Redpoint Global Leaps forward with Usability and Machine Learning Enhancements

Redpoint Global is pleased to announce several updates to the rg1 platform. The updates include enhancements to the Intelligent Orchestration (RPI) and Automated Machine Learning (AML) modules.

With an updated user interface, enhanced real-time capabilities and improved workflows for building dynamic customer journeys, the latest release not only makes rg1 easier to use but also more powerful for building and executing relevant cross-channel customer experiences.

Real Time in Omnichannel

Updates to rg1’s real-time capabilities include support for open-time email personalization, dynamic link redirects and improved geo-targeting (along with weather and drive-time targeting).

With open-time personalization, businesses can use rg1 to deliver experiences to email recipients when messages are opened, instead of when they are sent. Leveraging the latest available information about a specific person (or other situation data), rg1’s open-time email personalization ensures that businesses deliver contextually relevant email experiences to each and every customer.

The ability to target customers based on their location provides marketers with another means to engage customers. Using rg1, a marketer can build a campaign and make real-time decisions based on an individual’s geographic location, the local weather conditions (or future forecast) or the expected drive time from one point to another. A hardware store chain, for example, may use a forecasted snowstorm to promote snowblowers, salt and shovels to a group of nearby customers.

The latest rg1 update also includes a number of behind-the-scenes changes to real-time caching, supporting more client control over configuration and performance.

Smart Assets for Dynamic Customer Journeys

With a new capability called “Smart Assets,” marketers can define and control dynamic elements for both simple offers and complex multi-channel, multi-touch campaigns. Smart Assets let organizations personalize customer inbound and outbound experiences with dynamic offers and messages based on rules and machine learning.

Smart Assets offer marketers three core capabilities:

  1. Easily select and control all kinds of dynamic assets – images, HTML, links, SMS, and other channel-specific data that make up dynamic offers.
  2. Build unified cross-channel, cross-treatment assets, with all variants and rules for using them in one place.
  3. Optimize the use of assets with consistent and detailed views of usage and response over time and across campaigns.

Smart Assets make it easy to update, publish and control content based on rules and metadata, so messages, offers, and actions can be consistent across channels and treatments while meeting specific design, content, and channel format requirements.

Clustered Audiences and Automated Machine Learning Enhancements

The latest update to rg1 make it easier for marketers to use the machine learning capabilities of the platform, by streamlining model building for segmenting audiences and predictive models.

Clustered Audiences is a new feature in RPI that quickly segments any audience (using AML clustering) and allows the marketer to discover hidden similarities and differences within a defined audience. This brings the power of AI to campaign design and extends this power with Insights Dashboards to track audience and cluster changes and responses over time.

The latest version of AML includes Business Templates allowing marketers to easily build machine-learning models for specific business-goal-based use cases like “Predict Best Message Content” (or channel), “Predict Customer Retention/Attrition”, and Segment Customer Behaviors” (or Demographics).

Business Templates simplify model training setup and deployment for marketing use cases while preserving the power of evolutionary model building using an organization’s own customer data. The Redpoint Business Templates use an organization’s business goals and data – customer behaviors and transactions as well as product and other brand-specific details – to build models that are specific to the business. They automate the process all the way to model test and deployment, shortening model building timeframes and reducing workloads for data scientists and data engineers.

To simplify management and usage by the average marketer, rg1 offers a new “curated view,” providing all the details needed to define a machine learning (ML) model training project. Marketing analysts and “citizen scientists” get a checklist and summary, providing a faster and easier to use model building process, while always being one click away from the details needed to train an ML model.

These exciting updates are now available in rg1’s Intelligent Orchestration and Automated Machine Learning as part of the latest release, 6.1.

Usability for Today to Solve Tomorrows Problems

The rg1 platform was purpose-built to support real-time interactions across every customer touchpoint throughout an organization – web, email, mobile app, in call centers, stores, and branches, IoT, etc.  Across industries, ambitious marketers and business professionals use rg1 to solve complex customer use cases.

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