Share on facebook
Share on linkedin
Share on twitter
Share on facebook
Share on linkedin
Share on twitter

A Quick Guide to Customer Data Platforms

To solve the problem of disconnected data in a world where we are dealing with millions of touchpoints and interactions, 51 percent of marketers say they currently use a customer data platform (CDP) and 35 percent say they plan to use one. So, what exactly is a CDP, what benefits does it offer, and how does it compare to other customer data systems? 

 

What Is a Customer Data Platform?

A customer data platform is a type of software that collects and organizes data from a wide range of touchpoints in real time to create individual, unified customer profiles.

CDPs can also communicate with other delivery and engagement systems such as marketing automation software, websites, and social media management tools. This means it is possible to plan and execute campaigns directly from them.

Some customer data platforms also have additional functions built in, such as business intelligence, analytics, reporting, and tracking. Their ultimate purpose is to help businesses and marketers make better customer-focused decisions.

 

What Type of Customer Data Does a CDP Work With?

A customer data platform can collect and work with multiple types of first-, second-, and third-party customer data. This includes data from your CRM activities, web forms, website, apps, social media activities, e-commerce site, customer service calls, and even in-store interactions.

These specific types of data can be filed into four broad categories: Demographic data, behavioral data, transactional data and qualitative data.

Demographic data – This includes identity, socio-economic and descriptive data such as age, gender, population, race, income, location, education, employment, social profiles, and hobbies and interests.

Behavioral data – This is generated by online customer interactions. It includes website clicks, product views, social media engagement, email open and click-through rates, and customer service communications.

Transactional data – This comes from exchanges or interactions between a customer and a company such as purchases, returns, subscriptions and abandoned carts.

Qualitative data – This includes information made available through forms and surveys. It collects motivations, opinions and attitudes expressed by customers, such as why they chose your product over others.   

 

How Is a CDP Different From CRM Tools and DMPs?

Like CDPs, customer relationship management (CRM) tools and data management platforms (DMPs) also aggregate customer data for your organization. However, they work differently and serve different purposes. Here are some of the key features of each: 

CDPs

  1. Automatically create unified customer profiles
  2. Collect (mainly first-hand) customer-specific data (e.g., names, addresses, emails) on anonymous and known visitors
  3. Analyze customer behavior and journeys
  4. Track online and offline customer behavior
  5. Built for scale to handle multiple data points efficiently over long periods 
  6. Integrate with multiple other systems

CRMs

  1. Track customers’ interactions with your company
  2. Only collect data from known or potential customers
  3. Analyze sales forecasting and pipelining
  4. Can’t collect offline data unless collected manually
  5. Built to engage customers not to ingest vast amounts of data
  6. Limited integration with other systems

DMPs

  1. Automatically collect data mainly for advertising
  2. Mostly collect third-party data (e.g., through data providers and services)
  3. Reflect anonymous customer identities (e.g., cookies, devices and IP addresses)
  4. Only track online data via a server
  5. Built to retain data for a short period to target ads and build lookalike audiences
  6. Integrate with other marketing systems 

 

What Are the Benefits of a CDP?

Companies using a CDP are more than twice as likely to have significantly outperformed on their main marketing goal for the previous year. Here are some of the reasons why:  

They Make Data Accessible 

By collecting and unifying customer data from multiple data sources, a CDP makes all data accessible to other systems and business functions. This includes marketing, management, sales and customer service.

They Offer a 360 Degree View

CDPs offer a true 360-degree customer profile, or single customer views – unlike other customer data platforms which have never quite delivered it. These complete profiles can give a more rounded, accurate understanding of customer needs and wants. 

They are Flexible and Agile

CDPs allow marketers to be much more agile and responsive to ever-changing market trends and customer behaviors. As data is collected in real time, your communications can be more relevant. Your strategy can also be quickly acted on by connected systems. 

They Deliver More Accurate Predictions & Insights

Some CDP systems come equipped with AI and machine learning capabilities. This means, as well as unifying your customer data, they can also deliver accurate predictions and insights about customers and their future behaviors.

They Boost Efficiency

Not only can CDPs make data collection and unification much faster at scale, but they are also easier to update and can be used to troubleshoot any issues for all systems centrally. This can reduce IT resources and spend.

CDPs are the next generation of customer data management platforms, which will enable you to merge your online and offline activities, improve customer segmentation and personalization, conduct customer scoring, retarget, and achieve omnichannel automation. 

* Do you want to find out more about how to leverage AI to make data-driven business decisions? Get in touch with our team today for an exclusive consultation.

WE ARE HERE TO HELP

Let us know the marketing challenges that you’re facing, and how you want to improve your marketing strategy.

YOU MIGHT ALSO LIKE

Ask the Experts: Rich Wilson of Deviance.ai on the Evolution and Adoption of AI

We recently spoke to Rich Wilson, Founder of Deviance, on the current adoption of AI and data, the impact of technology on some of the key industries, and how to strike a balance between data privacy and customization.    You have founded and helped build a number of AI and data businesses, including in the marketing space. Tell us a bit about your experience and what you’re working on now. I have a background in software development, and during the dotcom boom I built some of the first online stores for companies like Motorola, Homebase and Ocado, and through that I was introduced to the commercial side. I found I really enjoyed being out of the office talking to people, and I realized my skill is translating technology into business and back again. For the past seven years I’ve been working in the language analysis space and generally working with data. I’ve set up a hedge fund on the back of an experiment with fast-moving data sets, applying AI to trading. My most recent business is Deviance, which uses AI to deliver unsearchable insights. We help brands and businesses understand how people are really feeling, helping them understand audiences at

AI in the Smart Retail Era

Author | Dr. Min Sun, Chief AI Scientist, Appier The concept of digital transformation is not new, and businesses of all types and sizes have been under pressure to keep up with the pace of technological change for the past several years. However, the global pandemic of 2020 has caused many organizations to speed up their plans and shift quickly with regard to digital-first operations. Retail is one industry that has had to make significant changes to how it meets the needs of consumers in light of the pandemic, but the transformation in the industry was already well underway. Retail has seen several phases of transformation over the past 70 years or so, from the rise of the department store to the rise of the supermarket, and then into mass production which led to the introduction of chain stores such as 7-11. We’re now in the fourth retail revolution, driven by e-commerce led by companies such as Amazon and Alibaba. A major element of this phase has been the use of technology not just to better meet and anticipate the needs of consumers, but also to make all parts of the retail supply chain more efficient. We are seeing an

How Artificial Intelligence Can Help Enterprises Gain Insights Into Asian Consumers

Artificial intelligence (AI) is without doubt one of the most talked-about technologies today, and for good reason: advances in computation, processing power and storage, and the tremendous volumes of data generated, thanks to new mobile and cloud technologies have come together to drive a renaissance in AI. On the other hand, this confluence of factors is also creating mountains of data – and a headache for any enterprise trying to make sense of all of it. Since Appier was established five years ago, we’ve accumulated a considerable database of billions of anonymized device profiles in Asia, which continues to learn as it grows. This data provides some very good insight into the cross-screen behaviors of people throughout the Asia-Pacific region. Today, I wanted to share a few highlights from our newly-released 2H 2016 Cross-Screen User Behavior Report, generated from our analysis of over 1,800 billion Appier-run campaign data points. For enterprises, one of the report’s key takeaways is just how important it is to understand the cross-device dynamics of today’s consumers. The complexity of these usage patterns make it difficult for marketers trying to reach them using conventional technology. Using AI, Appier is able to process these billions of data