Marketing organizations are on a quest to become more data-driven. As a result, they use, on average, about 16 different technology platforms—but only a few organizations reap the full value of their investment.
What's more, the most recent CMOSurvey.org study predicts analytics will consume 19% of Marketing's budget by 2021. About another 22% of the budget will go to technology. Together, those two investments will account for nearly 50% of Marketing's budget.
Yet, the CMOSurvey.org study reports that only about one-third of marketing organizations use analytics to make program or strategic decisions. And less than 20% of respondents reported that the use of analytics made a significant contribution to company performance.
Despite those increases in investment and advances in technology, "marketers are still challenged to maximize the potential value of analytics," according to the most recent CMOSurvey.org study.
Tom Davenport and Jeanne Harris, in their classic book, Competing on Analytics: The New Science of Winning, provided a road map for becoming an analytical competitor and using analytics to create value and growth—the purview of Marketing.
Marketers should learn to use analytics to address at least five growth opportunities:
- Acquisition of more valuable customers
- Acquisition of customers who will buy more from you
- Acquisition of customers who will buy more of your high-value products/services
- Retention of high-value customers
- Identification of marketing activities that have the greatest impact on accelerating customer acquisition and improving retention
Move these four analytics capabilities to the top of your list
For a decade, we've known what it takes to fuel growth with analytics. Yet four recurring themes account for the majority of the challenges continuing to thwart the progress of all organizations, including Marketing, regarding analytics:
- Lack of quality data
- Lack of people (that is, the number of people needed to perform the work)
- Lack of skills (the current talent doesn't have the necessary skills to perform the work)
- Lack of predictive tools (despite all the technology that is in play, there is still a high need for predictive tools)
By working to improve those four areas, every marketing organization can be smart with its analytics.
1. Collect quality data
Data is the basic ingredient for any analytics. Many organizations continue to be challenged by the sheer volume and problematic quality of data:
- According to Domo, "over 2.5 quintillion bytes of data are created every single day." And, it's estimated that 1.7MB of data will be created every second for every person on earth by 2020.
- According to the Experian 2018 Data Management Benchmark report, "on average, respondents in the US believe that 33% of their customer and prospect data is inaccurate in some way—a figure that has increased from 28% just one year prior." That is not a technology problem. That is a human problem. Almost half of the quality issues are related to human error.
Improve quality-data collection capability with…
- Basic blocking and tackling
- A solid data management strategy
- Good data management processes
2. Incorporate data from a wide variety of sources
Although traditional sources of customer data still dominate, companies are increasing their use of newer data sources, including POS data, transaction data, and research data. Make sure your organization has a data inventory so you can know what data you have, where it is, how frequently it is updated, and who is responsible for maintaining the data.
3. Recruit, train, and retain capable talent
You need the right people to translate the data into actionable insights. Many people may have the technical training for the math, but they may lack the ability to know which data is important and the business skills that help them see the relationship between the analytics and the business.
Developing business-savvy marketing scientists means investing in your analytics people beyond their technical skills. Improve that capability by teaching current marketing scientists how to translate and use the data to tell a compelling business and customer story.
Every marketer needs basic analytics today. Make sure every new hire is analytically inclined. The days when marketers could shy away from the numbers are over.
4. Look for tools to support predictive models
There are two distinct tools that marketing organizations need to be smart with for analytics: One is the set of tools to perform the computations; the other is a set of models that help you understand the impact of an action.
- Tools. Predictive analytics software can give your company the power to see the future. Selecting a tool is just like buying a bicycle: If you're a novice, start with a beginner's bike—not too many gears, durable tires, and so on. Plan to upgrade to something more specialized, sophisticated, and complex as you gain experience.
If you're an experienced rider, then you select a bike that will help you achieve your goals. Avid experienced riders might have several bikes—one for mountain-biking, one for road-riding, one for competitive racing, and so on. The same idea holds true for analytics tools. There are numerous resources to help you learn about tools. If you're a novice, be sure the supplier provides solid training in analytics as well as in how to use the tool.
- Models. Every marketing organization should have a library of customer-centric models to help understand and anticipate customer behavior and identify when customers are at risk. Build models for all stages of the customer lifecycle. Predisposition to purchase, attribution and mix, and customer vulnerability models should be in your library. Refresh your models as new data becomes available. Update every model at least annually.
There's no going back
Analytics and martech are essential tools for Marketing. They are essential to being a nimble, effective, and customer-centric organization. Together, analytics and martech pave the way for Marketing to serve as a strategic member of the organization, to manage and measure marketing performance, and to facilitate customer, market, and product decisions.
Sometimes, knowing what to do is not enough to successfully execute a project. But you can get help to better integrate analytics into your everyday processes to achieve your goals.
