How to Turn Big Data into an Actionable Marketing Tool

Print Friendly, PDF & Email

mike_iaccarinoIn this special guest feature, Mike Iaccarino, Chairman and CEO of Infogroup, contends that many of the more advanced approaches to big data analyses are not widely practiced among marketing organizations today. In order to turn big data into a valuable marketing tool, brands must do several important things. Mike served as the President and Chief Executive Officer of Mobile Messenger from 2009 to 2011, establishing the company as one of the dominant mobile technology players in North America. Prior to joining Mobile Messenger, he was Chief Executive Officer of Epsilon from 2001 to 2009, transforming Epsilon into one of the United States’ leading database marketing companies. He holds a B.S. in Accounting and English from Boston College where he graduated magna cum laude and is a former Certified Public Accountant.

Consumers are creating a digital footprint with every tweet, online purchase, Facebook post, Google search, and more. For marketers, these insights into the digital ecosystem have become the driving force behind the creative and messaging strategies for successful marketing campaigns.

However, simply having access to data is not enough to execute marketing campaigns that generate incremental marketing ROI. The actionable insights a company can derive using basic customer data analysis (focusing solely on demographic data) is marginal, at best. To truly turn customer data into an actionable and strategic marketing asset, marketers need to look at their customers from a more holistic vantage point. By using multiple sources of data, including purchase information, website history, open and click activities will enable the marketer to complete the customer’s journey from awareness, to interest to purchase activity. In essence, by having the right data to conduct a retrospective analysis to close the loop and actually measure the sales impact of a campaign is the optimum approach marketers need to recognize the actual ROI of their media spend.

Unfortunately, many of these more advanced approaches to big data analyses are not widely practiced among marketing organizations today. In order to turn big data into a valuable marketing tool, brands must do the following:

Leverage Multiple Data Types to Create Customer Micro Segments

Today, data is a critical component to a company’s marketing success. Creating and segmenting audiences across multiple touch points enables marketers to launch truly micro-targeted campaigns. To do so, brands must gather information from a variety of sources.

While some companies rely solely on first party data (such as purchasing history or email addresses), savvy marketers are incorporating second and third party data for a more robust understanding of their target segment groups. Outsourcing for second and third party data helps marketers build a rich portrait of shoppers that clearly depicts how they’re engaging on specific channels, including offline. Linking merchandise purchase history, demographics, lifetime value and fundamental recency, and frequency purchase behaviors, such as repeat, new, reactivated, or lapsed customers provides the marketer with the necessary 360 view of its customer. Marketers who leverage all of these data assets are able to create mutually exclusive segment differentiators that drive actionable marketing programs, which is the key to marketing program’s success.

To make these insights actionable, brands can then create localized audience micro segments from larger data sets. Marketers can leverage these groupings to build out customized creative strategies with targeted messaging and reach every segment with relevant information across a variety of digital channels and devices. This approach offers shoppers a more engaging customer experience and strengthens the brand relationship with the consumer.

Understand Relative Penetration

Many businesses falsely believe that the largest customer segment will drive the most revenue based solely on the recognized numbers. However, this is typically not the case. Marketers need to calculate relative penetration by determining the percentage of the total market each customer group represents.

For example, a business might have a lot of customers within a certain income bracket, but the percentage of the total number of consumers in that income bracket might be much lower compared to its other segments. In this case, the largest group of customers does not actually hold the most potential due to the low relative penetration compared to other income segments. This company would be smart to focus more of its efforts targeting the groups with smaller numbers but with a higher penetration rate.

Close the Loop on Big Data

With the right customer groups and relative penetration in mind, marketers can then quantify the impact of the  marketing program by tracking the cause and effect of when, where and why outreach efforts are driving sales. For example, if brands are sending multiple emails, direct mail and targeted display ads on third party publisher sites like Facebook, it’s crucial to be able to attribute the impact of the digital channel, message and/or offer is responsible for stimulating the customer to take action.. Brands would not be able to do this without the insights provided by big data linked to the marketer’s first party purchase history.

Closing the loop on big data can help marketers determine when they should up the ante on their current efforts, or perhaps when they should explore alternative audience segments or marketing channels. By leveraging the insights derived from big data, marketers can make more precise, more intelligent, sales-driving decisions that improve the customer experience and optimize the media spend.


Sign up for the free insideAI News newsletter.



Speak Your Mind