3 tips for using consumer data to create more personalized experiences

3 tips for using consumer data to create more personalized experiences

3 tips for using consumer data to create more personalized experiences

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The world was very different 50 years ago. The first cable network had just made its debut, the compact disc was still cutting edge technology, and the Internet’s official birthday was more than a decade away. Consumer expectations were also 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.

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

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

According to Salesforce’s “State of the Connected Customer” report, about 80% of people now consider the overall consumer 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 it is not new. 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 messaging – 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 experienced a return on investment 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.

Additionally, 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. These can be consumer behaviors on specific marketing channels, audience demographics, or external factors like 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, as Google plans to phase out third-party cookies by next year, it would 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 labeled?

2. Improve your audience segmentation

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

Humans contain multitudes, which means they will likely fall into multiple segments. Just because a person belongs to a particular segment when they interact with your website this month (or even this daytime) does not necessarily mean that they will fit into this segment when they return. So, to improve the overall consumer experience, you need to enable dynamic audience segmentation.

By doing so, you will allow consumers to enter and exit specific segments in real time, as their contexts change and their preferences change.. Ultimately, dynamic audience segmentation is about meeting consumers where they are at the time.

Related: Why Segmenting Your Target Audience Is Key

3. Leverage your consumer data

Once you have dynamic audience segmentation in place, you can begin to improve the overall consumer experience with better product and service recommendations based on many contextual factors, ranging from buying trends and from consumer search 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. When a consumer browses your selection online, you can (and should) optimize recommendations based on what products are in stock at your physical store, whether the consumer prefers spirits or wine, and the weather. After all, nobody wants a hot toddy on a hot summer day, or an ice-cold beer during a blizzard.

For a real-world example of a company that knows how to leverage data to personalize audience recommendations, look no further than Netflix. You would 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 is likely to want to watch next. And each time they click “play”, Netflix adapts its recommendations in real time to make them even more accurate.

Related: 5 concrete ways to improve your customer experience

Entrepreneurs today need to listen — and I mean really listen – members of their target audience to succeed in predictive personalization. Gone are the days when consumers expected brands to provide the bare minimum. Today you need to use consumer data to improve the overall consumer experience all the way.

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