The direct path to a 360° customer view and data science capabilities

Unify and utilize your customer, sales, marketing and service data more effectively than ever before

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What is the customer data lake?

The Flowtap Customer Data Lake (CDL) is a data management and analysis solution that uses big data technologies to integrate diverse types of data from various sources in an extremely efficient way. The technology is able to access a broad range of data sources and enables data analysis on a level of flexibility not possible with traditional methods. This creates to a cost-efficient unified view on customers, customer touchpoints and channels.

The Customer Data Lake is optimized for processing and analyzing any kind of customer data and data related to sales, marketing and service. It’s built on proven, open data management platforms (like Hadoop, Spark) but adds specific extensions for sales, marketing and service use cases.

Data management technologies like Hadoop or Spark open up new possibilities for scalable data processing, extensive data ingestion and modern data science.

But the underlying technologies are complex, require special knowledge and raise many architectural questions.

At the end of the day, the goal is to generate business value as quickly as possible. This is why we combined best practices and the best components to put together a package that ensures fast time-to-market for data projects in sales, marketing and service.

Whitepaper: Data Lake Architecture
Learn more about data lakes and how they compare to traditional business intelligence technologies.


Rapid Time-to-Value

Fast business value through focus on uses cases in sales, marketing and service with a functional solution

No Lock-In

Long term extensibility, maintainability and integrability through open standards and architectures

Start Small & Expand

Enables faster and more agile implementation of use cases than traditional analytics technologies


A foundation built on open standards

The Customer Data Lake is a preconfigured implementation of proven big data technologies (Hadoop, Spark and others) that are in use around the globe. The implementation contains knowhow and best practices that save valuable time during projects and lower risks significantly. Because the underlying technologies are de facto industry standards, there is no vendor lock-in and dependence. The customer data lake can be extended and customized freely. For instance, it can be used as a staging area to feed third party business intelligence systems.


Predictive insights into revenue potentials and hidden risks

The Customer Data Lake enables faster and deeper analysis of a wide variety of data structures and types (e.g. tables, text, images, IoT). A key component in this area is machine learning and advanced analytics. These technologies make critical patterns, early warning indicators and untapped revenue potentials with customers or processes transparent. The way data is stored and managed in a data lake make it particularly flexible. Solutions can be built incrementally in shorter iterations. Data scientists can realize truly agile data science projects.


Deep knowledge about customers with actionable recommendations

The Customer Hub an extension of the data lake specifically for sales, marketing, service and customer analysis. An AI engine constantly scans and links the data inside the data lake and detects customer risks, revenue potentials and leading indicators for specific customer behavior. Based on this metadata, the AI proactively generates recommendations that improve daily operations. For instance, the customer journey can be steered proactively with next best actions.