Customer data is an essential part of your company's marketing strategy. With it, you can create messages that engage with specific audiences, which helps you build high conversion rates and consumer loyalty. Given the enormous amounts of data available and highly segmented audiences in today’s complex business environment, however, marketers face several major challenges.
This article discusses the key challenges in data-driven marketing and how you can overcome them by earning a degree from a top online marketing master’s program.
What is Data-Driven Marketing?
Data-driven marketing uses information from customer interactions, in addition to that from outside parties, to gain insight into consumer preferences, motivations, and behaviors. These insights allow companies to personalize their marketing strategies to enhance the customer experience.1
The term “big data analytics” refers to the large, complex data sets that require interpretation tools with capabilities beyond traditional data management software.
Customers are producing greater quantities of data—through their mobile devices and Internet of Things (IoT) devices including smart home devices, geolocation services, and fitness apps. Therefore, data sets are growing and it is becoming more challenging to gather and analyze all of this information effectively.2
The Three Types of Marketing Data
The three types of marketing data are:
- Customer data: personal data and attitudes from online interactions
- Operational data: business processes such as customer relationship management data, shipping and logistics information, and data from hardware sensors
- Financial data: marketing and sales statistics, costs, and profit margins, which help companies measure their performance for greater efficiency 2
These data are typically collected by different departments and stored in various locations.2
Why Use Big Data in Marketing?
There are many compelling reasons to use big data analytics as part of a company’s marketing strategy. Data-driven marketing helps businesses reach the right customers with targeted campaigns.3 According to McKinsey research, 71% of consumers expect targeted, personalized interactions from the businesses they support, and 76% become frustrated when those types of interactions don’t occur.4
Using data helps companies quickly see which marketing strategies are working and which aren’t, and insights from data analysis show them how potential customers are learning about the company’s products and services. Knowing the social media platforms and websites that the consumers use, and when they visit, can provide valuable information for targeted marketing campaigns. Data also helps to illustrate the marketing team’s successes in presentations to company executives.3
Data-driven marketing is a key future trend since it has been shown to boost a company’s profits.3 In a Deloitte survey, businesses that had data-driven cultures were twice as likely to exceed their goals than those not focused on strategically using data.5 According to Zippia, organizations that use big data increase their profits by approximately 8% and reduce costs by about 10%.6
The Biggest Challenges in Data-Driven Marketing
Today’s marketing professionals must be able to navigate large amounts of data coming from myriad sources. They must also know how to manipulate and analyze that data for actionable insights in order to create marketing strategies that keep up with the changing market environment and customer expectations.
The biggest challenges in data-driven marketing are:
Maintaining High-Quality, Relevant, Timely Data
It is extremely important to use high-quality data to guide marketing decisions and strategic shifts. How big a problem is this? According to an Accenture study, just one-third of companies believed that their data was trustworthy enough to be effectively used and valuable.7 Marketing data must be timely, accurate, and complete, and this requires close maintenance and regular updates.
Since changes in the market occur very quickly, real-time data, such as information that comes from customer devices, is especially useful. However, it must be gathered, analyzed, interpreted, and acted upon before it loses its relevance.8,9
Avoiding Data Silos
For many organizations, crucial data about customers and business operations are found in multiple systems (silos) that are overseen by different departments, such as web analytics, email marketing, and customer relationship management (CRM). This makes it very hard to get a complete picture of the customer’s journey and to understand how the various channels interact. To solve this problem, a company should centralize its data using business intelligence (BI) tools.10
Cleaning and Normalizing Large Amounts of Data
To be analyzed, marketing data must have a consistent target schema—that is, it must be organized logically. Since it’s being pulled from a wide array of sources in a multitude of formats, it can be a challenge to clean and normalize (harmonize) it. This requires significant database expertise.9,11
Remembering the People Behind the Data
With the immense amount of data being collected and analyzed, one danger is to lose sight of the forest for the trees, so to speak: When marketers are so deeply focused on the data, they may forget the unique individuals at the source of that data. Customers want brands to pay attention to their needs, and they want to know that the company’s service or product will solve their problems.8
Using a Scalable System
Many marketing departments are engaged in large-scale, multichannel operations, and yet they’re using legacy systems, such as spreadsheets, for their analytics. These older systems weren’t built to handle large volumes of data. This will slow down the entire process of collecting, analyzing, and interpreting marketing data so that it can be effectively acted upon. If a company can’t trust its data, it’s less likely to be able to make timely data-driven decisions. The solution is to upgrade to a newer BI system that can handle the load, while interfacing with legacy software for easier migration.10
Understanding How to Interpret Data
If a company wishes to use its collected marketed data to make strategic decisions, there must be someone who can interpret that data. The information can be complex and spread out across various channels, and it’s important to make fast, informed decisions. Data-driven marketing professionals with up-to-date skills can make sense of the data to find patterns and trends.9
Having the Skills and Resources to Use Marketing Analytics Effectively
As marketing data becomes ubiquitous and data-driven analysis more complex, the need for data literacy skills increases. A 2020 Qlik/Accenture survey found that just 21% of employees had confidence in their data literacy skills, while 74% of employees working with data felt uncomfortable and overwhelmed.12
Companies that lack the skills and resources to use marketing analytics to their full potential can limit their ability to make informed, data-driven decisions and keep pace with the competition. This points to the need for more experience and training.11 This is perhaps the greatest challenge since data-driven marketing is changing so rapidly.
Become a Data-Driven Marketing Guru with an Online Master’s in Marketing
The Santa Clara University Leavey School of Business Online Master of Science in Marketing program will prepare you to be a highly sought-after marketing professional, with the latest tech skills that employers need, right now and in the future.
The immersive Online MSM curriculum helps you take a deep dive into marketing trends and technology, marketing analytics, channel marketing, social media marketing, and other technical skills that you’ll need to stand out in the world of MarTech and advance your marketing career.
- Retrieved on October 14, 2022, from gartner.com/en/marketing/glossary/data-driven-marketing
- Retrieved on October 14, 2022, from talend.com/resources/big-data-marketing/
- Retrieved on October 14, 2022, from yokellocal.com/blog/benefits-of-data-driven-marketing
- Retrieved on October 14, 2022, from mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying
- Retrieved on October 14, 2022, from deloitte.com/us/en/insights/topics/analytics/insight-driven-organization.html
- Retrieved on October 14, 2022, from zippia.com/advice/big-data-statistics/
- Retrieved on October 14, 2022, from accenture.com/_acnmedia/pdf-108/accenture-closing-data-value-gap-fixed.pdf
- Retrieved on October 14, 2022, from bdex.com/blog/top-6-challenges-data-driven-marketers-face/
- Retrieved on October 14, 2022, from adverity.com/blog/7-challenges-of-your-data-driven-marketing-strategy
- Retrieved on October 14, 2022, from domo.com/learn/article/the-five-biggest-challenges-to-data-driven-marketing
- Retrieved on October 14, 2022, from towardsdatascience.com/understanding-data-engineering-jargon-schema-and-master-branch-525dff66fcb8
- Retrieved on October 14, 2022, from accenture.com/_acnmedia/PDF-115/Accenture-Human-Impact-Data-Literacy-Latest.pdf