Move over, synergy, there's a new buzzword in town: big data. Okay, so maybe the idea of "big data" isn't new, per se (its roots date back decades), but marketers have taken renewed interest in recent years. A Google search of "big data" produces thousands of results and varying definitions. So, what exactly is it?
In simple terms, big data refers to massive data sets that are analyzed to reveal patterns and trends intended to inform better business decisions. Think Amazon and its ability to recommend products based on a customer's purchasing habits.
Not everyone, however, believes bigger is better when it comes to data analytics. Stephen H. Yu, president and chief consultant for Willow Data Strategy LLC, Old Tappan, N.J., is pushing for smart data instead. "Big data in itself should never be the goal, as the size of the data doesn't mean anything for decision-makers and marketers," he said. "What they need are smart answers in bite-sizes that they can use without having to have a degree in statistics."
Take the weather, for example. "A weather forecast is based on tons of data, but reads like: '70 percent chance of snow showers Friday afternoon.' Anyone can act on such information, and marketing answers should be like that, too," he contended. "When dealing with customers and prospects in near real-time, there is no second to waste to go through thousands of data points."
The only way to achieve smart data is through smart practices. This means having a proper strategy in place, employing best practices and prioritizing time. To make sure you don't miss the mark, Print+Promo asked Yu and Summer Gould, president of Eye/Comm Inc., Santee, Calif., for five of their best tips. Here is what they had to say:
1. Outline a Proper Data Strategy
Without a clear plan, companies will struggle to yield a positive ROI. The first step in outlining a data strategy is to create a data plan in your marketing plan. "You need to have goals and an overall idea of what you are trying to accomplish with your marketing before you can outline your data plan," Gould said.
Once the goal has been set, figure out what you want to capture and how you are going to get it. Then, determine how that data is going to be used. "Just having the data is not enough; you need to plan out ways to capitalize on it with analytics and reporting," Gould remarked. "Being able to group like people together for messaging will help you have less complicated campaigns."
Yu agreed, adding that it should always be about the business first—don't use a pile of existing data just because it's there. "Though that's better than not using it at all," he maintained.
Putting the business first also means sharing the data strategy between the involved divisions. "Most inter-department conflicts and delays in projects originate from communication breakdown," Yu noted. "And such breakdown cannot be resolved if there is no common business goal.
"That is why chief data officers (or chief information officers for that matter) must represent business interests first, with a deep understanding in enabling technologies and data sources," he continued. "If chief data officers, chief information officers or chief technology officers put technology issues above business goals, the organization is doomed."
2. Don't Be a Data Hero
Sizable data isn't the only "big agenda" being tossed around. In today's corporate landscape, the emphasis is on big campaigns, big ideas and, of course, big returns. When it comes to data—even big data—there is something to be said for the accumulation of small successes and improvements. For this reason, Yu suggested outsourcing from the beginning.
"If a company tries to do every aspect of data work internally, the amount of investment (software, hardware, storage, personnel, training, etc.) becomes so large, so that only huge jackpots would look like a real success," he said. "That is like setting up a ketchup factory for every household, without considering economy of scale. So, start small with a proof of concept."
3. Make Time for Data Refinement
Data refinement should precede any analytical activity. If you're waiting for a "genius data scientist" to show up and make sense of your mess, you're out of luck, Yu said. Marketers have to invest in this important step. During the refinement process, data is verified, edited, standardized, categorized and summarized, Yu explained. He offered the example of SKU level data.
"Even small businesses may carry hundreds of thousands of unique products. If they are not categorized and tagged properly, the product data become unusable free-form data for analytics," Yu said.
"Imagine a case where the very top product doesn't even represent 1 percent of the total sales. But if the products are properly categorized, they become the most potent predictor in analytics."
If marketing is the goal, Yu said, databases must provide a "buyer-centric" view—not just brand-, division-, channel- or event-centric views. "That must start with the proper definition of an individual, but unfortunately, most databases are not capable of answering a simple question like 'How many 24-month active customers do you have?' If the answer is: 'We have a million-ish email addresses,'" he continued, "well, that is not even close."
4. Let It Go
Holding on to old data is one of the biggest mistakes a marketer can make. Because companies are operating in an age of large data, they must be able to harness answers out of their data, as Yu previously mentioned. "Just like lots of rocks are thrown out during the refinement process of gold, irrelevant data must be dropped along the way," Yu instructed. "Now, the tricky part is that such relevancy depends on the business goals, and it should be determined by mathematics, not someone's hunch. That is the reason why the business goals must be set first, and enabling analytics must dictate database structure."
5. Clean Your Marketing Database
Database maintenance is a constant work in progress. Yet studies show that up to 20 percent of records within a typical house file are undeliverable, according to Gould. "You are wasting money sending offers to people who either are not getting them or are being offered something they are no longer interested in," she said.
A clean database will also help companies avoid penalties assessed by the USPS. Gould recommended using move update tools such as the National Change of Address (NCOA). The USPS maintains the NCOA file, which contains any nationwide address changes that have occurred over the last 48 months. Other beneficial tools include a deceased file (removing people when they die) and surveys (keeping information current by going directly to the source), Gould added.
While your marketing database doesn't need to be cleaned every day, limiting maintenance to a quarterly basis would be a disservice to your company, Gould concluded.