Customer Data Platform Use Cases Guide: Media

Customers engage with media brands across mobile, desktop, and connected devices throughout their day, with an average screen time totaling up to 12 hours per day. As media has become a critical part of customers' daily lives, customers' expectations have risen and brands are tasked with creating seamless, contextual, and concurrent experiences across every device. This represents a big opportunity and a big challenge for media companies, especially those looking to engage customers across mobile and OTT channels.

With interactions occurring across many devices and channels, media companies can no longer rely on legacy systems to understand who their customer is, how and when to reach them, and how to measure the influence of marketing, product, and engineering initiatives on the bottom line. That's why many forward-thinking media companies have started to consider using a customer data platform to unify and orchestrate their customer data.

To find the right CDP, marketers need to consider their current data maturity and how it can be used as well as what their future goals are and what data will be needed to achieve those goals. Data maturity levels can be broken down across four maturity levels, from least to most mature: Foundational, Insight and Experimentation, Omnichannel Engagement, and Continuous Optimization. This blog will take you through use cases at each level to help you determine which CDP features are relevant to your situation and find the CDP that will help you meet your current and future business needs.

Objective:

Establishing essential data processes and deploying standard marketing technologies

Organization focus:

Centralizing of clean customer data, connection to marketing, BI, and analytics tools.

Modern marketers want to innovate as quickly as their businesses and customers, but struggle to get the engineering resources needed to implement new tools. A well-instrumented CDP can democratize data access around a single source of truth, delivering and maintaining clean, complete data feeds to different business stakeholders’ systems of choice via pre-built connectors and/or API, without depending on engineering. A CDP should also be able to create, update, and send audiences to marketing and advertising platforms, without manual list pulls, enabling unparalleled speed and agility.

Use case: Launch new channels

Media streaming companies rely on their marketing teams to get the word out efficiently when new shows, movies, or specials become available for customers in specific markets. Because there are so many media offerings on a given customer’s homepage, marketing teams need to find new ways to engage with customers, like push notifications. To implement push notifications to customers using the streaming app, engineering would normally have to plan and implement the push notification vendor’s SDK. This data integration process can become a big time investment depending on the systems’ compatibility.

By using a CDP with a pre-built integration to the push notification vendor, like mParticle, marketers can connect customer data directly without relying on engineering. Taking the data integration planning and implementation process out of the equation allows marketers to test and find new engagement channels that resonate with the customer and further business goals.

The majority of active internet users still interact via browsers, making it the most important digital channel for consumers. As a result, web analytics are essential for marketing organizations; however, the shift towards mobile and connected device engagement has shown brands that they also need to be able to collect and analyze data from every touch point across the entire journey to understand how interactions influence customers. This can be tough because legacy systems are not built with mobile in mind, but a CDP can help; using mobile-specific SDKs to collect data from apps then delivering it to web analytics platforms creates a complete view of the customer’s journey and enables further analysis and attribution.

With a complete view of the customer journey, marketers don’t have to rely on “last click” attribution. Instead, they can test and integrate new tools to attribute weight to each interaction using a CDP. Marketers can use data from their as input to these tools to test different algorithms and interfaces without instrumenting each attribution tool individually. A CDP can also track the long-term performance of customers acquired through advertising by associating campaign membership with full lifecycle events and attributes with acquisition source to inform strategic resource allocation decisions or direct systems that programmatically calculate bids to reflect the value of each opportunity.

Use case: Sell more premium ad placements

Ad sales and audience monetization are the leading revenue drivers for media publishers, making expansion and innovation in this area key business initiatives. At the same time, publishers have to deal with price depression, competition in the media landscape, and audience commoditization, which makes it difficult to maintain current ad sales and monetization, let alone grow them. To improve audience monetization, publishers need to be able to understand how, when, and where visitors are reading and sharing their content.  

Using a CDP, publishers can collect customer data from the web, mobile app, and email to gain a better understanding of who their readers are, what they look for, and what they are likely to respond to, and leverage this information when negotiating with media service agencies. As customers visit the publisher’s digital properties, user and event attributes are collected and attached to a single profile, creating a single view of the customer. With a better understanding of their customer base, a media publisher’s sales team is able to provide more compelling visitor data insights to sell premium advertising placements for increased profit.

Brands want to create a superior experience for their users, which means they need a roadmap that delivers the best product to their customers consistently. For apps, that means minimizing reliance on third-party code that requires additional instrumentation and maintenance that may burden the user experience and divert engineering time.

By serving as a centralized data hub, a customer data platform is able to capture first, second, and third-party data through a single endpoint, then share it with multiple systems without placing additional tech strain on the app. This centralized data layer ensures the end-user remains unaffected as additional tools are introduced or updated, or as data schemas are changed. Minimizing dependency on third-party code allows product and engineering to avoid unforeseen SDK implementation and maintenance projects from marketing and other business stakeholders, so they can focus on building the best, most differentiated product.

Use case: Prioritize what customers want from streaming

Video streaming services are used by customers on the go more and more frequently, with telecom companies even offering special data plans to enable greater content consumption at a lower price. For customers to be satisfied with the service, however, the app needs to deliver content at a high quality with little to no lag. Delivering data at this speed and volume results in a high level of resource consumption, making video streaming apps prone to lags and crashes leading to very unhappy customers. Minimizing the load on a streaming app thus needs to be a priority for engineering teams, but that can be difficult to achieve when an app needs to connect to a variety of third-party services to perform app functions. This can feel like a real Catch-22 for engineers and product teams looking to deliver the best customer experience. Stabilizing the app without losing customer and marketing functionality can be done, however, you just need the right tool.

A CDP enables streaming apps to connect to the analytics, business, and marketing services necessary for quality customer experience and analysis by serving as a layer between the app itself and the services. Instead of implementing SDKs from each service, which can consume resources as well as additional engineering time to implement and maintain, streaming service teams can implement one SDK from their CDP to increase stability and lower consumption. A well-instrumented CDP can connect directly to the services and the app to collect and distribute data bi-directionally, reducing the need for additional third-party code in the app. Additional engineering time that would normally be used to maintain third-party integrations can then be used to make development changes to  further improve streaming speeds for better experiences all around.

Objective:

Creating structured methodology for running test-and-learn processes and creating a culture of data-driven decision making. This may include leveraging non-marketing data.

Organization focus:

Measure ROI and customer lifetime value (CLV) impact of new marketing and customer experience initiatives.

Brands want to understand the mobile customer journey holistically and use this knowledge to prioritize future roadmap items based on customer needs, and demonstrate the business benefits of their product recommendations. Using a CDP enables them to combine mobile product, marketing, and purchase events through a single combined data set so that they can understand bottlenecks, identify key areas of improvement, and make better roadmap decisions.

Use case: Build the features your customers want

Streaming music apps have enjoyed a massive boom in popularity and they have each done their best to make improvements to their catalog, quality of service, and accessibility through web and connected devices. But, not everyone is a convert. Using a CDP, a streaming data service can track engagement time, frequency, and device channel to understand how and when customers use their service to see what could be improved. For example, free users of a streaming platform are valuable to the platform as an audience for partner advertising, so increasing the level of engagement is a value-driving KPI. By analyzing free-tier customer usage across channels and devices, streaming services may find that a large proportion of customers use the web app rather than the mobile app.

Upon further analysis, may find that the amount of data used when streaming is what is stopping certain customers from enjoying their music on the go and use that to develop data-saving features. One company has recently debuted a data saver feature that leverages caching to reduce data usage by 75% to the delight of their free and paid tier customer base.

Brands want to be able to not only know what customers are doing, but how they can improve customers’ experience while they’re doing it. Improvement can only come from experimenting with new product features, content, and workflows and using a CDP allows you to do experiment with different parts of your business more easily and quickly. A CDP reduces the data wrangling required for each experiment, reducing the cost of set up failure by making it easy to revert, and making it easy to create experiment segments and holdout groups on which to experiment. Experiment variants can be created based on customer attributes and behaviors across systems, including entry channel, initial product purchased, content consumed, current sales funnel stage, etc. Variant behavior is then gathered from source systems and third-party enhancements for analysis. Whether a brand is running experiments on purpose-built software or by hand, a CDP makes experimentation easier and more scalable.

Use case: Create user-centric searching

Search is key for media consumers—if they can't find what they want, they will look elsewhere. To create user-centric search features, media brands can collect user and streaming data with a CDP then analyze it to see what kinds of searches customers are inputting and what results lead to engagement. From there, the media team can test different search algorithms using media attributes to test different display methods. By using a CDP's A/B testing capabilities, media teams can test many different variants to display to randomized user sample groups to find the right search model.

Objective:

Optimize organization-wide initiatives using customer data and supporting marketing campaigns

Organization focus:

Optimizing marketing, digital advertising, and product-led retention/growth leveraging customer behavior, testing, and targeting across channels and touch points.

Modern marketers want to personalize messages by segment or persona to improve experiences and outcomes, but many legacy systems don’t collect and store the right customer data, at the right level, in the right way, at the right time. A CDP enables marketers to collect information about customer preferences and profile information to determine what information, content, or offers are most likely to appeal to them. By using rule-based segmentation, customers are automatically placed into audience segments comprised of customers with similar profiles which can be used to power marketing campaigns across channels, including search.

Use case: Target the right sports fans

Sports matches have long been a big draw for fans unable to attend their favorite team’s matches and the development of streaming has only made it easier for fans to access this premium media. Instead of worrying about traveling or finding a television broadcasting the match, customers can stream directly from their mobile devices. For media companies looking to capitalize on this highly loyal subset of customers, using segmentation allows them to create personalized messaging campaigns with score updates, commentary, and highlights can lead to conversions and increased app usage.

Marketers, for example, can filter their user base by the number of app sessions per week, content viewed, and social media content, then further refine by sport, team, country or state, and gender to create highly personalized marketing pushes that resonate with your intended customer. Messaging can include upcoming match reminders, pre-match commentary, season updates, and more. Beyond sports, similar segmentation methodology can be used for other premium streaming events, like concerts.

A CDP can capture visitor behavior on one company site or app and deliver related messages when the same visitor appears on any other company-owned site or app—even if that person was anonymous when they abandoned. A CDP can also read behavior history to flag inactive customers. In addition to triggering an email or push message, it can also trigger special messages when they appear on a different app/site or the same app/site. This is especially useful because the email addresses of inactive customers may no longer be valid.

Use case: Re-engage inactive gamers

Gaming companies rely on users to incorporate mobile phone games into their daily lives to maintain engagement rates and improve ad impressions. When customers become inactive, a CDP can flag them and target customers with offers and reminders via push notifications to re-engage customers in a meaningful way. Personalized messaging allows for gaming brands to create tempting offers like free power ups, boosted game play, or discounted coin packages that are relevant to specific users.

Brands need to be able to use paid media efficiently to push customers stuck in their journey toward conversion. A CDP can address specific bottlenecks in the customer journey by syncing customer lists to paid media platforms. This is effectively the same as list selection for traditional marketing channels, with similar requirements for complex selections, access to full customer data, and extract creation. Customer lists can be selected based on user profile attributes and historical data available within a CDP. Unlike conventional (manual) methods, lists are updated in near-real-time to maximize relevancy and effectiveness.

Use case: Target smarter

Paid media plays a big part in the mobile gaming industry, but finding the right customers to display ads to is challenging. Gaming companies can use a CDP to create customer profiles detailing usage rates and times, types of games being played within the brand, and lifetime value to create segments for targeting. A customer that is a heavy, longtime player of a game like Candy Crush, for example, can then be served ads for the new version of Candy Crush or for a similar pop puzzle game. By targeting specific subsets of customers, brands can improve their return rate and limit wasted ad spend, leading to better marketing and increased returns.

Brands know that engaging existing and identifying additional customers that fit your ideal customer profile (ICP) is a solid growth strategy, but putting this into practice can prove difficult. Using a CDP enables you to select and deliver targeted messages to different cohorts of customers based on value-based scores by passing numeric attributes and customer IDs to paid media platforms, like Facebook. You can also create lookalike audiences using the value-based scores to find more customers like your current highest value customers with higher granularity than is available in the media systems’ limited data store.

Use case: Find lookalike subscribers and upsell

Enriched profiles can be used by marketers to target specific subsets of customers with custom subscription offers, increasing the likelihood of subscription. Campaigns based on these enriched profiles can be as simple and low-investment as an email campaign or they can be connected to paid media channels. For example, a newspaper publisher looking to increase subscription rates to a weekly lifestyle print magazine can use segmented marketing to target frequent readers of lifestyle articles online.

Because a CDP can track the frequency and the content a reader is accessing and unify it with other attributes, like demographics, a publisher growth team can create an audience segment comprised of frequent readers of the lifestyle articles that were already subscribed to the print version of their newspaper and lived within the delivery area. This highly targeted audience segment could then be sent a special offer to subscribe to the print lifestyle magazine for an additional $2 to their current subscription for a period of six months. This discounted rate provides readers with more of what they want at a price that is too good to turn down. Once the trial period is over, dedicated readers are more likely to continue paying the standard rate.

Just as you can target exactly who sees an ad, a CDP can create and sync suppression lists to paid media platforms to ensure campaign dollars are not spent targeting the wrong people. Using custom rules set by marketers, the CDP can move individual customers in and out of suppression lists as their attributes and actions qualify or disqualify them from receiving certain ad content.

Use case: Suppress ads to premium subscribers

Premium music streaming service subscribers have already seen the value of the paid service, like being able to download their playlist for data-less listening, greater mobile app features, and no ads played during their listening sessions. Because “no ads” is a major subscription selling point, creating suppression segments is critical.

In fact, ad suppression works on two levels here: the service needs to suppress its own ad and email campaigns targeting users that have have already subscribed as well as suppressing partner ads that play between songs. This two-pronged suppression not only ensure that paying customers aren’t annoyed by ads asking them to pay when they have already converted, but it also keeps partners happy because their ad budget and content isn’t being used to target people that don’t want to receive ads at all. When a customer makes the subscription purchase, they are automatically moved into the suppression audience by the streaming service’s CDP, which is then forwarded to their paid media providers and marketing services to ensure these customers don’t receive ads. If a customer were to cancel their premium membership, this data would be automatically updated in their profile, which would trigger their removal from the suppression list and addition to targeting lists for campaign marketing.

Objective:

Engaging and improving customer experience in real time

Organization focus:

• Incorporating algorithms for continuous optimization, managing channel-neutral customer preferences, and omnichannel attribution.
• Leveraging consistent data, technology, and processes across all channels to develop contextual customer engagement strategies that drive corporate objectives.
• Calibrating marketing technology capabilities for continuous adjustment based on customer needs.

At the highest stage of maturity, organizations need to focus on creating better experiences for their customers on an ongoing basis. Using a CDP allows companies to make adjustments based on data and improves how brands track attribution. A CDP’s view of product, marketing, and service interactions—and customer purchases—provides the data needed to inform bottom-up multi-touch attribution models that measure the impact of touch points on business results at the user level. Many businesses consider these models to be more reliable than top-down mix models that rely on statistical methods to discern contributions but struggle to assemble the granular data needed to make them work.

A CDP can be used an orchestration layer that provides an overview of all activity across all sources, and sets rules to direct messages based on complete information about the customer. Messages can then be personalized and delivered across all channels while maintaining a consistent customer experience. CDPs can also help customers set up cross-channel frequency capping, which limits the number of times an ad is scheduled to be displayed to a customer. Frequency capping reduces ad fatigue and ensures customers won’t grow tired of seeing your brand’s communication efforts.

Use case: Understand how customers are experiencing your property as they experience it

Media brands can track customer engagements across the journey to ensure customers' experiences are concurrent across devices; for example, streaming services can make sure that a customer can pick up where they left off in a show, movie, song, or album. Tracking the full customer journey also allows publishing brands using walled garden tactics to track the number of articles viewed by a single person, regardless of device, to help them determine when and what message a customer should receive to guide them towards conversion.

A CDP may ingest user scores from predictive models, whether they are homegrown or machine-generated, to provide the app or site CMS with real-time support for recommendations. These recommendations can include first product, cross-sell, and upsell. Because the CDP was also used to inform the models, these recommendations are based on data captured across every channel, not just the one the user happens to be visiting.

Use case: Recommend the right content

CDPs offer publishers and media companies the ability to better understand what their readers care about by collecting metrics like time on page, article visits, and social shares. By tracking readers through their customer journey, across many touch points, publishers are able to recognize a reader and personalize the content recommendation to cater towards that reader’s interests. Offering the right content encourages readers to click on the article, read it, and share it to generate more traffic and attract other readers with similar interests.

For example, a newspaper publisher looking to increase traffic to their site can use a CDP to connect inbox and website traffic data to create profiles of their customers to tailor their content outreach to each person based on their reader history. Readers that had read the previous week’s news report on the dangers of mercury, for example, were sent an article about fishing practices' found in the Metropolis Metro directly to their inbox as a suggested read. Because these recommendations were tailored to their interests rather than an aggregate of popular articles currently on the newspaper’s site, this publisher saw a surge in traffic and can then further refine content recommendations as their CDP ingests additional visit data.  

Brands need to reach customers not only when their messaging is relevant, but also where it’s relevant. A CDP can ingest location information from web and apps, append it with signal from location data services, apply rules to uncover opportunities, and then trigger relevant messages. This extends far beyond conventional push notification systems and helps customers receive messaging relevant to their geographic context.

Use case: Create contextual content experiences

The publishers of recipe websites’ driving purpose is to help customers figure out what to cook for dinner and how to make it. It only makes sense that a recipe publisher would see increased views around peak eating times, like late afternoon when people are beginning to plan their dinner. Using location beacons, however, a recipe publisher could also see increased traffic from the place many customers consider searching for recipes: the grocery store.

By partner with a grocery store and leveraging beacon data and connecting it to their app via a CDP, a recipe publisher to target shoppers with recipes using items on sale at the grocery while they are in-store. This helps meet two customer needs: deciding what to make for dinner and keeping grocery costs down. For the publisher, this beacon campaign can lead to massive upticks in mobile traffic, leading to increased ad revenue while driving sales for the grocery partner.

A CDP can assemble a complete set of interactions between the company and each customer to create maps of customer touch points over time, with separate maps built for different segments, products, tasks, or locations. With this information, a CDP can identify the most productive paths and find the points where customers are falling out of the process.

Use case: Maintain concurrency

Analyzing frequency of app usage, content, and location can help media brands understand how customers consume content at different intervals during the course of the week to determine content offerings across devices and fix service bugs. If customers search for certain pieces of content, that data can be used to create personalized messages to encourage customers to return to the platform and view similar content offerings. Similarly, if customers can't find what they are looking for and are dropping off, this data can be used to inform licensing strategy and prioritize search function fixes.

Legacy loyalty programs focused on serving promotions to repeat customers rather than driving loyalty. The next-generation of loyalty programs uses web/app usage data, in-store purchases, loyalty status, points balances, redemption, and in-store inventory to make the optimal offer for each customer. A CDP makes these data points available to systems that use predictive modeling and optimization to find the best offers while balancing customer goals, business goals, and business constraints, and can help these systems deliver relevant messages across channels.

Use case: Reward customers with tailored offers

Music lovers everywhere have rejoiced living in the golden age of music streaming services. Customers have their pick of music streaming platforms so streaming brands need to go above and beyond to differentiate themselves from their competition. One way to do this is to retain streaming customers by rewarding their loyalty, using their individual taste in music to dictate the reward. By connecting customer location data to their music streaming habits and email, streaming services can partner with concert ticket marketplaces to offer advance ticket sales to an upcoming concert nearby featuring an artist that that specific customer listens to frequently. Beyond advance ticket sales, streaming companies can provide exclusive offers like access to limited-run merchandise or even sending low-cost, high-impact gifts, like Spotify famously did in 2017, to the most loyal of customers. This tiered loyalty system is low investment for streaming companies but goes a long way in surprising and delighting customers.

A fully-enabled CDP can ingest customer transactions on web, apps, call center, retail kiosks, and other channels in real time, as they happen. Using Identity resolution features, the customer can be identified and the information about the engagement can be used to inform channel systems of the customer’s specific preferences and history to guide current and future interactions.

Use case: Proactive issue resolution

Customers not only rely on applications performing properly, they expect it. This is especially true for streaming service apps that rely on the app functioning to provide the customer with service. When a streaming app crashes or a user is unable to log in, customers can become frustrated and become less likely to continue using the app to interact with that brand. By connecting login event data, email messaging, and your help desk through your CDP, customers experiencing login failures and app crashes can be sent an email with a help desk link to alert your team of potential issues. Automating crash and login reporting allows your customer service team to get ahead of the issue and start working to remedy the problem, reducing response time.

Media is an integral part of customers' daily lives, whether they are consuming news on their phones, streaming music or video on their home devices, or are tuning into the television to watch their favorite teams play. As a result, media brands have access to unprecedented amounts of customer data thanks to customers' engagement across devices and channels. This data represents an opportunity that media brands would be remiss to not jump on—the chance to understand how different facets of engagements influence customers' journeys towards conversion and act on those learnings. But marketers are no longer dealing with a finite number of systems; rather, marketers are dealing with legacy systems unable to keep up with the ever-increasing number of SaaS applications that house and action data. Companies need a CDP that can not only help them overcome the customer data silos and unify their data from across their stack, they also need a CDP that is able to take their insight, orchestration, and activation to the next level by providing a way to create and maintain persistent customer profiles, execute experiments, improve targeting, and power acquisition and retention.

Finding the right CDP requires that marketers consider their current and future data goals and what kind of data they need to achieve them. Using defined use cases as the basis of their search for a CDP will ensure that marketers choose and implement the right customer data platform for their business' needs, making it a safe investment.

This guide has provided some of the most common use cases for travel companies at different data maturity stages, but there are still many more advanced applications for companies looking to improve their marketing and analytics ROI. mParticle is not only able to meet all of the use cases described in this guide, it is capable of becoming the customer data hub and agility layer that brands need to succeed in the digital era thanks to its ability to:

• Natively collect data from all sources
• Cleanse and transform customer data
• Resolve customer identities
• Create and maintain persistent customer profiles
• Enrich customer profiles with data from first-, second-, and third-party tools
• Support consent and privacy management
• Segment audiences on the fly
• Orchestrate data to the marketing and BI tools needed
• Do it all in real time

As the customer journey continues to fragment, finding the right CDP will only become more important. If you’d like to learn how mParticle can help you unify your customer data, boost engagement, and increase advertising and marketing ROI, get in touch!