Overview
Many have asked. Many have defined it. Here's my definition:
A modern Customer Data Platform (CDP) is a software solution that is intended to aggregate and compile information and insights for each of your revenue-contributing marketplace participants—Prospects, Customers, and trading partners, surfacing profiles, alerts, suggestions, and predictions to the business when needed, where needed.
You thought that was CRM. OR maybe BI or DW, or marketing…OK, is this just another new and costly software platform that is again promising to give us that “360” degree view of the customer we’re still missing?
Well, yes. The problem is in the way the world and the marketplace work.
Companies necessarily do not have just one application that serves the needs of all customer touchpoints. CRM, ecommerce, ERP, SCM, operational/ fulfillment system, marketing automation, POS, collaboration tools, web analytics, and many SaaS tools, etc. It’s a fact.
DW’s are intended for broad (often cubed) business analytics, not focused on specific customer comprehension and relationship or commerce optimization. DW’s are expensive and somewhat rigid; often latent.
Marketing Automation is best suited for scaled communications blasts and all the work that leads up the mass distribution of messaging.
BI is the analytical and presentation layer, but it needs one or more sources, which implies a prerequisite and expensive OLAP style database behind it. See DW.
Let’s face it, unless your business is simple and static, information is fragmented and dispersed. It is volatile and porous; and without a tool tuned to the customer or prospect as a real-life entity and has the full context of their nature and transactions across all channels, you will not get to a 360’ view or any computer-assisted actions to make you a high=performing business without a CDP.
So, let’s come to know the CDP. It’s not expensive; and it is a very interesting, beneficial technology for large and small businesses, including B-B and B-C models.
What Kind of Information can it track?
Ascendant Group’s Customer Science™ data model classifies business information that is the source of CDP in the following way:
1. Entity Identity Data
Identity data builds the foundation of each customer profile in a CDP. This type of data allows businesses to uniquely identify each customer and prevent costly replications. Identity data includes:
Name identifiers, such as business name, legal name, alias’s, contact first and last name
Demographic and firmographic information, such as age and gender
Geographic, such as address, city, and zip code
Channel URI’s, such as phone number, text/mobile, web ID, LinkedIn, Twitter handles
Professional information, such as professional license level, job title, job function
Account information, such as bill-to, credit type
2. Descriptive Data
Descriptive data helps you understand the nature of the contacts and organizations that interact with you
These data points can be publicly known or privately compiled. They fall into three groupings: Demographics (for residential consumers), Firmographics (for business consumers and business partners) and Personae or role descriptors (contacts at households or businesses)
Business: industry, tenure, ownership type, size, model, brands, category positioning, locations, etc.
Resident: age, income, occupation, home type, location, family structure, asset types, ethnicity, gender, lifestyle
Personae: personality attributes, decision role, job function, promoter type, skills, licenses, reports-to, etc.
3. Commercial Data
Commercial data is important transactional data in your various systems of record that encourage revenue. These records indicate processes and show a positive commercial outcome or an attempted and lost/rejected outcome; both outcomes are critical to understanding your customer.
Shopping carts
Favorite products
Quotes
Opportunities
Sales Orders
Subscriptions
Trials
Invoices
Payments
Shipments
Returns
4. Behavioral Data
Online visits
Communications events: calls, emails
Retail or interpersonal visits
Social conversations
Event participation
Ecommerce behaviors
Issues, complaints, surveys
Promotional offers accepted
5. Derived Data
Ideas
Sentiments
Preferences
Measures
Scores
Segments
Trends
Derived data is the ultimate objective and is the basis for decisions about how to proceed in any situation. It is the basis for use of your individual business intelligence or artificial intelligence or both. Once you have this information in the CDP, you can create strategies, develop refined messaging, campaigns and suggest prices, offerings, promotional offers, and next best actions. You can detect and predict future events such as customer intent, churn and buying patterns.
CDP Comparison to other business solutions
To help you understand the value proposition and where it fits into your solutions portfolio, here are the three comparisons that are frequently requested.
CDP vs. CRM
A CDP collects information from CRM and other OLTP’s and then compiles it in a way that accelerates and energizes all 1-1 customer communications and marketing. It allows CRM users and executives to make better decisions as the most appropriate and impactful type of BI for the strategic revenue and product planning.
CDP needs CRM data for proper digestion and summarization. CRM needs CDP information to allow it to see full customer profiles from CRM transactions as well as all other systems.
CDP vs. DMP
DMP is a progenitor to CDP, which focuses on online, browser-to-URL tracking and online behavioral analysis involving nameless visitor metrics. DMP allows instant ad targeting and message customization. DMP serves digital marketing. DMP’s rely heavily on 3rd party data and real time services.
CDP is for all identifiable and anonymous channels, allowing the user to collate information from many sources and present them or AI-driven recommendations and alerts about them from across all touchpoints. CDP serves sales, marketing and customer service…the primary CRM constituents. CDP uses 3rd party data but blends that with 1st and 2nd party data from across all applications that touch the customer. CDP needs DMP inputs but not vice versa.
CDP vs. DW
DW is a broad organizational resting place for business knowledge at various business dimensions but is not generally structured to focus on the intimate details that make your customers tick. You can get aggregates, but you can’t relate it to specific customer awareness where and when you need it. It’s not intended to recirculate data like a CDP, rather expose it in BI sessions.
Key Benefits of a CDP
CDPs improve your organization, better your customer relationships, and complement your current software and marketing efforts. Here are a handful of key benefits of having a CDP.
• CDPs Break Data Silos: CDPs can help your organization prevent natural data silos that occur as motivated and empowered business leaders use various applications and services to do their jobs. But line-of-business applications are not meant to collate and compile big data. They create the data from everyday business processes, but struggle to unify it from across the business.
• Know Your Customer: CDP’s are uniquely geared to provide information compilations about all aspects of your customers, letting you know them better than they know themselves. This is critical for making decisions, crafting messages, and taking confident action. These are the degrees of differentiation that most businesses need to compete in their marketplace.
• Feed CRM: Your CRM is not intended to be a transactional warehouse with feeds from every other application. It is not good at summarizing and synthesizing big data. It is an everyday tool to manage full-service customer interactions. Give it the fresh, complete customer profiles that come from all channels and applications. Provide it on time, and in the proper context.
• Amplify Marketing: Marketers struggle to get the information they need to message and fine tune campaigns, so ROI is guaranteed on marketing spend. Eliminate the noise and fine tune the messaging; create more conversions and MQL’s.
• Take Pre-emptive Action: use the trends, measures, scores and changes over time with machine learning and AI to suggest when and how to act. Your next best actions should be well times and appropriate to maintain high-performing commerce. Churn threats, CSAT issues, competitor threats, pricing opportunities, retargeting lost sales, offer presentation…all of these depend on detecting and predicting customer intent.
Explore how a CDP can boost your business. You’re closer than you think.
Ascendant Group Inc. is a consulting and data services business specializing in CRM advisory services, data management services and CDP managed services. Contact us today for more information.
See this Forbes article