Data has become something of a holy grail for modern marketers, offering insights that not only help businesses better attract and retain consumers but also provide an improved experience for those consumers. It’s why 63% of marketers increased their spending on data-driven marketing in the last year. Consumer data is especially valuable in retail, where the ability to deliver a truly personalized experience for each shopper can give a retailer a competitive edge over its peers.
However, much of this potential is trapped behind improper data organization and management. Properly gathering and organizing data is a crucial step for tapping into the full value of consumer information. Otherwise, marketers can’t make truly data-driven decisions that improve the retail consumer experience.
In particular, a poor data tagging strategy can hinder the quality of insights into consumer behavior and actively steer retail marketers in the wrong direction. For instance, if purchases are tagged incorrectly, it could cause marketing teams to make decisions based on inaccurate data and prevent data-driven practices from scaling as their businesses grow. As more data is collected, the problems of poor data organization will only compound and lead to challenges with delivering personalized content for consumers.
So if you don’t want to get caught in a mess of unusable metrics, organizing your data correctly needs to be a top priority. By gathering and organizing data consistently with a data science foundation, you make it easy to deliver personalized, scalable experiences that are based on consumer preferences, purchasing behavior, geographical information and other demographics. Well-managed data can lead to better, more relevant personalization, allowing you to deliver the proactive and customized experiences that modern consumers expect.
If you’re a retail marketer struggling to figure out how to best organize your data to turn it into actionable insights for personalization, you’re not alone. Data organization and personalization aren’t automatic processes. They require the right planning and the right technology. Luckily, this planning doesn’t need to be overcomplicated.
Ask yourself these questions to get started organizing and using your data effectively for personalization:
1. What business objectives will personalization help you achieve?
There are a wide variety of business objectives that can benefit from the data you collect for personalization. Whether you want to increase the number of completed checkouts, develop more accurate product recommendations or grow your CRM, personalization can help. But fashioning the data into the right shape after the fact can be extremely difficult, if not impossible.
You first need to figure out what you want to get out of the data you collect. Set business goals specifically designed to take advantage of personalization. That way, not only will you know the destination you want to reach, but you’ll also be able to figure out exactly what data you need to get there.
2. What data do you need to reach your objectives?
Once you have clear business objectives, you must determine the kind of data you need to make those goals a reality. This could be historical data (such as purchasing and browsing data), demographic data (such as age and location information), or contextual data (such as changing consumer preferences according to weather or events).
The important thing is to know what you’re looking for so you can better gather and organize the data for more accurate, efficient personalization.
3. What does your current data organization process look like?
To move forward with a better approach to your data and personalization goals, you first need to reassess what you’re doing right now. Look at your current technology stack. Examine what data you already have access to and how it’s currently getting tagged and organized. At this stage, you will need some data science expertise, either as a resource on your team or a tool built on a foundation of data science.
You’ll likely find some areas that fall short of your needs. It might be that you lack the necessary technology, or it might be that your current data organization strategy is not working correctly for your personalization goals. Finding gaps in your process shouldn’t discourage you. Instead, frame it as an indication that you’re now putting yourself on the right path toward data-driven personalization decisions.
A purposeful approach to data collection and management is essential for retail marketers in today’s environment, where personalization is no longer a nice addition but an expected feature. By creating clear objectives and ensuring that your data is properly organized, you can develop a marketing strategy that’s tailor-made for the modern consumer, better for your company’s bottom line and scalable.
Diane Keng is the CEO and Co-founder of Breinify, an AI and predictive personalization engine that helps brands curate dynamic, meaningful experiences for their consumers at scale. Keng is on Forbes’ 30 Under 30 for enterprise technology and has been featured in The Wall Street Journal, HuffPost, TechCrunch, OZY and Inc. Magazine. She ran three successful businesses before she was 18 and is a noted software innovator who frequently speaks on the intersection of AI, personal data, privacy and the future of smarter products.