Efficiently link touch points, understand customers holistically.
Touchpoint Analytics is a data management and analytics solution that uses next generation technology to connect customer touchpoints faster than ever before. The platform taps into a very wide range of data, allowing more flexible analysis than traditional approaches. This creates a cost-effective end-to-end view of customers, customer touchpoints and channels.
Customer Touchpoint Analytics is purpose-built for customer analytics, sales, marketing and service. The solution is built on proven, open data management platforms but extends them with specific use cases around customer-facing processes.
Connect and analyse data about customer touchpoints, sales, marketing, and service more efficiently and flexibly than ever before
Data management technologies such as Neo4J or Spark open up new ways of tapping into data of any size and structure delivering insights using AI. But these technologies are complex, require specialized knowledge, and raise complex architectural questions.
Today’s business moves fast, insights must be available as fast. That is why we built a solution leveraging best practices and cutting-edge components that ensures rapid time-to-market for data projects in sales, marketing and service.
Customer Touchpoint Analytics is a solution built for sales, marketing, service and customer experience management. An engine continuously scans and links available data points anticipating customer risks, potentials and early indicators of customer behavior. Artificial intelligence proactively generates recommendations, which are fed into channels (such as CRM, apps, portals, call centers). This makes it possible to proactively manage the customer journey and every touchpoints with customers.
Customer Touchpoint Analytics makes it possible to analyze a wide variety of data in a wide variety of formats (such as tables, text, images, IoT) in a holistic manner. Machine learning and advanced analytics are an integral part of this. It makes important insights and warning signals clearly recognizable. The special type of storage and processing makes customer touchpoint analytics particularly flexible. Solutions can be adapted in shorter iterations. Data scientists can deliver value faster.
Customer Touchpoint Analytics connects a multitude of data points about customers, customer touchpoints and the customer journey and offers pre-built algorithms to deliver insights. This saves time in projects and reduces risk. Thanks to the open platform, there is no technological lock-in. The platform can be further developed as desired.