3 tips for using consumer data to create more personalized experiences

The opinions expressed by entrepreneurs contributors are their own.

The world was very different 50 years ago. The first cable network had just debuted, the compact disc was still state-of-the-art, and the Internet's official birthday was more than a decade away. expectations also seemed very different in 1972. For the most part, consumers expected the basics of brands: good service, quality products and reasonable prices. As long as you could stick to these three points, you were likely to win the hearts (and wallets) of your target audience members.

Entrepreneurs today, however, are playing a whole different ball game, and consumers have learned a new argument or two. Not only do modern buyers want a customer journey that connects seamlessly across digital channels and touchpoints, they also demand precisely personalized interactions, offers and experiences.

Related: Why a "Personal" Customer Experience is Critical to Your Business Success

According to the 'State of the Connected Customer' report, around 80% of people now consider the overall customer experience to be as crucial as a company's products or services. 66% expect businesses to understand and meet their needs, and more than half expect predictive personalization in offerings.

In many ways, this is not news. Salesforce research proves something many entrepreneurs already know: building one-to-one relationships with consumers through predictive personalization has become a big deal. Yet companies continue to go wild. The same Salesforce report found that two-thirds of consumers think companies still treat them like cogs. So the question entrepreneurs need to answer in this modern competitive landscape is how they can evolve to improve the overall consumer experience.

How to use data to achieve predictive personalization

Any business worth its salt strives to understand its target audience and create scalable personalized messages, and for good reason. The benefits of improving the customer experience are well documented. According to a survey conducted by KIBO Commerce, Monetate and Certona, 70% of organizations that have used advanced AI-based personalization have seen an ROI of at least 200%.

In practice, however, achieving this level of personalization in digital marketing is not so easy. Indeed, creating truly personalized experiences at scale requires going beyond rudimentary audience segmentation and simple data collection. With that in mind, here's how to leverage data to achieve predictive personalization:

Related: Personalization: A Perspective on the Future of Targeting

1. Ask the right questions

Companies often fail in their predictive personalization efforts because they don't ask the right questions. So first ask yourself what business goals predictive personalization could help you achieve. Your goals should be both specific and measurable.

Also, think about the type of questions you ask about your target consumers. Answering these questions will help your marketing team identify actionable insights and personalization use cases that make sense for your business. Next, ask yourself what consumer data is needed to achieve those goals. This can be consumer behavior on specific marketing channels, audience demographics, or external factors such as seasonal trends.

Companies have long relied on third-party data from website cookies to track consumer web activity and personalize advertisements and product offers. However, with the planning of