How to Use Data-Driven Personalization to Boost Sales

How to Boost Sales through Data-Driven Personalization in Digital Marketing

Marketers: Do you ever feel like your audience is maybe just not that into you? Sure, they liked your latest Facebook video. They tapped on your Instagram story. But your follow-up emails go unopened. It’s getting challenging to turn that initial engagement into something the sales team can get excited about.

If any of the above sounds familiar, the problem may be the opposite of what you might think. It’s not that people don’t want to get personal with your brand. Your brand may not be getting personal enough with them. Consider these statistics:

  • Over one-fourth of consumers expect personalized experiences within an hour of identifying themselves to the brand
  • 79% of consumers say they are only likely to use a brand’s promotions if they’re tailored to previous interactions
  • 88% of marketers saw measurable improvements from personalization—half reporting over 10% lift
woman takes photo of shirt in retail store

Clearly, data-driven personalization is a key part of turning potential prospects into paying customers.

It’s likely your organization is already collecting the data you need to personalize more effectively. The challenge is to bring the information together across data silos and put it to work.

Here’s how to use data to provide a more personalized experience at every stage of your marketing process.

How to Use Data-Driven Personalization to Increase Relevance, Drive Conversions and Boost Sales

  1. Get a Sharper Focus on Your Audiences

    There’s never a bad time to reevaluate the fundamental information that drives your marketing: who your potential customers are, what they want, and how to find them. You can get a clearer picture of your audience by bringing in data from across the organization:

    • Marketing Data is the most familiar dataset, but it’s likely there is still untapped potential in the data your department is collecting. Do you have the ability to track people’s brand interactions online and offline? Can you combine anonymous data with tracked data in a meaningful way? If not, it’s time to bring your internal data together for a 360-degree-view of your potential customers.
    • Sales Data can show who already bought from you and what compelled them to buy. Just as importantly, the sales department knows who ultimately decided not to buy and why. Both sets of information are priceless.
    • Customer Service Data can tell you what existing customers think about the product, how it fits into their daily lives, which pain points are solved and which remain. This data can help you tell compelling stories rather than focusing on selling.

    A customer data platform can help pull in data from across the organization, making it available for analysis and action without compromising security.

  2. Identify More Meaningful Signals

    With all the data in one place, you can start analyzing customer behavior for patterns. The goal is to create a more accurate customer journey map, one that clearly identifies opportunities for your marketing messages to make a difference.

    For example, combining online and offline data could show that customers tend to check prices online, but make actual purchase decisions in your brick-and-mortar store. If your strategy had been to push every visitor to an online conversion, that data can help inform a new strategy.

  3. Create More Relevant Experiences

    At the heart of it, the purpose of data is to add memory to your marketing. If potential customers browsed through a specific set of products on your ecommerce site, your messaging should “remember” what they were interested in. If they looked at a series of articles on your blog, your marketing should “remember” what research they were doing.

    When designing experiences that respond to the signals you identified in the last section, keep that marketing memory in mind. Look for opportunities to demonstrate to your customers that they are unique and valued, not simply “generic visitor #2357.”

    Continuing the example from the previous section, imagine you have aggregate data that a majority of customers check prices online before buying in person. Then combine that with individual data: Say a potential customer looked at four blog posts, then two product pages. Instead of sending a coupon code for your website, your martech stack can offer personalized highlights on in-store products and a coupon for your brick-and-mortar location.

  4. Set More Purposeful Goals

    As you identify signals and create experiences, it’s important to keep both measurability and relevance in mind. Each experience should be designed to lead to a single specific action. That action should lead the customer closer to a purchase, and should be trackable for reporting and future optimization.

    In our example, the coupon code you send the customer online for use in-store can have its own unique tracking code. Your PoS could then record the code’s usage, and at reporting time you could reconcile the codes generated with codes used. That way, your goal (of having customers redeem the code) is both directly tied to revenue and easily trackable.

  5. Test Experiences in Campaigns

    Even when you’re using all the data available to your marketing team, marketing does come down to hypothesis and testing. Real-world customers will always be individual and unpredictable. The data helps to iron out some of that unpredictability, of course. But it’s still crucial to measure and monitor.

    As you roll out your experiences, keep an eye on the metrics you have identified. Compare your behavior goals with actual, live customer behavior, and adjust low-performing experiences on the fly. One big advantage of our fast-data world is not having to wait months to make changes—you should have enough data to test new hypotheses in days, not weeks.

  6. Optimize, Improve, Repeat

    The blessing and curse of data-driven personalization is that there’s always room for improvement. On the downside, it means setting and forgetting is not an option. On the plus side, it means a little effort can drive continuous growth.

    And because your new experiences are designed to promote specific trackable goals, you can build a new data empire, with the ability to see trends over time, check long-term performance, and suggest new ideas you can test and track.

Get Closer to Your Customer with Data-Driven Personalization

If you feel like your potential customers just aren’t that into you—if their attention seems to be wandering, affection waning—it’s time to take a more personal interest in them. Data-driven personalization can boost every stage of the customer journey, from awareness to nurturing to the final sale. Your organization likely has the data you need to get started: Take an inventory of what you have, get a complete view of the customer, and start enhancing your marketing strategy.

Treasure Data is an enterprise-grade customer data platform designed to help business unify, analyze and activate your data. Check out Treasure Data to see how to make data-driven personalization easier, more automated, and more powerful.

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Tom Treanor
Tom Treanor
Tom Treanor was head of marketing at Treasure Data. He focuses on marketing, martech, CDPs, and digital marketing. Follow him on Twitter @RtMixMktg.
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