Content marketing, direct mail marketing, email marketing, social media marketing, guerilla marketing—with so many options to reach potential and existing clients, it’s hard to know where to begin. One thing’s for sure, though: If you don’t know who your audience is, your chances of reaching them, regardless of marketing avenue, are slim. Instead of wasting boardroom brainstorms and company resources by rushing into multichannel campaigns, consider taking the time to uncover who your target audience is, and what it needs. Enter data marketing.
There are several reasons for marketers to implement a data strategy. “Data is a valuable commodity in any business when it is activated, and rendered accessible [and] useful, and made actionable,” said Michael Ferranti, founder and CEO of Endai, New York City. “In almost any organization, activating data isn’t trivial.
“Data strategy enables marketers to intelligently take concerted steps from collection to processing to transformation—yielding intelligence that did not exist before. A data strategy also helps produce the speed and dexterity in moving from intelligence to action—and ultimately to competitive advantage.”
Now that we have your attention, here are five steps to put into action.
1. Plan It Out
For a data strategy to be successful, it is imperative that you outline your steps and business goals. “Define what is to be collected first, and never [leave] the machine on a default mode,” said Stephen Yu, associate principal of analytics and insights practice lead for eClerx, New York City. “Data becomes uncontrollably big as no one throws out anything. Define what matters for what you are trying to do.”
As for what matters, here are some questions to ask yourself: “Is it about conversion, value creation, qualification, churn prevention, cross-sell/up-sell, budget optimization, channel strategy or what?” said Yu. “Do not treat the work as simple data collection, but as asking questions to solve business problems.
“Now, if it is about the audience management, make sure you collect elements, such as who, what product, when, for how much and through what channel. Those five elements will lead to many data variables, but those are the basics of the CRM.”
Ferranti agreed that your goals need to be on target to obtain valuable data. “All too often, data conversations begin with phrases like ‘ingesting social touches’ or ‘cleaning out data’—you don’t have a data strategy to be clean or social—you do it to grow the value of customers, acquire new ones and keep them longer,” he said. “Start there, and you’ll target the right data in the first place. Goals should be practical, move you to a competitive advantage and be driven by business users.”
2. Ask The Right Questions
The questions you ask your database are as important as your business objectives. Brian Mattingly, president and CEO of Welcomemat Services, Atlanta, explained why with an example. “Data collection is very industry-centric,” he said. “For example, an auto center wants to store vehicle type, year and model, last service data, last oil change date, etc. They may also want to try to capture email and physical address information, so they can set up an automation scheduled based on the collected data to send out reminders about upcoming service needs, service tips, etc.”
As you can see, an auto shop’s business goals center around keeping existing customers engaged and visiting the store, whereas a new business would instead try to gain new customers. Thus, the process of gathering information and asking questions will be different.
For all types of business, however, Ferranti recommended a simple first step for data collection. “A great place to start is the email address,” he said. “It’s the ‘primary key’ to the internet. You can do anything from data enhancement, to messaging, to developing audience profiles and retargeting ads with the email address.”
For more general question suggestions, Ferranti listed these tried-and-true examples:
- Who is this target audience? What are the key demographics and psychographics?
- What was their original source of acquisition?
- What promotion led them to become a customer?
- Which products have they purchased?
- What is the timing and frequency of their purchases?
- What other interactions have [you] had with the customer?
- How engaged are they?
3. Check In at Every Step
A data strategy cannot be an autonomous campaign—it must be screened at every step to see what’s working and what’s not. “Monitoring the success of campaigns should be an indicator as to the value of the data points being targeted,” said Mattingly. “Understanding open and click-through rates on email can help determine the success of data-driven campaigns. On the direct mail side, it’s important to understand redemption levels through tracking; this, too, will be an indicator of campaign success.”
Yu agreed that a data strategy should be examined at every stage. “Take a phased approach,” he suggested. “The initial steps must be about eliminating pain points, but one should not lose sight of the long-term business goals. This is important as each phase may call for different types of talents and expertise.”
4. Avoid Common Traps
With data strategies, there are several mistakes that can derail the whole campaign. It’s important that you arm yourself with the knowledge you need to avoid these problem areas.
Yu suggested putting business goals ahead of technology and analytics considerations, as well as enforcing the data strategy consistently. “Make sure that there is an internal champion of data strategy, and make sure that all decisions are made based on business priority, not the interest of Internet Technology (IT),” he said. “Chief data officers must represent business interests first, fully understanding the capability and limitations of technology and toolsets.”
For Ferranti, a data strategy will fail if the goals set at inception are not on target. “Don’t start with variables—we want to collect and use X,” he said. “Start with the outcomes in mind. Articulate what success looks like if you had a great data strategy in place. Go ahead and think big at this stage. What would happen if you had a great data strategy in place?”
Additionally, he asserted that businesses should not get wrapped up in the “big data” trend. “‘Big data’ [is] a buzzword pundits love, and experienced practitioners roll their eyes when they hear it,” he said. “Big doesn’t matter. Your goals and objectives matter. Getting the right product to the right individual at the right time matters.”
5. Measure Success Accurately
To judge whether or not your data campaign is successful, there’s one key metric to look at. “Success should be measured through sales now and over time,” said Ferranti. “The composition of your sales should be further measured, that is the value of sales data-driven marketing drives. Full price versus discount purchases, for example, aren’t the same. Just ask any retailer who is hurting out there right now from the ‘culture of coupons’ that’s been created.
“Success ultimately is when data-driven marketing empowers you to acquire the right customer as defined by value upfront and over time, and the rate and effectiveness that customer value [has] created,” he added.