3 Tips for Using Consumer Data to Create More Personalized Experiences Today's consumers expect personalized experiences from brands, and data is the key to delivering on that promise and improving the overall consumer experience.

The world looked a lot different 50 years ago. The first cable network had just debuted, the compact disk was still cutting-edge technology, and the official birthday of the internet was more than a decade away. Consumer expectations also looked quite different in 1972. For the most part, consumers expected the basics from brands: good service, quality products and reasonable pricing. As long as you could deliver on those three points, you were likely to win the hearts (and wallets) of your target audience members.

Today's entrepreneurs, however, are playing a whole other ballgame, and consumers have learned a new pitch or two. Not only do modern buyers want a consumer journey that connects seamlessly across digital channels and touchpoints, but they also demand precisely tailored interactions, offers and experiences.

Related: Why a 'Personal' Customer Experience Is Critical to Your Business Success

Per Salesforce's "State of the Connected Customer" report, about 80% of people now consider the overall consumer experience equally as crucial as a business's products or services. Another 66% expect companies to understand and meet their needs, and more than half expect predictive personalization when it comes to offers.

In many ways, this isn't news. Salesforce's research proves something that many entrepreneurs already know: Creating one-to-one consumer connections through predictive personalization has become table stakes. Yet, companies continue to strike out. The same Salesforce report found that two-thirds of consumers believe companies still treat them just like cogs in the wheel. The question entrepreneurs must answer in this modern competitive landscape, then, is how they can evolve to improve the overall consumer experience.

How to leverage data to achieve predictive personalization

Any business worth its salt strives to understand its target audience and create scalable personalized messaging — and for good reason. The benefits of improving the consumer experience are well-documented. According to a survey by KIBO Commerce, Monetate and Certona, 70% of organizations that employed advanced, AI-driven personalization enjoyed an ROI of at least 200%.

In practice, however, achieving this level of personalization in digital marketing isn't so easy. That's because crafting truly customized 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

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

Additionally, consider what kind of questions you have about your target consumers. Addressing these queries 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 required to achieve these objectives. This could be consumer behaviors on specific marketing channels, audience demographics or external factors such as seasonal trends.

Businesses have long relied upon third-party data from website cookies to track consumers' web activity and customize advertisements and product offerings. However, with Google planning to sunset third-party cookies by next year, you'd be wise to plan ahead and prioritize collecting first-party data directly from consumers. To that end, look at your current technology stack, and ask yourself: What data do I already have access to, and how is it tagged?

2. Level up your audience segmentation

The fact of the matter is that demographic data alone won't help you deliver the personalization in digital marketing that 71% of modern consumers expect, according to McKinsey & Company. Yes, audience segments are still important. But when you employ only traditional segmentation with historical data, you pigeonhole consumers.

Humans contain multitudes, meaning they'll likely fall into multiple segments. Just because someone fits into a particular segment when interacting with your website this month (or even this day) doesn't necessarily mean they'll fit into that segment when they return. So, to improve the overall consumer experience, you need to enable dynamic audience segmentation.

In doing so, you'll allow consumers to move in and out of specific segments in real time, as their contexts shift and preferences change. Ultimately, dynamic audience segmentation is about meeting consumers where they are at that moment.

Related: Why Segmenting your Target Audience Is Essential

3. Put your consumer data to work

Once you've got dynamic audience segmentation in place, you can start improving the overall consumer experience with better product and service recommendations based on numerous contextual factors — ranging from consumers' purchase and search trends to geolocation, season and even weather.

What does this look like in practice? Imagine, for example, that you run an alcohol retail business with a "buy online, pick up in-store" option. As a consumer browses your online selection, you can (and should) optimize recommendations based on what products are in stock in your physical store, whether the consumer prefers spirits or wine and what the weather looks like. After all, no one wants a hot toddy on a sizzling summer day, nor are they looking for an ice-cold beer during a blizzard.

For a real-world example of a business that knows how to leverage data to personalize audience recommendations, look no further than Netflix. You'd be hard-pressed to find two users with the same home screen recommendations. Netflix leverages consumer data so effectively that it can determine exactly what a user will most likely want to watch next. And every time they hit "play," Netflix adapts its recommendations in real time to make them even more accurate.

Related: 5 Actionable Ways to Improve Your Customer Experience

Today's entrepreneurs must listen — and I mean truly listen — to their target audience members to be successful in predictive personalization. Gone are the days when consumers expected brands to deliver the bare minimum. Today, you need to use consumer data to improve the overall consumer experience at every turn.