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Real-time Marketing

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Real-time Marketing

For a real-time platform to work, data must be gathered from multiple and disparate sources, which can include Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Social CRM (SCRM) platforms, geofencing applications (like Jiepang and Foursquare), Over-The-Top services (like WeChat and WhatsApp), mobile apps, augmented reality apps, and other mobile and social media systems. This data must be collected and then seamlessly integrated into a data warehouse that can cleanse it and make it ready for consumption.

To succeed, real-time, personalization marketing must meet or exceed a consumer’s expectations by providing proactive, contextually relevant content, which should be based upon a customer’s location, his or her most recent interactions, and any potential, overriding customer sentiment. Marketing channels should be aligned with consumer behavior and mobile and social media should be looked at as one of the most important marketing channels in the not too distant future. Collecting piles of data is one thing, but a near real-time content management system can provide real value to an audience, and, by association, to a gaming organization.

A solution like SAS’s Real-Time Decision Manager or SAP’s Real-Time Offer Management  can automate and enhance the decision-making process for high-volume, customer-facing systems as well as help organizations execute strategies across multiple channels in a consistent, focused manner. The solution enables business users to construct decision processes in an interactive, visual environment. As they build decision processes that incorporate various data sources, business users can apply advanced analytic techniques and business logic to their campaigns. As a result, customer-facing employees can quickly make decisions that enrich the customer experience and increase profitability.

With a real-time solution, businesses can make “next best action” an integral part of their marketing strategy. This is important, because deployment of next best action can achieve much higher response rates than standard outbound promotions. Next best action asks such questions as:

  • What approach will maximize the customer relationship when contact occurs?
  • Is selling more important than reten­tion?
  • Is risk management more important than selling?
  • Is the next best action ever no action?

Once these questions have been answered, highly granular differentiation is enabled through further segmentation, determi­nation of offer eligibility and prioritiza­tion – all using analytical insight, which forms the basis for delivering a wide variety of customer propositions.

To use insight gained during real-time customer interactions and to ensure that each interaction is relevant, a real-time solution relies on real-time analytics to recommend the best action for each customer. By com­bining analytics with business rules, you can use both historical and real-time data to make the best possible decision about each customer.

Key Benefits:

  • Automate the decision-making process. Access and analyse critical, up-to-date information during decision cycles to determine which choices are optimal for your business. The solution provides faster, more accurate decisions about cus­tomers during real-time interactions – even in high-volume environments like call centres and Web applications. Automated decisions are repeatable and reusable to improve cycle time.
  • Meet customer needs – right time, right place, right context. Real-time analytics provides insight during cus­tomer interactions and helps ensure that each interaction is relevant. Through a single solution that spans all channels, the software recom­mends the best action for each customer during each interaction. Immediate decisions can be made based on analysis of current and his­torical customer data, the customer’s preferences and past decisions – combined with information obtained during real-time interactions.
  • Reduce dependency on limited IT resources. Business users can construct and modify the automated decision-making process without IT’s assis­tance, including incorporating analytical models into these decisions. They can also coordinate interac­tions across multiple channels by accessing customer interaction data from other software solutions.