Implementing a Big Data Plan (Sometimes by Thinking Small)

Big data is an intimidating concept. It sounds hard. It sounds overwhelming. It sounds expensive.

Data has always been with us. The difference now is that is it more accessible and more immediate. Data, lots of it, is available in real time. 

“It’s been here for a very long time,” Vinny Sosa, director of web intelligence and optimization at Citrix Systems, marketers of GoToMeeting, said of big data. “Now it just has a name.”

The key to getting big data right at your company is not to get bogged down with the concept of big data. Start by identifying the needs of your customers and your business. Also, think small—focus on the parts of data you think can change your business for the better, not on the entirety of the data available to you. Keep in mind the old proverb: The journey of a thousand miles begins with a single step. 

Note that leveraging data is not reserved for big companies. Big companies do have advantages, such as deep pockets. But small companies have advantages, too. For instance, they are nimble and are often not tied down by legacy systems and data siloed in various corners of the company.

It’s instructive to examine how George Stenitzer approached bringing more data and analytics into his marketing department when he was the vice president of communications at Tellabs back in 2010. Stenitzer focused first on what he wanted. He knew Tellabs, a telecommunications equipment company, had been investing a significant amount in its website. Not only was Tellabs investing time and money into building the website and populating it with content, but it was also investing in search engine optimization, e-mail promotion, display advertising, and other tactics to drive prospects to the site.

Stenitzer, who now runs his own marketing consulting firm, Crystal Clear Communications, didn’t believe that Tellabs was getting its money’s worth from its website. He wanted more “soft conversions” from site visitors; he defined soft conversions as reading a blog post, watching a video, or interacting with certain other content on the site without having to supply an e-mail address. He also, of course, wanted more “hard conversions,” where prospects shared their e-mail addresses to download white papers and other similar content.

 In 2010, Tellabs was generating soft conversions at about a 10 percent rate, meaning that one out of every 10 visitors to the site interacted with a piece of Tellabs content. Stenitzer wanted to improve that rate. At the same time, he wanted to demonstrate marketing’s contribution to revenue. To accomplish these goals, both of which required collecting and analyzing more data, he took three basic steps:

First, he revamped Tellabs.com to encourage more content interaction.

Next, he invested in new analytics tools from IBM and marketing automation technology from marketing automation firm Marketo.

And finally, he used these software tools both to measure his content efforts and to nurture prospects in the Tellabs e-mail database toward becoming genuine leads and ultimately customers. 

In revamping Tellabs.com, Stenitzer identified that four basic kinds of content were responsible for the company’s soft conversions: blogs, videos, ungated white papers, and articles from Tellabs’ custom publication, Insight.

He also sorted Tellabs’ content into four tiers, based on the amount of time the content demanded of prospects. The first tier asked for no more than seven seconds of a prospect’s time. This content included headlines on the Tellabs.com home page that pointed readers to other content on the site. This approach put the path to content front and center on the company website. In addition to these headlines on the website, these seven-second bursts of content also comprised tweets and Facebook and LinkedIn posts that drove prospects to Tellabs content. 

The second content tier asked for two minutes of a prospect’s time. This tier included blog posts and web pages, each about 400 words long, and short web videos, also typically about two minutes in length. The third tier asked for five minutes of time and consisted of longer videos and articles. The last tier consisted of detailed white papers that required 20 minutes or more from a prospect.

“If we can get you with that seven seconds of attention, the idea is I want to ladder you up to two minutes,” Stenitzer said.

Stenitzer organized the entire website around this concept of laddering up content. “I think the main idea that we had when we rebuilt the Tellabs.com website was: how do we make the customer’s path to conversion easy?” Stenitzer said. “We rewrote it from scratch, and we had in mind that what we wanted to do was get customers to go along the path with us, starting with a soft conversion.”

Focusing on how to ease the customer’s path to conversion, Stenitzer and his team relentlessly analyzed data delivered by the IBM analytics tool that indicated what was being read and what pathways prospects were taking—or not taking—to get there. 

One pathway to enticing readers into deeper engagement was to list links to related content on the right-hand side of Tellabs.com web pages. But the data showed that prospects were not clicking on a text link to “PDF Resources.” To make these PDFs more noticeable, Stenitzer placed a red button on the right-hand side that read “PDF Resources.”

“Until that big red button got planted in the right column, nobody even noticed [the PDF link],” Stenitzer said. “One of the first things we saw with our Net Analytics from IBM was that nobody went there. We had all this great content that people were missing, and the red button helped change that.”

The IBM analytics helped Tellabs determine which content was performing best. At regular meetings, members of the marketing staff would discuss what the analytics indicated. “It’s like, ‘This is working; let’s do more of it,’” Stenitzer said. “‘This isn’t working; let’s get rid of it.’ And that’s what the data tells you.”

The analytics also demonstrated the value of white papers, which require at least a 20-minute commitment to read from start to finish. “If I take my top five white papers, I actually get more hits on them than on the top five videos or on the top five blogs or the top five Insight articles,” Stenitzer said. “So, even though the white papers are long-form content, when you get a serious buyer who’s going down the path toward a purchase, that white paper is really important, and they pay a lot of attention to it. While I put emphasis on the seven seconds, two minutes, five minutes, and then 20 minutes, one of the surprises that we got from the analytics is 20 minutes is where they really want to go.”

But did all of this effort pay off? Stenitzer said the soft conversion data proves it did. From the time the website was revamped with a data-driven approach focused on pointing prospects to content, soft conversions increased every year. “Back in 2010, our soft conversions were running about 10 percent,” Stenitzer said. “By 2011, they were 20 percent. By 2012, they were 30 percent. In 2013, they were right around 40 percent, and in 2014, they hit 46 percent.”

But getting more content read by more prospects isn’t worth much if it doesn’t lead to more marketing-sourced revenue. So at the same time he was revamping Tellabs.com, Stenitzer was also strengthening a data-driven demand generation team that used Marketo marketing automation software.

As part of this effort, Tellabs hired a demand generation manager to optimize usage of Marketo software. Many Tellabs white papers were gated content, meaning that a prospect had to provide an e-mail address and other information in exchange for downloading the white paper. At first, Tellabs required 13 fields on the forms that prospects had to fill out to download the white paper. Data showed that five fields enticed more prospects to share their e-mail addresses. 

With the e-mail addresses, Tellabs nurtured these leads via the Marketo system. Tellabs tracked the behavior of the leads. With Marketo, Stenitzer said, “We can see your footprints on the site. And if you hit a lot of content in a short period of time, the algorithm automatically generates an e-mail to use and tells us, ‘Here’s a marketing qualified lead,’ which we then hand off to sales.”

Using the e-mail addresses in Marketo, Stenitzer was able to track whether those leads turned into actual revenue after they were handed off to sales. The tracking showed, beyond doubt, that marketing helped drive sales. Stenitzer said that between 2010 and 2012, marketing tripled the revenue that it had a hand in generating. He said the figure may be even higher, because deals can take 18 months or more to close in the telecom equipment business.

Tellabs also discovered other details from using data to tie together content, leads, and revenue. “We learned that almost all of our marketing-sourced sales came from North America and Europe,” Stenitzer said. “We learned that marketing was much more successful in selling our optical product than in selling our mobile product. We were more well-known for our mobile product in the first place and probably less well-known for our optical product—but we could move the needle more in optical.”

He added that marketing helped more with customers outside of Tellabs’ traditional telecom market. “A lot of the sales leads created through our content and demand gen were coming from the enterprise,” Stenitzer said. “They were coming from electrical utilities. They were coming from local governments, like county governments. There wasn’t a salesforce dedicated to these kinds of customers.” 

The Tellabs story shows that large corporations (Tellabs had revenue of $1.1 billion in 2013, the year it was acquired by Marlin Equity Partners) can implement data-driven marketing principles. But many observers believe it’s harder for big companies to embrace big data, because they have so many legacy systems. Marketers can be overwhelmed by the data contained in different silos and the prospect of somehow merging all of this data into a single system. The cost, in time and money, of unraveling what Lisa Arthur, CMO of Teradata Marketing Applications, a marketer of integrated marketing management solutions, calls “the big data hairball” can be daunting. 

At smaller companies, the process of becoming a data-driven business can be easier. In the big data age, being nimble can also give smaller companies an advantage.

“The small to middle-sized companies are in the best position to do so, because they have a single unified marketing team,” said Chris Robison, general manager of the direct business at Poppin, an office supplies e-commerce start-up. He was previously senior director of product and strategy at marketing technology vendor Adobe Systems.

“You can really be David to the big companies’ Goliath by leveraging data effectively,” Brian Kardon, former CMO of Lattice Engines, and now CMO at Fuze said. “You can beat much bigger, well-funded companies if you’re able to harness that data. It’s a way to get an amplifier effect to do amazing things. Big data could be the key for a lot of smaller companies, giving them a much better return on their marketing dollar. It’s a great leveler.”

If embracing big data is easier at smaller companies, at start-ups the process can be easier still. Bill Macaitis, the former CMO at Zendesk, which markets cloud-based customer service software, had the luxury of building a data-driven marketing team essentially from scratch when he joined the company in 2012. (Macaitis is now the CMO of Slack Technologies).

Macaitis started working in digital marketing after he graduated from the University of Illinois. Working in management positions at Salesforce.com, Fox Interactive Media, IGN Entertainment, and elsewhere, he has witnessed digital marketing evolve at an ever quickening pace as marketers have seized the power of websites, search, social, and mobile. 

But even as marketers have taken advantage of these new digital tools, they have grappled with how to continue to make the most of embedded legacy marketing tactics, such as media buying, brochures, and trade shows. So Macaitis was intrigued in 2012 when he took the CMO job at Zendesk, because the job would offer an unusual opportunity to start a new digital marketing organization from the ground up—without any legacy silos. “The primary reason I came there was they didn’t really have a big marketing organization,” he said. “It’s really kind of a rare chance to build a marketing org almost from scratch. It’s a new age marketing organization that doesn’t have any traditional silos. . . . I came to build the most advanced, sophisticated B2B marketing team ever.”

In building the organization he envisioned, Macaitis had four words as his foundation: data driven, customer focused. “I’m a 100 percent data-driven, customer-focused believer,” he said. “I think those four words really sum up the new paradigm.”

When creating his marketing department at Zendesk, Macaitis focused on two key elements: content marketing and analytics. “We made a couple of big investments,” he said. “One of the first ones was we created a big content team. We hired six full-time content people. All they do is create content left and right.”

On the face of it, content seems unrelated to data-driven marketing. But Macaitis says that content is crucial to understanding how prospects are self-educating as they move through the buyer’s journey, most of which now takes place online. Analyzing individual content pieces can provide insight into which ones are the most influential in driving prospects through the marketing funnel. “Which ones drove the most leads?” Macaitis asks his team about the content it creates. “Which ones actually drove the most pipeline? Which ones helped accelerate the deal velocity? Which ones allowed us to get the giant, big deal that made our quarter? There are interesting lessons in it, and it’s not an arbitrary process or a philosophical call.” 

In addition to building the content team, Macaitis hired a large analytics crew. This group is in charge of constructing Zendesk’s marketing stack, which now includes more than 30 different kinds of software such as Optimizely and Convertro. “They are in charge of all the attribution, the reporting, a lot of the insight,” he said. “They are in charge of training the rest of the team to use the tools. They make sure we are leveraging all the data out there. We built out a pretty sophisticated marketing technology stack.”

The ability to properly attribute what marketing tactics are accelerating prospects through the funnel is vital. The attribution software that Zendesk uses, Convertro, is the foundation of the stack, Macaitis said. This software, combined with the rest of Zendesk’s marketing stack, enables the company to track the impact of marketing on prospects long before they ever share an e-mail address. 

“Attribution, especially here in B2B marketing, is so important,” Macaitis said, “because people don’t really understand how much of that research comes in before a person arrives at your site. . . . You come across prospects 10, 20, 30 times before they ever become a lead. Marketers say, ‘Oh, it’s a long sales cycle. From the minute prospects become a lead until we close them, it’s three months.’ But you know there’s another three months before that, where the prospect is anonymously researching your company and seeing you again and again. . . . We have always thought that the average time someone spent interacting with a brand before they formally announce themselves was pretty long. Attribution actually confirms it. We saw these 10, 20, 30 clickstreams. People interacting with a display ad or seeing a display, display, display. Then social paid, then social organic. And branded, nonbranded.”

Macaitis also uses the Net Promoter Score (NPS), which is another aspect of Zendesk’s data-driven, customer-focused marketing approach. NPS asks customers the likelihood, on a scale of 0 to 10, of whether they would recommend the company to their friends or colleagues. If the customer answers 9 or 10, the customer is a promoter. Those who answer 7 or 8 are considered neutral. An answer of 6 or below is considered a detractor. 

In its use of NPS, Zendesk digs a little deeper, asking customers what attributes of the company influenced their likelihood to recommend the company. Macaitis said the NPS survey has helped Zendesk by demonstrating the importance of customer service, which has helped the company in marketing its customer service software.

“We classified the top five reasons they recommend us, and the number two reason was: ‘I had a great experience with one of your support people, and because of that, I am much more likely to recommend you,’” Macaitis said. “That was amazing, because here you have the power of data. Marketing should be saying, ‘If I want to grow my organization, if I want to get more leads . . . I actually should be arguing for more support people.’” 

After installing his marketing team at Zendesk, Macaitis is more convinced than ever about the power of the data-driven, customer focused approach. He said marketers who aren’t following this path are “underestimating the power of data, the power of targeting, the power of the marketing tech stack and what it can do.” 

He adds, “When I tell people that we can in real time know every single visitor when they arrive on our site and what company type they are from, and that we can target specific titles or regions or individual companies, they’re blown away.”

Eleven Principles to Follow When Bringing Big Data into Your Business

Whether you’re at a large company or a small company, there is some basic advice that applies to every size of company when taking those first steps to make your business more data driven. Here are 11 principles to keep in mind when bringing big data into your business. 

Focus on the Customer to Determine What Questions You Want Your Data to Answer 

The best companies have a data-driven focus on the customer. These companies use data to understand their customers, which, in turn, gives them a better understanding of prospects. 

A key to using data efficiently is to know what you want to know about your customers and prospects. Look for the signal amid the noise. Knowing their attributes and how they behave online can move the needle when it comes to revenue and profits. 

“The most important thing when you’re dealing with big data is what are the questions you’re trying to answer,” Vinny Sosa, director of web intelligence and optimization at Citrix, said.

When targeting prospects, what are their important characteristics? Their company size? Geographic location? Job title or job function? Industry? When prospects visit your website, what behaviors indicate a readiness to buy? Downloading certain white papers? Viewing product data sheets? Spending time on the pricing information? 

When analyzing customers, what characteristics do your best customers have in common, and where can you find more of them? What behaviors indicate a likelihood of customers switching to a competitor, and what steps can you take to retain them? To understand prospects, Ruth P. Stevens, president of marketing consulting firm eMarketing Strategy, said the key is digging into the buyer’s journey. “It’s about analyzing the buying process of your target audience,” she said, adding: “The first step is to figure out what it is that you need to measure, and in order to do that you need to understand what are your goals. Are you going to measure based on leads generated? Are you going to measure based on sales or revenue?”

It’s Big Data, but Start Small

When incorporating big data into your processes, think little triggers. The amount of data that the average company has the potential to collect through its website alone can be overwhelming. 

For each website visitor, a company could collect data on that visitor’s demographics (based on his cookie), could identify whether she is a repeat visitor, could track his onsite behavior, and could analyze what drove her to the site—among many other pieces of information.

The key is to determine what precise pieces of data about the customer are most important to your business goals. “You can’t take on everything at once,” Sosa said. “Look for the small wins.”

Starting small makes sense for several reasons. First, it won’t tax your technology budget. Second, it enables you to build the processes around big data slowly and in a controlled fashion. And third, it gives you the opportunity to have small wins using data that can ultimately earn you buy-in—and budget allocations—from the decision makers. 

Implementing small but impactful data-driven programs can be deceptively simple. In fact, some of the easiest steps can be overlooked. In a Harvard Business Review guest blog post on May 22, 2014, “Why Websites Still Can’t Predict Exactly What You Want,” Kaiser Fung, a statistician for Vimeo, said that personalization based on your past website behavior is a simple step ignored by even the best companies. 

He writes that FreshDirect, an online grocer he uses, is taking simple steps to get personalization right: “If you search for a product you have purchased in the past, FreshDirect lists those items first, labeling them ‘Your Fave.’ When I look for ‘water,’ Poland Spring shows up at the top of the list; if I search ‘Poland Spring,’ the computer knows my standard order of a six-pack of one-gallon containers.” That’s the kind of personalization that leads to better customer service.

Don’t Bet Everything on Technology

Don’t get us wrong. Selecting the right technology is critical, but don’t start with technology. Don’t get your heart set, for instance, on using a data management platform before you analyze the buyer’s journey, your customer’s needs, and your company culture.

“If you start throwing technology at it, you are missing the human element, which is critical,” Teradata Marketing Applications’ Arthur said. “The human element means there is a buyer with a face, with a need. My first caution is, regardless of the size of the company, do not start with the technology. That is a recipe for disaster. You have to start with the interaction strategy, the buyer’s journey.”

However, some observers advise that certain baseline resources can be considered essential. For instance, Molex’s Brian Krause said, “There are some specific needs. One is an e-mail database. Two is a very focused lead generation team that is very close to the sales organization.”

Richard Roberts, senior vice president of sales and marketing for BusinessOnline, a B2B digital marketing agency, said, “The first step is absolutely implementing the right customer data management capabilities for your company.” At the heart of this is an analytics tool—even something free such as Google Analytics—that can give any company insight into its website traffic and how tactics like paid search and display are influencing that traffic. 

Hire the Right People 

When considering your marketing staff, think less about raiding art schools and more about setting up a recruiting booth at a Star Trek convention. Embracing big data means hiring more mathematicians, data scientists, and chief marketing technologists. Or put more simply, hire people who are very comfortable with numbers and spreadsheets and are curious enough to want to understand the underlying details of what is driving success. 

The marketing department still needs creative people, but it also demands analytical people who can provide insights so the creative team stays on track. Matt Ackley, former CMO and senior vice president of product at Marin Software and now the CMO at Practice Fusion, identified two hurdles to building a data-driven marketing team. “The challenge becomes two bullets,” he said. “One is getting access to the data, and then the second piece is finding the analytics people who can do something with the data.” 

Getting those analytics people, however, may be easier said than done. There is an increasing demand for their services. “Google and Amazon can afford to attract and pay the experts on this stuff,” BusinessOnline’s Roberts said. “But it’s really hard to find and afford these people. The average B2B company is not going to be able to cost-justify a senior analytics person, because you’re likely talking around six figures. If it’s a data architect, then you’re going to be paying him what you pay your VP of marketing.”

Maintain Some Control of the Technology Piece

Almost every marketing chief has experienced the frustration of being at the mercy of the information technology department to get a sentence modified on the corporate website. But that is changing quickly. Marketers are demanding that new technologies be accessible by their staffers and not just IT.

Technology is now an integral part of marketing. The user experience on a company website is just as important as the company tagline. Marketing must at the very least share control of the technology that is increasingly a part of its responsibilities.

“I strongly believe every marketing organization should have a technical arm that reports to the marketing organization, and every marketing organization should have an analytics group that is dedicated or reports to the marketing organization,” Marin Software’s Ackley said.

Measure, Measure, and Measure Some More

In addition to providing insights into prospects and customers, big data can tell marketers which of their programs are working—and which are not. The enhanced measurement capabilities of digital marketing and the ease of A/B testing in digital environments enable marketers to put more money behind the most effective programs. 

Additionally, digital programs can be measured essentially in real time. Marketers need to monitor their campaigns on a weekly, daily, or even hourly basis. Glenn Gow, president of the marketing agency Crimson Marketing, said, “You need a dashboard mentality.”

In the past, measurement was limited and slow. Marketers had a difficult time, for instance, measuring the impact of a print advertising campaign on revenue. They might get a creative award for it, but even that took months.

The rise of marketing technology systems has changed that irrevocably. Joe Payne, the former CEO of Eloqua and now CEO of Code42, described this change: “Today we want to look at the effectiveness. How many people opened the campaign? How much time did they engage with it? How many people responded? Three weeks later, how many people we closed business with were touched by that campaign? There are lots of different ways to measure effectiveness, but now we can measure effectiveness. And so what you’re going to see is the sophistication of the user and the use of the marketing technology systems come together for the next two years, and you’re going to see pretty much everybody adopting these systems.” 

Stay on Top of Your Data and the Processes Around That Data

With new technologies appearing almost every day, it can be overwhelming for traditional CMOs, who are tempted to cede control of, say, the marketing automation software to someone from the millennial generation or a digital native. 

Payne described the situation this way: “All too often the CMO will say, ‘I let Jennie handle that.’ But Jennie is new and doesn’t know how to measure the effectiveness of marketing in general. And since Johnny the CMO didn’t understand how the technology works, he just froze and said, ‘I don’t deal with that.’” 

There is a danger in this approach, because technology is inextricably linked with marketing’s goals. Strategy and software are bound together: the CMO must understand both.

Conduct a Data Audit and Strive to Integrate Data Silos

Many companies are already collecting more data than they know what to do with and are not using that data effectively. A data audit can help them identify what data they have access to and give them a better handle on what data they actually need to boost revenue and profits.

“It is good to also take stock of all the sources of data that you have available, because most people overlook the fact that they have tons of behavioral data already that can be leveraged—but they don’t incorporate it or send it to the right places,“ Citrix’s Sosa said. 

At most companies, much of this data sits in separate silos. Customer service has different data on the customer than sales has, which has different data than marketing, which has different data than the e-commerce platform, which has different data than a company’s advertising agency. 

Many marketers (and marketing technology vendors) envision being able to centralize this data now contained in a variety of silos in a single database that will give a complete or 360-degree view of the customer. 

All of this is a noble goal but may, for the time being, be beyond the reach of most companies and most budgets. “We as marketers and we as technology providers are both a long way off from making that vision a reality for most companies. The promise is there, but it comes down to, ‘How do I do this in a scalable and cost-effective fashion?’ It is all about measuring the return on investment,” said Poppin’s Robison.

 Cooperate with IT, Sales, Human Resources, and Other Stakeholders

Start small, but think big. Start with small data-driven projects but have an eye on using data to improve not only marketing performance but the entire business. To accomplish this big goal, a marketing team will need buy-in from other departments. At a smaller company this is often easy, but at larger companies it can be one of the most difficult barriers to change.

A 2014 IBM report, “Stepping Up to the Challenge: CMO Insights from the Global C-Suite Study,” advises CMOs to “get the CIO on your side.” Having the CIO on board is a necessity for building out the technology necessary to make the most effective use of big data. Sales must be on board to make sure marketing qualified leads are taken seriously. And human resources must be on board to help marketing find the data-oriented employees necessary to take full advantage of big data.

“The technology in many cases actually works pretty well,” Poppin’s Robison said. “Now the biggest barrier that I’ve seen is related to the business management and the process change management that is required to execute data-driven integrated marketing.”

Practice Good Data Hygiene

You’d think that keeping data in a marketing database up-to-date would be a straightforward task. But it’s not—especially when you consider that one in five businesses changes a postal address every year.

A report by NetProspex, a data vendor catering to marketing, called “The State of Marketing Data,” found that 88 percent of business databases were lacking very basic data, such as the prospect’s industry, company revenues, and number of employees. An astonishing 64 percent of records did not include a phone number. 

This kind of information is critical for marketers and salespeople looking to start conversations with prospects. In the digital age, databases are essential, and it is essential that they are kept up-to-date. “Database quality now has an unprecedented impact on the success of our marketing campaigns,” Michael Bird, CEO of NetProspex, wrote in the report. “Simply put: data drives revenue for your company.” 

To ensure that these databases are as productive as possible, marketers must maintain good data hygiene. In a column, Ruth Stevens, president of eMarketing Strategy, outlined a list of five steps for cleaner data:

1. Make sure your data entry team is keying in data accurately in the first place. Make the data-entry team a priority.
2. Incentivize your sales team, call center squad, and other customer-facing employees to regularly request updated contact information and other data from the customers they encounter.
3. Use available software, such as Trillium, to streamline the process of cleansing, correcting, and appending e-mail and postal addresses.
4. Allow customers access to their records, so they can help keep them accurate. Consider offering discounts as an incentive for customers to participate.
5. Regularly contact customers, either via phone or e-mail, to update records. This approach is critical with the most important accounts.

Develop a Road Map, but Anticipate Detours

Embracing big data at most companies can require a massive transformation. It can involve a culture shift, new technologies and processes, and the hiring of different personnel. This transformation means big plans, and it may require outside consultants to help you map a strategy, choose the right technologies, and make all the right moves. But be careful not to slavishly adhere to a blueprint that has worked for other companies. Big data is not about keeping pace; it’s about building a big—and unique— advantage.

“Don’t be a cookie cutter,” said Heather Zynczak, CMO of Domo. “Get your data in place, so that you can measure and do things outside the box and do things that are wildly different. That will leapfrog you over the competition. There’s not a cookie-cutter approach to marketing, because then you’re only going to be as good as your peers.”

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Chapter 9 of my book The Big Data-Driven Business (Wiley).  I will be posting a chapter every few weeks here on LinkedIn.