What Is a Customer Data Platform?
Customer data platforms (CDPs) are becoming more important at a time when businesses are trying to maximize the value of every customer amid the decline of third-party cookies that restrict how a business can track a person’s behavior across the web.
As Apple and Google both enact stricter privacy controls, businesses are leaning more into their first-party data (the data they collect directly from customers) to create more personalized and valuable content and offers. CDPs help them to do that.
At Pactera EDGE, our own CMO.AI practice works with Adobe and Acquia CDPs to help businesses create personalized content based on first-party customer data. But what exactly is a CDP? This post answers that and other commonly asked questions about CDPs.
What Is a Customer Data Platform?
A customer data platform (CDP) is a software that collects and stores all your customer data in one place. All your business applications, processes, and marketing efforts use that data for a variety of reasons, including the creation of individual profiles for personalized marketing.
A CDP differs from a data warehouse or data lake because a CDP does more than store data. It is a unified platform that makes it possible for different business departments to analyze a customer rather than requiring them to use different data bases to meet their needs.
What Kind of Customer Data Does a CDP Collect?
CDPs mostly rely on first-party data. This is data collected by your company when someone interacts with you directly, such as on your own website or via an email subscription. It’s the most valuable data that a company can get about its customers. From there, CDPs build customer profiles that make it possible to personalize content such as marketing offers.
To be effective, CDPs collect both device-level data (cookie IDs, device IDs and IP address) and personal data (e.g., names, addresses, email address and phone numbers). So, it’s crucial that CDPs operate with strong security and privacy protocols. Once people have opted in to have their data collected, a CDP needs to give them the ability to delete visitor data if a user asks them to do so.
In fact, GDPR, CCPA, and other emerging privacy regulations can be more easily complied with through a CDP. Personal data can be filtered from data streams, preventing it from being sent to destinations which do not (or should not, for legal reasons) need to receive that data.
CDPs may also use second-party data and third-party data. Second party-data is first-party data that is collected by another company and shared or sold to a noncompetitive partner. Third-party data is tracked by a data-collection company and then shared with anyone who wants to purchase. But the use of first-party data makes CDPs effective.
What Is the Benefit of Using a CDP?
CDPs help businesses create more personalized and intelligent experiences for people online.
Major shifts in competition and customer behavior are propelling enterprises into a new data-driven era. Businesses that make intelligent, data-driven decisions are enjoying a major advantage over those that cannot. But doing so is not easy.
Marketing teams need high-quality data to make informed decisions. However, this data is often spread across silos. Instead of making your marketing efforts easier, all these decentralized data silos make it harder. Scrapping information piece by piece from multiple sources leads to drawing inaccurate conclusions and wastes a lot of energy.
Meanwhile, CMOs are under pressure to create one-to-one personalized customer experiences. But doing this effectively requires deep insights into customer behavior, which can be difficult to glean from disparate data.
CDPs are not the single solution to these challenges, but they help overcome them by provide a clean, consistent, and unified view of your customer, with access to the right data sources. Here are some of the ways businesses can benefit from using CDPs:
- Sales: more personalized offers based on an understanding of a customer’s lifestyles and interests.
- Personalized content: because CDPs rely on first-party data volunteered by a customer, a business can customize content for that person on a more one-to-one level.
- Better omnichannel marketing: because a CDP aggregates data from multiple sources, a business can tailor marketing more effectively across multiple touchpoints.
- Predictive marketing. By combining a CDP with machine learning (a form of artificial intelligence), a business can reliably predict a person’s future behavior (e.g., likelihood to purchase a product) and improve marketing content accordingly.
As more and more companies embrace insights-driven marketing, it’s only going to evolve to become more valued and sophisticated as it enables CMOs and their teams to make even better predictions of customer needs and behaviors.
We’re already seeing the rise of artificial intelligence in marketing, with chatbots and intelligent assistants becoming more common. And as machine learning gets better at understanding customer intent, we can expect even more personalized and relevant experiences to come.
How Do CDPs Differ from Data Management Platforms?
Both CDPs and DMPs help businesses create personalized relationships by managing customer data. But CDPs primarily use first-party data (although not always exclusively). DMPs mostly use third-party data, also with a bit of second-party data.
Another major difference is the type of data collected. CDPs collect personally identifiable data that a customer volunteers. This makes it possible for a CDP to develop the most accurate and complete picture of who is actually interacting with your brand. But DMPs use anonymized data. As a result, DMPs don't use personally identifiable information. But they still collect data on anonymous users.
What Are Best Practices for Succeeding with a CDP?
- Make sure that you have the correct privacy controls in place. It’s essential that protocols allow customers to opt in and opt out of sharing their data on their terms.
- Security needs to be airtight especially because CDPs collect personal details.
- A business needs to apply expertise to know how to use the data to create personalized offers and content. Having the data is one thing. Making sense of it to create a personalized experience is another.
- A CDP needs to improve with technology. For instance, in 2022, Adobe announced that its own CDP has incorporated a feature known as Real-Time CDP Connections. This makes it possible for businesses to act on real-time customer data faster than ever before – without the need for third-party cookies. Adobe also create a unified view of the customer that makes it possible for businesses to accelerate the development of new products and services online.
How Are CDPs Evolving?
We see CDPs helping businesses become more predictive and adaptive. This means knowing what the customer will want tomorrow and having the right product at the right place and time (a challenge retailers face in particular):
- Being predictive: anticipating what a customer will want tomorrow and being there to meet that unexpressed and unmet need they didn’t know they had.
- Being adaptive: customizing the experience to have the right product at the right place at the right time, whether in the permanent store, at the curbside, on the consumer’s front porch, in a pop-up store, at an event, or anywhere the shopper is and will be.
Without predictive and adaptive intelligence, a business is only personalizing its existing products and services – which is important to do for today, but not sufficient to win tomorrow. We see CDPs playing an exciting and even more essential role as experience ecosystems become predictive and adaptive. To help retailers understand and respond to customer preferences tomorrow, CDPs will provide an end-to-end view of the customer, regardless of channel or behavior.
Contact Pactera EDGE and Unlock Value with CMO.AI
CMO.AI from Pactera EDGE is a data-driven approach to marketing that optimizes marketing – and the operations that support it – to help your business leverage customer data and best-in-class technology in all-new ways through:
- Data-driven insights that inform every decision you make, from strategy and planning to execution and optimization.
- Real-time experimentation that uses technology to test, learn, and iterate quickly to find what works and optimize for results.
- One-to-one personalization that delivers the right message, to the right person, at the right time at scale.
- Omnichannel orchestration that weaves together the best mix of channels and tactics to reach your customers where they are.
Delivering personalized experiences to people at scale is a challenge all CMOs face. Our CMO.AI solution helps you discover the data patterns that matter, so you can create relevant experiences for each customer and move the digital needle. Contact us to learn more.