A few years ago, David Raab’s definition of a customer data platform (CDP) for the Customer Data Platform Institute was a reasonable enough starting point to understand its purpose. It said that a CDP was:
a marketer-managed system that creates a persistent, unified customer database that is accessible to other systems
But the CDP industry has changed a lot over the past few years. New entrants to the CDP category position their offerings as providing the solution, when in fact they may often be solving for only one very specialized function like email, while including some additional features one might consider as those of a CDP. Corporate acquisitions by big players in CX and MarTech space have created all-in-one tech stacks that include CDP offerings, but they are not fully developed or only function within a limited technology ecosystem.
And the emergence of a new and rightfully dominant platform--the Cloud Data Warehouse in the form of offerings like Google Cloud, Amazon AWS, Snowflake and Microsoft Azure--has made the all-in-one CDP essentially a dead-end proposition.
The forces behind digital transformation
Technological advances aren’t the only force driving these changes. Structural changes in the economy are dictating that companies with the scale to benefit from CDPs fast-track their digital transformation initiatives: reaching out directly to consumers, through digital channels, to deliver real-time personalized experiences.
Digitally native companies are disrupting multiple industries, from consumer packaged goods and retail to media, entertainment, and even consumer services like transportation and fitness. COVID-19 and its effects rippling through the economy have accelerated these trends as more and more consumers eschew traditional channels like retail in favor of direct digital interactions with brands.
The end of the marketing technology suite
Gartner sees that these disruptive changes are signaling an end to the self-contained marketing technology suite. In the report Marketing Technology Drivers of Genius Brand Performance, they explain:
The COVID-19 pandemic and economic disruption are likely to accelerate the best-of-breed trend. Many enterprises are quickly confronting new business realities and applying coordinated pressure to drive transformation efforts, overcoming historical inertia in their own marketing technology stack. According to the Gartner 2019 Marketing Technology Survey, the proportion of respondents with a strong preference for the integrated suite approach shrank from 24% in 2018 to just 8% in 2019.
Leading brands have recognized that all-in-one suite solutions can provide value, but they must be complemented with point solutions that address technology needs specific to the organization.
Today, a “persistent, unified customer database” is not a goal in itself. It’s another tool to be deployed in the service of larger, revenue-focused goals. For companies looking to go direct-to-consumer, a customer data platform is not a single tool or database, but rather a piece of an integrated best-of-breed system to deliver the 1:1 digital marketing experiences necessary to build meaningful, personal relationships with their customers.
What does a best-of-breed customer data platform look like?
So what are the functional requirements of a modern CDP (whether you build or buy) that can deliver truly personalized marketing to thousands if not millions of prospects and customers? It needs to meet three key requirements: a data pipeline (or Customer Data Infrastructure), a data warehouse for your Customer 360, and decision engine--a way to translate date into actionable insights for your marketing activation channels.
It needs a data pipeline. A CDP must be able to collect critical behavioral and intent data from an organization’s owned digital assets, such as its website, social channels, ads, mobile apps, and email interactions. First-party behavioral data signal intent and translate into predictive insight far more effectively than static, third-party, and demographic data. As individuals’ intents evolve over time, new behavioral data must continue to be ingested for the business to stay up-to-date with its customers’ needs. Companies like Segment, and Rudderstack are excellent examples of customer data pipelines to be considered in a best-of-breed CDP stack.
It needs a cloud data platform for Customer 360. Industry-leading cloud data platforms today are flexible, open, and secure. They can host, analyze, visualize, and secure the vast quantities of data required to maintain a single source of truth: complete, accurate 360° customer profiles. Building a single source of truth across the entire organization requires a cloud data platform like Google BigQuery with robust customer data management features and enterprise scale. Instead of creating yet another customer data silo with a standalone CDP, the cloud data platforms provide industry-leading data storage, management, security, and analytics capabilities and are the right place to build and manage your company’s Customer 360.
It needs a decision engine to take action. Your CDP must provide actionable customer insights to the people that need them: marketers. This stage is where a best-of-breed CDP solution, rather than opting for a marketing technology walled garden, truly differentiates itself. The companies that are driving the new digital economy--companies like Netflix, Amazon, Spotify, and Peloton to name a few--separate themselves from the competition. They’re using artificial intelligence and machine learning to derive valuable insights from their data to deliver differentiated experiences, things like:
- Personalized web experiences delivered in real-time
- Customized offers based on customer preferences
- Content and product recommendations identified by affinity patterns
We believe that the best brands should take (if they’re not already taking) this approach. Lytics CDP resides in this “decision gap” between your customer 360 data in the cloud and your activation channels--your website, your mobile application, your ads, social media, and emails. It applies its machine learning capabilities to your data, focusing specifically on the first-party behavioral data that underlies most customer actions, and derives insights from them.
Powered by data science but built for marketers, Lytics:
- Activates those insights, giving marketers the ability to deploy them across ad platforms and marketing tools
- Orchestrates them in personalized campaigns delivered through multiple channels
- Recommends products and content based on customer affinity, increasing engagement and maximizing return on spend