Customer Journey Orchestration: The Evolution of Marketing Automation

Blog Post
July 25, 2017

If you can deliver more contextual, relevant interactions throughout the buyer’s journey, your customer will be more likely to engage with, purchase, and renew your product or service.

But for most companies, achieving this marketing nirvana of a connected, behavior-driven journey is a complicated challenge. How can you automate interactions with your brand without losing the feel of a high-touch sales or service process? Is it possible to automate conversations with your buyers without interactions feeling irrelevant, mechanical—or worse—coming off as creepy?

The answer to automating your marketing while maintaining context—and a human touch—is customer journey orchestration.

Customer Journey Orchestration

Traditional marketing automation is usually managed by workflow tools within your marketing technology (martech) stack, CRM, or other systems, connected via point-to-point integrations. Orchestration, however, is the unification of customer data and signals into a 360° customer view, which you can use to power concerted actions across disparate systems and teams.

The objective of orchestration is to turn real-time customer insight into immediate actions across your systems of customer engagement. It is the key to going beyond demographic data and linear customer journeys—to using customer context to drive a contextual experience for every individual, across all your systems of engagement, at scale.

With a dedicated platform for orchestration, you can build customer journeys that are operationalized across systems and teams, and appropriately listen for customer signals and data about their intent, no matter which channel or system is logging the interaction.

For example, let’s say a customer files a support ticket for a problem using your service.

With automation: A customer experiences an issue in your online product. A previously-scheduled marketing drip email campaign continues to run and reaches your customer with a promotional offer while they’re upset with your company. They wait for a reply from customer service.

With orchestration: A customer experiences an issue with your online product — analytics from your application are appended to a proactive support ticket. The customer is removed from regular marketing email cadences. A rep reaches out, armed with the knowledge of what the customer has already experienced. Once the service issue is resolved, a Net Promoter Score survey is triggered.

The Need for Automation Governance

It’s easy to automate an individual touchpoint like an email, a sales demo, or a service call. It’s much more difficult to operationalize an end-to-end relationship between a customer and your company.

Marketers often run into trouble with traditional automation because the data and workflows are siloed in a single platform (usually the marketing automation platform or MAP). The MAP is siloed from other platforms like content development and management, web analytics, CRM and customer support, for example. These silos lead to gaps in knowledge about the customer, which can result in irrelevant and/or inconsistent interactions between the brand and customer.

Additionally, maintaining traditional marketing automations is a huge amount of work. What happens when a single customer gets enrolled in conflicting automated workflows? Do your marketing workflows pause when a customer is experiencing a service issue or has an open support ticket?

Cross-system and cross-team automation governance is critical to maintaining meaningful customer engagement. However, most MAP workflow engines don’t include context from other disconnected or incompatible systems. Additionally, most workflow tools are limited to sequential flows, and don’t easily accommodate nonlinear journeys.

To accommodate nonlinear journeys, automation should be governed by combinations of criteria, including milestones within your product or service, actions taken, inaction, time, lead or opportunity status, account details, product or service tier, and other information. This information should help clarify what the customer experience should look like and what next steps should be for each customer, based on individual context at any given moment in time.

Artificial Intelligence Makes Customer Journey Orchestration Possible

Even with effective governance, orchestrating the customer journey would be unwieldy at scale without AI.

Simple, manually built workflow rules don’t allow for contextual interactions based on complex customer profiles. The most advanced companies are building predictive models based on available customer data, and operate their customer journey automations around those models. With orchestration rules based on machine-learned models of customer behavior—rather than one-off criteria—you can adapt your workflows to customers’ behavior over time.

In other words, AI helps us to decode all of the data and signals customers are providing us with, and continuously turn them into new insights and actions across your many systems of customer engagement. Your workflows and customer conversations are always evolving and getting better, rather than staying static based on your rules-based triggers.

An example model would be for a customer’s preferred communication channel. If a customer doesn’t open any emails, but responds immediately to every SMS you’re sending, that customer’s repeat behavior (both action and inaction) qualifies them for a model-based segment, “prefers SMS.” If you’re operating automated campaigns based off dynamic models, rather than one-off triggers, you can automatically communicate with customers in their preferred channels.

What It All Looks Like

In the perfect, utopian vision for customer experience, your customer is always:

● Communicated with via their preferred channel at their preferred cadence

● Encouraged to take the appropriate next best action

● Routed to a human touch when necessary

● Proactively engaged whenever a potential service issue arises

With customer journey orchestration, it’s finally possible to manage relevant, human-feeling experiences for every customer, every time. With the right mix of technology, workflow governance, and a way to measure complex customer behavior patterns over time, you’ll be able to deliver what used to be unattainable: omnichannel personalization, for every customer, at scale.