Teradata new capabilities empower marketers to visualize customer paths, simulate the impact of new campaigns in advance, and engage customers with the most relevant content
Teradata announces several enhancements to the Teradata Customer Journey solution that will give marketers easier access to analytics, dynamic visualizations, machine learning and predictive simulations.
The new upgradation combine Teradata’s expertise in data integration, advanced analytics and multi-channel interaction management, boosts marketers’ ability to treat every customer as an individual, increasing response rates, reducing churn and ensuring greater customer satisfaction.
“We want businesses to grow by delivering more sales, reducing churn and improving customer satisfaction. In this release of Customer Journey we are putting more analytics into the hands of marketing, so they can build a deeper understanding of customer experiences and then proactively optimize related journeys,” said Dan Harrington, Executive Vice President, Consulting & Support Services at Teradata. “Our solution brings together all the required technology, plus the consulting expertise to achieve faster time to market. With Teradata, organizations can have a complete customer journey hub, without the implementation challenges of cobbling together a solution from multiple vendors.”
Sunil Jose, Managing Director, Teradata India explained, “To understand the behavior of customers, you have to integrate customer information and identify and track that customer across multiple channels. Today, the Chief Marketing Offer (CMO) not only wants to know who their customers are and what they are purchasing, but what kind of interactions or engagements they are having with their business. It’s really all about their experience. Teradata’s Customer Journey solution helps companies understand and optimize each customer’s experience over time, across all channels and touch points, in real time. Providing marketers with this holistic view, the right analytical insights and built-in automation enables them to execute thousands of concurrent, individualized, multi-channel campaigns without adding headcount. It empowers marketers to visualize customer paths, simulate the impact of new campaigns in advance, and engage customers with the most relevant content or offer at the right time.
The new capabilities deliver faster business outcomes, ease solution deployment and improve user experience.
- Integrated customer path analytics offer better understanding of the customer journeys, as well as ideal points of entry to engage with them. Marketers can use this capability to target customers on a specific path, such as churn, with personalized offers to influence decisions for desired business outcomes.
- Communication journey visualizations show how customers actually flow through a multi-step campaign, so marketers can evaluate factors driving offer acceptance and decline decisions. Parameters can then be refined for improved marketing performance.
- Visualizations for self-learning models show the relationship between customer attributes (age, income, life stage, life event, etc.) and response rates. This helps marketers understand the profile of customers most likely to respond to an offer and plan communications. Exposing the model to the marketer also enables confidence, thus increasing adoption.
- Real-time offer simulation gives marketers a predictive ability to see the impact of a new message, offer or strategy on existing campaigns. By understanding the impact on the number of targeted customers, and ultimately response potential, marketers can run more effective campaigns, and optimize their offer strategy.
- “Bring your own model score” allows marketers to inject third party or internally generated model scores into the arbitration logic of self-learning models to optimize the message for any given customer, ensuring no previous work goes to waste.
New features will begin to become available in Q2, 2017 with all features implemented by June 2017.