10 Elements of a Successful Data-Driven Marketing Strategy The more work you put into the front end of your marketing strategy, the less sleep you'll lose worrying about results.

According to a Insights Report, which surveyed 162 U.S.-based senior executives, a "a whopping 64% of survey respondents "strongly agree' that data-driven marketing is crucial to success in a hyper-competitive global economy." While there's no denying that both executives and marketers are realizing the benefits of data-driven marketing, there are still a number of hurdles to overcome. For example, "data stemming from disparate providers, disconnected systems, varying internal teams, incongruous accountabilities can prevent marketers from reaching the right consumers, at the right time, with a relevant and consistent message."

To resolve these issues, you can create a data-driven marketing strategy by implementing the ten following techniques.

1. Assemble your team.

Using data to create a marketing strategy obviously begins with handling the data. For this to be effective, however, there has to be cross-departmental and cross-disciplinary teams in place. Richard Bayston suggests on Effin Amazing, "That doesn't just mean someone from IT gets together with whichever guy from sales that managers think they can spare the best." It means that you have to find individuals "who are willing to go beyond their areas of knowledge." For example, "Data scientists have to be willing to learn about marketing; sales people have to be willing to learn about IT."

So when assembling your all-star team, look for data scientists who come from "very divergent specialty areas" or placing someone in the C-Suite, for example, to oversee data and analytics. And, make collaboration between these people a priority by having frequent meetings where everyone not only shares ideas and information, but also shares credit for success.

2. Mind your own business.

Jim Bergeson points out in an article for MarketingProfs that "Data is sometimes hiding in the inner resources of your organization—perhaps with dealers or resellers of your product or service, your sales force, or locked up in an IT vault."

You can begin mining this data by building "a unique customer identifier to connect disparate data sources at the customer-record level." This will provide insights into the entire customer experience, such as "what's happening in the dealer channel, point of sale, complaints or service calls from the call center, online recommendations, referrals, warranty data, enrollments, renewals, and subsequent purchases."

From there, you can identify and investigate these relationships among the data elements.

Related: Data-Driven Marketing in 2016: Bigger, Faster, Better

3. Data goes beyond numbers.

"Give the data and numbers a meaning outside of their numerical value," says Erik Bitmanis of Iversoft Solutions. "This is done by first knowing what your goals are and the KPIs that will have an impact on those goals."

Bitmanis concludes by saying, "Once your team sees how these indicators can positively (or negatively) affect your progression towards a goal, then these data points become more tangible than simple numbers on a spreadsheet. Tangibility is key to making people care about, and want to use, data."

4. Identify the right channels.

Did you know that "90 percent of Twitter users who see a TV show-related tweet are likely to immediately watch the show, search for more information, or share tweet-based content about that show?" Clever marketers are able to tap into data to uncover what messages connect best with their customers and which channels to use to send those messages.

Ted Karczewski, Marketing Content Specialist at Skyword, says for the Content Marketing Institute that "Arby's does a great job of balancing its data initiatives with its creative marketing." For example, during the 2014 Grammy's, Arby's knew "that a high percentage of its audience would be engaging in live conversation around the event on Twitter." While listening on social media during the show the company's social media director "watched the awards show and waited for an opportunity to embed itself in the conversation with relevant, real-time social media content."

5. Build models to predict and optimize business outcomes.

Dominic Barton and David Court remind us on McKinsey & Company that "Data are essential, but performance improvements and competitive advantage arise from analytics models that allow managers to predict and optimize outcomes." When building this model you don't start with the data. Instead, identify business opportunities and the models can improve performance.

Barton and Court have found "that such hypothesis-led modeling generates faster outcomes and roots models in practical data relationships that are more broadly understood by managers."

Related: Without Good Analysis, Big Data Is Just a Big Trash Dump

6. Identify which metrics to measure when evaluating success.

After you've determined your strategy's goals, you need to identify the metrics that you're going to use to determine how successful your strategy is. Tricia Moon uses the goal of increasing blog readers on Rival IQ where you would use metrics like "Engagement rate of posts, number of link clicks, how many times the article is shared on social, average time spent on an article by people coming from social, percentage increase of readers coming from social sites"

When evaluating your goals review these numbers and ask how they impact your business.

7. Make sure that your data is accurate.

"You want everything to be as close to perfect as possible, especially when people are using you as the source and possibly building case studies or reports off your information," says Amy Medeiros, a marketing manager with BroadbandSearch, on CIO. Akamai CMO Brad Rinklin adds, "The worst thing you can do is get a lot of press about your data, then have a competitor or a major publication say your data is crap."

You can avoid this mistake by having your data vetted by a third party, such as a as a professor at MIT or Stanford, a data scientist, or an industry analyst, before going forward with your strategy.

8. Create buyer personas and customer-focused content.

While you're busy digging through data, it's easy to forget one extremely point, "Data alone can't form a marketing strategy" says Sreeram Sreenivasan on StartUp Nation. Insights are developed after your team analyzes the data and then "form hypothesis, vision and next steps." This includes analyzing "customer behavior, buying patterns, preferences and background to develop different buyer personas." With this information you can "figure out who each customer is, what they like to buy, what they like to search, what their interests are and what influences them."

After you've created your buyer personas, you'll want to create customer-focused content that has been personalized and is intriguing to your target audience.

Related: Customer Retention Is No Accident -- How Small Business Can Get It Right

9. Establish company-wide goals.

Farnaz Erfan, director of product strategy at Birst, tells Neil Davey of Mycustomer.com:

"It has become harder to measure marketing ROI, because it requires alignment with what sales defines as sales ready leads or what the services team believes determines a customer's readiness for upsell. The ROI conversation in this context requires marketers – and their business counterparts – to have a consistent, single view into what describes a customer, and in particular what defines a high value customer."

Davey adds, "it would be helpful for organizations to break down silos between the departments, bringing data from CRM, marketing automation, service and financial systems together in a single view, as well as agreeing on shared definitions, and aligning definitions of ROI as well."

10. Keep on testing.

While data can provide us with a starting to develop a marketing strategy, it has to be frequently manipulated and tested. Thankfully, Matthew Buckley says on New Breed Marketing, that testing your marketing your efforts with small experiments "can be achieved in a day."

Buckley suggests that you use the scientific method when testing. This includes;

1. Start with the data.
2. Ask a question of what information you have available to you.
3. Construct a hypothesis.
4. Test with an experiment.
5. Confirm the test/procedure worked as planned.
6. Analyze the data and draw conclusions
7. Present results and determine the next steps

Remember, the faster you see what works, the faster you'll be on your way to growing your business.