How to use your marketing analytics smartly

The latest survey predicts that the analysis will consume 19% of the marketing budget by 2022. Another 22% of the budget goes to technology. Together, these two investments will represent around 50% of the marketing budget.

However, the CMOsurvey.org study reports that only about a third of marketing organizations use analytics to make strategic or program decisions. And less than 20% of respondents indicated that using analytics significantly contributed to business performance.

Despite this increase in investment and technological advances, “marketers still face the challenge of maximizing the potential value of analytics,” according to the latest study by CMOsurvey.org.

Tom Davenport and Jeanne Harris, in their classic book competing on Analytics: The New Science of Winning, offer a roadmap to becoming an analytic competitor and using analytics to create value and growth: the marketing sphere.

Marketers need to learn how to use analytics to address at least five growth opportunities:

  • Acquire the most valuable customers
  • Attract customers who will buy more from you
  • Attract customers who will buy more high-quality products / services
  • High-quality customer loyalty
  • Identify the marketing activities that will have the greatest impact on accelerating customer acquisition and improving retention

Move these four analysis items to the top of your list

For ten years, we’ve known what it takes to drive growth with analytics. However, four recurring themes are responsible for most of the challenges that continue to hamper the progress of all organizations, including marketing, in the analysis:

Lack of quality data

  • Lack of people (ie the number of people needed to do the job)
  • Lack of skills (current talent doesn’t have the skills to do the job)
  • Lack of predictive tools (despite all the technology that comes with it, there is still a great need for predictive tools)

When working to improve these four areas, any marketing organization can be smart with its analytics.

1. Collect quality data

Data is the main ingredient for any analysis. Many organizations still face the challenge of the sheer volume and problematic quality of data:

  • According to Domo, “over 2.5 million bits of data are created every day.” It is estimated that by 2022, 1.7MB of data will be created per second for every person on Earth.
  • According to the 2018 Experian Data Management Benchmark report, “US respondents found that an average of 33% of customer and prospect data was somewhat inaccurate, a number that has increased by only 28% in just 28 years. ” This is not a technology issue. This is a human problem. Almost half of the quality problems are related to human error.

Boost the ability to improve quality data collection with…

  • Basic block and attack
  • A solid data management strategy
  • Good data management processes

2. Add data from a wide variety of sources

As traditional customer data sources continue to dominate, companies are increasingly taking advantage of new data sources, including POS data, transaction data, and survey data. Make sure your organization has a data inventory so you know what data you have, where it resides, how often it is updated, and who is responsible for maintaining it.

3. Recruit, lead, and retain competent talent

You need the right people to translate data into actionable information. Many people have a technical background in math but may lack the ability to know what data is important and the business skills that help them see the connection between analytics and business.

Developing marketing scientists with business experience means investing in their analytical people as well as their technical skills. Hone this skill by teaching today’s marketing scientists how to translate and use data to tell a compelling story of business and customers.

Every marketer needs a basic analysis these days. Make sure each new rental is analytically biased. Gone are the days when marketers could walk away from the numbers.

4. Look for tools to support predictive models for marketing analytics

There are two different tools that marketing organizations need to be smart about for analysis: one is the set of tools to perform the calculations; the other is a series of models that help to understand the impact of an action.

  • Predictive analytics software can empower your business to see the future. Choosing a tool is like buying a bike – if you’re a beginner, start with a beginner’s bike, not too many gears, durable tires, and so on. Plan to move to something more specialized, sophisticated, and complex as you gain experience.

If you are an experienced rider, choose a bike that will help you achieve your goals. Avid and experienced cyclists can own several bikes: one for mountain biking, one for road riding, one for competitive racing, and so on. The same idea applies to analytical instruments. There are several resources available to help you learn more about the tools. If you’re a beginner, make sure the vendor provides full training in the analysis and use of the tool.

  • Every marketing organization should have a library of customer-centric models to understand and anticipate customer behavior and identify when customers are at risk. Create templates for all phases of the customer lifecycle. Customer predispositions to buy, assign, and match vulnerability models and models must be present in your library. Update your models as new data becomes available. Update each template at least once a year.

There’s no going back

Analytics and martech are essential tools for marketing. They are essential to being an agile, effective, and customer-oriented organization. Together, analytics and martech pave the way for marketing to act 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 complete a project. But you can get help to better integrate analytics into your daily processes to achieve your goals.