Data-First Marketing

How To Compete and Win In the Age of Analytics

Janet Driscoll Miller, Julia Lim

• Publisher: Wiley
• Year: 2020
• ISBN:
  9781119701248
• Edition: 1
• Topic: Commerce
• Subtopic: Marketing
• Index: Marketing

Supercharge your marketing strategy with data analytics

In Data-First Marketing: How to Compete & Win in the Age of Analytics, distinguished authors Miller and Lim demystify the application of data analytics to marketing in any size business.

Digital transformation has created a widening gap between what the CEO and business expect marketing to do and what the CMO and the marketing organization actually deliver. The key to unlocking the true value of marketing is data – from actual buyer behavior to targeting info on social media platforms to marketing's own campaign metrics. Data is the next big battlefield for not just marketers, but also for the business because the judicious application of data analytics will create competitive advantage in the Age of Analytics.

Miller and Lim show marketers where to start by leveraging their decades of experience to lay out a step-by-step process to help businesses transform into data-first marketing organizations. The book includes a self-assessment which will help to place your organization on the Data-First Marketing Maturity Model and serve as a guide for which steps you might need to focus on to complete your own transformation.

Data-First Marketing: How to Compete & Win in the Age of Analytics should be used by CMOs and heads of marketing to institute a data-first approach throughout the marketing organization. Marketing staffers can pick up practical tips for incorporating data in their daily tasks using the Data-First Marketing Campaign Framework. And CEOs or anyone in the C-suite can use this book to see what is possible and then help their marketing teams to use data analytics to increase pipeline, revenue, customer loyalty – anything that drives business growth.

PART I
Data-Driven Marketing Is Not Enough

CHAPTER 1
Marketing in the Age of Analytics

PROVING MARKETING'S VALUE TO THE BUSINESS

In 2006, I (co-author Julia) met the CMO of a VoIP startup at a local technology marketing event. Founded in 2004, it was well-funded to the tune of $80 million after a couple of rounds of investment. This was clearly a competitive space, with other VoIP startups investing heavily in marketing and advertising to establish themselves, in addition to the very large and well-known phone company competitors who already “owned” the customers that the upstarts were trying to steal. The main business strategy seemed to be to acquire as many new customers as quickly as possible, but customer acquisition costs were high while revenue per customer was not, as VoIP's main competitive edge was being the low-cost alternative to traditional phone call plans, in particular for international calls.

In a discussion with the CMO, she talked about the search engine optimization (SEO) that her team was doing – optimizing for something like 15,000 keywords. To say I was speechless was probably an understatement. I had several thoughts (none of which I actually blurted out, thank goodness). Fifteen thousand keywords? How was that even possible? Were there really fifteen thousand keywords around VoIP? How many people did she have on her team, whether in-house or at an agency? This was years before Amazon came to be so dominant; with all the brands that they sell, if Amazon said they were optimizing their website for fifteen thousand keywords, I would believe them and maybe consider that number on the low side since they offer millions of products. But all this startup had was VoIP services.

Let's look at this another way. Let's say that her SEO team spent 10 hours optimizing the website for each keyword, at 10,400 work hours per person in a year, that would require dedicating nearly 15 people just to do this one task, and that doesn't include the keywords research, content development, monitoring and reporting, analysis, technical SEO tasks, and more that are all required for SEO. How could her team effectively optimize for that many keywords? The answer really is that they could not, and within the year, I was not surprised to hear that that well-funded startup shut its doors.

Volume Metrics versus Value Metrics

Beyond the disbelief in optimizing for that number of keywords (or questioning if that was even a good idea) was the realization that there is something very fundamentally different regarding how marketers look at the metrics that make up what it is that we do.

One of the data challenges many marketers must overcome is a bias for volume metrics over value metrics. Volume metrics track performance or efficiency. Value metrics, in contrast, assess the quality of an interaction or its impact on the customer relationship and on profitability. (Starita, 2019)

Marketers are seduced by volume metrics. Why wouldn't we be? They make us look good. Website traffic is up 100% year over year. We had 2 million visits to our website last month. With numbers like those, the outcome could only be good for the business, right?

But if you look more closely, you can see that volume metrics like these are only the beginning of the story. It's value metrics that can tell you more about why these numbers are important for the business. Why is traffic up so much? Is it due to specific content on the site? Is traffic up on the products and services pages or is it up on job listings? And most importantly, can I connect these traffic increases to actual pipeline or revenue for the business?

Volume metrics like website traffic are easy to get; they are the first things you see in most out-of-the-box performance reports. By contrast, value metrics require some digging, and the knowledge behind what you are doing to make sure you are digging in the right directions. Even trickier is trying to tie any kind of metric to revenue. This usually requires some level of data integration since numbers like website traffic can sit in a completely different database or platform from sales numbers, not to mention requiring some level of coding or workflow automation to track a lead from a website visit, through all the other marketing interactions they might have along the buyer's journey all the way to a possible sale. It should not be any surprise that the more “valuable” the value metric, the harder it seems to be able to achieve.

Back to the VoIP startup example. Perhaps the thinking went like this:

CMO to the CEO:	We are optimizing the website for 15,000 keywords.
Translation:	Look how much work we are doing! Look at all the work you can tell the VCs that they are getting for that big investment they made in the company. What we do is important and complex – just look at how many keywords we actively optimize to make sure we show up on page one of Google searches for every long-tail term.

Perhaps focusing on SEO and likely digital ads was the marketing strategy for rapid customer acquisition at volume. But if I were the CEO, that's not the first number I would want; the first would be how many new customers did SEO bring in?

It's very shortsighted to think that you can trot out volume metrics to show how well you are doing – in a board meeting, in a monthly agency or client meeting, or the like – and not be asked why. More and more, marketers are being asked to prove it – by CEOs, CFOs, sales, clients – and that brings up a whole new set of challenges that many marketers are failing to overcome.

We live in the Age of Analytics surrounded by data, but that doesn't mean that we have the right mindset, skills, and experience to use it in our daily marketing tasks to do more, faster, better. We know we should be pushing toward a data-driven marketing model, but what does that really mean for our marketing teams, and how can we get there? In this book, we try to answer these questions and define a data-first marketing strategy that is achievable by everyone, from large company to single-person business, and that, first and foremost, ensures you never have to settle for volume metrics to show marketing's value to the business.

DIGITAL TRANSFORMATION LEADS TO THE AGE OF ANALYTICS

Who could have known just how much our world would change in a few short decades because of technology? Since the invention of the World Wide Web in 1989, we have experienced a dot.com boom and bust, the rise and dominance of mobile, Internet video, and social media platforms that consume people's time and attention, the emergence of cloud computing and big data along with the tools needed to make them ubiquitous and meaningful, and much more.

The digital marketing transformation we focus on in this book that spawned actionable data and a whole new slew of marketing technologies started a little over a decade ago. But the roots of digital marketing can be traced to about 10–12 years before that – with the next 10 years spent shaking out which technologies would survive.

When we took a look back at the major milestones for digital marketing, we realized that we could divide the digital marketing revolution so far into three “ages” – the Age of Discovery, the Age of Reckoning and finally, where we are now, the Age of Analytics (see Figure 1.1). From the figure, you can see that when a new age starts, the previous age may still continue for a time. For example, the Age of Discovery is characterized by foundational digital marketing technologies such as the World Wide Web in 1989, but new foundational technologies are continually emerging, such as data-driven TV ad targeting, which offers the type of audience targeting previously only found in digital advertising, instead of the traditional and imprecise age and gender segmentation that is all TV was able to offer.

FIGURE 1.1 Ages of Digital Marketing.

(Thank you to Scott Brinker of chiefmartec.com and HubSpot for kindly letting us borrow the term “Age of Reckoning,” which we use a bit differently but first saw in his 2^ndGolden Age of Martech graphic.)

The Age of Discovery

The Age of Discovery (see Figure 1.2) began in 1989 with the birth of the World Wide Web, making websites as we know them today possible; the first commercial website with ads, Global Network Navigator, was created in 1993. It was in this period that the foundational and pioneering technologies for what we do in digital marketing today were launched.

FIGURE 1.2 Age of Discovery: Foundational Digital Marketing Technologies.

(Please note: We clearly could not include every company and every milestone in the timeline so we tried to show the most readily recognizable and/or “firsts.”)

In 1996, there were only 100,000 websites, compared to over 1 billion websites today. The most popular sites were early search engines and online communities like AOL and CompuServe, where people just went to check their email or chat with other subscribers. For the most part, commercial websites were online billboards and measurement still followed traditional advertising methods using “eyeballs” or impressions.

By the end of the first part of the Age of Discovery, AOL had grown to more than 23 million subscribers and along with the first blast email programs came spammers. Google launched their ubiquitous search engine. Both Eloqua (an early leader in the marketing automation space, now folded into the Oracle Marketing Cloud) and Salesforce (not the first sales CRM but certainly the 800-pound gorilla for B2B companies) also launched, pushing digital marketers to begin to understand databases and capabilities that went far beyond keeping customer contact information in Excel spreadsheets. And Google launched their highly successful AdWords platform, building on the pay-per-click model introduced by GoTo.com.

Digital Marketing Enables Precise Measurement

Digital advertising is a great example of the true difference between then and now, and traditional and digital when it comes to tracking and measurement. Measuring the effectiveness of print advertising has alway...