Mohammed Zafar Ali Snowflake Contributors Team: Ganesh Subramanian, Vincent Morello, Rachel Dell, William Wash, Tim Fletcher, Mike Klaczynski, Matthew Fischer, Jack Yusko, Leslie Steere

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Table of Contents INTRODUCTION ............................................................................................... 1 About This Book ................................................................................... 2 Icons Used in This Book....................................................................... 2 Beyond the Book .................................................................................. 2 CHAPTER1:

Understanding Marketing Analytics............................ 3 Defining Marketing Analytics .............................................................. 3 Tracing the Evolution of Marketing .................................................... 4 Understanding the Value of Data ....................................................... 6 Grouping customers and prospects ............................................. 7 Understanding marketing attribution .......................................... 8 Setting Analytic Objectives .................................................................. 9 Identifying Roles and Responsibilities ............................................. 10 Enlisting IT Expertise .......................................................................... 11

CHAPTER2:

Gathering Data for Marketing Analytics ................ 13 Gathering Customer Data ................................................................. 13 Expanding Customer Data Sets ........................................................ 15 Properly acquiring second- and third-party data ..................... 17 Gaining visibility into partner channels...................................... 17 Gathering Product Data..................................................................... 18 Enforcing Data Quality ....................................................................... 19 Gathering Company Data.................................................................. 19 Determining Where to Store Your Data .......................................... 20 Dealing with Streaming Data ............................................................ 20 Leveraging the Power and Reach of the Cloud .............................. 21

CHAPTER3:

Ascending the Marketing Analytics Maturity Curve ............................................................................ 23 Starting the Journey: Customer 360................................................. 23 Pursuing ROI Analysis ........................................................................ 24 Optimizing Campaigns....................................................................... 26 Getting to “really” know customers ............................................ 27 Getting personal without being creepy...................................... 29 Pursuing Advanced Analytics ............................................................ 30

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CHAPTER4:

Sizing Up Data Challenges .................................................. 31 Sizing Up the Problem ....................................................................... 31 Dealing with rising data volumes ................................................ 33 Uniting fragmented data.............................................................. 34 Enforcing Data Quality and Consistency ......................................... 36 Addressing Data Privacy and Regulatory Concerns ....................... 37 Simplifying Audits with Consistent Policies ..................................... 39

CHAPTER5:

Overcoming Challenges with Technology ............. 41 Integrating Essential Data Sources .................................................. 41 Engineering Data Pipelines ............................................................... 42 Bringing in First-, Second-, and Third-Party Data ........................... 43 Keying and Matching Data ................................................................ 44 Centrally Storing Data ........................................................................ 45 Activating Data for Analysis............................................................... 47 Tapping into Marketplaces and Exchanges .................................... 48

CHAPTER6:

Mapping the Marketing Analytics Tech Stack........................................................................................ 49 Defining the MarTech Stack .............................................................. 49 Extending Your Analytic Horizons .................................................... 51 Using BI tools................................................................................. 51 Graduating to data science.......................................................... 52 Using CDPs and DMPs ....................................................................... 53 Extending Your Reach with a Cloud Data Platform........................ 54 Summing Up the Value of a Cloud Data Platform .......................... 55 What to Look for in a Cloud Data Platform ..................................... 57

CHAPTER7:

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Seven Steps to Get YouStarted ..................................... 59

Cloud Marketing Analytics For Dummies, Snowflake Special Edition

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Introduction

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oday’s consumers are in control. They choose how, when, and where they wish to engage your brand. They select a blend of channels they want to use, whether it’s email or web, mobile or social, telephone or chat. Along the way, they expect you to know their interests and preferences and to use this knowledge to provide consistent, timely, relevant, and personalized experiences. Each consumer engagement leaves behind a trail of data — clues about a particular encounter and about how that individual might behave in the future. Analyzing these interactions helps business-to-business (B2B) and business-to-consumer (B2C) marketers make quantifiable assessments about what consumers will respond to and what they will ignore, as well as when to make real-time adjustments to their marketing campaigns.

Data about customers, prospects, and campaigns builds up quickly: in customer relationship management (CRM) systems, in marketing automation systems, and in dozens of specialized marketing apps that can comprise your marketing technology (MarTech) stack. Much of this data gets sequestered in individual “silos.” Hence, it’s difficult to unify and integrate, either in a customer data platform (CDP) or in other common data repositories. And yet properly acquiring, managing, and analyzing data is the supreme task facing marketers as they seek to enrich their customer profiles and refine their marketing strategies. To succeed with marketing analytics, you must access, centralize, and normalize all types of data and make it actionable for business intelligence (BI) and data science initiatives. Acquiring consistent, accurate data is the key to segmenting customers, creating specialized content, formulating unique offers, and measuring the return on your marketing investments. That’s what this book is about.

Introduction

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About This Book You will find this book important if you want to:

»

Supply your marketing team with simple but powerful analytics, without the complexity of managing a traditional data warehouse, data lake, or other type of database management system

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Efficiently acquire and share first-party, second-party, and third-party data to maximize the impact of your campaigns without having to copy or move data

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Help your team use its data to progress up the marketing analytics maturity curve, from customer 360 marketing, to ROI analysis, to campaign optimization, to data science

Icons Used in This Book Throughout this book, the following icons highlight tips, important points to remember, and more: Advice about how to maximize marketing analytics in your organization

Concepts worth remembering as you immerse yourself in understanding today’s analytic platforms, processes, and tools

Current stories about organizations using analytics to improve their businesses in innovative ways

Beyond the Book If you like what you read in this book, visit www.snowflake.com to learn more about analytic solutions from Snowflake and its partners, order a free trial of Snowflake’s platform, view webinars, or get in touch with a member of the Snowflake team.

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IN THIS CHAPTER

» Defining key analytic concepts » Tracing the evolution of marketing » Understanding the value of data » Defining analytic objectives » Building your marketing team

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Chapter

Understanding Marketing Analytics

T

he adage, “I know half of my marketing dollars are going to waste. The trouble is, I don’t know which half,” describes the scatter-shot approach of mass marketing that characterized the discipline for decades. Marketers can no longer make that excuse, however. Marketing is expensive, and management wants proof that it works. The chief marketing officer (CMO) and other senior executives expect marketers to roll out creative campaigns that generate positive results and explain how well each campaign works and why. CMOs insist on accurate measurements that demonstrate value to the organization.

Defining Marketing Analytics Customers and prospects generate data when they click your offers, interact with your websites, and respond to your campaigns. All B2C marketing departments collect this data to varying degrees, both online and in-store via beacons, point-of-sale (PoS) transactions, and other data gathering and customer engagement methods. B2B marketers also gather data from many digital touchpoints. They generally don’t meet customers in a store, but

CHAPTER 1 Understanding Marketing Analytics

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they still engage in face-to-face interactions via webinars, conferences, and other events. Marketing professionals use analytics to measure the impact of their offers and campaigns through each channel and customer touchpoint. Marketing analytics provides a consistent framework for measuring each initiative in terms of its strategic returns, overall value, and payback period.

Tracing the Evolution of Marketing For both B2B and B2C scenarios, your data should clearly tell a story of how marketing impacts revenue. Unfortunately, many of the traditional approaches to marketing don’t adequately address today’s hyperconnected customers and the growing number of digital and in-person channels they use. The marketing world has shifted from mass-media outreach to personalized engagement. Rather than blanketing an entire market with a general message, marketers now routinely home in on demographic subgroups— such as college-age males or retired seniors — and target them with offers designed just for them. Over time, as marketers collect more data, they refine their messages to these subgroups. Taking the relationship further, personalized marketing, sometimes called one-to-one (or 1:1) marketing, involves getting to know your customers as individuals, establishing mechanisms for interacting with them, and customizing your business for them. Each new campaign seeks to deliver relevant messages at the right time, on the right channel, and to the right people to help the organization achieve its business goals (see Figure1-1). The Internet has caused a decisive shift from vendor-initiated interactions (such as TV commercials that push messages to prospects) to customer-initiated interactions (such as when customers decide to follow your brand on Instagram). Turning the tables from push to pull has fundamentally altered the nature of marketing. For example, marketers use search engine optimization (SEO) techniques to target people searching on specific keywords on Google, Yahoo!, Bing, and other search engines— often

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Cloud Marketing Analytics For Dummies, Snowflake Special Edition

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in conjunction with “pay per click” advertising campaigns on those same search engine sites. They also run ads on social media networks to target individuals based on known hobbies, shopping patterns, and interests.

FIGURE1-1: The path to personalized marketing.

Compare these precision marketing tactics to the mass-market approach of yesteryear, when marketing consisted of generalized display ads in magazines and newspapers, along with expensive TV commercials geared for large audiences. While mass marketing is still a viable way to build awareness, establish a brand, or attach your company to a larger trend, it has slipped into the background with the advent of these newer, more precise forms of outreach. According to CNBC’s article “Super Bowl draws lowest TV audience in more than a decade, early data show,” Nielsen ratings found that 98.2 million people watched the Super Bowl in 2019, and advertisers paid an average of $5.25 million for each 30-second spot. By contrast, advertisers spent nearly $135 billion on Google Ads in 2019, according to Statistica’s report “Advertising revenue of Google from 2001 to 2019.” Google’s economic impact reports claim that businesses obtain an average return of eight dollars for every one dollar invested in these campaigns. As TV viewership dwindles, marketers must acknowledge that consumer eyeballs are looking elsewhere and that sending targeted offers to select groups of qualified prospects is much more cost-effective. Mass marketing campaigns remain an important aspect of building your brand, but more targeted forms of outreach should supplement them. Back up your general awareness-building campaigns by intelligently segmenting your customers and delivering personalized messaging and offers to each of those customer segments that address their needs and interests.

CHAPTER 1 Understanding Marketing Analytics

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Understanding the Value of Data Every tool marketers use to communicate with consumers generates data. However, to be truly data-driven, a marketing team must base its strategies on the analysis of large, diverse data sets that combine information from multiple sources, applications, and tools. This allows marketers to determine which creative assets drive the most engagement, which creative materials result in the best conversion rates, and which channels yield the greatest results from highly targeted audiences. Each initiative builds on the ones that precede it as you gather data about opens, click-throughs, responses, and sales. Analyzing this data helps you refine your campaigns, gather leads, and turn prospects into customers. Gradually, you amass more and more information about the people you are trying to engage as you segment ...