Some people like to joke that marketing is really just a combination of pretty designs and interesting words. But while design and content are key components to successful marketing, today’s best B2C marketers know there’s a LOT more to it than that.

While you might think of a traditional marketer as a right-brained, creative professional, marketers today need to add a new qualification to their resume: data science.

In the past few years, data has moved from a peripheral part of marketing to become a central skill that every marketer must have. Data is now a core component of every single marketing campaign, from customer segmentation to email open rates to A/B testing. You have to analyze every aspect of your marketing in order to succeed in today’s hyper-competitive B2C market.

Here is why B2C marketers have to not only understand, but also become fluent with data — almost like a data scientist.

What is a Data Scientist exactly?

Data Scientist (n): A person employed to analyze and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.

Source: Google

The skillset of data scientists is an overlap of math and statistics, data analysis, and coding. Data scientists care about three types of analytics:

  1. Descriptive
  2. Predictive
  3. Prescriptive

Using these types of analytics, data scientists can uncover key insights into a business like:

  • What is your highest converting product line today?
  • What number of site visits predicts that an anonymous visitor will make a new purchase?
  • What channel should you use for your next marketing campaign?

True data scientists have deep technical skills and are comfortable with SQL, data visualizations, and are even comfortable working with unstructured data and much more.

Why should marketers focus on data science?

If that level of technical knowledge is intimidating to you, you’re not alone! Data science is clearly its own vocation, so why should marketers care about data science in their roles?

Well, as ecommerce and B2C becomes more competitive, the difference between success and failure can be as small as a 1% conversion rate. Organizations now expect marketers to do more.

Unfortunately, today most marketers are only looking at descriptive analytics, i.e. what has already happened. It’s important to move toward using data in a predictive and prescriptive way, to answer the questions:

“What will happen next?” and “What should I do next?”

These questions are almost always answered with data. Today’s marketers can’t just come up with a great campaign — they also have to measure and optimize it continually. This expectation comes at a time where businesses have the privilege of capturing an abundance of customer data and have little excuse not to use it to optimize campaigns and drive up revenue.

Why is it so challenging for marketers to become data scientists?

The main challenge hindering your success as a data scientist/marketer is access to reliable data. Although we live in a world with seemingly endless data, the reality is that much of it is unreachable or unreliable. Too often marketers get stuck waiting on IT or other members of the organization to understand how campaigns performed or to gain key insights into customer behavior.

This is why marketers have to own the data themselves and tie that data directly to marketing execution. Here is a checklist of the data you need to have access to:

  • Customer profile: name, age, gender, location
  • Behavioral insights: visits, preferred channel, browsing history, purchase history, average order value, total revenue generated
  • Product catalog: how buyers interact with specific products your brand offers
  • Trends: products that are highest converting, or lowest converting over time

Unfortunately, most marketers just don’t have the time or resources to learn how to do a SQL query, for example. This is exactly why you need a data platform that enables you to do the work of a data scientist — all without the full suite of technical skills.

Luckily, there is now technology that gives you descriptive, predictive, and prescriptive analytics all based on your customer data. With the right tools in hand, you can become a true data scientist.

About the Author: Rick Kennedy is Vice President of Industry Strategy at Zaius and a thought leader on data-driven retail trends. Previously, Rick was Head of Consumer Insights at Salesforce where he spearheaded the Salesforce Shopping Index and pioneered Demandware’s benchmarking practice. Rick also led segmentation strategy while running a portfolio of enterprise retail and media client engagements while at e-Dialog (acquired by GSI Commerce). Rick holds dual BS degrees from Boston College and an MBA from Babson College.