The ultimate guide to Customer Data Platforms

In 2016, a new form of technology, christened the Customer Data Platform, started to gain a lot of attention in the marketing world for its ability to connect disparate data sources, such as a brand's CRM, email, marketing automation and eCommerce platforms, and do away with data silo issues. Essentially, a Customer Data Platform (CDP) will centralize all customer data, unify that data into a Single Customer View, and then enable you to push it to whatever execution or analysis tool needs it.

Over the years, marketers have bought, replaced and re-bought countless technologies with the aim of delivering 1-to-1 customer experiences. The different marketing platforms each help to store customer data, deliver insights to the business, and transfer the information to the marketing, sales and customer services teams, to aid their ability to deliver optimal customer experiences that drive more revenue.

The problem with acquiring new technologies, however, is that each new platform you add to your technology stack will create these silos of data, but also create silos of insights and a siloed way of executing a message or experience to the customer. When you consider that there are over 8,000+ marketing technologies to choose from (social media, content management, mobile, advertising etc), and that a marketing team may use as many as 40 tools to manage customer data, over time we've created a mass of silos everywhere.

What is a Customer Data Platform? Data feeds | Unified Customer Data | Marketing Channels

For that reason, the interest in CDPs has grown over the years, with connected data becoming an ever-harder thing to achieve, even as it has become an increasingly appealing and important goal. All sorts of technology providers have revamped their offerings in an effort to offer 'CDP-like capabilities', or even renamed their products accordingly, so the market has become very confused, with marketing professionals being unsure what capabilities are, and are not, essential or optional elements of the Customer Data Platform definition.

This blog is therefore designed to help you understand what is, and isn't, a Customer Data Platform, how it can benefit your business, the common CDP use cases, and the issues caused by data siloed data, insights and execution within the 3 layers of effective data-driven marketing. It will also explain what features you should look for when selecting the right vendor for your company, how you can use the functions on offer, what to expect when integrating one into you marketing stack, what results are commonly achieved from a CDP investment, and how the market is evolving.

Table of Contents

What is a Customer Data Platform?

BlueVenn 2020 Galaxy

In order to excel at personalization and deliver omnichannel customer experiences, marketers need a centralized marketing database that collects and integrates customer data from all business systems, giving them a full and accurate picture of each individual customer and their end-to-end buying habits. It is not enough to just consolidate this data however; marketers need to be able to access the unified data and use it within their marketing campaigns, without needing to learn to write SQL, rely on the IT team, or upskill in data science. It is important, therefore, that marketers have the ability to feed this trustworthy data into their marketing automation or BI tools, or any other marketing application, for that matter.

The Customer Data Platform (CDP) empowers marketers to do this by acting as the hub of a wheel with many spokes, enabling brands with siloed marketing platforms and technologies to fix their data issues. A CDP can integrate with all your existing systems to ingest every byte of customer data from across the business, both online and offline, then merge it into a Single Customer View (SCV) and make the data accessible to all your execution platforms, so that offers and experiences can be personalized using the data points that reside within the business.

Organizations leverage the Customer Data Platform as an undisputed source of customer knowledge upon which to base their campaign decisions, reporting and customer insights. Some CDPs go further to cleanse, enhance and normalize the data from the many sources, to improve its overall quality.

However, the hype surrounding CDPs over the past few years has led to many vendors and service providers re-positioning their offerings, so CDP capabilities within the market can vary wildly. 

Core features of a CDP

To be classified as a Customer Data Platform, the technology needs to conform to the following criteria:

It should be 'marketer controlled' 

Marketer controlled Customer Data Platform

This means that a CDP can be purchased and operated by the marketing department, with minimal assistance from others (such as internal or external IT teams, or other external vendors or partners). For this to happen, a CDP must enable non-technical users to undertake customer data management tasks, without a reliance on code, IT or third parties.

It must create 'a unified and persistent database'

Creates a unified, persistent database - CDP

A CDP must unify customer data from disparate, siloed business systems. These may include your CRM, PoS, mobile app, eCommerce and email platform, your marketing automation engine, loyalty program, third party data pool, legacy systems, etc. The data is ingested, then undergoes processing to create unified customer profiles and a single customer view. 

It should 'integrate with external systems'

The Customer Data Platform will allow you to send the cleansed and unified data to other systems, so that they can use it in their own processes, whether to build customer engagement campaigns and predictive models, power cross-channel personalization, or enable better use of first party data for programmatic and social advertising. It will also supply customer data to CRM systems, data buckets or SFTP zones, for use in offline marketing campaigns.

In addition to these points, the Customer Data Platform Institute's Vendor Comparison guide outlines the following additional requirements:

Customer data profile - indivudual data includding PII
  • Retain original data: The system must store data (transactional, browsing, personal, etc.) with all the detail provided at the time it is loaded, not to mention every time it is loaded again. This ensures that an audit trail is available to track data accuracy and consistency.
  • Access individual data details: The system should be able to access all data associated with individuals (as opposed to customer segment tags), and this should never be summarized.
  • Manages personally identifiable information (PII): It musty be able to handle PII in accordance with privacy and security regulations. (Across Europe, within regulations such as the GDPR, PII is more commonly referred to as "personal data".)

Different types of CDPs

A recent ‘Customer Data Platform Benchmark report’, authored by the Winterberry Group, defines different segments of CDP vendors as follows:

Basic Customer Data Platform

CDP type - CDP
  • These CDPs have strong capabilities in gathering customer data from source systems (including emerging data feeds). They leverage a combination of integrations (API, SDK and/or tag management) to ingest data.
  • They then commonly offer customer profile management, support customer segmentation, and make unified customer profiles accessible to other systems.

Customer Data Platform with analytics

CDP type - CDP analytics
  • These CDPs provide data ingestion, integration and profile management, plus analytical applications (including CDP-powered attribution, predictive modeling and segmentation). Their systems will often push customer segments to marketing automation and campaign management tools, or other providers, to activate the data.

Customer Data Platform with applications

CDP type - CDP applications

  • These CDPs provide data ingestion, integration and profile management, plus customer engagement applications (e.g. journey mapping, marketing automation and/or activation tools for both inbound and outbound communications, message personalization, predictive recommendations).
  • Many such CDPs have their roots in marketing automation, online personalization or campaign management solutions, where the need for unified data ensures better success from those activation features.

CDP type - CDP cloudMarketing clouds

  • In the past 12-18 months, marketing clouds have entered the CDP arena to take advantage of the popularity of CDPs with their customers, who struggle with the inability to use a unified data set across the various elements of their suite of products. They have done so by integrating a wide variety of mostly acquired solutions, the majority of which focus on customer engagement, with the goal of being to create a one-stop solution for marketers.
  • At the time of writing, some marketing clouds have announced basic CDP-like offerings, whilst for others these are still in the pipeline, with no set release date.

CDP type - CDP  b2b

Customer Data Platforms for B2B

  • CDPs focused on B2B use cases and applications have mostly emerged from ABM platforms, and have a focus on digital advertising to support a multichannel ABM outbound strategy.
  • Many other CDP solutions are now being adopted by B2B organizations, since they have started to realize the need for unified data to support longer buying cycles and appreciate the many use cases beyond ABM advertising.

 

Download the 2020 Winterberry Group Customer Data Platform Benchmark report

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This 14-page Customer Data Platform benchmark report by Winterberry Group provides much-needed clarity on the 'core' and 'adjacent' capabilities you should expect from a Customer Data Platform.

This download includes:
- A guide to different types of CDP technologies
- A definition of core CDP capabilities
- An outline of CDP market trends and insights
- An overview of CDP adoption trends and questions
- A CDP capabilities matrix

Download Now

 

The importance of a no-code 'user interface'

The Single Customer View (SCV) is nothing new, but over the years it has become synonymous with long, complex and costly data services projects that require heavy-lifting from IT, or an ongoing reliance on a database services agency to maintain the database. Essentially, the SCV, often referred to as a 'marketing database', provides the same benefits as a CDP, but if there is no user interface marketers cannot gain access to the database, so they would traditionally require a campaign management tool to be connected to the database to make use of it.

In contrast, a Customer Data Platform is a product rather than a service. Instead of paying an agency day rates to create a Single Customer View, you are investing in a software tool that provides non-technical users with the ability to perform the same functions, but with more control, less complexity, faster time to value, and a significantly reduced cost.

A no-code CDP user interface, for managing the loading, transformation and unification of customer data in one place, is therefore the key ingredient of a CDP. A keen observer of the CDP market may notice, however, that many tools fail to provide this no-code UI, but nonetheless label the activation features of their technology (segmentation, campaign management or journey planning) as CDP functionality, without providing the flexibility to manage the underlying data and how it joins together.

A Marketer’s Guide to Customer Data Platforms eBook

CDP-ebook

Download our eBook for more CDP advice, information on how a CDP differs from other data management technologies, or to find out more about the different types of CDP and what to look out for when researching technology vendors.

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Why you need a Customer Data Platform

Business requirements and Customer Data Platform use cases vary significantly from organization to organization, but some of the main operational needs and aspirations for a CDP project are:

To create a unified 360° customer view

Having a unified view of your customers lays the foundation for more effective marketing. A CDP enables marketers to see all their data in one place, ask and answer questions of their data at will, build predictive models powered by larger volumes of data, and power personalized marketing content and omnichannel campaigns. The common benefits of a 360° customer view include:

  • Increased customer acquisition.
  • Reduced customer churn.
  • Higher average order values.
  • Increased customer engagement.
  • Improved campaign management and ROI.
  • Cost savings through more efficient access to data.
  • Mitigation of human error at the data processing stage.

To improve data compliance

Through the creation of a cleansed, unified, structured and accessible customer database, a CDP mitigates some of the risks associated with data governance and compliance. For companies that handle the personal data of EU citizens, conforming to the General Data Protection Regulation (GDPR) is a top priority, and they can do so with the help of:

  • Multichannel preference centers.
  • Centralized management of all marketing permissions.
  • The ability to action data erasure and the 'right to be forgotten'.
  • Data usage tracking.
  • Data field screening and anonymization.
  • Streamlined data Subject Access Request (SAR) responses.
  • An audit trail of marketing permissions and suppressions.

To facilitate accurate data analysis

A CDP lets marketers leverage all their data by putting the power in their hands, not those of IT, whilst at the same time benefiting the IT team, which is no longer at the beck and call of marketers for ad-hoc data requests. Customer data is therefore made readily available for analysis and research, and to build customer segments, manage campaign audiences, and produce more trustworthy reports for the business. Marketers can manipulate the data themselves, resulting in: 

  • Reduced time to access data.
  • The removal of IT as a bottleneck.
  • Reduced campaign development time.
  • Greater campaign visibility.
  • More relevant customer segments.
  • Lower marketing costs.

To unify the marketing stack

Gartner refers to some Customer Data Platforms as 'Smart Hubs', due to their ability to inform execution systems (email, mobile, SMS, etc.) of the audience to send a campaign to, but also tell the execution platform when and what to send. Essentially, a 'Smart Hub' CDP not only unifies all the data sources, but also unifies execution channels, which enables the consistent and holistic use of data to power the delivery of a customer communication across many channels. By using predictive models, segmentation and even a campaign management workflow within the CDP, it helps to unify technologies in your stack that don't otherwise integrate very well. This enables the company to transition to becoming 'customer-centric', without having to replace key components of the marketing stack, and lets you:

  • Create and use predictive models effectively.
  • Orchestrate omnichannel customer journeys from one platform.
  • Automate messaging via the realtime streaming of event data back from execution platforms.
  • Create triggered cross-channel campaigns with centralized campaign management.

To improve personalization and customer engagement

More detailed, accurate customer data forms the basis for personalized marketing strategies, such as targeted email marketing and dynamic web content. It can also ensure that a consistent customer journey is maintained across online and offline marketing channels, improving channel performance. This allows you to:

  • Identify, and act upon, customers moving from offline to online, and vice versa
  • Deliver the right message, at the right time and on the right channel.
  • Create more targeted and personalized communications.
  • Provide consistent customer experiences.

Making strategic use of Customer Data Platforms

Two core business objectives apply to almost every company contemplating a CDP project to increase their sales and to reduce their costs. However, beyond the basics there are common business strategies, which are seen across a broad range of industries:

1. To increase acquisition success by identifying the right prospects and high-value customer segments 

Identify the right prospects and high opportunity

For example, a media company might want to identify new, high growth subscriber groups and feed relevant customer information to its advertiser network to help with the placement of more targeted ads.

2. To improve engagement over the customer life cycle, leading to increased customer retention, cross-sell and upsell

Increase engagement over the customer lifecycleA retail company may want to analyze its top-selling products and how likely they are to lead to repeat purchases, as well as identify and promote complementary products that are most commonly bought alongside other items.

3. To nurture repeat buyers, build advocates, and move others down the funnel

Nurture repeat buyers and move others down the funnel

For example, segmentation analysis by a leisure company will reveal how they could cater better to loyal members, or identify members who are at risk of churn without intervention and take action to bring them back before it's too late.

4. To focus marketing efforts on the right people and save time/money/resources by removing wastage on prospects who will never convert

Focus marketing efforts on the right people

For retailers that post direct mail catalogs, a clean, deduplicated database, along with a refined view of customer behaviors, will ensure expensive mailings go to the correct people and addresses, while also improving conversion rates and marketing campaign success. 

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

Make marketing more effective and efficient

Access to the entire history of transactions and behaviors in the CDP enables marketers to uncover patterns in buying journeys, so they can tailor a communication with personalized content, offers and experiences that increase the likelihood of conversion.

6. To deliver the right message, at that right time

Deliver the right message at that right time

A travel company that uses a CDP with integrated realtime marketing tools can send triggered cart abandonment messages to customers who did not complete their ticket purchase, but also use all offline and online data to power additional recommendations and offers, leading to measurable uplifts in revenue.

7. To create cross-channel customer experiences that increase customer satisfaction and overall lifetime value

Unify the omnichannel customer experience

A CDP helps retailers to build an omnichannel customer journey ‘ecosystem’, where responses from one channel can trigger or influence another and conversations can be maintained as customers move between touchpoints.

Read 'A Marketer’s Guide to Customer Data Platforms'

Download our eBook for more CDP advice, information on how a CDP differs from other data management technologies, or to find out more about the different types of CDP and what to look for when researching technology vendors.

Download now

CDP-ebook

 

Questions to ask when considering a CDP

Before undertaking a Customer Data Platform project, or creating your request for proposal (RFP) to attract vendors, there are several questions you should ask yourself and other stakeholders:

1. Business goals

  • What marketing activities do I hope to drive with better customer data management?
  • In what areas of marketing activity am I hoping to reduce costs?
  • In what areas of marketing activity do I have the potential to save time?
  • Do I currently have a full view of my customers' actions on all branded platforms?
  • Are my competitors using this sort of technology? Do I need a CDP to stay competitive?
  • What is the impact of not investing in unified customer data?

2. Data management and visualization

  • What does my existing marketing stack look like?
  • Where is my data currently stored, what is the quality of the data, and how can I use it?
  • Which marketing systems do I need to extract information from to manage my campaigns?
  • Do I need to merge online and offline customer data?
  • Does my data management strategy adhere to privacy regulations and is it future-proofed?
  • Is there the necessary time and skillset available to manage and maintain a CDP?

3. Compatibility with different vendors

  • How compatible will my marketing channels be with the new technology?
  • Will I be able to manage the customer database myself, or will I need help from third parties?
  • What ongoing management costs do I anticipate will go into maintaining integration? 
  • Does the CDP I'm looking at qualify as a 'RealCDP' that will be able to ingest all data?
  • How often do I anticipate requiring updates and developments of my technology stack?
  • How much experience does my chosen vendor have of integrating their technology with customer marketing stacks?

 4. Marketing automation and data orchestration

  • Where are the black holes in our knowledge of the customer journey?
  • Do I understand the needs and interests of my customer base?
  • Is my team spending too much time preparing data for a campaign?
  • How much of the data preparation process is manual and repetitive, and how much is automated?
  • Would we prefer to handle the overall creation and execution of campaigns in-house or with third party help?
  • If in-house, do we have the necessary knowledge base and skillset to do so?

5. Customer analytics and reporting

  • What types of customer segment do we think we need?
  • Would the addition of predictive modeling and machine learning enhance my analytical capabilities?
  • Can I track all customer interactions with my brand, throughout their journey?
  • Can I track campaign progress and take action as the campaign happens?
  • What KPIs do I wish to track around my marketing activity?
  • How will I assess marketing campaign effectiveness?

What benefits are you expecting from a CDP project?

Organizations often desire a Customer Data Platform solution to deal with the following challenges:

1. Data management and data analysis requirements

  • I need to have the ability to handle and share data from a range of inputs, including physical stores.
  • I want a customer data software solution that is packaged and ready to go ‘out-of-the-box’.
  • I want a ‘single source of the truth’ on which to base analysis and reporting.
  • I want to compile customers’ communications preferences in one place, for easy reference.
  • I want to hold customer data indefinitely and anonymize it to enable safe sharing.
  • I want a single view of customers so that I can optimize product and service offers.
  • I want to be able to identify, query and extract data myself, without deferring to IT or to third parties.
  • I want to be able to print SARs and capture a timed history of all data processing actions.
  • I want a solution that drives integration between my website, CRM and email solutions.
  • I want a solution with the ability to manage multiple marketing campaigns, track the results, and provide campaign metrics in realtime to facilitate realtime marketing and decision making.

2. Action customer data and execute omnichannel marketing

  • I want to create personalized and targeted messages, based on understanding a customer.
  • I want to automatically manage my customers across all stages of the customer life cycle.
  • I want to drive marketing campaigns based on customer segments and their individual behaviors or preferences.
  • I want to inform the way we deliver services to give our customers a great, tailored multichannel experience.
  • I want to create triggered content, such as cart abandonment emails, based on my customers' online behavior.
  • I want to be able to integrate my loyalty platform and reward any brand promotion.
  • I want a high level of integration between my website, CRM and email solution to reduce manual intervention and the risk of errors.
  • I want to manage campaigns, track results and provide metrics in realtime for decisioning.

Overcoming disconnected technology stacks

A typical customer journey today incorporates dozens of different touchpoints. New execution systems and channels of engagement are appearing all the time, and marketers want to be able to deliver an optimal customer experience across all of them.

In particular, more and more products are being purchased using smartphones and other forms of wearable device, such as smart watches, with spending on wearables set to increase by 27% in 2020, according to Gartner, while IMRG Capgemini reports that smartphone sales have surged by a massive 58% this year (with overall mobile commerce up by 15.2%).

The explosion of options within the technology landscape means marketers lean towards ‘best-of-breed’ solutions that optimize one channel (or part of a channel), rather than opting for marketing suites or marketing clouds. So, your average organization has developed a technology ‘stack’, containing many different systems that work together to create a customer experience.

The problem is, each system interacts with customers in a different way, and collects different information about them, which leads to the creation of siloed data systems and disparate data. Decisions, too, can become ‘siloed’. These problems can prevent you from forming a complete picture of your customers, and make it challenging to put data to use in an omnichannel way when engaging with them.

A retailer, for example, may not connect the data from their eCommerce and PoS systems. This could lead to an online shopper receiving a cart recovery email after abandoning  basket, even though they completed the purchase in your store. This lack of communication between systems results in a disjointed customer experience and inefficiencies, instead of cross-channel marketing opportunities for retailers.

In an attempt to counter such issues, marketers leverage different systems for different purposes, structuring the architecture of their stacks in a variety ways. How do CDPs compare to other common marketing architectures? Let's first take a look at the 3 layers of data-driven marketing and the role a CDP plays in optimizing those layers:

The 3 layers of effective data-driven marketing 

Effective data-driven marketing is made up of three layers:

1. The data layer

The data layer is where your data is stored in any given system. This is the information collected about customers and their behaviors. An email platform, for example, will have an underlying database collecting email addresses, names and other personal data related to email marketing, as well as clicks, opens and timestamps for those events. This information will likely be stored in the cloud and often represents a data silo. Similarly your website will hold different data, as will the eCommerce platform, the CRM, the PoS, etc.

2. The decision layer

The decision layer is where you are interrogating the data layer to make decisions about an audience to help you execute your campaigns. Here you manage and orchestrate your campaigns, conduct segmentation, and use workflows to plan when and what communications will be sent out to customers. It is typical for marketing teams to manage the decisions they make across a range of marketing tools. The CRM will use decisions to help build call lists for telemarketing, the email platform for planning email journeys, the mobile marketing platform for planning automated pop-ups, push notifications, and so on.

3. The execution layer

The execution layer is how your systems push out interactions, communications and offers to the customer. These systems, tasked with delivering your campaigns, can include your email platform, social media platform, website, mobile app, call center, etc. Typically, marketers will use a variety of tools and platforms to execute messaging to customers. Communicating in a consistent manner across many platforms can be challenging when tools do not integrate very well.

To showcase how a CDP can optimize the data, decision and execution layers of your technologies, this illustration looks at three approaches that we call 'siloed', 'data hub' and 'Customer Data Platform', as well as the pros and cons for each approach:

Data Decision Execution layer

Siloed model explained

A siloed model is where the different marketing systems are independent and the channels are not connected. None of the data is being unified, and execution systems are not communicating effectively, or sharing data between them, so decisions tend to be made independently, in a siloed fashion, as well. 

Siloed Model System

Pros

Cons

Cheap  to implement 

Slow decision making

Encourages departmental accountability

Difficult to analyze and action data across different channels

 

Customer data can be duplicated and non-compliant

 

Marketers are ‘blinkered’ to other channels

 

No shared information

 

Inconsistent brand experience


Data hub model explained

A data hub starts to share data by passing information back and forth between systems. While you begin to use multichannel data when making marketing decisions, that data is still being stored within the individual channels, rather than in a centralized, persistent database.

This creates accuracy and continuity issues. For example, if someone changes their address in just one of your systems, you are going to have differing address records and not know where your correct information lies. You could decide upon one of your systems to be the master, commonly the CRM, but the CRM will have limitations in terms of the volume, variety or format of the data it can ingest.

Data Hub Model

Pros

Cons

Supports data discovery, indexing and data analytics  

Does not retain historical data (persistence)

Data formats can be partially harmonized as data 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


Customer Data Platform model explained

In this approach, all the data being generated by different systems is unified into a central database. The advantage is that you begin to have a single source of truth that stores all the data from the different siloed databases in the data layer. It leaves the siloed systems where they are, but centralizes, unifies and transforms the data, providing a single place to base all decisions and analysis from.

However, the typical CDP approach is to then share segments of the data with the execution platforms. So, whilst a CDP will remove the issues of data siloes, it doesn't  solve the issues of siloed decisions, which you will continue to make across a variety of technologies.

To orchestrate and automate a seamless customer experience across all channels therefore demands that the decision layer also be unified, otherwise you will still have customers receiving mixed messages or multiple promotions from different channels.

Customer Data Platform Model

Pros

Cons

Unifies data into a Single Customer View

Separate execution systems may create a disjointed customer experience

Owned and operated by marketers

Requires decisions to be made across a variety of tools to make data actionable

Keeps data persistent

Lack of coordination creates barriers to multichannel/omnichannel strategies

Creates relevant communications

 

Analyzes customer journeys

 

Makes SCV data available to external marketing systems

 

 

Extending CDP capabilities with X1X to unify decisions

Finally, we arrive at BlueVenn's unique CDP vision of X1X, in which we leverage our centralized customer database with a unified orchestration engine that also centralizes the decisions you make across your marketing channels. Ultimately, this architecture means that marketers can plan and manage cross-channel marketing execution, and orchestrate omnichannel customer journeys and personalization, across all touchpoints from one place. 

BlueVenn X1X Model

Pros

Cons

All the benefits of a CDP, with additional cross-channel marketing capabilities

Does not commonly include native execution or message design. Still relies on execution platforms to design and deliver the communication, but marketers can choose the best tools for the business, rather than be tied to any one platform.

Delivers 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

 

 

Customer Data Platform conclusions

The Customer Data Platform industry generated $1 billion in 2019, and the CDP Institute’s January CDP Industry Update forecast that it will generate $1.3 billion in 2020. (Of course the Coronavirus pandemic in 2020 may slow this down somewhat.) Meanwhile, a RearchandMarkets.com report forecast that the market will see a 29.3% Compound Annual Growth Rate to 2023, so that the value will increase to over $3 billion. It’s no wonder, therefore, that the CDP continues to be a hot technology topic.

Another noteworthy insight is Gartner’s ‘Hype Cycle for Digital Marketing’ 2020, which shows CDPs slipping into the 'Trough of Disillusionment'. This acknowledges that CDP usage has entered the point where businesses are reviewing the benefits that they are seeing, or not seeing, from their CDP investment. What should follow is that, as the hype around CDPs starts to reduce, some CDP vendors (the 'pretenders') will disappear, while the few that deliver true value will come out of the other side as established technologies. Watch this space on that! For the moment, the discrepancies in CDP functionality between vendors remain. 

In terms of implementing CDP technology, then, before making a buying decision it is vital to establish your business needs, understand the qualities and abilities that a CDP must have to meet them, and ensure that all vendors you’re considering can offer these. Otherwise, you will be wasting your time and money chasing an empty dream.

The fact is, despite the new acronyms and buzzwords, marketers face the same problems they have for years, namely:

  • The need to bring their data sources together into an accurate and compliant view of multichannel customer interactions, both online and offline.
  • The requirement to access their data in order to independently perform analysis, segment customers and collect customer insights.
  • The wish to increase the ease, rapidity and effectiveness of multichannel campaigns.
  • The necessity of being able to demonstrate the ROI of their efforts.

A Customer Data Platform will help your business to achieve most of these goals, but only with the addition of a user interface and a unified decision layer can marketers truly hope to use a CDP to unify their customer experience.


To discover more about how BlueVenn X1X can unify data AND decisions, register now for the next BlueVenn live demo.

Join our 30-minute live demo to learn how to:

  • Integrate online and offline data into the BlueVenn Customer Data Platform to create a Single Customer View.
  • Centralize cross-channel decisions into one customer journey workflow.
  • Use predictive analytics to make realtime decisions that positively impact the customer journey.
  • Improve the targeting of campaigns using customer segmentation and RFV analysis.
  • Use realtime personalization as part of the multichannel customer journey for improved engagement.
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Topics: Single Customer View Customer Data Platform customer journey orchestration