Which is better? Data-driven marketing or creative marketing? New changes in the industry are making this debate even hotter.
What’s changing and which one of these methods should you focus on?
Is digital marketing losing out because of the focus on data-driven marketing?
There’s no doubt that data is at the very core of digital marketing today. Almost every digital marketer measures their success by tracking likes, shares, conversions, etc.
Yet some feel that too much data-driven decision-making can cause people to ignore the creative side of marketing.
What is data-driven marketing decision-making?
Data-driven decision-making is simply using data to make decisions. It’s a powerful way to validate an option before you commit to it.
How does it work? You might use survey responses to choose which products, services or features to offer your audience. You could leverage user testing to find out how people use a new product or service, allowing you to identify issues before you fully launch that new item.
This decision-making might also involve analyzing smaller test markets to predict larger market performance. Sometimes it means examining changes in demographic data so you can find business opportunities and threats.
Data-driven marketing decision-making examples
Amazon uses machine learning to analyze people’s prior purchases and search behavior. This is how they decide which products to recommend.
In 2017, McKinsey reported that 35% of Amazon sales were from these recommendations. Likely this percentage has increased since then. Netflix boasts that 75% of its sales come from its product recommendation algorithm.
Starbucks had to close hundreds of locations in 2008 because they weren’t profitable. Now they use location analytics, examining things like demographics and traffic patterns. This predicts the success of a location before they invest in it.
What is creative marketing?
Creative marketing means making and delivering memorable, unique messages using invention and ingenuity. It often involves using design, art and music. This creativity results in better branding and customer experience.
Artificial intelligence, while improving, still can’t invent or innovate. Mere data analysis cannot entirely explain subtle nuances of a company’s, or its customer’s values, culture, and psychology.
Many companies, such as Apple, use a messaging architecture (a set of prioritized rules) to guide the creation of their content.
Creative marketing can also involve “soulful marketing.” This means spending time listening to a client, empathizing with their pain points, and then marketing in a genuine, true-to-self manner.
New industry changes and the data vs creative debate
Privacy concerns and violations sparked the creation of the General Data Protection Regulation (GDPR) law. GDPR has somewhat reduced the level of marketing data available.
Because of even more privacy concerns and legislation, Google plans to eliminate browser cookies in 2023. Marketers have long depended on the data from this browser tracking information.
Marketers with a data-driven-only approach may have to get more creative in how they use the data they have.
Why should you use both kinds of marketing?
They both have advantages. Data-only marketers may push cookie-cutter solutions. They might say: “Here are the numbers to watch. Here’s a dashboard you should use to measure your success.”
This requires less effort to serve more people, yet it alienates some clients. Many customers would rather you take the time to understand their pain, show empathy, and make a custom solution for them.
On the other hand, creative-only marketers may ignore all the new and powerful advantages that data analysis can provide. Millimetric reports that data-driven organizations get 2300% more customers, are 600% more likely to keep their customers, and are 1900% more profitable.
How can you make room for both kinds of marketing?
No matter how much you grow and scale, commit to knowing your clients. Build relationships. Take the time to understand their pain and how they measure success.
This requires having enough people and resources to provide at least some tailored solutions, client by client and project by project.
Commit to learning how to make better use of your data. Adverity says that 54% of all marketing agencies listed data wrangling as their biggest challenge in 2022.
What does data wrangling mean?
Data wrangling is the process of changing raw data into a more useful format. This may include:
- Merging multiple sources into a single dataset for analysis
- Identifying then either filling or deleting gaps in data
- Eliminating irrelevant or unnecessary data
- Examining outlier data (that doesn’t fit a usual pattern), then explaining or eliminating this data so you can analyze the rest
Large datasets require using automated wrangling methods. Smaller companies may only have access to manual methods.
How can you make better use of your data?
Many data processing methods may not fit your company. Don’t let basic data operations tie up your creative resources that could be better used on more creative activities.
Don’t focus on all your data, but only on what is relevant.
How can you find which data is relevant?
Clarify your most important goals. Determine which data can help you reach those goals. You should use each of the 4 main types of data analysis.
Descriptive analysis answers what happened: “What were sales last quarter?” Diagnostic analysis seeks to answer why it happened: “Why did our sales increase from the previous quarter?”
Predictive analysis helps you know what will happen: “What will our sales be next quarter?” Prescriptive analysis helps you see what to do about your findings: “Build 25% more product based on predicted demand.”