In the overviews of CDP Institute and other Martech overviews, you will hardly find the large cloud platforms. They are not 'packaged' and therefore do not fit their definition of customer data platform software. At the same time, public clouds in unified customer data analytics are growing by 30% year on year, on revenues of tens of billions.
If we see public platforms at all in the Martech lists it is with an analytical datastore like Google Big Query, Snowflake, AWS Redshift, or a measurement and activation product like Google Analytics. What they don't show is that the real revolution is in the combined set of natively integrated components that manage the entire data lifecycle of collection, analytics, and activation for you. Not less important, these clouds offer essential supporting functions like governance, orchestration of processes, and security. All functions can be accessed through one console, this is the environment where you can access a cloud.
An increasing number of companies like Coolblue, BOL, Rituals Cosmetics, eBay, Philips Healthcare are building their CDP foundations, including Martech features and tools, in the Google Cloud Platform. You can think of a global customer identity graph and audience segmentation. This is built on top of the entire data lifecycle management of Google Cloud. Soon I will publish an article on how these tools and features are made.
The cause is twofold, creating a paradigm shift:
The major marketing tech players such as Adobe, SAP, Salesforce promised to deliver platforms. However, they didn’t keep their promise. None of these players was in fact building a real platform and a real ecosystem. Their CDPs weren’t designed as frameworks on which third-party applications could run. In other words, their Customer Data Platforms were software suites, not platforms. And even in these suites, not all components are natively integrated; offering an API for a company they took over as an example. And don’t forget the massive cost of licenses, storage, and computation. See also my article on ‘Should I bring my data and analytics to Salesforce?’
In addition, there are many packaged CDPs (from data to analytics to activation and hybrid) from smaller vendors such as Segment, Lytics, Tealium, and 100+ others. These tools can profit from the cloud but they might suffer because of substitution by the cloud platforms as well. This segment is growing at a fast pace too.
The competitive axis is not the data itself alone. Data means nothing if you can’t execute it properly. To win the hearts of the external and internal customers it takes something different:
Cloud is delivering flexible, integrated technology and the ability to orchestrate technical processes.
Soon I will write an article about Data Ops, Marketing Ops, and other Ops principles that cover orchestration of business processes.
My general advice for mid-to-large size companies with large customer databases: build, compose and buy in the public cloud what is possible. Integrate with tools that these clouds don't offer natively. For example, a component as a user interface for creating customer process flows like Salesforce Einstein and Selligent offer. This way you can get the best out of both worlds: integration, orchestration, and adding these tools from other vendors you want to use.
Why would you use tangled tooling from various vendors in your data and analytics cycle? Suppose you keep working this way. Then you have to integrate all those products that are not naturally designed to talk to each other. You probably end up with an unnecessarily complex system. And if you don’t implement it well, your central (customer) view and the possibility to model on all data instead of data in silos gets wasted. Also, aspects such as privacy, security, orchestration of processes, checks on data flows, etc. become too complicated and error-prone. You don’t want to focus on technical issues. You want to serve the customer!
The art of finding the optimum between cloud and the thousands of Martech apps available is the way to go if you ask me. This is one of the aspects that make our work fun.
Cloud platforms are much more than a 'data lake' and a feed for tools put 'on the cloud'. In addition to the aforementioned data lifecycle, marketing-related functionality is increasingly being created in the cloud so that cloud integrates up into the Martech software world. And, as a result, the cloud competes with the big Martech vendors and also with some point solutions/apps. Example of establishing an identity graph that starts with Google Analytics where a customer gets a Google ID. Delivering this ID in natively integrated Datastore Big Query enables you to establish a global customer ID where all customer interactions are linked. You can define your set of rules and data doesn’t have to leave Google Cloud (data gravity principle). I will cover examples like this in another article soon.
Centralizing core functions such as data, analytics, campaign management, identity management, and content management on common ground in the cloud, adding orchestration is a prerequisite for easily testing and producing new Martech tooling.
Having core data functions such as a common data model centralized and centralized persistent data in the cloud, you can easily switch from Martech apps. So you can become flexible and try out the packaged tooling from the SAAS vendors you like!
Centralizing feeds the point Martech solutions with the right fuel thus enhancing the performance of these tools. If you implement this properly you have the best of both worlds in building and composing CDP features and tools in the cloud and the joy of buying those Martech tools that have a specific added value.
The real CDP revolution is in the cloud and not the Martech suites. Sure, Adobe, Salesforce, and the entire longtail of other logos in the packaged Martech world are growing fast. However, the core of centralizing functions and orchestrations is in public clouds that integrate with buy components. Both are growing fast and are reinforcing each other precisely if you implemented it properly.
Get started on your data strategy, engage your stakeholders, take the lead and get good advice from smart and experienced solution architects.