10
min read
/
August 3, 2021
Analytics

What's a CDP? The Definitive Guide to Customer Data Platforms

Bilal Farooq
|
Principal at ikaros
Bilal is a veteran growth professional. He has over a decade of experience growing marketplaces, eCommerce and SaaS businesses in North American, UK, South Asian and ANZ markets. He is passionate about all things growth. He is an approved angel investor at the AngelList Ventures and was the lead organiser of Blockstack (now called Stacks) Sydney chapter. He also volunteers for Give Light Foundation and teaches mathematics to orphans in Indonesia.

Think about the last time you bought a luggage bag online. Probably you started with a Google search on your mobile phone. Visited Amazon, Google Shopping and several eCommerce websites on your laptop. Read reviews on a blog site. Watched video reviews on YouTube before deciding on a particular brand. 

The path to purchase was hardly linear. Most online shoppers follow a similar path moving between different websites, apps, devices and even physical stores before making a purchase. Keeping track of all those different touch points is the modern marketing challenge. CDPs help companies solve that challenge by stitching together data from a myriad of sources into a single user profile. 

Looking to learn about CDPs? That is why we have authored this comprehensive guide for you. Use the table of contents below to jump to any section of the guide.

What is customer data?

Customer data is any piece of information that businesses collect directly from the customers through websites, mobile apps, social media, physical stores, surveys or through any other touch-point. The business objective of collecting customer data is to improve marketing, product, support and overall customer experience.

What are the different types of customer data?

There are several types of customer data including personal, behavioural and attitudinal.

1. Personal data

Personal data consists of Personally Identifiable (PII) and non-personally identifiable information (non-PII). 

Personally Identifiable Information (PII) can be categorised into linked and linkable data. 

Linked data can directly be used to identify a person. For example:

  • Full name
  • Address
  • Email
  • Social security number
  • Passport number
  • Driver’s license number
  • Credit card numbers
  • Date of birth
  • Phone number

Whereas, linkable data cannot be used to identify a person unless that is combined with another piece of information. For example:

  • First or last name
  • Location: country, state, city, zip code
  • Gender
  • Race
  • Non-specific age (e.g. 30-40 instead of 30)
  • Job position
  • Workplace

Non-Personally Identifiable Information (non-PII) is that data that cannot be used to identify any person e.g. IP addresses, cookies, device IDs etc.

2. Behavioural data

Behavioural data captures how customers interact with the products and services. Web, mobile, email, social media, video, advertising platforms, chatbots, SmartTVs and wearables are among the numerous behavioural data sources. Below are details on the type of behavioural data collected from the aforementioned sources:

  • Web: Page-views, bounce rate, sessions, device choice and goal completions are the usual metrics used to measure user behaviour with web apps. Google Analytics is a popular tool that captures this data. Enterprises also use Adobe Analytics to perform web analytics at scale.
  • Mobile: Active usage (DAUs & MAUs), app downloads, retention rate, and exit rate are common metrics to understand mobile user behaviour. Mixpanel and Amplitude are popular tools used for mobile analytics.
  • Email: Open rate, CTR, List growth rate, number of unsubscribes, conversion rate, and revenue per email are used to analyse user behaviour with emails. Constant Contact, HubSpot and Drip are tools of choice for capturing and analysing this type of data.
  • Advertising platforms: Ad clicks, impressions, conversion rate, cost per conversion and attribution are important data points to measure behaviour on the paid advertising side.
  • Social Media: Virality, shares and the number of comments are used to measure behaviour on social media.  
  • Video: According to research by Cisco, 82% of the Internet's traffic will come from videos by 2022. Therefore, videos have become an essential channel for businesses to engage with their customers. Video views, play rate, watch time, and completion rates are important metrics to measure user behaviour with video content.
  • Chatbots: Number of sessions, conversation length, user distribution by time, interaction rate, and user feedback are used to track engagement with chatbots.
  • Smart TVs: Device-level data is usually measured by Smart TVs. However, Smart TVs provide an option to create user accounts. Therefore, if user accounts are used then user-level data can be also captured. Total viewing time and viewing time per screen are used to measure the viewing behaviour of Smart TV users.
  • Wearables: Wearables are normally used to track health and fitness-related user data, such as sleep, heart rate, blood pressure and activity such as the number of steps taken.

In addition, businesses need to collect transactional data to understand & improve business performance including the cost of acquiring a customer (CAC), lifetime value of a customer (CLTV), average order value (AoV), number of abandoned carts, order dates and RFM (recency, frequency and monetary value) of purchases.


3. Attitudinal data

Attitudinal data identifies the factors affecting customer's behaviour such as feelings, emotions, needs and motivations. Attitudinal data is mostly qualitative. It is obtained through user surveys, interviews, focus groups, feedback, customer complaints, and reviews. Below are a few examples:

  • Customer experience: Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS) are examples of attitudinal data used to measure customer experience. ZenDesk is a commonly used software that captures this type of data.
  • Usability: System Usability Scale (SUS) is measured by asking 10 questions, of which 5 have positive wordings and 5 have negative wording. The user answers the questions on a scale of 1 (strongly agree) to 5 (strongly disagree). The overall score is calculated by adding and subtracting the answers following specific rules. The result is always in the range of 0 to 100. The diagram below shows a SUS questionnaire.
Source: Design Kisk


As you can see, there is a wide variety of data that CDPs collect and organise. Much of the data types and categories that you need to collect depend on your business and industry.

What is the importance of customer data?

Companies have realised the value of customer data collection. In recent years, the focus of companies has moved from how to collect data to how to leverage customer data to:

  • Understand the complete customer journey 
  • Create effective marketing strategies
  • Improve customer experiences
  • Personalise products and services
  • Optimise operations
  • Gain a long-lasting competitive advantage

Now that we discussed the different types of customer data and their importance, next, we explain what is a CDP and what it is not.

What is a CDP?

According to David Raab the founder of CDP Institute, a CDP is defined as "a packaged software that creates a persistent, unified customer database that is accessible to sales, customer service, online advertising, point of sale, and any other customer-facing system."

The following diagram illustrates the relationship of a CDP with other systems.

Source: EmailVendorSelection.com


Why do you need a customer data platform?

Businesses need CDPs as those offer several benefits to improve customer experience. Here are few of the key benefits that CDPs offer.

CDPs break Data Silos

Data silos are created when one department of an organisation holds a data set that is inaccessible by other departments. Data silos obstruct the process of creating a holistic view of the customer. They create a barrier to having a single version of truth that can be used to gain deep and actionable insights. 

CDPs break data silos by unifying data from all online and offline sources in real-time. Thereby enabling deep analytics. CDPs also make data accessible to everyone in the organisation.

CDPs collect first-party data

Google is ending third-party cookies in the Chrome browser by 2023. Many other browsers have already deprecated the use of third-party cookies. So, cookies are crumbling. Privacy laws like GDPR are making organisations realise the importance of first-party data. 

CDPs are primarily focused on collecting first-party data. Therefore, businesses can make most of their first-party data with the use of CDPs.

What are customer data platforms examples?

Here are two of the leading CDPs.

Segment

Twilio's Segment is a leading CDP used by thousands of companies including Intuit, FOX, Instacart, and Levi’s. Segment can be readily connected with over 300 marketing and analytics tools.

Segment offers three pricing plans: Free, Team and Business. The Free plan is free forever but offers very limited features. Only two data sources and 1,000 monthly users are supported under this plan. Team plan offers the essential set of features but the Business plan unlocks the full potential of Segment CDP including the two add-ons, Protocols and Personas. 

Tealium AudienceStream

Tealium offers a CDP that has gained significant traction. Tealium's customers include New Balance, Barclays Bank and Hotwire.

The main differences as compared to Segment include that Tealium does not offer a free trial. Pricing is not transparent i.e. not available on the website and one has to contact the sales team to get a quote. Tealium is considered to be more suitable for large enterprises than small organisations.

CDP vs CRM vs DMP

CDP is usually compared with other customer data collection platforms especially, CRM (Customer Relationship Management software) and DMP (Data Management Platform).

CRM also collects customer data but the main difference between a CRM and a CDP is that a CRM only collects customer-facing interactions with a business via manual entry. CRM records the customer's name, history of the number of interactions, and any support tickets the customer has opened with the business. CDP, on the other hand, automatically collects data about each step of the customer journey and each interaction with the product or the service.

CPD works with both personally identifiable and non-personally identifiable information. Whereas, DMP works almost only with non-personally identifiable and anonymous information, such as cookies, device IDs and IP addresses.

The diagram below illustrates the differences between CDP, CRM and DMP.

Source: Exponea.com


What does a customer data platform solve?

Here is a case-study that highlights the use of CDPs in solving marketing challenges.

Case study: America's Test Kitchen achieved 72.9% direct conversion to click ratio with the use of a CDP (Source: blueconic.com)

Use-case: Increase cross-sell & up-sell conversions.

America's Test Kitchen is a multimedia company with TV shows and magazines. They also sell their cookbooks online. 

America's Test Kitchen deployed a CDP and took the following steps to get 72.9% direct conversion to click ratio.

  • Used the CDP to organise, connect and unify 10+ years of historical data (about their customers) available in their disparate systems, into individual profiles.
  • Analysed the unified profiles to understand how the customers were interacting with their brand.
  • Created various journeys based on behavioural analysis for certain target audiences based on their likelihood to buy an additional product at the checkout.
  • Created email campaigns that they sent regularly to customers. Advertised their cookbooks and other products at reduced prices.
  • Tracked when a customer clicked through the email campaigns. Knowing that the customer was part of a specific audience segment, personalised the landing pages in real-time to match the sale price with the price that was shown to the customer in the email.
  • If the customer chose to add a product to the cart, then she was also shown an upsell and a cross-sell product, related to the carted product.

In addition to increasing direct conversion to click ratio, the CDP eliminated the need to create multiple experiences specific to each customer segment because the CDP enabled America’s Test Kitchen to update the data dynamically on the site.

Conclusion

Customer Data Platforms have become an essential part of the growth stack. CDPs unlock the full potential of customer data. CPDs enable single view of the customer, segmentation, personalisation, predictive analytics and running AI on customer data. Without a CDP companies can’t future proof their marketing and can fail to deliver revenue growth. 

If your company is looking to implement a CDP or needs help with getting the most out of your existing CDP implementation, give us a call on +61 2 8311 8689 or email us at hello@ikaros.io.

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