Imagine you could increase every transaction your business does by 20%. How much business value would that bring in? It’s a compelling calculation that’s even more important in times of economic uncertainty. No doubt, the rewards of personalization can be high. However, on a daily basis it can pose significant challenges-especially when marketing teams are spread across the globe and data is splintered across multiple silos. If personalization was easy, wouldn’t everyone use it? While a path toward improving your bottom line may not seem clear, one marketing strategy can yield impressive returns. According to a survey of marketing executives from 200 global firms, 40% of executives reported that marketing personalization efforts directly impacted sales, basket size, and profits. Moreover, studies show that personalization can also reduce customer acquisition costs by 50% and increase marketing spend efficiency by 30%. Personalization can also reduce churn, improve customer engagement, and increase cross-sell of relevant products. Personalization Is Complex. Today’s customers have come to expect hyper-personalization based on their needs and desires-a staggering 80% are more likely to buy from brands that meet this expectation. However, coordinating and tracking highly personalized experiences can be next to impossible. Here’s why: Customer data is siloed. Data lives in various sources across the organization; stitching it back together is difficult. Without connecting the dots, how can you identify interested customers? If you don’t know your customers, how can you effectively segment your audiences or send them relevant messages? Who individuals are and where they are in their journey isn’t transparent. It’s impossible to know exactly where each customer is on their journey, especially when you haven’t first resolved each customer's identity into a single customer view. How can you determine where customers should go next in the funnel when the same customer is using multiple devices and identities without your knowledge? Messaging isn’t comprehensively tracked. Tracking how many messages customers receive from disconnected platforms is time-consuming and impractical. If you can’t track your messaging, then how do you know when you should reach out again and when you should stop? 3 Steps to Solving the Challenge of Personalization. Treasure Data CDP helps you deliver real-time personalized experiences by unifying all of your customer data into a single profile database. Then, using the Audience Studio dashboard, you can explore and segment audiences based on common behaviors, create unique customer journeys, and activate messages to multiple channels. You can also apply machine learning to derive insights like next-best action and content affinity, and then segment your audiences based on those results. In this article, we will take a deeper dive into each of the following steps. Step 1: Audience Management. Combine customer data to ensure you’re targeting the right customers at the right time with the right messaging. Step 2: Customer Journey Orchestration. Make sure marketing campaigns are effective at moving customers towards a conversion. Step 3: Multi-channel Messaging. Deliver messages across digital, social, display, email, and more to targeted audience segments. Step 1: Audience Management, Segmentation, and Targeting. Before you can deliver personalized experiences, the first step is to understand your customers. Essentially, the purpose of audience management is to aggregate all available customer data and sift through it to find common demographics, attributes, and behaviors. Depending on the size of your organization, your parent segment might include tens of millions of users. Such an enormous dataset can be overwhelming, so where do you start? You begin by identifying your business goals. To do that, you need to stitch together data from all of your silos to create the most complete user dataset possible. Once you’ve created this parent segment (your entire customer base), you can explore customer data more easily with Treasure Data's Audience Studio dashboard and create audience segments in Treasure Data's Audience dashboard. Exploring data helps you: Identify key attributes of both high lifetime value customers and customers that churn. Better inform customer acquisition efforts by finding lookalike audiences. Discover common behaviors and attributes that can be grouped into smaller audience segments for activation. Audience Exploration. Perhaps your business goal is to increase revenue. Or, maybe it’s brand awareness. Think of your goals as you explore your data, including geographic location, products, user commonalities, product purchase history, and usage patterns. Generally, you’re aiming to understand where your consumers are today and where you want them and your business to be in the future. Example-Using Geo Location and Product Targeting to Boost Revenues. With the goal of increasing revenue, a global beverage firm wanted to know the best geo locations to focus marketing efforts. Using Audience Studio, marketers created a report that divided its audience by country to see which locations generated the brand’s highest revenues and which had the most active users. Results showed that Japan had the most users, but their spending habits were low. In comparison, users in the U.S. and South America spent considerably more. This enabled the firm to focus marketing in locations that would generate the most revenue. The beverage firm also had a number of product lines under various labels, ranging from small craft beers to globally recognized liquor brands. Aiming to improve revenue through savvy product targeting, the firm wanted to promote its most profitable products and engage in cross-promotion. Marketers used Audience Studio to view product lines by usage, user interests, revenue, and other key metrics. Reports showed that while beer was the most popular category, whiskey generated the most revenue. Also, interest in sake was slowing. With this data, marketers were able to boost revenue by launching campaigns promoting whiskey. And they began cross-promoting sake to beer users because they knew sake and beer users shared similar interests. Segment Exploration. Exploring your data by audience segments is another way to achieve your goals. Audience Studio is powered by machine learning, which can cluster user data together from your parent segment into smaller digestible content. Enriched with third-party data, these segments can help you better understand common user interests and how user behavior represents important business trends. Example-Using Behavior to Increase Brand Awareness and Purchasing. During its segment exploration, the beverage firm discovered light beer customers in the U.S. were likely to be runners or belong to a gym. To increase brand awareness in that segment, the firm began sponsoring marathons. It also began offering this segment timely, well-targeted promotional coupons for light beer purchases when they attended a running event or visited their local gym. Kirin + Treasure Data. Kirin improved its campaign conversion by 10% using Treasure Data CDP. By combining its offline and online customer data, it was able to gain important insights to significantly boost marketing campaign performance. Read the case study. Step 2: Orchestrating Customer Experiences and Journeys. After you’ve explored your audiences, it’s time to design paths for your users and segments. Using customer journey orchestration, you’re solving the problem of knowing where users are in the funnel, and then designing where you want them to go next. That way, you can make sure users are receiving relevant content at every step. Customer journey orchestration features within the Audience Studio enable marketers to deliver personalization at scale and design the best customer journey stages (based on complete customer profiles). Typically, customers move closer to a purchase through these stages: awareness > interest > intent > purchase > retention. Frequently, designing customer journeys and customer experiences means mapping out all the combinations of behaviors a customer may take, creating hundreds of micro-journeys that look like this: “If a user clicks this link, then send this email,” or “if a user opens this email, then send this coupon.” Such a highly detailed approach requires considerable time and effort to build on a granular level. In comparison, Audience Studio enables you to design macro journeys depending on where the customer is in their journey. Segmenting Out the Journey. Customer journey orchestration features provide the ability to mark critical stages in the journey to trigger messaging that helps users move from awareness to intent, and from interest towards purchase. For additional customer journey insights, machine learning such as next-best-action modeling can be used to identify the most marketing activation to deliver next and influence your users. Customer journey orchestration helps marketers see whether their marketing efforts are working and moving customers closer towards a purchase. This enables marketers to plan the best possible journey to progress a customer towards a purchase. Example-Moving Users from Intent to Purchase with Macro-journeys. An electronics firm has designed a macro journey to guide users from awareness to purchase of home thermostats. Its journey starts with awareness using targeted Google Ads. In the interest phase, users read online reviews and use comparison tools to evaluate competing products. During intent, users are tracked on the firm’s website as they compare features and pricing. In the purchase phase, users either make a purchase online or visit a retail store to speak to a sales rep. At each step of the journey, Treasure Data’s CDP gathers data from various online and offline channels for a comprehensive view of users’ brand interactions. Because this data is compiled for thousands of users, marketers can generate analytics reports that show exactly where users drop out of the journey. Using their CDP, the electronics firm’s marketers discovered that the bulk of users were dropping out in the intent phase. As a result, they designed a special pop-up offer on the homepage for 15% off the first purchase with any email sign-up. Later, users were sent personalized follow-up emails with coupons for products viewed on the website. Shiseido + Treasure Data. Shiseido leveraged customer journey personalization to increase in-store revenue by 20%. Using Treasure Data’s CDP platform, it boosted the effectiveness of its loyalty program by creating multiple cross-promotion and upsell opportunities. Read the case study. Step 3: Multi-channel Messaging. Now, you’re ready to push out messages to users at every stage in the journey across digital ad channels. With Audience Studio you can: Deliver personalized messaging to specific customers or segments. Track and score user behavior to identify the best time for action. Activate messaging to multiple channels at the same time. Multi-channel messaging is intrinsically connected to the customer journey. During each stage of the journey, there might be a different activation. For example, in the awareness stage you might want to activate to your social channel and use lookalike modeling to reach a wider audience, while in the interest stage an email activation might work best since you’ve already collected their personally identifiable information (PII). Multi-Channel Activation. You can also activate to multiple channels at once, which means you can send users an email marketing campaign as well as an ad on social media. Then wait and see if they move to the end of the funnel and make a purchase. If they don't, you can send another. Treasure Data is partner agnostic, offering 170+ connectors across 15 technology categories to ensure your possibilities are extensive. Audience Studio tracks how often you reach out to users. Example-Sending Multiple Messages with Audience Studio The process of activating messages to multiple channels is simple. Once you’ve created your segments, Audience Studio can generate lists of users whom you want to target with messages based on where they’re at in your funnel. These lists are periodically pushed out to your channels. For example, let’s say you’ve connected your Treasure Data CDP to Marketo. When you open Marketo, you’ll see a list of files named according to date and segment (e.g., journey phase or audience type). Each file contains a list of users who should be sent messaging according to that segment’s personalized campaign. Conversely-when users respond to this messaging-data is compiled by the Treasure Data CDP so that users can be removed from one list and put into a new segment. This moves them further down the funnel. Scoring. Audience Studio can also provide user scoring. Powered by machine learning and next best action, scoring helps you know whether you should be spending your valuable time and money sending users additional messages to move them down the funnel or whether those efforts will likely be wasted. Example-Using Scoring to Reduce the Costs of Customer Retention. A gaming company wanted to streamline its marketing efforts and customer support. It had a huge group of users who spent $10 to get activated on its platform. Not being able to distinguish whether these users would likely make future purchases or upgrades, the company spent considerable time and money reaching out to all users and managing support tickets. It needed to identify high value users so that it could send them promotions and prioritize their customer support needs. The company used Audience Studio’s scoring capabilities to segment users according to whether they made additional purchases after their initial account activation. It also tracked how many times they contacted customer support. Users who did not make new purchases were placed on a suppression list and the company stopped making further efforts at acquisition. Users who spent at least $50 per month and created few support tickets were sent monthly discount offers and received priority customer support with an email message response sent within two hours. More Resources for Data-driven Marketers. Want to uncover insights for real-time decisions? Check out our series of guides for data-driven marketers, and learn the latest regarding identity resolution, multi-touch attribution, predictive analytics, and data enrichment. If you have questions about CDPs and Treasure Data, ask one of our experts.