CDP & DMP: how multichannel digital marketing is revolutionising customer relations

[SPECIAL FEATURE] Since the early 2000s, the amount of customer data has multiplied, expanding the possibilities for marketing actions. However, traditional marketing solutions (CRM, email marketing, etc.) are far less relevant and incapable of managing all this data in a unified way. This is the exciting issue that gave rise to DMPs and, a few years later, CDPs, which not only aggregate all your data, but also promise to put it into action across all your channels. Without further ado, here's an overview of these two marketing trends that many experts see taking off in the coming years.

CONTENTS

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Digital strategy and the customer journey: from CRM to omnichannel marketing

Historically, the first tool to centralise customer intelligence was CRM (Customer Relationship Management) in the 1990s. This was followed by direct marketing tools (email marketing, SMS marketing, content marketing) in the 2000s. It is only in the last 10 years that platforms exploiting online data (DMP, CDP) have developed, making it possible to take advantage of Big Data to improve customer knowledge. What customer data platforms (CDP) and online data management platforms (DMP) have in common is the promise of offering a complete view of the customer. We will see below that in the case of CRM and DMP, this promise has not been entirely fulfilled, but that in the case of CDP, this card remains to be played:

Definitions

Definition of CRM or Customer Relationship Management

CRMs are customer relationship management tools that have been used in the direct sales and loyalty sectors since the 1990s. Their aim is to centralise customer knowledge around a CRM identifier with a view to improving the quality of customer relations. In terms of marketing data, CRM provides a nominative view of customers and prospects.

Advantages of CRM

• CRM makes it possible to automate sales and loyalty actions for identified individuals, thereby increasing productivity and competitiveness.
• Data has a higher unit value than in a CDP/DMP, because it is qualified by humans.
• CRM data can be used to initiate direct marketing actions quickly (email campaigns, SMS).
• No technical skills (Business Intelligence, Data Mining) are required to exploit this data.

Disadvantages of CRM

• CRM is limited to offline data (does not aggregate cookie data, for example).
• CRM is a "single channel" tool only, unlike cross/multi/omni channel platforms.
• CRM is limited to structured data only (which represents a very small proportion of available customer data).

Which companies use CRM?

• All companies that sell goods or services are concerned by the use of a CRM.

What does a CRM tell us about a customer?

• Name, gender, SPC, family background, age, interests, frequency of purchases, etc.

Definition of DMP or Data Management Platform

The Data Management Platform (DMP) is an aggregator of anonymous data reconciled around the cookie. To simplify matters, we can think of it as a very large database. The DMP is designed to improve the operation of digital campaigns (programmatic) in an open world. The DMP is based on Hadoop, Hbase, Map Reduce and other technologies, and offers a statistical view of visitors and audiences.

Advantages of the DMP

• Precise audience targeting
• Integration of a DMP is simpler and less costly than a CDP
• The DMP allows you to separate yourself from advertising agencies and have direct access to precise data in order to manage the most relevant marketing actions (channel, banners).
• The cookies collected may come from proprietary sites (first-party data) or affiliated sites (third-party data).
• Some DMPs have connectors with third-party tools such as CRM, marketing automation (such as Marketo) and DSPs.
• The DMP makes it possible to understand the customer journey in order to adjust RTB campaigns across different channels.
• It also makes it possible to calculate the return on investment (ROI) of campaigns by channel
• It can be used to manage raw data that has not been interpreted (dates, till receipts, GPS coordinates, etc.).

Disadvantages of the DMP

• Offline data is missing to achieve the customer knowledge objective (non-media value).
• Data is only kept for a few months. This is too short to understand a customer's life cycle.
• The data is not cleansed (raw data and sometimes duplicate data), making it more complex to access and activate than in a CDP.
• It is rarely, if ever, possible to implement direct marketing actions from a DMP.
• Data mining and machine learning functions are either non-existent or very rare.
• The DMP is only of interest when 100,000 cookies or more have been collected.
• It does not offer real data management in real time.

Which companies use a DMP?

• Retail companies (ecommerce and physical shops), travel and tourism companies, affiliation agencies (for more detailed retargeting and campaign optimisation), as well as banks and insurance companies.

What does a DMP tell us about an audience?

• gender, age, interests of content consumers

Definition of the CDP or Customer Data Platform

The Customer Data Platform (CDP) is a solution for aggregating and putting into action all online and offline customer data. The CDP was born in 2013 from David Raad's concept of creating a complete understanding of the customer. Like the DMP, the CDP is most powerful in programmatic (media), but can also be used to activate other marketing levers. CDP provides an individual view of customers, prospects and visitors.

Advantages of CDP

• It optimises multi-channel campaigns and reach.
• It enables marketing professionals to manipulate data easily (vs. Business Intelligence professionals for DMPs).
• It provides a 360° view of the customer and offers very precise targeting leverage.
• CDP makes it possible to create precise segments and analyse buying behaviour.
• It enables multi-channel ROI to be analysed accurately, as well as the repercussions between channels.
• It facilitates compliance with the European regulation on the management of personal data (RGPD) mandatory from May 2018: centralisation of personal data, delivery of data on request and data purging.

Disadvantages of CDP

• Complex integration: setting up a CDP involves a large part of the company for 3 to 6 months (business lines, Information Systems Department, managers, legal department).

Which companies use a CDP?

• Companies with siloed data, mature data processing and substantial financial resources (e.g. SNCF, SAMSUNG, etc.). These companies will make several thousand segments per year.

What does a CDP tell us about a customer?

• Time spent on a web page by an identified or unidentified user, email open and click rates, interest in a subject, relationships, etc.

What are the differences between a CRM, a CDP and a DMP?

We have seen the major structural differences between CRM, DMP and CDP, as well as the advantages and disadvantages. Here is a functional comparison of the 3 platforms:

*ROPO: Research Online, Purchase Offline

MarTech, AdTech: welcome to the era of Data Marketing

Why use a CDP or DMP?

According to the Marketing Agency Growth Report (Hubspot, 2018), 37% of agencies are unable to attract the ideal client, and 39% of these agencies do not abandon a commercial relationship even if the prospect's profile does not match their model. This is exactly the problem that CDPs and DMPs solve.

CDPs and DMPs are aligned with the abundance of data and the opportunities and constraints inherent in this context. Let's be more concrete: here are 6 reasons to choose one or other of these two solutions.

1. Multiplication of channels

All consumer activities have a digital footprint, even the most mundane. The simple act of shopping generates loyalty card data that is then widely exploited. There are hundreds of different channels, all of which necessarily have an impact on each other, and the only way to collect and unify this data around unique profiles is via a CDP or DMP-type platform. For example, they can be used to create synergies between channels by targeting newsletter subscribers who do not open emails with advertising banners (thus breaking down the silos between advertising purchases and emailing).

2. Segmentation

The relevance of a customer, prospect, visitor or audience segment is only really relevant if there is sufficient data. For example, segmenting buyers of white shoes is not very relevant. However, segmenting buyers of white shoes who are about to get married is much more relevant. On the media side, DMPs make it possible to optimise investments by excluding customers who have already purchased or who are overexposed. In short, CDPs/DMPs are the only tools that can be used to set up ROI-effective segments thanks to the volume of data and the richness of the profiles.

3. Activation

Data aggregation platforms can transmit segments to marketing automation or programmatic tools, or even activate marketing actions themselves. This centralised orchestration of marketing actions is the only way forward for marketing. On the one hand, because it is becoming standard practice in all commercial enterprises and, on the other, because irrelevant marketing approaches are very poorly accepted by consumers (spamming, complaints on social networks, brand image damage, etc.). Consumers have become accustomed to individualised marketing: this is the norm.

4. Tools for marketers

No marketing professional will accept having a partial, blurred and therefore almost certainly erroneous vision of an audience or customers. It is impossible to commit to marketing performance when the information system does not supply marketing with complete and accurate data, just as it is difficult to be a good cabinetmaker in 2018 without laser cutting...

5. Personal data management

Today, no web host accepts to host personal data, and for good reason: data leak scandals (including the one involving Facebook on 16 March 2018) are repeating themselves and burning the hands of those who must ensure their protection. In addition, data protection legislation is being tightened everywhere, the most important of which is the RGPD (General Data Protection Regulation). To be compliant, you need to be able to control the completeness of your personal data (reconciliation, transmission, deletion), which is the basis of a CDP.

6. Behavioural prediction

Data collection is the only way, thanks to artificial intelligence or data mining, to detect purchasing intentions (in particular thanks to browsing data).

Which customer knowledge management platform should you choose?

Let's not make the mistake of choosing a solution by looking at its data; that's quite simply the biggest mistake we can make. The choice between DMP and CDP depends on the type of data activation you want to do: online activation or offline activation. And although there is a functional overlap between the two platforms, DMP clearly tends towards online activation whereas CDP tends towards offline activation.

With this in mind, you don't necessarily have to be desperate for access to a holistic view of the customer (a sort of holy grail sought by the most technical among us). On the other hand, relevant personalisation of the touch point is a sound objective and an excellent starting point for drawing up the project specifications.

This corporate objective, which is also the starting point for the project, must be defined by the business, which must also be integrated into the entire DMP/CDP lifecycle (choice of data, data quality, creation of segments, data activation, etc.). All the other specialisms must also join the project on a more ad hoc basis (legal, IT, management, etc.).

What impact will Data Science have on marketing managers?

The role of marketing in the customer acquisition and retention cycle has steadily increased. Just a few years ago, marketing focused on introducing consumers to a product and stimulating their interest. The rest of the cycle was carried out by 'salespeople'. Today, webmarketing knows and must also stimulate consideration, intention to buy and product trial. Its KPIs therefore include the conversion rate and the profitability of campaigns.

This evolution is due to the increase in the mass of data and the tools available to exploit digital footprints. As a result, the profile of the marketer is changing: from a creative profile looking for ideas for marketing actions to a decision-maker who makes choices based on the information he sees (lower ROI, growth of a channel, repercussions of a campaign from one channel on another, etc.). In 2020, the ideal marketer will have a scientific approach to marketing with the empathy to make the right decisions. Data science will be a key skill for understanding the predictive algorithms that will recommend marketing actions.

Is this already the end of DMPs?

Criticism of the model

Before we talk about the end, let's talk about the beginning of the DMP. The promise of the DMP was to bring together all customer data, but in reality this has never been the case. DMPs are platforms for aggregating contact data of low unit value only. This is all very well for all the companies that use the media to promote their products (and there are many of them), but this vagueness has been the cause of many, many disappointments. Some companies that thought they could access all their customer data at the snap of a finger with DMPs have met with painful failure.

The notion of easy access to data brings us to the second reason why some DMP projects fail: the complexity of accessing data. As we saw in the table above, the DMP is fed with raw data that can be used by technicians (Business Intelligence Analysts, Data Scientists) who are also the ones who set up the DMP. Yet the success of a DMP depends on the resulting marketing success: it is the marketers themselves who must have easy access to all the data they need, which is unfortunately rarely the case.

The third reason for DMP setbacks is the underestimation of the effort involved, including the difficulty of unifying data, the time it takes to train teams, the time it takes to set up, and the costs. These are just some of the reasons why DMP projects are so frustrating.

Finally, many DMP projects have never been profitable, because there is a minimum threshold of data required to operate the platform properly. For some, however, the volumes of media purchases and in particular retargeting (third-party) are not sufficient to make their DMP profitable.

Double-digit growth by 2020

However, the end of Data Management Platforms is not in sight. The comparison table above shows that CDPs are not capable of processing as much data as DMPs, and that access to raw data at a low unit value is still useful for making sense of things. In addition, DMPs have the great advantage of making advertising budgets transparent (expenditure, ROI, campaign management), which used to be in the hands of the agencies. Perhaps we should be talking about Audience Management Platforms rather than DMPs.

The first part of this video explains the subject of this article very well.

Between DMP and CDP, which marketing solution should you choose?

The market for centralising marketing data (Data Marketing) is highly protean, because all the players - CRM, Marketing Automation, DMP, CDP - want to offer this holistic vision of the customer. This is the case, for example, with Salesforce, which covers all channels with Sales Cloud for CRM, Service Cloud for customer service and Marketing Cloud for SMS, email, etc. The marketing giants are also embarking on this quest, such as Marketo with Turn (its DMP) and HubSpot with the increase in its functional coverage. Here are the main DMP/CDPs on the market:

• Adobe Audience Manager ;
• Cxense ;
• KBM Group (Zipline DMP) ;
• Krux ;
• Lotame ;
• Neustar (PlatformOne) ;
• Oracle DMP ;
• Makazi ;
• Weborama ;
• Ysance ;
• Mapp Digital ;
• Eulerian Technologies ;
• 1000Merci ;
• Quintessence (Base Camp) ;
• Cabestan ;

Each of these players has one or more specialities that you need to look at carefully to make the right choice. Camp de bases, for example, offers a good standard of Data Quality and supports its customers with a proven method (Data Deep Dive) that enables them to rapidly achieve ambitious objectives. We invite you to refer to the list of DMPs and CDPs on appvizer to compare the different solutions.

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Conclusion

We have seen in this article that CDP and DMP solutions make it possible to unify marketing data so that it can be activated across several channels. This centralisation of data management and marketing actions makes it possible to create smarter campaigns offering better returns on investment. The competition between DMP and CDP is often mentioned, but we have seen that, despite a functional overlap, the purpose of the former is online activation (media) while the purpose of the latter is offline activation (direct marketing).

Although the data culture and data marketing solutions are relatively new, the market is now ready to accelerate, and this has a direct impact on the marketing professions. Marketing professionals are becoming more decision-makers than creators.

By 2020, Data Management Platforms and Customer Data Platforms will be moving towards the integration of predictive models (Smart Data) and the unification of cookies (audience data) with CRM data (personal data).