« See all blog posts

Building the Consumer Engagement Platform

By Jonathan Joseph on November 5, 2018


Rethinking Consumer Engagement in the Age of Intelligence

Over the last 300 years, our world has seen incredible innovation and unprecedented technological change. Today, we're entering a world where artificial intelligence, robotics and the Internet of Things are transforming the customer experience.

  • AI is making devices and apps smarter
  • The lines between the physical and digital worlds are blurring
  • We are seeing incredible new products and services - like connected motorcycles and connected coolers

You can see this change in our everyday lives: shopping via voice command, autonomous cars, and smart devices that keep you connected and always on. These next generation technologies are connecting us to our customers in a whole new way, and customer expectations, in turn, are changing. Customers expect your business to be just as smart, always-on and connected as they are.

How do businesses build the capability to deliver the personalized, connected experience that their customers want? How will you adapt and harness the innovation required to meet the needs of the evolving customer?

The Consumer Engagement Platform

The Consumer Engagement Platform starts with the customer at the center of your business and uses the power of machine learning and artificial intelligence to break down channel silos by unifying data, providing personalization at scale, and activating seamlessly across all systems and channels.

There are 5 main components to the Consumer Engagement Platform:

1. Building a Single View of your Customer

Today's consumer has a digital footprint that spans the personally identifiable, such as email, and phone numbers - typically housed in a Customer Relationship Management (CRM) system, and the anonymous, like Mobile IDs, Browser Cookies - typically housed in a Data Management Platform (DMP). An important innovation has been the development of a consolidated view across the DMP and CRM, resulting in a single view of your customers. A key use case here has been the use of DMP data to personalize CRM communications.

Building a single view of the customer requires an Identity layer that actively manages a consumer’s digital footprint and reconciles data points and attributes it to the person level - across CRM and DMP, but also across other forms of customer interaction, such as Call Centers, and data that resides in legacy systems.

Collecting and reconciling data to obtain that single view of the customer, requires a robust Data Governance and Rights Management & Consent capability. This is a critical component to securing and protecting consumer data, managing permissions that extend across opt-in (CRM) and opt-out (DMP) privacy environments. In a complex data and privacy world, granular control over where and how that data is stored and used is essential to fulfilling the responsibility we have to our customers to provide a compelling customer experience while protecting consumer data.

The single view of the customer helps to enhance customer visibility and segmentation capability, by giving you the tools to understand who your customer (and potential customers) are.

2. Personalization at Scale

Personalization begins with the understanding of our audience and using that insight to personalize a message - at the right time, in the right context, on the right channel/device. Increasingly, the demand from businesses (and customers) is to have this happen in real time, leveraging machine driven insights on consumer paths to purchase. This begins with a Content layer that stores and builds content and creative assets, which can leverage a decisioning and dynamic creative assembly engine, assigning the right mix of creative assets to a specific audience.

The magic around sequencing and customer journeys happens in the Orchestration layer, where Journeys are designed and executed in real time, learning from the most effective paths to action. Journey sequences can span across channels (such as Video, Email and Display), creative (such as Brand / Awareness and Call to Action), and devices (such as Mobile and Desktop).

3. Omni-channel Engagement

The goal is to be able to deliver relevant messaging to the customer's preferred channel - from advertising delivered on the open web, to email, mobile and social pushes. The Identity layer is critical here, in order to understand how to reach a specific customer on each channel, and in the case of advertising on the open web, to understand and reconcile the various identifiers media companies use to deliver messages to their audiences. Thinking about channel engagement as an end goal rather than a starting point, is a disruptive notion relative to today's organizational structures and workflows, which are typically organized in channel silos (more on that in the Innovator's Dilemma, below).

4. Unified Data & Analytics

The lifeblood of the Customer Engagement Platform is data. Data and signals across the entire platform feed an Analytics layer that supports models providing insights on Customer Lifetime Value, Propensity Scoring, Next Best Action and so on. The dynamic nature of today's data models ensure the flexible free-flowing of data back and forth into the Customer Engagement Platform, informing segmentation, messaging, and journey recommendations.

5. Artificial Intelligence and Automation

The exponential growth in data is fueling the Artificial Intelligence and Machine Learning revolution. The volume of data sets is one of the most important variables in determining the quality of deep learning algorithms (Google / Carnegie Mellon), and the importance of flexible data models with the capability to capture, unify and store large data sets is critical to the development of machine driven insights and automation. We are just scratching the surface on the capabilities of Artificial Intelligence but are already seeing progress with machine driven segmentation, predictive identity algorithms, creative and journey sequence recommendations.

Changing Organizational Models

We think a core part of the solution is to evolve organizational structures as well as technology platforms around a single view of the customer. We're keenly observing examples of refreshed organizational models such as Centers of Excellence and Innovation Pods, and workflows such as Experience Planning that cut across traditional channel silos. At the executive level, the evolution of the CMO and rise of the Chief Customer Officer is more evidence that businesses are seriously thinking about and tackling the challenges of engaging tomorrow’s customer.

Click here for a Consumer Engagement Platform – Update (published August 2019)