A decade ago, predictions pinned journey marketing tools as the only solution marketers of the future would need to convert raw customer data into a powerful revenue generation machine fueled by immersive customer experiences. But in the years since, reality simply hasn’t lived up to that early promise.
In that time, I’ve been fortunate to work on journey marketing implementations with dozens of incredible organizations. While some have had the resources and infrastructure to implement journeys broadly and successfully, many more have struggled and had to significantly scale back their plans or even abandon them completely. Journey marketing is still extremely challenging to implement at a meaningful scale. My experiences have brought me to the conclusion that all existing journey marketing tools still have four major blindspots that hold marketers back. There’s a bright way forward, but first let’s unpack how journeys are falling short.
Data is often inaccessible. Many journey building tools make it difficult to collect and leverage all the data they need to power relevant one-to-one customer interactions.
Customer interaction points are often unsupported. Journey tools typically coordinate only a small handful of channels, nowhere near the entirety of the actual customer journey, requiring manual work-arounds or expensive and inflexible development work to power more complete journeys.
Journeys aren’t flexible enough. The unpredictable nature of real customer journeys isn't accommodated well by existing journey tools, which are only capable of creating rigid pathways that make it difficult to pivot your marketing strategy as customers interact with you.
Journeys aren’t smart enough (yet).This is the big one: journey tools still don’t have the higher level logic to know who should go where when there are several valid journey options for every engaged customer. For example, a new customer to an eCommerce store might easily qualify for a welcome journey, a post-purchase journey, and multiple low-intent educational journeys in different categories, all at the same time. Existing journey marketing tools simply don't provide the toolset to queue those journeys, prioritize them, run them one at a time, and respond to any new interest signals that the new customer may show along the way.
As a result of these limitations, the disappointing reality for most marketing organizations is that they can only use journeys for fairly rare use cases where: data is simple and easily available, disparate activation channels don't need to be coordinated, and marketers don’t have to worry about overly frequent or conflicting messaging coming from other sources.
The journey vision is still compelling
But the original vision for journey marketing remains compelling today, across nearly every industry.
Consumer app companies would love to have a journey for every part of the buying funnel, every level and category of intent, every sticky feature they want people to adopt, every cross and up-sell opportunity, and every potential churn signal they might detect.
Many retailers want to be able to run a vastly larger number of promotional campaigns and dynamically insert each user into the right campaign on any given day.
Financial services and insurance companies would love to be able to have a journey for every combination of (a) product line and (b) customer (or agent) intent level to capture as many of those potential cross sell or up-sell opportunities as they can across their many lines of business and provide a consistent customer experience across every touchpoint.
And the list goes on…
What all these desired solutions contain are non-linear customer paths where there can be dozens or even hundreds of potential journeys that a single customer qualifies for at any given moment. And while it’s sometimes possible for companies to build all these journeys, existing tools universally lack a cohesive way to control the experience so that individuals aren’t being inundated with different, possibly conflicting, messages.
The good news is that this problem is solvable. Over the past few years I’ve designed and built several custom solutions, on a handful of different platforms, for customers looking to scale their journey marketing strategy using a model I call “Air Traffic Control”.
Journeys 2.0: The “Air Traffic Control” Model
Based on the ways journeys are falling short, we know that we need a way to control journey flow at the individual level. To be able to queue journeys up and prioritize them, to respond to customer engagement in the middle of a journey, and to throttle messaging so that our engagement level matches that of our customers, we need an Air Traffic Controller.
For an Air Traffic Control (or ATC) framework to deliver on the game changing potential that we’ve been dreaming about, we need to design a system that has:
System-of-record status for customer data, interest, and intent.
Access to every relevant customer activation channel.
A queue for each journey in our portfolio - this will contain the list of all customers who qualify for each journey.
A customizable decision engine that contains the logic we want to use and has access to all of the data above. This will be used to prioritize and select the next-best journey for each user. This gives our system the intelligence to pick the journey and nail the timing for each user from among all the available, valid journey options.
The relevant metadata about each available journey – how long it is, what interests/intents it’s catered to, priority level, linked next-journeys, etc. This will make our system flexible enough that we can add in new journeys at any time without rearchitecting.
This will allow us to build truly compelling and immersive customer experiences at scale, free from any worries about conflicting messaging, over messaging, or rigid technology structures that limit your flexibility. The system will behave as an air traffic controller would: sitting in the sky, constantly keeping track of where all of your customers are, and routing them into the next best journey at just the right time.
Air Traffic Control with Segment
Building all the components in the ATC framework from scratch is a huge undertaking. Each one of the components above can take months or even years to build and you’ve got to consider reliability, maintainability, and scale at each step along the way. Add to that the fact that the requirements at each step will be constantly evolving along with your customer experience, and you’ve got a very difficult challenge to solve.
The Segment solution, however, turns the tables on this problem by providing a scalable toolset that allows us to build a flexible ATC with a minimum of cost and effort. As a recap, here are the requirements we need to solve for:
Customer data, interest, and intent
Every relevant interaction channel
A queue for each journey
Customizable decision engine
Segment takes care of the first three requirements right out of the box with (1) Sources, (2) Destinations, and (3) Personas Audiences. The very foundation of the Segment CDP is to reliably collect every customer interaction, distribute that data to every one of your customer touch points, and be the focal point for all of your audiencing. These three requirements are incredibly challenging problems to solve, even on their own! It makes the most sense, then, to build our ATC system inside of Segment.
So it's the final two requirements that we need to find solutions for.
Customizable decision engine:
This is the real brains of the ATC system and Personas SQL Traits is the perfect tool for the job. SQL Traits has access to all the data we need to run the decision engine and can handle all of our qualification and scoring logic. Running on a schedule, it will continuously reassess each user and determine if they should stay in the journey they’re in, get a new journey, or not be in any journeys at all. It will return back into Segment the single next-best journey for each user which can then be activated into every system we want to coordinate. The SQL logic looks something like this:
For each user in our system, create a row for each journey that they currently qualify for, including a “none” option.
Join the journey and user metadata required for further qualification and priority scoring to each option.
Qualification - eliminate potential options based on suppression dates, journey lengths, etc.
Priority Scoring - apply score values to each remaining journey option based on the priority of the journey, how closely it matches the users interests, etc.
Select the next journey option with the highest score for each user.
Finally, since SQL Traits will power our decision engine, all we need to do with our journey metadata is simply drop it into a table in our data warehouse. This is an elegant solution that’s simple to set up and easy to maintain.
Your CDP will then allow you to scale your journey strategy massively - you can now spin up journeys of any length in any system for any use case or revenue opportunity you come across. You’ll be able to easily register new journeys into the ATC framework (by creating a queue audience and putting the metadata into the system) and let the decision engine find the right users for your journey without any disruption to the rest of your journey ecosystem. You can activate those journeys on the Segment platform or use our extensive destinations catalog to coordinate journeys in any systems they sit in.
Wrapping things up
From my years of experience building similar solutions for customers, I believe that this architecture -- customer data, interest, and intent data, every relevant interaction channel, a queue for each journey, customizable decision engine in SQL, and journey metadata -- should provide all the degrees of freedom you need to adapt the approach to your businesses’ specific needs. This will give you the layers of agility and control you need to fulfill the journey marketing vision as the path forward for your company.
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