Omnichannel Customer Experience Management with Adobe

Omnichannel customer enagement

Customer journeys are often asymmetric in nature, but the proliferation of additional channels over the past few years has left CX decision-makers scratching their heads. Insights don’t always jump out when there’s so much data to contend with. And this throws a wrench into finding the best course of action to engage with customers.

For years, many brands perfected customer engagement via mobile phone. But the growing need to focus on connected devices—smart devices , laptops, voice, digital assistants, and more—now requires a sophisticated MarTech stack. As a result, many brands have begun to analyze these connected experiences using real-time predictive capabilities to reach out to customers.

This challenge calls for innovative ways of mixing in existing marketing technologies, including content management, commerce, personalization, and analytics, along with new capabilities in customer experience management (CXM) to redefine omnichannel for digital. This can be broken down into three parts—analyze your customer’s intent, define how you will react, and reach out to the customer using innovative means .

Let’s take a look at each part.

Analyzing Customer Intent

Knowing in real time what your customer is looking for across channels is the foundation of omnichannel customer experience, and it’s essential to focus on the customer’s—not just their current interaction with one of your touchpoints. Collecting, combining, and analyzing customer data across digital, traditional stores, and customer service channels are key features of platforms that offer customer journey analytics.

While some organizations have built similar analytics capabilities in-house, platforms such as Adobe Experience Cloud bring the bundled, accelerated capability of combining such analysis with a real-time customer data platform (CDP) and journey orchestration. Adobe Experience Cloud’s analytics solution, Customer Journey Analytics, turns journey analytics into real-time actions on the most appropriate medium for the present customer journey stage.

Simplify Complexity with Customer Journey Analytics and Generative AI

In order to better understand customers, most organizations collect copious amounts of data—which, unfortunately, can be challenging to integrate, analyze, understand, and share across the business. Often the workflow for asking questions and garnering insights about the customer journey is inefficient and resource intensive. This results in an incomplete view of the customer and how they’re engaging across channels.

Gaining insights from the data to better understand customers requires the right data, from all channels, working together to paint a holistic picture of the customer journey, as well as the right tools to analyze the journey and quickly activate discovered insights. Adobe Customer Journey Analytics can help facilitate that process and shift the focal point of company’s analysis to center on your customer. Customer Journey Analytics provides a toolkit to business intelligence and data science teams that helps them stitch together and analyze cross-channel data, delivering context and clarity to complex multichannel journeys. This context, when paired with tools like Analysis Workspace, provides actionable insight into how to remove pain points from the customer experience. Plus, Customer Journey Analytics comes paired with Adobe Experience Platform, making any data stored there readily available to other Adobe solutions.

The best part? Customer Journey Analytics now has Adobe’s generative AI solution, Sensei, built into it, helping to further encourage data democratization across teams. Here are a couple of options for leveraging Sensei within Customer Journey Analytics:

  • Customer journey analytics with intelligent captions: Natural language insights are automatically generated by analyzing the key trends and important events in the data, simplifying analysis and insights in Adobe’s Analysis Workspace by providing high level takeaways. Intelligent captions can provide narratives that help share insights to other users. Analysis using visualizations is accessibility friendly.
  • Customer journey analytics with natural language queries: Adobe’s AI assistant in Customer Journey Analytics is a gateway to simple, quick answers for the non-analysts using generative AI. This feature uses natural language to query the data for simple, ad-hoc questions. Users can easily get answers to questions on the fly, such as, “What are my top 10 pages?” or “Which products have the highest revenue?”
Adobe Sensei
Source: Adobe

Reacting to Customers’ Needs with Journey Orchestration

Armed with such real-time insights, along with a unified view of what the customer is looking for, you can customize your subsequent response (next best actions) to each customer’s needs. By leveraging customer information from their CDPs, journey orchestration engines can help you to pivot from running marketer-initiated CX strategies into real-time, adaptable interactions based on each customer’s latest actions.

For example, let’s say a customer is shopping for a new phone. They’ve compared an iPhone 15 and Samsung Galaxy S23 on their carrier’s website, and logged into their account to look for any upgrade offers. Looking at this behavioral data, the carrier could then quickly analyze the customer’s device and purchase history to build a propensity model for a purchase and determine its next best action. This could include showing more content from its CMS to assist with the comparison or delivering offers through Adobe Target to nudge a purchase.

Reach Out and Humanize Digital Interactions

Traditional websites exist as pull-based marketing channels with thousands of content pages waiting to be discovered by the customer. Email marketing has served as an effective follow-up to abandoned shopping carts, but emails can’t seize upon the moment with the customer at your digital doorstep. It’s time to rebuild the in-store experience of interactions leveraging virtual, intelligent customer assistants. While chatbots may have had their small role to play here, the larger game is to build a virtual channel layer over existing web, mobile, and voice tools, pushing relevant content from your CMS and next best action recommendations from the journey orchestration engine. Furthermore, with the advent of 5G, video streaming has become more prevalent. Humanized video assistance, such as a five-second video clip of a store rep, could now capture your customer’s attention.

Going back to our mobile phone example, while comparing the different mobile phone models, the web chatbot could analyze any relevant content through its CMS to deliver personalized recommendations. Better yet, a video bot of a store rep handling the phone and explaining its features could entice the customer to make a purchase.

Taking an omnichannel approach to customer experiences can help brands leverage multiple channels of engagement. By combining existing marketing assets with new CXM capabilities, brands can meet their customers where they’re at, with what they want, at the right time.

Learn more about how we create rewarding omnichannel customer experiences with Adobe.

Viren Pandit

Viren Pandit

VP, Digital Experience Technologies

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