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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 has just debuted, optical discs are still cutting-edge technology, and there are still more than ten years before the official birth of the Internet. Consumer expectations were also very different in 1972. To a large extent, consumers expect the basic elements of a brand: good service, quality products, and reasonable pricing. As long as you can achieve these three points, you have the potential to win the heart (and wallet) of your target audience. However, today’s entrepreneurs are playing another ball game, and consumers have learned a new pitch or two. Modern buyers not only want a seamless consumer journey across digital channels and touchpoints, but they also want precisely tailored interactions, offers and experiences. RELATED: Why the “Personal” Customer Experience Matters to Your Business Success According to Salesforce’s “Connected” The State of the Customer” report, about 80% now believe that the overall consumer experience is as important as a business’ product or service. Another 66% want companies to understand and meet their needs, and more than half want predictive personalization when it comes to offers. In many ways, this is not news

. Salesforce’s research proves what many entrepreneurs already know: Creating one-to-one consumer connections through predictive personalization has become the bet. However, the company went on strike. The same Salesforce report found that two-thirds of consumers believe companies still see them as cogs in the wheel. In this modern competitive landscape, then, the question entrepreneurs must answer is how can they evolve to improve the overall consumer experience.

How to Leverage Data for Predictive Personalization

Any competent business strives to understand its target audience and create Scalable, personalized messaging – 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 adopt advanced AI-driven personalization enjoy at least a 200% ROI. In practice, however, achieving this level of personalization in digital marketing is not easy. That’s because building truly customized experiences at scale requires going beyond basic audience segmentation and simple data collection. With that in mind, here’s how data can be leveraged to enable predictive personalization: Related: Personalization: Outlook for future goals 1. Asking the right questions Businesses in predicting personalization Often fail because they don’t ask the right questions. So first, ask yourself what business goals predictive personalization can help you achieve. Your goals should be both specific and measurable. Also, consider what questions you have about your target consumers. Addressing 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 could be external factors such as consumer behavior on a particular marketing channel, audience demographics, or seasonal trends. Businesses have long relied on third-party data from website cookies to track consumers’ web activity and customize advertising and product offerings. However, since Google plans to retire third-party cookies by next year, you’d better plan ahead and prioritize collecting first-party data directly from consumers. To do this, look at your current tech stack and ask yourself: what data do I already have access to, and how is it tagged?

2. Boost Your Audience Segmentation

The truth is, according to McKinsey & Company, demographics alone won’t help you achieve the personalization of digital marketing that 71% of modern consumers expect. Yes, audience segments are still important. However, when you only use traditional segmentation for historical data, you are grouping consumers into one category. Humans are numerous, which means they may be divided into multiple parts. Just because someone fits a certain niche when they interact with your site this month (or even this day), and Doesn’t necessarily mean they’ll fit that segment when they return. Therefore, to improve the overall consumer experience, you need to enable dynamic audience segmentation. By doing this, you will allow consumers to move in and out of specific segments in real-time as their environment changes and preferences change . At the end of the day, dynamic audience segmentation is about where consumers are at the time. Related: Why Segmenting Your Target Audience Is Essential

3. Putting your consumer data to work

Once you have dynamic audience segmentation, you can begin to improve the overall consumer experience and search trends to geography, seasons and even weather) to provide better product and service recommendations. What does this look like in practice? For example, imagine you run a liquor retail business that offers “buy online, pickup in store” options. As consumers browse your online selections, you can (and should) refine recommendations based on what’s in stock in your brick-and-mortar stores, whether consumers like spirits or wine, and weather conditions. After all, no one wants to drink a hot toddy on a hot summer day or look for a cold beer in a snowstorm. 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 recommendation. Netflix uses consumer data so effectively that it can pinpoint exactly what a user is most likely to want to watch next. Every time they click “play,” Netflix adjusts its recommendations in real time to make them more accurate. Related: 5 Actionable Ways to Improve Customer Experience Today’s entrepreneurs have to listen – I mean really listen – their target audience members can At Predictive personalization. Gone are the days when consumers expected brands to offer the bare minimum. Today, you need to use consumer data to improve the overall consumer experience all the time.



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