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3 tips for using consumer data to create more personalized experiences

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The world looked very different 50 years ago. The first cable network had just been launched, the compact disk was still the very latest technology and the official birthday of internet was more than a decade away. Consumer expectations also looked 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 live up to those three points, you’d probably win the hearts (and wallets) of your target audience members.

However, today’s entrepreneurs are playing a very different ball game and consumers have learned a few new pitches. Modern buyers not only want a consumer journey that connects seamlessly with digital channels and touchpoints, but they also demand precisely tailored interactions, offers and experiences.

Related: Why a “Personalized” 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 as crucial as a company’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 is not news. The Salesforce research proves something many entrepreneurs already know: creating one-to-one consumer connections through predictive personalization has become a staple. Yet companies continue to fail. The same Salesforce report found that two-thirds of consumers believe companies still treat them like a cog in the wheel. The question entrepreneurs need to answer in this modern competitive landscape is how they can evolve to improve the overall consumer experience.

Using data to achieve predictive personalization

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

In practice, however, it is not so easy to achieve this level of personalization in digital marketing. To create truly customized experiences at scale, you need to go beyond rudimentary audience segmentation and simple data collection. With that in mind, here’s how you can 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.

In addition, consider what kind of questions you have about your target audience. By answering these questions, your marketing team can identify actionable personalization insights and use cases that make sense for your business. Then ask yourself what consumer data is needed to achieve these goals. This can be consumer behavior on specific marketing channels, target demographics or external factors such as seasonal trends.

Companies have long relied on third-party data from website cookies to track consumers’ web activity and tailor advertisements and product offerings. However, with Google planning to sunset third party cookies by next year, it is wise to plan ahead and prioritize collecting first-party data directly from consumers. To do this, look at your current technology stack and ask yourself: what data do I already have access to and how is it tagged?

2. Increase Your Audience Segmentation

The fact is, demographics alone will not help you achieve the personalization in digital marketing that: 71% of modern consumers expect, according to McKinsey & Company. Yes, audience segments are still important. But when you only apply traditional segmentation with historical data, you pigeonhole consumers.

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

By doing so, you enable consumers to move in and out of specific segments in real time as their contexts and preferences change. Ultimately, dynamic audience segmentation is about meeting consumers where they are.

Related: Why segmenting your audience is essential

3. Put your consumer data to work

Once you’ve implemented dynamic audience segmentation, you can start improving the overall consumer experience with better product and service recommendations based on a variety of contextual factors, ranging from consumer purchases and search trends to geolocation, season, and even weather.

What does this look like in practice? For example, imagine running an alcohol retail business with the “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 at your brick-and-mortar store, whether the consumer prefers spirits or wine, and what the weather looks like. After all, nobody wants a hot toddy on a sweltering summer day, nor are they looking for an ice cold beer during a snow storm.

For a real-world example of a company that knows how to use data to personalize audience recommendations, look no further than Netflix. It would be difficult to find two users with the same home screen recommendations. Netflix uses consumer data so effectively that it can determine exactly what a user is most likely to want to watch. And every time they hit “play,” Netflix adjusts its recommendations in real time to make them even more accurate.

Related: 5 actionable ways to improve your customer experience

Today’s entrepreneurs need to listen – and I mean really listen — to their 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 bend.

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