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Real-time decisioning. Better customer engagement.

Deliver your customer’s needs instantly and make every experience hyper-relevant

What is real-time decisioning?

Real-time decisioning allows brands to analyze customers as they interact in-channel, then use the insights to personalize their experience in real time (within milliseconds) – all while the interaction is still taking place.

How is real-time decisioning different from traditional customer engagement tools?

Real-time decisioning, backed by artificial intelligence, constantly adapts to your marketing approach to present the most relevant offer or message possible during an interaction – instead of relying on traditional engagement models like segments and batch campaigns.

How does real-time decisioning work?

Decision engines interpret huge volumes of customer data as it’s being received, using propensity models to constantly re-analyze customer context and update the “next best action” for that individual. This allows the brand to read and react almost instantly to customer behavior – and make their message as relevant as possible.

Why does real-time matter?

Brands that can “re-decision” multiple times within a single experience, based on a customer’s ever-changing context, will become far more relevant than brands who cannot – that’s where the enormous competitive advantage comes in.

Real-time decisioning capabilities

  • Identify customer needs and opportunities early. Digital windows of opportunity open and close in seconds. Analyze fast- and slow-moving data to predict what’s likely to happen next.

  • Understand contextual shifts quickly. Customers’ environments, emotions, situations, and behaviors can shift in seconds; adaptive modeling lets you pivot as quickly as they do.

  • Move beyond sales and create long-lasting relationships. Identify your customer’s needs so you can present the content that is right for them in the moment. It may be a sales offer, nurture, resilience, retention, or service message.

  • Unify customer experiences across channels. Having a central brain at the core of your decision hub means that you can deliver hyper-relevant and consistent messaging regardless of which channel your customer is on, or when.

How does real-time decisioning work?

Real-time decisioning is the core capability of Pega Customer Decision Hub™. Our always-on, AI-driven engagement engine ingests interaction data instantly, evaluates all options, and selects the next best action for each individual. It enables you to predict customer needs and personalize every interaction on any channel.

Explore the Customer Decision Hub

Pega named a Leader in The Forrester Wave™: Real-Time Interaction Management, Q1 2024

According to the Forrester Report, “Pegasystems sets the gold standard for sophisticated enterprise RTIM Implementations..."

The architecture of real-time decisioning

Predictive and adaptive models

Onboard pre-built models, as well as auto-create and self-optimize using analytics to run your programs.

Complex event processing

Detect patterns and pivot seamlessly to address customer needs.

Decision engine

Utilize predictive and adaptive model outputs, combine them with rules, and arbitrate them to make complex decisions.

API channel integration

Deliver the most relevant content to your customer on the ideal channel – all within 200 milliseconds.

Frequently Asked Questions about real-time decisioning

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Challenges include handling large volumes of data in real time, maintaining data quality, ensuring low-latency processing, integrating with legacy systems, managing decision accuracy, and addressing privacy and security concerns.

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Batch processing involves collecting and processing data in groups or batches, usually over longer intervals. Real-time decisioning processes data as it arrives, making immediate decisions without waiting for batches to accumulate.

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Real-time decisioning can benefit industries such as finance (fraud detection, algorithmic trading), e-commerce (recommendation engines, pricing optimization), healthcare (patient monitoring, diagnostics), manufacturing (predictive maintenance), and more.

Explore what's possible with Pega for AI decisioning

Deepen relationships and maximize value, every moment, everywhere

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