A Marketer’s Guide to Customer Data Platforms

Making a CDP Work for You and Your Business

ContentsIntroduction Page 3

What is a Customer Data Platform? Page 4

Core Features of every CDP

Different Types of CDPs

The Importance of Being ‘Marketer Owned’

Technologies Commonly Confused with CDPs Page 9

Data Warehouses (EDW)

Data Management Platforms (DMP)

Customer Relationship Management (CRM)

Tag Management Systems (TMS)

Master Data Management (MDM)

Why You Need a Customer Data Platform Page 15

Making Strategic Use of CDPs

Questions to Ask When Considering a CDP Page 20

What Do You Want a CDP Project to Achieve?

The Marketing Technology Stack Page 22

Marketing Architecture Concepts

BlueVenn x1x

Conclusion Page 28

Page 3

Introduction

At the beginning of 2018, Martin Kihn, Research Vice President at Gartnersaid, “No marketing tech in recent memory has shot up the hype curve so far,so fast, as the Customer Data Platform (CDP)”.

This hype has not been without good reason.

Marketers want control of their own customer data. Ideally in a database thatcollects and integrates all customer data sources, across all the businesssystems that manage and record customer touchpoints. It is not enough tojust consolidate this data in one place; marketers require an accurate andconsistent record for each customer and for this data to be available to allmarketing applications and processes.

The rapid upward trajectory of CDPs has sent waves through the industry.Over the last couple of years, new CDP providers have sprung up around theworld, including many vendors of similar solutions that have rebranded tocapitalize on the intense interest surrounding the term.

To manage this extraordinary growth, Customer Data Platform ‘godfather’,and founder of the Customer Data Platform Institute, David Raab, has helpedto refine the classification of the term, grouping this burgeoning number ofvendors into new and appropriate sub-categories.

Yet no one piece of technology, even a CDP, is the final answer to all of yourmarketing issues. However, our perspective is that the single view of thecustomer, combined with multi-channel customer journey orchestration, canhelp businesses achieve personalized and targeted marketing.

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What is a Customer Data Platform?

Ecommerce

POS

Website Behavior and Analytics

Customer Complaints andFeedback

Mobile App

Unified Customer Data

CDP

Representatives

Email

Web / App Personalization

DMP

Social Media

Direct Mail

Data Feeds Marketing Channels

Page 5

Core Features of a CDP

To be classified as a CDP the technology needs to conform to the following criteria:

Marketer controlled

This means that a CDP can be purchased and operated by the marketing department, with minimalassistance from others (such as internal or external IT teams or other external vendors or partners).Marketers can take full advantage of its capabilities, without needing the same degree of skill andtechnical knowledge as data scientists.

Create a unified, persistent database

A CDP unifies customer data from disparate business systems. This can include, but is not limitedto, your CRM, PoS, mobile data, transactional data, website data, email data, third-party data,legacy systems, etc. Persistent means that the CDP stores its own copy of the data, rather thanshuffled between applications that do not store the data themselves. This database bringstogether this siloed data, where it undergoes processing to bring data together from disparatesources into a unified database, forming linkages on customers from these separate systems.

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Accessible to external systems

This means the Customer Data Platform is vendor-neutral, easily leveraged by external systems to use in their ownprocesses. For example, the CDP provides data to build campaigns and models, the data for rules-basedpersonalization on web and mobile, and manages the customer profile database used for creating campaigns,sending emails and display ads. It can also supply accurate, unified customer data to CRM systems. Equally, the datacan be surfaced to the operational systems that need it.

In addition to these points, the 2018 Customer Data Platform Institute Vendor Comparison guide outlined thefollowing additional definitions. Although these features are not exclusive to CDP solutions, all CDPs can do them:

• Retain original data details: The system stores data (such as transactional data,browsing data, personal data, etc.) with all the detail provided when it was loaded.This means it maintains an audit trail to ensure data accuracy and consistency.

• Access individual data details: The system can access all detailed dataassociated with each person (as opposed to segment tags).

• Can manage Personally Identifiable Information (PII): This includes name,address, email and contact numbers. As PII, it means that the data can only behandled subject to privacy and security regulations.

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Data Assembly CDP

Perhaps the most ‘basic’ Customer DataPlatforms, Data Assembly CDPs perform thecore functions of a CDP but nothing else. Theygather customer data from your various sourcesystems, forming a unified, persistent databaseof ‘golden records’ (a clear, non-fragmentedpicture of the individuals who make up youraudience), and makes these records available toall your external systems.

Customer Experience CDP

Customer Experience CDPs can perform all ofthe aforementioned data and analyticaloperations, with the addition of multi-channelcampaign management and customer journeyorchestration. The delivery of these treatmentscan include personalized messages, real-timeweb and email content, as well as sendingaudiences to a DMP for the placement of hyper-targeted adverts.

Analytics CDP

In addition to the essential data assemblyfunction, these CDP solutions include analyticalapplications to track a customer acrosschannels, provide insight into customerbehavior, and analyze third-party data. AnalyticsCDPs can perform customer segmentation,data modeling, and have the ability to sendsegmented lists to marketing tools, like emailsoftware, Data Management Platforms (DMPs)and personalization platforms.

Different Types of CDPs

In January 2018, the Customer Data Platform Institute released an Industry Update report, which sought to provide clarity to the different subsets of CDPs based on their capabilities. This led to the following refined CDP categories:

Page 8

The Importance of a ‘Marketer Owned’ Database

The marketer’s need to access, manipulate and use data, rather rely on athird-party marketing services provider or acquire IT resources, is a large partof the aspiration for a Customer Data Platform. Marketing teams need toiteratively analyze and activate customer data and create targeted, relevantcampaigns. More importantly, they need to be able to do this in the space ofminutes, not wait hours or days for their requests to be processed bysomeone else.

However, when investigating the need for a Customer Data Platform,consideration needs to be given to whether this ‘marketer owned’ databasealso means ‘marketer responsible’.

There are risks that come with the handling and processing of customer data,and strict policies for ensuring the privacy, security and governance of it. Ifmarketers are given total access to customer data, they are also exposed tothe many hazards associated with this ownership.

The risks of non-compliance include both punitive action by data protection regulations and also the damage that the misuse of personal data can do to customer relationships and company reputation.

While CDPs can help with compliance to data laws (you can read more about this in the ‘Why You Need a Customer Data Platform’ section), that is assuming marketers do not have completely unrestricted access to data.

When looking at Customer Data Platforms, you may want to investigate solutions with the appropriate safeguards that mitigate the data ownership risks. For example, CDPs with a Single Customer View process that adheres to internal and industry data management policies and requirements and creates a time-stamped audit trail that provides full visibility of all actions, queries, errors and results that can be traced back to source if required.

Page 9

Technologies Commonly Confused with CDPs

As anyone familiar with Scott Brinker’s annual Marketing Technology Landscape ‘supergraphic’ will know, it can be challenging to keep up with new technologies – particularly with the proliferation of buzzwords, acronyms, and with many vendors in different categories claiming to have similar functionality.

As such, it is worth clearing up the differences between CDPs and some of the other solutions they are most commonly confused with.

Page 10

Data Warehouse (EDW)

What is it?

A data warehouse (often referred to as an enterprise data warehouse, orEDW) is a central repository of large amounts of business information frommultiple data sources. Data warehouses contain data from sales, marketing,purchasing, finance, and other business functions. They help organizations tostore and manage data, making data easier to find, access and use.

What does it do?

A data warehouse consolidates and standardizes data, structuring it in a wayfor use in analysis and business intelligence reporting.

How is it different to a CDP?

The main differences between an EDW and a CDP are the scale, and thepurpose. As data warehouses store all corporate data, this typically makesthem large, expensive, IT-driven (and IT owned) projects designed to serveanalysis for the whole enterprise. A CDP, as the name suggests, is interestedonly in customer data, built for the needs of marketers and operated by them.

Like the other technologies mentioned here, an EDW does not include cross-channel identity resolution for the creation of a Single Customer View, nor dothey support real-time updates or access. This means marketers cannotextract and use the data they need as quickly as if they were using a CDP.

Additionally, EDWs do not transform data specifically for marketing purposes.A retail business, for example, may store purchase and/or transactional dataas codes (‘MX1294’ rather than ‘brown leather shoes’). Being able to bring allthis data together in a standardized format is extremely valuable formarketers to track the buying behavior of their customers across systems andbuild a more joined-up view of their engagements.

Unlike a continually refreshed CDP database, EDWs aren’t updated as often,which can create some of the issues that come with poorer quality data.

OperationalEnterprise

Applications

Data Warehouse

BI Users

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Data Management Platform (DMP)

What is it?

A DMP is a platform that ingests, collates and stores first-party (the data abusiness collects about its own customers and visitors) and third-partyaudience campaign data from external online, offline and mobile sources. Itmakes refined audience segments usable by other platforms to place displayads and customized ad content.

What does it do?

It allows users to create highly targeted adverts, personalizing the onlineexperience to specific audiences of people based on their demographic,psychographic and behavioral data.

How is it different to a CDP?

DMPs use aggregated (mostly third-party) data to target anonymous cookiesfor advertising and retargeting strategies. CDPs use first-party data (anorganization’s own customers), combining online and offline data (oftenenhanced with third-party data), to deliver personalized experiences, acrossmany marketing channels. While a DMP can ingest first-party data foronboarding, it cannot make Personally Identifiable Information (PII)actionable like a CDP can.

A DMP creates lookalike audiences using anonymous digital identifiers fromacross the web, gathering data about their interests based on their internetbrowsing behavior. As a CDP works with ‘known’ individuals, it can createone-to-one treatments for many different types of marketing, likepersonalized web pages, emails, offers and more.

As one focuses on real, personally identifiable customers and the other onanonymous customers, CDPs and DMPs often work very well together andcompanies may consider using both.

External Sources/ Users

Internal Data Sources

Data Management

Platform

Display Ads, Email Campaigns, Social Platforms, etc.

Page 12

Customer Relationship Management (CRM)

What is it?

CRM systems compile and consolidate data from customer interactions withcompany touchpoints (website, telephone, mail, live chat, social media, etc.),to help businesses manage relationships with their customers and prospects.

What does it do?

CRMs give businesses visibility of customer contact information and sales opportunities. Some have the ability to automate marketing campaigns to those customers (others may do this with the aid of an additional execution tool). They help with lead nurturing, customer retention, and forup-selling to existing accounts. Unlike a CDP, marketersare not the primary users of a CRM.

How is it different to a CDP?

A CRM compiles customer data and helps optimize a company’s interactionswith its known customers. However, if a customer is ‘unknown’ (as in, youhold data about them but it’s in a system or data point your CRM doesn’trefer to), a CRM cannot identify them or engage with them.

A CDP, on the other hand, can identify customers (and new prospects) frommany different data sources and, importantly, unify that data into a single,persistent record. Data collected by a CRM is not treated to a SingleCustomer View process, meaning customer records are not matched, mergedor deduplicated.

As a contract management solution, CRMs can be used to view as much dataas possible about an individual record. A Customer Data Platform, on theother hand, can handle large volumes and types of data, integrate it, andmake it usable to orchestrate cross-channel communications. It canpersonalize customer experiences at scale, while CRMs are better suited forsalespersons to manage their accounts.

Like a DMP, a CRM can be included as an input channel of a CDP, providingdata that can improve a company’s ‘golden record’.

Marketing Transactions

Analysis Reporting

ERP and Finance

Customer Service

Sales

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What is it?

A Tag Management System assists with the implementation andmanagement of ‘tags’ within a business’s websites and other digitalproperties. Tags are snippets of code embedded into a web page to recordinformation when a customer accesses and interacts with a company’swebsite. This therefore enables a company to perform customer tracking,analysis and reporting – which proves to be useful when implementing agilemarketing to boost conversion rates.

What does it do?

A TMS is used by businesses that want to establish a foundation for theirdigital data collection. It is primarily designed to help manage the lifecycle ofthese tags, replace the tags with single container tags and prioritizeindividual tags over others based on business rules, navigation events andknown data.

Tag Management Systems are also used for increasing website speed,boosting workflow efficiency and providing behavior classification so thattools for analytics and personalization can be applied to enhance campaigns.

How is it different to a CDP?

A TMS is not designed to gather clean customer data, and therefore it doesnot automatically provide an insight to individual customers that a CDP can.However, marketers can feed a TMS into their CDP in order to enhance theirview of the customer.

Despite their differences, TMSs and CDPs are sometimes confused – partiallybecause both are concerned with the collection of data. Marketers can usethe data collected by a TMS to improve the customer experience and refinetheir marketing strategies.

Tag Management Systems (TMS)

Tag

Website

TMS

Tag

Tag

Page 14

Master Data Management (MDM)

What is it?

Master Data Management (sometimes referred to as a ‘data hub’) is a set ofdisciplines, processes and technologies to ensure data accuracy, reliabilityand consistency across a business. It provides a single point of reference thatallows the business to work together to ensure its master data assets areshared throughout the organization.

What does it do?

MDM tracks the most essential data points within a company, known asmaster data, to provide various departments with insights to companyoperations, customers and business goals.

Through pulling in data from different sources, MDM locates the coreinformation that is most relevant to the business and its objectives. This datacan then be used and implemented by teams throughout the organization.

MDM ensures the uniformity, accuracy, consistency and accountability of abusiness that shares its information. It achieves this by identifying, collectingand repairing data to create a high quality master reference for those thatrequire it.

How is it different to a CDP?

While MDM can unify data to create a ‘single source of truth’, it is not specifically designed for the needs of marketers or solely capturing customer data. Therefore MDM is not traditionally a marketing-led (or marketing-operated) initiative.

Moreover, unlike a CDP, MDM does not easily connect to marketing delivery systems. It can, however, be a source of information that feeds into a Customer Data Platform.

Instead, MDM facilitates the sharing of enterprise data within a business,rather than being a platform to enhance the customer journey and increasepersonalization within marketing campaigns.

MDM

AccountsCredit

Product

Transactions

Sales

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Why You Need a Customer Data Platform

To improve operational and marketing efficiency

Having a unified view of customers lays the foundation for more effectivemarketing. A CDP enables marketers to answer complex questions of theirdata, build accurate models and personalized marketing content that can beintegrated into optimized campaigns. With a CDP, marketers can utilize adata-driven strategy that leverages their entire understanding of a customer.

Increased customer acquisition

Reduced customer churn

Higher average order values

Increased marketing engagement

Improved campaign ROI

Cost savings through more efficient analysis of data

Human error at the data processing stage can be mitigated

To improve data law compliance

With greater control over data, and through the creation of a ‘single source oftruth’, a CDP mitigates some of the risks associated with adhering to datagovernance and auditing laws. This can include greater administrativeprocedures for the processing and use of customer data for marketing. Forthose companies that handle the personal data of EU citizens, conforming tothe General Data Protection Regulation (GDPR) is a high priority.

Preference centers

Right to be forgotten

Usage tracking

Data field screening

Streamlined data Subject Access Request (SAR) responses

Audit trail of marketing permissions

Although we have covered some of the benefits of a Customer Data Platform, your business objectives will vary greatly from another organizations. Even so,some of the main operational and aspirational reasons why an organization might choose to undertake a CDP project are:

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To ‘own’ marketing data

Rather than working with a database owned by IT, a CDP lets marketersleverage their data by putting the power in their own hands. This can be usedfor analysis and research, to make segments, to build and execute campaignsand get reports. A CDP means marketers do not have to go back and forth toIT and make requests to access data and get that data back. Marketers canmanipulate data themselves, enabling “train-of-thought” analysis.

Reduced time to data

Reduced campaign development time

Greater campaign volume

Deeper customer segmentation

Lower marketing costs

To integrate disparate systems and channels

As we cover in more detail later, the most effective marketing solutionrequires a unified view of channels and unified customer data. A CDP canbring previously fragmented data systems together. However, the addition ofa marketing automation platform (a feature of ‘Customer Experience’ CDPs)can orchestrate the creation and sending of communications across all ofyour channels. This enables companies to maintain the integrity of customerjourneys, preventing customers from ‘falling between the cracks’ as the movefrom one of your touchpoints to another.

A sound basis for creating and using predictive models

Build omnichannel customer journeys

Continual feedback loop from campaigns to refine future messaging

Create triggered campaigns

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To improve the customer experience

While many of the features of a Customer Data Platform benefits marketers, it is important not to overlook how the technology can help improve the customer experience.

For example, more detailed, accurate customer records is the basis for personalized marketing strategies, real-time web and email engagements.

It can also ensure a consistent customer journey is maintained across marketing channels, improving customer lifetime value.

Right message, right time

Create targeted and personalized communications

More consistent, satisfying customer experiences

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Making Strategic Use of Customer Data Platforms

To identify the right prospects and high opportunity segments to increase acquisition of new customers

For example, this could be a media company wanting to identify new highgrowth subscriber groups and to feed relevant customer information to itsadvertiser network to help with the placement of more targeted ads.

To increase engagement over the customer lifecycle to increase retention and repeat purchases

This could be a cosmetics company that wants to analyze its top-sellingproducts and how likely they are to be repurchased again, as well as thoseproducts that are most commonly bought alongside other items.

To identify the top customers to nurture and to get other customers to this level

For example, this could be a leisure company using segmentation analysisto reveal how it can cater to loyal members, or identify members who areat risk of churn without intervention.

To focus my efforts on the right people to market to and save my time/money/resources by not wasting effort on marketing to the wrong people

For retailers that make use of a direct mail catalogs, for example, a cleanand deduplicated customer database, along with a refined view of theirbehavior, a CDP can help ensure that costly mailings are only sent to thecorrect people and addresses.

While different verticals will undoubtedly have their own specific business objectives, it’s safe to say that there are two that will be applicable to almost every company: to increase their sales and to reduce their costs. Plus, there are key business strategies that are applicable to a fairly broad range of industries, for example:

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To make marketing more effective/efficient through targeted and personalized communications

Analysis of the history of online and offline product and transaction data,combined with a trustworthy, unified view of customers, enablesmarketers to tailor communications. For example, by referencing pastpurchases and behavior in order to make marketing messages personal.

To deliver the right message at that right time

For example, a travel company that uses a CDP withintegrate real-time marketing tools can send triggered abandoned cartmessages to customers who did not complete their ticket purchase.

Any company can use a CDP to create automated, multi-channelmarketing campaigns for acquisition and retention strategies.

Unify the customer experience across channels to increase customer satisfaction and overall LTV

Retailers are under particular pressure to deliver an omnichannelshopping experience. A ‘Customer Experience’ CDP helps brands build acustomer journey ‘ecosystem’, where responses from one channel caninfluence and adjust another. Conversations can be maintained ascustomers move from one touchpoint to another.

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Questions to Ask When Considering a CDP

Before undertaking a Customer Data Platform project, there are several questions you should ask yourself, and other stakeholders, before creating an RFP to attract vendors.

Data

• What does my existing marketing stack look like?

• Where is my information stored currently?

• What marketing systems do I want to feed into a unified customer database?

• Do I need to merge online and offline data?

Integration

• Which marketing channels do I wish to coordinate customer experiences across?

• Are there existing technologies I want to connect with a CDP?

Analytics and Reporting

• What types of segmentation do I wish to conduct?

• How can I incorporate predictive modelling and machine learning into my marketing decisions?

• Which KPIs do I wish to track around my marketing activity?

• How do I assess campaign effectiveness?

Marketing Automation

• How do I currently manage customer journeys across channels?

• Am I spending too much time preparing data for campaigns?

• Do we want to handle the creation and execution of campaigns in-house, or with a third party?

Business Goals

• What activities do I hope to drive with an enhanced understanding of my customer (increased acquisition, reduced churn, etc.)?

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What Do You Want a CDP Project to Achieve?

Organizations often desire a Customer Data Platform solution to approach the following challenges. Here are common requirements we see from businesses:

Managing Data and Data Analysis Action Data and Execute MarketingI want the ability to handle structured data from a wide range of data inputs. I want to create more personalized and targeted messages based on my full

understanding of a customer.

I want a single view of my customer to better understand them, interact with them,and acquire new prospects in a targeted manner.

I want to automatically manage my customers across all stages of the customerlifecycle.

I want a ‘single source of the truth’ on which to base analysis and reporting on. I want to drive marketing campaigns based on different customer segments,behaviors and preferences.

I want a single view of my customers in order to be able to improve the products andservices that the business offers.

I want to enable and inform the way we deliver our omnichannel services to give ourcustomers the best service, whatever the channel they choose.

I want to be able to quickly identify, query and extract data to support and drive mybusiness decisions.

I want to be able to create triggered content, such as abandoned basket emails, basedon customers’ online behavior.

I want a security framework and data governance process to ensure my data isaccurate, protected and compliant with relevant data protection laws.

I want to be able to integrate my loyalty platform and reward brand promotion.

I want to be able to analyze data and be able to use this analysis to predict trends andpatterns and create predictive models.

I want to be able to personalize email and website content based on a blend of offlineand online data.

I want a solution with a high level of integration between my website, CRM and emailsolution to reduce manual intervention and the risk of errors.

I want a solution with the ability to coordinate multiple marketing campaigns, trackthe results and provide campaign metrics in real-time for decisioning.

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The Marketing Technology Stack

A typical customer journey today incorporates dozens of differenttouchpoints. New channels of engagement are appearing all the time.Understandably, marketers want to be able to deliver an optimal customerexperience across all of these channels.

As we’ve established, the explosion of options within the marketingtechnology landscape means marketers tend towards ‘best-in-breed’solutions that manage one channel (or just one part of a channel), ratherthan opting for marketing suites.

This means that your average organization has developed a technology ‘stack’that contains many different systems to create the customer experience. Theproblem is, each system interacts with customers in a different way, andcollects different information about those customers.

Unmanaged, this quickly leads to the creation of siloed data systems anddisparate data.

Decisions, too, can become ‘siloed’. Even within a marketing department,teams might have the same goal, but work independently. For example, anemail marketing manager could have their own objectives, and their own toolto create and send emails. However, any campaigns created might not factorin other stages of the customer journey, and the results of theircommunication may not influence the messaging across other channels.

This disparate data and decision-making presents one of the biggest hurdlesto your understanding of your customers. It prevents you from forming acomplete picture, and makes it challenging to put data to use when engagingwith those customers.

A retailer, for example, may not connect data between their ecommerce andPOS systems. This could lead to an online shopper who abandoned theirpurchase receiving a cart recovery email, even though they completed theirpurchase in your store. This lack of communication between systems meansa disjointed customer experience and marketing inefficiencies, by sendingirrelevant messages.

In an attempt to counter this, marketers leverage different systems fordifferent purposes, structuring the architecture of their stacks in a varietyways. How do CDPs compare to other common marketing architectures?

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Marketing Architecture Concepts

Data-driven marketing consists of three stages: data, insight and action. In terms of a marketing stack, we tend to talk of these stages as layers:

Execution layer

The execution layer is the systems that drive the interaction or touchpointwith the customer – delivery of an email, website experience, etc.

These systems are the ones tasked with delivering your communication toyour customer and can include your email service provider, social mediaplatform, etc.

Decision layer

The decision layer is where you are using that data to plan, manage, andorchestrate your marketing activities. This is where you would do things likeconduct segmentation of your customers for targeting and plan yourmarketing outreach to them.

Data layer

The data layer is where your data is stored. This is any information you collect about your customer, and their transactions and behaviors.

In this illustration, we look at three approaches to the three stages of data-driven marketing:

Siloed Data Hub Customer Data Platform

Executionlayer

Decisionlayer

Datalayer

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Siloed Model

A siloed system is where all your different marketing systems are independent, andthe channels are not connected. None of the data from across the channels is beingunified, and the execution systems do not communicate with each other. Typically,this means decisions are made independently by channel. For example, an emailstrategy relies on the data contained in email data system without looking at whatyou already know about a customer from other channels.

Pros Cons Cheap to implement × Slow decision making

Encourages departmental accountability × Difficult to analyze and action data

× Customer data can be duplicated and non-compliant

× Marketers are ‘blinkered’ to other channels

× No shared information

× Inconsistent brand experience

Executionlayer

Decisionlayer

Datalayer

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Data Hub Model

A data hub starts to share data across systems by passing information back andforth between these systems. The problem with this is that while you begin to usecross-channel data when making marketing decisions, the data is still being storedwithin the individual channels as opposed to a centralized and persistent database.

This creates accuracy and continuity issues. For example, if someone changes theiraddress and that is picked up by just one of your systems, you are going to havediffering address records for that customer across different systems and not knowwhere your correct information lies.

Pros Cons Supports data discovery, indexing and

data analytics × Does not retain historical data

(persistence)

Data formats can be partially harmonized as it is moved

× Do not resolve identities

Can move data between systems to unify a customer view

× Can create data inconsistencies

× Can create copies between data systems

× Siloed decision making

Executionlayer

Decisionlayer

Datalayer

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Customer Data Platform Model

The evolution continues to a Customer Data Platform model. In this approach, all the data being generated by different systems is unified into acentral database, which can exist as a Single Customer View.

The advantage is you begin to have a single source of truth for all of your customers. However, when decisions and strategy for marketing are stillmade independently across channels, it becomes very hard for you to orchestrate a customer’s experience between all channels seamlessly.

Pros Cons Unifies data into a Single Customer View × Separate executional systems may create

a disjointed customer experience

Owned and operated by marketers × Requires separate decision tools to make data actionable

Keeps data persistent × Lack of coordination creates barriers to multi-channel/ omnichannel strategies

Creates relevant communications

Analyzes customer journeys

Makes SCV data available to external marketing systems

This makes it difficult to orchestrate a journey across multiple channels collectively ifthe decision systems are not managed together. This can still result in issues wherecustomers who have responded to an offer through one channel may still receiveredundant messages from other channels.

Executionlayer

Decisionlayer

Datalayer

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BlueVenn x1x

Finally, we arrive at the vision of x1x, in which we leverage our centralized customerdatabase with one marketing platform that drives a unified decision system acrossall channels.

This means that marketers can plan and manage the execution of all channelstogether. They are now enabled to orchestrate journeys across that decision systemand optimize and personalize across all possible touchpoints.

It’s clear here that this goal of achieving optimized marketing across all channels isnot achieved solely through the creation of a CDP, but also needs to leverage amarketing platform that empowers marketers to utilize that CDP across any of thoseexecution channels.

Pros Cons All the benefits of a CDP × Requires an in-house team to create and

send communications

Create consistent, coordinated (omnichannel) messages from a central decision engine

Unifies the customer experience, not just the data

Behavioral data can inform new campaigns and journeys

Executionlayer

Decisionlayer

Datalayer

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Conclusion

As a market calculated to generate $1 billion in revenue by 2019, theCustomer Data Platform landscape will continue to grow. In this time, we’llsee many more vendors wanting a slice of this profitable pie, pushing theinterpretation of what is or isn’t a CDP to its limits, and making bold claimsthat it may not be possible to deliver.

Gartner’s research has predicted as much in its 2017 Digital Marketing andAdvertising Hype Cycle. This is why CDPs are currently teetering at the top ofthe ‘Peak of Inflated Expectations’ before its inevitable dive into the ‘Trough ofDisillusionment’.

Organizations that have been in the business of database marketing,customer analytics and cross-channel campaign management for a whileshould be able to see through any developing identity crises.

Yet marketers will need to stay similarly focused, keeping an eye on theirmost important business objectives. We’re all guilty of being distracted by thelatest new and shiny technologies and buzzwords.

The reason being, despite the new acronyms and buzzwords, they face thesame problems they have had for years, namely:

• The need to bring their data sources together into an accurate andcompliant view of customer interactions across online and offline channels

• The ability to access their data in order to perform analysis, segmentationand collect insights

• To increase the velocity and effectiveness of their multi-channel campaigns

• To be able to demonstrate the ROI of their efforts

A Customer Data Platform will help your business achieve most of thesepoints. Only with a unified decision layer can marketers unify the customerexperience, too.

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