The Gist

  • Experience revolution. Adobe Summit showcases the power of experience-led growth in the digital economy.
  • Personalization priority. Achieving personalization at scale is critical for exceptional customer experiences.
  • Generative AI impact. Next-generation creativity is propelled by advancements in generative AI technologies.

The experience economy was alive and well in late March at the Adobe Summit, which was held in person in Las Vegas for the first time since 2019. This gathering of marketing professionals has become one of the world’s largest digital experience conference with over 10,000 participants and an even larger worldwide virtual audience. This ecosystem of digital experience professionals is at the forefront of redefining personalized experiences to drive customer engagement, brand loyalty and growth.

During this time, Adobe’s experience business has seen skyrocket growth of almost 60%. The Adobe Experience Cloud is now used by 87% of Fortune 100 companies and 74% of Fortune 500 companies across numerous sectors, including healthcare, financial services and telecommunications.

Adobe’s mission continues to be to change the world through digital experiences. Empowering organizations to imagine and express new ideas, create meaningful content and apps and deliver powerful, personalized experiences.

Digital is reshaping how we connect, inspire and engage with our customers. The pandemic accelerated many brands' journeys to become fully online. It also changed behaviors and paradigms significantly. There is an insatiable appetite for dynamic context and applications. Work is becoming increasingly hybrid and global. Consumers continue to expect more personalized experiences.

This requires brands to begin to think about experience at scale. We've had some time between the conclusion of the Adobe Summit and now to digest some of the key takeaways and where we go from here in the world of digital customer experience.

The Era of Experience-Led Growth

We are now in an era of experience-led growth. As the digital economy continues to expand, profitable growth will come from connecting the complete customer experience. Brands that compete on experience don’t have to compete on price. In these current market conditions where revenue growth needs to come with profitability, the lure of driving profitable growth through experience is infectious.

AI, content and data are foundational to experience-led growth.

Adobe Experience Platform (AEP) has unified all four key categories such as marketing planning and workflow, data insights and activation, content and commerce and customer journeys into an integrated end-to-end platform that provides the foundational capability to drive experience at scale. The AEP platform is now delivering experiences at scale with over 210 billion edge network calls per day, over 600 billion predictive insights each year and over 30 trillion segment evaluations per day.

On top of AEP, Adobe has built several purpose built applications such as the Adobe’s Real-Time Customer Data Platform (RT CDP). Brands large and small are using Adobe’s CDP to create unified customer profiles that update in real-time as they get signals from their online and offline channels. These power personalized campaigns across their channels to drive growth.

To achieve real-time connectivity, Adobe has spent time doing deep integrations across the rest of their product portfolio. For instance, they have the first native ecommerce application directly integrated into the platform. This enables a new segment generated in the RT CDP to be easily be accessed within the commerce platform. Other integrations include Marketo, Adobe Target and Adobe Analytics.  

Adobe Customer Journey Analytics is another critical application that connects data across every channel that you interact with your customers on. It provides end-to-end visibility to customer activity and is able to provide AI-powered insights in real time to understand each step of the customer journey.

Platforms like Adobe Journey Optimizer can then generate immediate action on insights from other touchpoints, such as paid media to identify what drove users to new products and ultimately drive more targeted personalization. Through Intelligent Captions in Customer Journey Analytics, which is powered by Adobe Sensei GenAI, companies can respond with greater speed, and instantly offer descriptions on key takeaways for visualizations from cohort tables to fallout charts.

This is what delivering experience at scale is about.

Related Article: DXPs and CDPs: How to Measure and Improve Your Digital Customer Experience Metrics

Enabling Personalization at Scale

What exactly does experience at scale mean? Experience at scale means personalization at scale. It means digitally connecting with your customers across all channels. And to understand context across those channels. This is the next wave of customer experience.

Personalization at scale means aligning your entire business to provide valuable, individualized experiences to your customers. This means being able to personalize every interaction on every channel in real time. It also means anticipating your customers’ needs and demonstrating you have an integrated view of who they are and how they have interacted with your brand. This means pre-populating new account opening forms for existing customers or pre-populating shopping carts with related items from previous purchases. This means generating custom visualizations of how your product might look in your customer’s context.

Achieving personalization at scale requires a new way of thinking by embedding new customer-centric thinking into your process and cross-disciplinary tools. Adopting creative workflow management tools such as Adobe Workfront or Aprimo to avoid silos or typical chaos that can occur when workflows aren’t integrated and employees don’t have insights into how their work impacts strategic marketing goals. Personalization at scale means using connected data platforms that have unified customer profile data. Personalization at scale means content is on call 24/7 with more audiences and communication channels than ever before. Email campaigns, landing pages, microsites, pop-ups, display ads, social posts, push notifications all need to be carefully managed, curated and activated.

Personalization at scale requires a customer experience platform to deliver around five foundational capabilities:

  • Build unified customer profile. First, you need to build a unified customer profile to provide a deep understanding of your customer. It is imperative that you have a multidimensional view of your customer by connecting first-party data, partner data and any enrichment data.
  • Provide real-time activation. Second, provide real-time activation by ingesting customer behavior and marrying it with the customer profile to provide contextual, relevant experiences in milliseconds.
  • Deliver deep integration. Third, delivering deep integration across your martech technology stack and architecture ensures a fully connected data and application stack to ensure real-time performance.
  • Help marketers self-serve. Fourth, providing best in class applications to enable self-service for marketers to easily personalize at scale.
  • Respect customer data privacy. Finally, built in trust and data governance to ensure privacy and regulatory commitments are being met. Your customers need to trust your brand and your data policies. They need to see that giving you their data helps them. That’s the only way they’ll offer first-person data to help with personalization, and their permission to use other data you may have.

Personalization at scale is the key to delivering individualized, relevant, valuable experiences that wow your customers and keep  them coming back.

Related Article: Adobe Unveils Generative AI Tech and Major Partnerships at 2023 Summit

Generative AI Powers Next-Generation Creativity

The generative AI craze continues as text-based ChatGPT platforms are now evolving to images, videos and other digital assets. DALL E2 is a recently launched AI system from OpenAI that can create realistic images and art from a description in natural language. The name is a mashup of artist Salvador Dali and Pixar’s WALL-E. It can not only generate complex, realistic images form basic text commands, but can also do intricate photo editing called “outpainting” by replacing objects in new surroundings.

Generative AI is the next evolution of AI-driven creativity and productivity, transforming the conversation between creator and computer into something more natural, intuitive and powerful. In the future everything from brand assets to corporate videos to illustrations will be created differently leveraging AI based platforms.

Adobe’s announcement of its generative AI tool Firefly is a big step in this direction. Adobe isn’t new to AI. For over a decade, it’s powerful AI platform Sensei has powered tools such as Neural Filters in Photoshop, the ability to discover missed segmentation opportunities and to automatically create new audiences, the ability to simulate customer journeys based on past campaign performance and profile preferences and the ability to use conversational insights to continually integrate and improve audience definitions and outcomes. Adobe believes this capability will generally amplify human performance and is not trying to replace human creativity.

The new promise to let creative users speak to create images, videos, illustrations and 3D images. It will create vectors, brushes, textures, graphic designs, video and social media posts. It can run 3D models, make brand assets and automate much more. This productivity gains can literally save thousands of hours of creative time.

Adobe has designed Firefly to be “safe” for commercial use. This means all of the content is fully licensed and has been trained on the numerous generative models Adobe has created over the years. The volumes of image data in Adobe Stock photo catalog have been used to train the models. Adobe remains “creator centric” and has championed the Content Authenticity Initiative (CAI), which has 900 participants focused on ensuring creators get proper attribution for their work. All content created by Firefly will be watermarked “Created by AI” so the origin is known, and there will be tags available for content creators to specify the image should not be used for AI training purposes.

Adobe is committed to uphold a high ethical standard as it makes further use of AI in its products. It has created a framework of AI ethics and is applying a formal review process within its engineering teams to ensure the AI used within its products reflect the company’s and human values.

Related Article: Making Digital Customer Experience Rounds at Adobe Summit 2023

The Customer Journey Becomes Fully Digital

The entire customer journey is becoming increasingly digital. Enterprises need a strategy to connect and optimize the complete customer journey while keeping the customer at the center of all its channels of engagement.

Today, the challenge in most enterprises is there are still a variety of disconnected system and processes. Frequently, there is no easy way to bring together cross-channel insights that empower teams to uncover engagement opportunities or identify where customers hit roadblocks. Even more challenging, is the increase in disjointed data and complexity that has lowered trust and efficacy in current measurement and planning capabilities.

Learning Opportunities

Additionally, with third-party cookies going away and the emergence of more walled gardens, it is becoming increasingly difficult to target and measure ad effectiveness. Determining how to efficiently spend your ad dollars has become harder than ever.

Marketers need a solution that measures marketing campaigns and optimizes planning holistically across paid, earned and owned channels. Marketers need the ability to answer foundational questions about the impact of marketing investments on business outcomes.

Enterprises need to reimagine their customer journeys not as a funnel or linear progression but rather an integrated, iterative journey across acquisition, engagement and retention. This will enable real time measurement and the ability to pivot campaigns and advertising spend in an agile fashion.

Adobe Mix Modeler is a new AI-powered product that provides the ability to measure, plan, monitor and adjust marketing campaigns all within a single application. It leverages machine learning models against essential datasets like marketing spend, walled garden, offsite engagement and exogenous data to provide insights on the historical and future impact of marketing investments on key business objectives.

The Mix Modeler uses Attribution AI which is a multichannel, algorithmic attribution service that calculates the influence and incremental impact of customer interactions against specified outcomes. Attribution AI enables marketers to measure the impact a specific touchpoint has across a user’s decision journey. The different touchpoints can include events like display ad impressions, email opens, or paid search clicks. Once the customer journey endpoint is identified, each touchpoint along the path is fed into the attribution AI model, and an output is returned that can be used to help make decisions to influence potential customer behavior.

A process that used to take months can now be reduced to weeks enabling marketers to make real time decisions on advertising spend.

Working together, product and marketing teams can now create more effective customer engagement strategies, messaging and enablement content, ultimately improving customers’ opinions of brands.

Optimizing the Content Supply Chain

Customers continue to demand better experiences at an increasingly fast pace requiring you to get the right content if front of users at the right time. Becoming a fully digital, experience first business requires new levels of efficiency within an organization’s content supply chain. Connecting the planning, production, delivery and analysis can drive efficiencies and significant cost savings.

Today, 70% of the content preparation time is spent on non-core work and managing manual tasks across disparate systems. Over 30% of creatives and marketers indicate their inability to share assets effectively across stakeholders.

Working together, product and marketing teams can create more effective customer engagement strategies, messaging and enablement content, ultimately improving customers’ opinions of brands. An integrated content supply chain is the process of bringing together people, tools and work streams to effectively plan, create, manage and deliver content.

Getting your content together in one place and embedding metadata allows you to optimize the process for content creation, management, and distribution. Using a DAM (digital asset management) tool will help you collect all the data pertaining to a product and spread this across the entirety of the organization. You can also enable rapid search and AI capabilities to help you find branded content much faster.

Historically Adobe’s Creative, Document and Experience clouds were not well integrated and tended to operate in silos across the organization. Adobe’s new Content Supply Chains solutions connects content activities across their clouds.

With the new product announcements from Adobe, you can now optimize the planning, production and delivery processes. During the planning phase, you can now intake hundreds of connect requests across your business and then prioritize them against your roadmap. You can utilize Adobe Workfront to provide transparency, alignment and perform workload monitoring. As you move into production, projects are created and populated with creative briefs, promotional requirements, content strategy and other project data. Finally, as you get into delivery, you can directly publish offers, assets sand content to Experience Manager.

Preparing for New Data Privacy and Cookie Regulations

The foundations of the modern marketing model are shifting as data privacy protections become more prevalent. The phaseout of third-party cookies is challenging established digital marketing techniques for targeting ads, identifying unknown users and acquiring new customers. This has the potential for marketers to lose up to $10 billion in ad related revenues.

Google has announced that it will stop the use of third-party cookies in Chrome by the end of 2024, delaying from 2023. But the end of third-party cookies is not the end of tracking. Publishers and marketers now need to control their destiny and transition away from cookie-based identity to people-based identity.

Google has been pitching its Privacy Sandbox as an alternative to third-party cookies, but it will take time for them to get it fully embraced by the advertising industry. The approach is to use a series of API’s that are based on anonymized signals within a person’s browser to uncover browsing habits. The goal is to design these new tools to avoid cross-site tracking, provide people with better transparency and control.

While these larger initiatives are still formulating, brands will need to double-down on first party data to fill the gaps. In addition to Google’s Privacy Sandbox there are other solution approaches such as identity solutions, publisher provided identifiers (PPID’s), data pools, contextual targeting, digital fingerprinting that can be considered but there is no single best option. The reality is that a diversified approach centered around first-party data and supported by some of these other approaches are probably the most practical.

Reducing your overall dependence on cookie information is probably the best long-term strategy. Adobe Customer Journey Analytics and Cross-Device Analytics allow users to include durable identifiers, such as hashed logins, in addition to cookies. This allows you to understand the customer journey across devices and, in the case of Customer Journey Analytics, across online and offline channels.

Operating in Real-Time — And Delivering Experience at Scale

The world now operates in real-time. Brands need to move from reactive personalization toward anticipating their customer journeys and delivering proactive personalization at scale. Accomplishing this requires foundational, unified customer data, AI drive automated insights and integrated content supply chain.

That is experience at scale.

fa-solid fa-hand-paper Learn how you can join our contributor community.