Request Demo

The 3 Qualities a Great Data Science Leader Needs in 2021

December 15, 2020

In this article you will learn:

To remain afloat in the midst of COVID-19, companies had no other choice but to make significant changes. This included accelerating their digital transformation so they could better address the needs of the market. As dramatic as these initial moves may have been, for many companies they represented just the first baby steps.

Achieving true digital maturity requires companies to fully embrace data and analytics. Nowhere is this more important than in marketing, which will drive customer loyalty and retention efforts that are vital to helping businesses survive throughout the pandemic and thrive in the long term. The key to making this work is data science.

Data science capitalizes on expertise at the intersection of business analytics, computer science and statistics. Using traditional software and research techniques, combined with advanced marketing technology that leverages artificial intelligence and machine learning, data science can uncover unique insights and, in essence, predict the future. In marketing, a data scientist can answer important questions, such as identifying the most promising customers, understanding what consumers think of your brand and determining which marketing offers may be most relevant and deliver the best results.

To achieve greatness in data science in 2021, and put in place a strong foundation for digital maturity, your marketing team will need to hone three important qualities.

3 Key Things Data Science Leaders Need in 2021

#1 – Know your customers

Of all your company's assets, one of the most important ones – customer data – isn't accounted for on the corporate balance sheets. Even so, you probably realize how valuable it is.

Organizations are now more disciplined about monetizing, managing and measuring customer data, much like they do with other corporate assets. They use this customer information in many ways, spending it like cash, selling/licensing it to others, participating in emerging data marketplaces, applying asset management principles to improve its quality and availability, and quantifying its value and risks in a variety of ways, according to Gartner.

Collecting and continually updating this information is the lynchpin for understanding your customers, taking the right actions to retain them and keeping ahead of your competition.

#2 – Improve customer loyalty

Smart brands are pivoting from spending on product- or performance-based marketing, and instead focusing that budget on retaining customers. Forrester predicts that spending on loyalty and retention marketing will increase by 30% as brands double down on driving recurring purchases from existing customers. And data science is critical in improving the effectiveness of loyalty and marketing offers

As a first step in this process, many companies are revamping their loyalty programs, evolving from offering a frequency-based rewards program to becoming a loyalty company. Brooklinen is one example of a company that has pivoted, relaunching its Comfort Crew loyalty program with new membership levels that unlock greater benefits, including exclusive access to events and sales, and points for taking a variety of actions.

#3 Construct offer variations from customer insights and then optimize them

Data science can help improve effectiveness of loyalty by enabling creation of multiple variations of offers that give customers the relevance they demand. As consumers have higher expectations of their digital communications since the pandemic hit, and data science can help them take this to the next level.

If you think you can set and forget your marketing campaigns, you're setting your company up to fail. You need to continually test, analyze and adjust offers to optimize loyalty and customer retention.

In the post-COVID era, marketing teams need to be more flexible and agile than ever. Data science makes this possible, allowing you to experiment faster and fine-tune offers to get the best results.

Traditional offer creation and deployment tools can't cut it. Be sure to reassess your MarTech stack, with data science in mind, to ensure it supports tracking, testing and reporting. These capabilities are important because data science requires the analytics to target customers based on any attribute, and personalize offers along any dimension. And having the right MarTech stack will also continuously feed more information back to data science to keep them on the cutting edge of customer insights.

By focusing on these aspects through the lens of data science, your company can be well positioned to reach the highest levels of digital transformation, and deepen customer loyalty to strengthen your business long into the future.

Learn more on how data science plays an important role in retention marketing. Read our latest white paper, Formation’s Ultimate Guide to Measuring Customer Loyalty Offers.