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Transcript

Hello, and welcome to the Introduction to Decision Management. In this video, we’ll cover the business challenges Decision Management solves, the key capabilities, the basic architecture, and the main use cases.

Offers are more than just discounts, offers are the purpose of each marketing message you deliver to your customers. Offers could be discounts, but they could also be promotions, notifications, product suggestions, a brand message, a loyalty status update, et cetera, et cetera. For example, an offer could be an invitation to join a loyalty program after your first transaction with a brand. And it’s challenging to manage offers across all your marketing and customer facing departments, making it difficult to personalize each offer for each customer. We did a study at ÃÛ¶¹ÊÓƵ focused on email marketing that found 55% of consumers are most frustrated when brands recommend products that don’t match their interests or contain expired offers. A lack of centralized offer management results in these disjointed poor customer experiences. Disparate marketing and customer facing teams activating data from different sources and different silos creates a confusing and inconsistent customer journey. For example, and I’m sure everyone has had this experience, when you receive an offer for a product over and over and over again, and it’s something you already bought. So organizations typically face a number of challenges when it comes to delivering personalized experiences at scale. First, legacy data governance and disconnected databases result in silos across the business. Marketers and customer facing teams don’t have a centralized source of truth of the customer’s profile and personal journey, resulting in disconnected identities and offers presented without the complete context. Organizations also tend to lack a dedicated application for the creation and management of offers that all marketing and customer teams can leverage. Thus, offers are typically managed separately by each unique team in their separate marketing or customer tools. The lack of a centralized decision engine to determine the best offer in the context of a customer’s channel and point in their life cycle is very difficult to manage. Finally, deployment of offers to different channels and marketing systems is cumbersome, resulting in expired, fulfilled, or offers delivered out of context.

To create, manage and personalize offers across marketing channels, there are a few key building blocks each organization needs to consider, which can be boiled down to a few key questions. Who is the offer being delivered to? Essentially, a centralized profile that’s kept up to date with all customer data. What offer’s being delivered? Where is the offer being delivered to the customer? Is it sent in an email or spoken by a call center rep? Why is the offer being delivered and what is the business purpose behind it? And finally, how is the offer being delivered? What rules are in place to manage all the offers that a customer could receive at any given time. Decision Management answers these questions and addresses the business challenges mentioned earlier with these four key capabilities. Real-time customer profiles, a Centralized Offer Library, a Decision Management engine and cross-channel delivery. So let’s go through them one by one. Real-time customer profiles are unified customer data incorporating rich PII customer preferences, customer behaviors, and contextual data. The Centralized Offer Library allows you to create offers and manage rules in one central library, regardless of the delivery channel. The decision engine applies rules for ranking, capping, arbitration, and constraints. And finally cross-channel delivery to keep your marketing channels for consistent and relevant customer experiences. Decision Management is a located within ÃÛ¶¹ÊÓƵ Journey Optimizer, which utilizes ÃÛ¶¹ÊÓƵ Experience Platform data. To the left, you see Experience Platform’s real-time customer profile, all the profile attributes and experience events captured in platform and sent to the profile are available in Decision Management, allowing us to write rules and use them in our intelligence models. In the center is the heart of Decision Management, the Centralized Offer Library and the Decision Management Hub. In the Centralized Offer Library, your business teams can create and manage all of your cross-channel offers. The Decision Hub then processes your rules, frequency capping, ranking, eligibility, arbitration, basically saying, here’s John Doe, and this is the best offer to show. The third part is the delivery. You can add offer decisions to messages within Journey Optimizer, or deliver it to other applications via APIs. The same APIs are available to customers, partners, consulting teams, and ÃÛ¶¹ÊÓƵ product teams. So whoever wants to integrate with Decision Management can integrate it the way they want. And when a delivery takes place, everything comes full circle, and the result of the decision is written back to platform’s data lake. So how can you use Decision Management to provide better customer experiences and apply them throughout the customer life cycle? First, Decision Management could help you grow your customer base by increasing conversions across channels. Secondly, you can deepen your relationships with customers by providing personalized next best offers throughout their customer journey.

Finally, you can retain customers by identifying and proactively targeting customers at risk to turn with personalized offers. With that, you should have a working understanding of Decision Management, the business challenges it solves, the key capabilities, the basic architecture and the main use cases. But I’m sure you still have some unanswered questions and we look forward to answering them in subsequent tutorial videos, where we will go into more detail and explore more advanced use cases. Thanks for watching and see you in the next video. -