4

Building Talent and Skills

From Traditional to Modern

Once you've assessed the mind-set of the people in your organization and have thought through some of the structural changes you'll make, you need to think about who belongs in your marketing organization. Who's in? Who's out? What new positions should you create to optimize analytics? We turn to this topic next.

As you shift your organization to be both more analytical and customer-centric, you need to ensure that your people have the requisite skills to perform in the new kinds of roles you're creating. And that takes two components: incorporating a different filter for hiring new employees, and also assessing your current staff to see if they have the desire and capability to evolve and embrace the new analytical skills they'll need. “We know that pure data people rely more on the left side of their brains, while more classically trained marketers are more right-brained,” according to Jennifer Chase, senior marketing director. “Building the analytically driven marketing organization is all about bringing the left and right sides of our brains together. You may excel at one side of your brain more than the other, but need to have an appreciation for both.”

What Does An Analytical Marketer Look Like?

Marketing managers must look for evidence of different skills and experience in evaluating both applicants and current employees interested in becoming analytical marketers. But what to look for is open to debate. Here are some thoughts:

1. Sales skills. It's no longer good enough for marketing to simply focus on filling the top of the funnel and passing leads off to sales. The analytical marketer needs to be active throughout the buying process and work hand in hand with salespeople to provide the information that will help them close deals.

2. Social media skills. Social media dramatically change the buyer-seller-influencer dynamic. But only those actively participating in social media tangibly appreciate the differences between old-style, one-way media conversations and group interactivity.

3. Journalism and storytelling skills. With buyers getting the majority of their information from the web, and with potential sales an increasing priority, there's no end to the need for juicy, targeted content. Storytelling also comes into play in campaign design.

4. Process design skills. Automation is just beginning to penetrate the market. As anyone who has been part of a reengineering effort can attest, it's not the automation that increases productivity. It's the process changes that automation enables and enforces. Deploying marketing automation will require skills such as process modeling, project management, the ability to train and manage change, and ease with technology.

5. Data and analytics skills. Technology captures and makes available enormous amounts of data about buyer and seller behavior. A marketer must be a data guru with a passion for analytics and curiosity. (I'll get into more detail about these skills later in the chapter.)

6. Domain expertise. Customers don't care about our products. They care about themselves and their problems. Building a bridge between our products and the customer requires knowledge of both realms.

7. Collaboration and exceptional communication. These skills are not mutually exclusive. On just about every job posting these days, you will see that “communication” skills are a must. Communication has a different meaning for marketers in our world. Traditional communication skills need to be supplemented with an intense focus on collaboration through effective communication. There are no one-man or -woman bands, only full orchestras with very clear objectives and constant interaction.

8. Creativity and innovation. We need people to reach for the next idea. The term “creativity” is no longer applicable to just the agencies or the designers. Today's channels and digital work approaches enable and encourage creativity at all stages of marketing and the marketing process. Creativity is at the heart of innovation, which is not only required but rewarded.

9. Leadership. A leader is someone who is willing to take risks, drive change, and build trust. We need these skills at every level of the organization, not just the vice president level. Today's marketers, regardless of their role, have a unique opportunity to demonstrate leadership in their field and across their business for maximum impact.

The New Analytical Marketers

With the foundation for a modern marketing organization in place, new roles have emerged:

 

While far from exhaustive, this list of skills confirms that we are no longer looking only for traditional marketing skills. Marketing managers need evidence that candidates or existing employees bring different skills and experiences. Good analytical marketers leave a well-lit trail to make sure such evidence is easy to find.

But to evolve into an analytical marketing organization, marketers today need to be more like scientists than artists, according to Phil Brojan of RCI. This requirement has changed how his organization thinks about hiring new marketers. “We now look for scientific and analytical skills and pick and choose where we put creative,” he told me, while noting that finding and evaluating people with these skill sets can be difficult. “You have to have the right players in the right positions. Hire as much relevant experience as you can and mix that in with the folks that understand the business really well.”

Regardless of the role someone plays in marketing, the expectations related to data and analytics should be consistent. While there will always be more advanced analytical and technical positions, there is a new baseline for all marketers. The skill set includes knowledge of data management principles and analytical strategies, and an understanding of the role of data quality, the importance of data governance, and the value of data in marketing disciplines. Today's marketer needs to go well beyond reporting and metrics, and be more proficient in a full range of analytics, which may include optimization, text, sentiment, scoring, modeling, visualization, forecasting, and attribution.

Marketers should have experience with the technology, tools, and design approaches that leverage data and analytics. Campaign design, multichannel integration, content performance, personalization, and digital marketing can all be driven by fact-based decision making, ideally with direct accountability to results and the ability to very quickly react and adjust to the demands of the customer and the market. The marketers I am referring to have a distinct blend of creativity and reasoning talents; they are inquisitive, inventive, and enthused by a culture that is advanced and agile.

As our functional needs have changed, we've had to adjust the kinds of jobs and job descriptions of people throughout our marketing organization. The emergence of data science combined with the proliferation of new channels has radically changed some traditional marketing jobs, while also leading to the creation of brand-new roles and titles. As a whole, all these changes are part of the evolution away from marketing simply as art into a hybrid of art and science. As a result, we've redefined four new categories or job families:

• Digital marketing

• Content marketing

• Marketing science

• Customer experience

Digital Marketing

The world of digital marketing includes the functions of web, search, social media, e-mail, and digital advertising and media buying. This category has been going through tremendous growth and change over the past decade as the number of channels has exploded. Consider how the job of someone like Elizabeth Creech, a SAS digital marketer involved in our paid search and display advertising efforts, has changed as advertising has shifted from print publications to digital. In the print world, it was difficult, if not impossible, to know if you were reaching your intended audience. Creech's job is now much more precise, thanks to analytics. As Creech said, “The transition to digital has made it much more likely that we can target the right person, at the right time, on the right device. We can also see what the world is looking at, based on keyword prices and search volumes. You can't fool digital like you could with print.”

As the number of digital channels grew, our reaction was to continue to add channel specialists who could learn every nuance of how that channel operated in a way that allowed us to get closer to our customers. Consider how complicated it has become to orchestrate organic search result placement or people who can manage the daily investments required to make an effective paid search campaign relevant to the customer's decision journey. Similar dynamics apply to the rapidly shifting social media realm. We need to constantly add people who can drill down and drive communication through every new channel.

But what we've learned is that the real opportunity is in convergence and in creating strategies that leverage multiple channels rather than silos (as discussed in chapter 3). The result of that shift is that we now require multiple skill sets from each of our team members so that they can maintain excellence in their channels, but also understand the importance of coordinating with other components in a campaign as well. Put another way, we still have a need for skills that are narrow in one sense, but we also have to have people who can connect those skills to a broader view of where we're going as an organization to meet our goals. We can't have someone so focused on his one social channel, for example, that he doesn't recognize he is cannibalizing another one at the same time. That's counterproductive, because we are not serving our customers by doing that.

We're looking for people who are both passionate about their channel but also understand how it intersects with others. We need marketers who are capable of collaborating and who prioritize connection points while also using the data to guide them.

For example, before he recently transitioned into a new role as a segmentation analyst, Scott Sellers was one of our go-to resources for tapping into the world of online advertising and paid search. Sellers was responsible for helping the team understand where the best opportunities were for, say, purchasing keywords that our potential customers were most interested in getting information on. Sellers told me that his job was not unlike that of a police investigator who simply wanted to uncover the truth, rather than to prove any particular outcome for a potential campaign. “From an analytical standpoint, we need to be impartial with regards to the final outcome or decision,” he said. “The key is to show people how you reached a conclusion based on your interpretation of the data. Someone else might reach a different conclusion, but at least we have something objective to talk about. Ideally you want every outcome to be perfect, but nobody is an oracle.”

When Sellers and I discussed some of his experiences, he recalled that when he was involved in supporting paid search advertising, a campaign he was analyzing was using some very expensive search terms related to customer intelligence, which meant that our company wasn't alone in believing there was value in associating our brand with the campaign. That alone seemed like justification for keeping the campaign alive, since our goal was to engage with customers on their decision journey, wherever that might begin. But in our analytical era, making those kinds of assumptions simply doesn't suffice anymore. “It's all too common when you have a target market that you decide what you will focus on,” Sellers explained. “You then look around your organization at the structures in place and decide to align your strategies, messaging, and campaigns along those internally created lines. The major problem with this approach is that it focuses on company thinking and ignores the behavior your market exhibits.”

Although the keyword campaign had been in place for some time, Sellers examined two years' worth of data to analyze what actions people took after they engaged with the ads we attached to those search terms. “No matter how we tried to manipulate the campaign-budget, ad text, asset offerings, etc.-we were never able to see a real, sustained performance improvement,” he said. “So, I set about finding out if we actually should be running the campaign, despite the topic's importance and emphasis for SAS. Maybe paid search just was not the proper platform at that time.” As part of his analysis, he compared the results to the actions people took when they engaged with similar terms via an organic search. He also tracked the behavior of contacts who clicked on the ads to see what other activities they undertook to see if the campaign was beneficial in producing auxiliary actions, or those not explicitly promoted by the campaign itself. What he found was sobering: despite the high cost of the paid search campaign, only fourteen contacts opened sales opportunities with us, but none was related to the initiative being promoted. And, none of those opportunities turned into successful sales.

Armed with that kind of insight, the decision to kill the campaign was easy, but only because we had done our analytical homework and not let our emotional subjectivity or inertia get in the way of digging for the real answers about that campaign's efficacy.

Content Marketing

Content has become an especially critical component of the modern approach to marketing. Everything we do as marketers now involves some kind of content. Just offering white papers isn't enough anymore. The content used today has to be designed as “channel appropriate,” meaning that the format, length, and relevancy must work in that channel. You cannot run a two-minute video in a display ad. That's why we have created an entire new family of jobs whose role is to fill in the gaps and help ensure we are offering the kind of relevant content our customers are looking for. The challenge of that content doesn't have just one form, and it is consumed differently across different channels. So we came up with a strategy for how best to procure, manage, and distribute our content across our website, blogs, social channels, campaigns, and more.

That means the people we trust for our content marketing roles have a very good understanding of all our different channels, how they function, and how they can complement each other. They use the power of analytics to assess a piece of content and understand how it fits into a marketing campaign or a customer-nurturing strategy. They also assess what kind of content works at what stage of a customer's decision journey: when do they want slides, videos, or even a book? Content marketers, therefore, are very analytically driven and act almost like consultants to a marketing campaign; they provide knowledge about what's available inside the organization and where the gaps might be.

For example, we have content creators all over our company, from leadership ranks down to data scientists who might be blogging or authoring research papers. We also hire people to provide content, like white papers. What had been happening was that without coordination and convergence, we were generating lots of duplicate content or content that was underutilized because no one knew it was there. Now, our content marketers can oversee that inventory and, by applying analytics, understand what pieces of content work best and when. For example, when we are putting together a campaign, Ericka Wilcher, a member of the digital content marketing team, works with the campaign orchestrator to perform a “content audit,” in which we select content that scores best with the target customers of a particular campaign. Wilcher told me, “We are responsible for analyzing, surfacing, and recommending content that will be the best fit for a campaign.”

Marketing Science

The role of the marketing data scientist or data visualization analyst is also new to marketing; this role is distinct from that of a pure data scientist. In some ways, we are still defining the different roles that fall under the umbrella of a marketing data scientist. One descriptive title I have seen for this role is “data artist” or “data storyteller.” For example, Shawn Skillman is a senior marketing data visualization analyst who is skilled at modeling and storing data; he is employing the analytical tools and digging into the data we collect using a different lens. Skillman's job is to look at the data objectively to see what stories it's telling, without being tainted or biased by what someone running a campaign might want to see. Marketing data scientists like Skillman are also able to see what happens when we make changes and tweaks; they can tell us how the story begins to change.

Another job title that currently falls under the same umbrella is what we call a “segmentation analyst.” Someone running a campaign will come to a segmentation analyst like Julie Chalk, for example, and ask for her help in building a contact list that the campaign should target. To do this, Chalk relies on “scoring models,” in which she parses out the key factors in a contact database that might make that person a good target for the campaign. Chalk is then able to track the results of the campaign and suggest where it might be working well or not. “We have a ton more data at our fingertips than we used to,” she told me. “Part of our role is to figure out how valuable different pieces of information are and how we can make the most use of it. I didn't know jobs like this existed when I graduated college. But I love the creativity involved with it, as well as the ability to use black- and-white data to prove your hypothesis.”

Chalk recalled her analysis for a campaign around one of our customer-experience software solutions. By tracking the activities of customers on our website, Chalk realized that 26 percent of visitors were dropping off before they registered for a free white paper we were offering on our product. That was great insight, because it made us question why: Were we asking too much information from the visitor? What other barriers were we putting in the way? And perhaps most importantly, what could we change to help reduce that dropout rate and create more conversions instead?

The ability of the data artists and storytellers, like Skillman and Chalk, to tackle questions like these has become a central tenet of the marketing modernization efforts we are making. They help to provide that analytical muscle that lets us make better investments in campaigns, while also letting us know when we might need to try again.

Customer Experience

Many people might think of marketing as purely an “outbound” function in which we are reaching out to potential customers. “Inbound” marketing is another evolving area in the world of marketing that ties directly to the customer decision journey, where we need to engage with customers wherever they are in their journey. We created a new position called a “customer engagement specialist” (what we used to call a “prospect development specialist”), whose role is to create deeper and more intelligent conversations with potential customers who have questions they want us to answer.

Because potential customers have so much information available to them-everything from what they obtain in a Google search to insights they get from a social media contact-it's rare that any interactions are now considered “cold.” Customers have some expectations about us already, and we need to be prepared to engage them at that level. Someone might not know who we are, but he might know exactly what kind of solution he is looking for; it's up to us to understand if we can meet that need. This shift results in higher-quality interactions that have a far greater chance of conversion into actual sales than we might have experienced in the past.

While we spend much time and effort trying to land new customers, we also rely on the power of data and analytics to service our existing customers as well-something we call “relationship marketing.” Once someone becomes a customer, his needs change, and it's our job to nurture that relationship and help retain his business. We have to keep up with our customers' needs and make sure they know what we can deliver to meet those needs.

One big shift we've made is to rethink the talent and skills of the people manning our customer contact center, which is itself an evolution from the traditional call center; we now address far more than telephone calls for inbound customer interactions. When we acknowledged this, it changed how, when, and where we are available, and in what languages. “The world is so much more complex now,” Chase said. “It requires a higher-level individual to help resolve customer inquiries. We need problem solvers and people committed to solving whatever issue that customer might be contacting us about.”

Marketing Analytics at Work

Using Chat Transcripts to Understand Customer Sentiment

Each day, the SAS customer contact center participates in hundreds of interactions with customers, prospective customers, educators, students, and the media. While the team responds to inbound calls, web forms, social media requests, and e-mails, the live-chat sessions on the corporate website make up the majority of these interactions.

The information contained in the chat transcripts can be a useful way to get feedback from customers and prospects. As a result, departments across the company frequently ask the contact center what customers are saying about the company and its products, and what types of questions they ask.

The challenge

Chat transcripts are a source for measuring the relative happiness of those engaged with SAS. Using sentiment analysis, this information can help paint a more accurate picture of the health of customer relationships based on the content of the interactions.

The live-chat feature includes an exit survey that provides some data about visitors' overall satisfaction with the chat agent and with SAS. While 13 percent of chat visitors complete the exit survey (above the industry average), thousands of chat sessions only have the transcript as a record of participant sentiment.

Previously, analyzing chat transcripts often required the contact center to pore through the text to identify trends. With other, more pressing priorities, the manual review only provided some anecdotal information.

The Approach

Performing more formal analytics using text information is difficult due to the nature of text data. Text, unlike tabular data in databases or spreadsheets, is unstructured. There are no columns that dictate what bits of data go where. And words can be assembled in nearly infinite combinations.

For the SAS team, however, the information contained within these transcripts was a valuable asset. Using text analytics, the team could start to uncover and understand trends and connections across thousands of chat sessions.

SAS turned to SAS Text Analytics to conduct a more thorough analysis of the chat transcripts. The contact center worked with subject-matter experts across SAS to feed the text information into the analytics engine. The team used various dimensions in the analysis:

In addition, North Carolina State University‘s Institute of Advanced Analytics began to use the chat data for a text analytics project focused on sentiment analysis. The partnership between the university and SAS helped students learn how to uncover trends in positive and negative sentiment across topics.

The Results

After applying SAS Text Analytics to the chat data, the contact center better understood the volume and type of inquiries and how they were being addressed. Often, the analysis could point to areas on the corporate website that needed updates or improvements by tracking URLs for web pages that were the launch point for a chat.

Information from chat sessions also helped fine-tune SAS’s strategy. After the announcement of Windows 10, the contact center received customer questions about the operating system, including some negative sentiment about a perceived lack of support. Based on this feedback, SAS released a statement to customers assuring them that Windows 10 was an integral part of the product road map.

The project with North Carolina State University has also provided an opportunity for SAS and soon-to-be analytics professionals to continue and expand on the analysis of chat transcripts. They continue to look at the sentiment data and how it changes across different categories (products in use, duration of chat) to see if there are any further trends to explore (see figure 4-1).

FIGURE 4-1

Contact center workload report screenshot

image

Today, sentiment analysis feeds the training process for new chat agents and enables managers to highlight examples where an agent was able to turn a negative chat session into a positive resolution.

  1. Title: Contact center workload report
  2. What: Reports on overall inbound customer interactions by channel.
  3. Value: Provides insight into which inbound channels are driving the most volume.

    – Gives insight into how customers want to engage with us. Which channels do they use most frequently?

    – Drives decisions about resource alignment to channel.

 

Analytics now plays a bigger role in helping arm our customer engagement specialists with a snapshot that enables them to understand the customer, her relationship with our company, and any other relevant behavioral or historical information that can make that interaction as productive as possible for the customer. We have developed a tool called Customer 360, based on our data mart, to help in this process, but the problem is complex, especially when the timing is essential. We need to decide what information is most important for engagement specialists without drowning them in the details. We continue to evolve our systems along these lines, but the issue is so complicated that we won't ever really reach a finish line with a perfect solution, as more channels and customer data become relevant.

The new frontline of customer engagement is an emerging topic, as we've begun to recognize that marketing can play a key role in not just winning new business but retaining existing customers as well, which is another role we ask our customer engagement specialists to play.

How Do You Assess the Analytical Marketer?

When assessing candidates, there are some techniques that can help you test for an ideal analytical marketer. As you evaluate candidates' experiences, look for examples of campaigns, projects, and other key accomplishments that highlight the role that data and analytics had in decision making and evaluation. All marketers (not just the creative side) must have a “marketing analytics portfolio” that can demonstrate their use of data in the design phase, the types of analytics they employed as part of strategic decisions, the testing strategies they applied, and a performance assessment.

For example, when the directors who work for me, like Matthew Fulk or Jennifer Chase, conduct interviews, they ask candidates to share situations and projects in which they employed analytics to drive or influence a campaign. They might ask questions such as: How do you gather requirements when defining technical projects for the needs of the business user? How would a business client describe working with you? Perhaps more tellingly, if candidates progress to a third interview, they ask them to present a recent analytics project they were involved in and explain how they handled a stressful situation or overcame an error. “We want to really test if they have analytic chops and also if they can talk about it in front of a group,” Chase said.

Asking the Right Questions

What sets a high-performing marketing organization apart is its ability to hire people who can find insight in data by asking the right questions. This isn't something that can be learned easily or that a lot of businesses have time for coaching and mentoring in new hires. We want candidates to tell us how they approach what they do, but we need to ask the right questions during the interview. We have used the STAR (situation, task, action, results) behavioral approach to formulate a list of questions to ask candidates. Some examples of behavioral questions we've used include:

 

Brojan at RCI explained that his organization has also evolved its interview process along these lines; RCI relies more on panel interviews, in which it gives candidates complex business scenarios and then asks them to explain what they'd do and why.

Analytical marketers must to be able to articulate and demonstrate how they influenced change and learned from failed efforts. Marketers tend to focus on the visual and the message, which are both critical. Analytical marketers can explain the what, how, and why, or why not.

Using both verbal and written assessments to gauge a candidate's technology and “analytical IQ,” in addition to their marketing savvy, is important. Request written responses to such questions as: How do you approach decision making as it relates to marketing planning and investments? What is the difference between metrics and analytics?

I look for marketers who have a clear, passionate understanding of the value of data and analytics in the work that they produce. They need to articulate value with data and analytics as an integral part of their strategies. They should justify investments backed by data and analytics. And, they must take risks, innovate, and fail, using data and analytics as their guide. When I add all this up, I am looking for marketers who have a high analytical IQ.

Evaluating Analytical IQ

After a first round of interviews, we bring finalists back for a second interview, where they are required to do a presentation. In this interview, we are specifically evaluating communication skills (how easily they can convey their material) and how they address their audience. Here's an example of what we ask of them:

Hi Candidate,

Congratulations! We would like to bring you in for a second interview. You will need to prepare for a sixty-minute meeting (thirty-minute presentation/thirty minutes for Q&A). Your audience will be the marketing sciences team and other internal customers (members of the marketing campaign teams).

Presentation details:

 

In order to get what I want, I train and empower marketers accordingly. We have established frameworks that create governance and consistency. We have established training and certifications that are required and aligned to their objectives for performance, and we supply them with a marketing analytics portal on their desktop.

Our goal is to hire marketers who have a passion for and understand the value of data and analytics in decision making. This is not as hard as it was ten years ago. The modern marketer has evolved from being purely creative and logistics driven to appreciating data and the role of analytics. Anyone accustomed to measuring digital and social media efforts or experimenting with A/B web pages or one-to-one marketing is primed to use more advanced analytics to measure the overall value of a program. You're not killing creativity or innovation, just seeking naturally curious employees with updated skills.

Amplifying Analytical Skill Sets

The Big Data movement had a big impact on marketing at computer maker Lenovo, so much so that it helped spur an initiative to centralize its customer data and uncover new opportunities and improve the end-to-end customer experience. The Customer Insight Center of Excellence became the initiative's nerve center and arms the company's marketers with a new level of data and analysis.

As Mohammed Chaara, director of the center, told me, “We're analyzing the voice of the customer by conducting text mining on our brand mentions to help understand sentiment, identify new customer segments, and test how our messaging is resonating. And this is where all customer feedback data is getting captured. So when you layer this data on top of some of the traditional campaign measures, you get a really rich picture of your market. This has fundamentally changed how marketing operates. Now the majority of our product meetings start with customer insights, and those insights drive the actions.”

Lenovo's approach represents a centralized model that provides analytics services to the marketing organization along with other business units. The Customer Insight Center of Excellence reports to R&D, and according to Chaara, this works for Lenovo “because it gives us the flexibility to draw from a broader variety of technical solutions.”

In a similar way, to leverage the shared strengths of our team, we have put an internal structure in place at SAS to help team members continually learn from each other. We call these “competency centers,” which are virtual task forces whose goal is to allow people inside the organization to share expertise and knowledge in five different areas: social media, analytics, marketing leadership, operations leadership, and search engine advertising.

The idea behind the competency centers is to leverage the skill sets and experience levels across the organization so that we can share best practices and learn from each other and from our mistakes. The teams, which each have fifteen members, are cross-functional; they have a representative from every marketing department and no formal management structure. Rather, they provide opportunities for team members to grow their leadership skills by helping their peers keep up with the many different changes occurring daily in the digital marketing world. We ask our people to both acquire deep expertise in an area like web search, and then share that skill with others, so that it connects with the broader view of our organizational goals.

We've already seen the centers pay off because they provide a way for team members to take risks in their daily work and then share with the broader group what they tried, why they tried it, and what happened. Everybody then reaps the benefit of that learning experience. The centers also expose people inside the organization to the capabilities of tools they might not have been aware of. The centers also support the premise that because of channel convergence, a better understanding of the channels and approaches allows for better integration and joint planning. Digital and social channels can complement or conflict with one another, so the approaches must be deliberate and planned, in addition to leveraging the organic components.

The Objectives of Competency Centers

Since we focus so much on our efforts' return on investment, it's crucial that we leverage our investments in training people, which is the true value of our competency centers. At a high level, their goal is to provide integration across the organization by:

How are they structured and led?

Why are they valuable to marketing?

While we offer external training opportunities to team members, the competency centers are our internal training group for distributing information and expertise throughout the organization. What's so exciting about this approach is that it happens organically when someone is passionate about something and wants to share it with everyone. As a leader, I find it rewarding to see people gravitating toward areas that they are truly interested in. In this way, the competency centers serve as both forward-looking research entities, because they serve as a source for the latest experimentation, and centers for expertise that team members can rely on for answers.

For example, Skillman serves as a member of the analytics competency center. He and the other members of that team play a critical role in helping others in the organization understand the power within the data that we have collected. But rather than having people sidle up to Shawn's desk and ask him one-off questions, his role on the competency center is a way for everyone to learn from those questions when they pop up. “We are the first line of defense for anything analytically driven,” he said. “And because we have a group that has a diverse background in using analytics in the organization, we have helped everyone reach a higher level of understanding of how they can use data and analytical reporting in their jobs on a daily basis.”

Now that we've covered the shifts in organizational mind-set, structure, and talent, we turn now to look at what kind of leader a marketing organization needs.

APPLYING THESE IDEAS TO YOUR ORGANIZATION

How Does Your Organization Identify and Hire Analytical Marketers?

Having the right people on your team is an obvious need as you evolve into an analytical marketing organization. You might need to shift how you are hiring and who you hire. Just as importantly, you may need to take a fresh look at your training programs to modernize your existing marketing team members and leverage their experience, while also equipping them with the tools that will make their skills relevant in the analytical marketing era.

✓ Has your marketing organization changed the types of skill sets you want in the people you hire?

✓ How does your organization balance the creative side of marketing with the analytical components?

✓ What systems do you have in place to emphasize teamwork and collaboration among marketers above and beyond their own area of focus?

✓ Do you have any systems or procedures in place to help educate existing marketers and give them the analytical skills they need to compete?

✓ How do you enable marketers from within your organization to communicate, collaborate, and share best practices with each other?

✓ Are there performance objectives in place that are aligned to analytical skills?

✓ Are you highlighting stories of marketing's success in leveraging analytics?