What is Customer Journey Intelligence?
Customer Journey intelligence is the representation of holistic, real-world customer experiences, as individuals interact with an organization across touchpoints and silos, over time.
It is the foundation for the right-time, context-sensing, and actionable insights that drive a continuous learning, orchestration, and optimization of customer engagement. Customer Journey Intelligence is the most important dimension of Digital Intelligence*; its implementation directly leads to improved business outcomes and customer value creation.
[*Forrester defines Digital Intelligence as “The capture, management, and analysis of customer data and insights to deliver a holistic view of customers’ digital interactions for the purposes of continuously innovating and optimizing business decisions, operations, and customer engagements.”]
Standard Customer Intelligence overlooks a customer’s needs
‘Customer Intelligence’ has become something of a catch-all term for the gathering and analysis of customer information, from who customers are to what they do. Once understood, it helps organizations improve the effectiveness of their customer-facing decisions. This supports the development of more meaningful relationships by being more relevant to needs and empathetic to circumstances.
Contributory data contains ‘customer attributes’, which are typically:
- Demographic data (such as age, gender, nationality, income, or interests)
- Psychographic data (including personality, opinions, interests, and values)
- Geographic data (like country, city, or climate)
- Behavioral data (think purchases and choices, communications and touchpoints)
When it comes to analysis of this information, delineation between Customer Intelligence and Customer Insight is important, since the two are often used interchangeably: Armed with Customer Intelligence, Customer Insight materializes by deducing trends; traditionally, to support the efficacy of a product or service for the customer or business. In the absence of journey information, Customer Insight is fed solely by attributes and individual interactions (rather than each customer’s entire journey). As a result, it can often fail to provide a complete picture of a customer’s experience with a brand.
Conversely, Customer Journey Intelligence uses attributes, plus behavior: it is an AI-driven, holistic solution designed to represent the customer experience by connecting omni-channel data in a completely integrated platform.
Another point of differentiation is ownership. Commonly, customer intelligence (and associated analytics) is ‘owned’ by the marketing department of a business. And although this is logical given its historic oversight of customers, this often limits the distribution of data and scope for the generation of customer insight to supporting marketing objectives, such as A/B testing or campaign management. In other words, customer intelligence is organizationally (not customer) focused, and interpretation is limited by department. When other departments mobilize customer intelligence, the story is similar. Take customer service; customer intelligence is used to identify opportunities for operational efficiencies (think call center handling times or contact frequencies). Again, the beneficiary is the organization and not the customer; being perceived departmentally, customer satisfaction is then processed in very linear terms, which can be counter productive.
None of this is deliberate, of course, and there are good reasons why customer intelligence has been developed and used in this way. Technically, many analytics solutions effectively squash all data sources into a single data store. And since they tend to focus on demographics and psychographic data, analytics solutions are then limited in their ability to understand subtle changes on an individualized level. So, while convenient in principle, the capturing of customer interaction lacks context – a foundational requirement to deduce (and act on) customer intent.
The reliance of Customer Intelligence on these data sources attributes also constrains the speed with which an organization can amass its actionable insights. Since much of the associated information is fairly static (after all, people only tend to change their age annually), the intelligence we glean lacks dynamism, and can even be classified as ‘slow’. Taking a different approach, Customer Journey Intelligence arms a business with a continuous and evolving flow of intelligence. If we then consider that the information feeding customer intelligence is not real-time (or even near real-time), source data won’t represent immediate customer interests. This means critical moments to engage with customers (through in-the-moment Journey Orchestration and RTIM) are lost.
Ultimately, if a business cannot understand customer intent or initiate a customer conversation when the time’s right, the use of intelligence becomes self-serving yet lacking in relevancy. Provocative this may sound, but the end goal of customer intelligence effectively becomes flawed, drawing on customer data to solely support a business’s interests without mutual benefit. In this sense, customer intelligence can be construed as ‘fed by customers, to the detriment of businesses’.
Journey Intelligence is a game-changer for Customer Insight
Customer Intelligence and Customer Journey Intelligence sound so similar that you’d be forgiven for confusing the two. We defined the latter upfront; by understanding journeys, the lens through which we understand customers suddenly becomes long-term, ever-evolving and crucially, customer-based. So, while they sound the same, inserting the word ‘journey’ into customer intelligence leads to a radical shift in subsequent insight generation and organizational impact.
Since its focus is on behavioral (as opposed to mostly customer-based) attributes, Customer Journey Intelligence creates deeper understanding. In basic terms, it’s the difference between knowing facts about an individual (think age, gender, location, or hobbies) and meeting them in the flesh, when one can view their behaviors and infer valuable information about what makes them tick or what they need. Clearly, the more we empathize, the more helpful we can be, leading to a more meaningful relationship. And while Journey Intelligence provides a temporal context for analyzing customer behavior, its real contribution is in identifying key moments (or sequences of key moments) in each customer’s end-to-end experience.
This begins, as they say, at the very beginning: in the acquisition phase. The Internet Advertising Bureau (IAB) recently published a joint report with PwC [2021 Digital Ad Ecosystem – Galvanizing a reset for future consumer-centric success], stating the importance of multichannel customer journeys, and our ability to understand them. It explains that “As ongoing battles for consumer time, attention and dollars escalate, organizations will find that a consumer-first approach is imperative, or risk losing them to competitors…The future models and innovations in ad tracking must provide both better detail on the consumer’s journey and do so more holistically, with consumer needs and expectations kept front and center.” The document goes on to explain that businesses that proactively address the challenges of identity resolution and changing consumer journey pathways are “much better positioned to protect their relevance (and growth) in the long term.”
“Consumer journeys have changed—attention fragmentation and compression in decision-making are putting evolutionary pressure on traditional marketing funnel evaluation criteria.”IAB/PwC Digital Ad Ecosystem Report, 2021
The visualization and understanding of multiple, long-term journeys are critical enablers to progress customers towards their goals. Historic behavior (over all time), coupled with in-the-moment behavior (what a customer is doing right now) are aligned to determine both the ‘next best conversation’ (to achieve deeper engagement for every individual), and more accuracy in the prediction of their unique future behavior. This is in stark contrast with ‘traditional’ customer intelligence, which is effectively concerned with the understanding of group behaviors and mass communications, or the anticipation of group responses (e.g. to a campaign).
With its ability to ‘pan out’ and reveal wider trends, Customer Journey Intelligence also unlocks pivotal insights about the behavior of customer cohorts to create product or service audiences. Harnessing Artificial Intelligence, visualizations will identify opportunities to support the optimization of interactions and journeys at a cohort or audience level. This can be gold dust for media targeting or campaign planning.
It also fuels new and powerful levels of understanding:
- Which particular combination of channels and touchpoints (digital and physical) lead to the best outcomes from an individual on a particular journey
- Where in a journey a brand can engage in a natural (frictionless) way, to help each individual customer get to where they seek to go – or resolve their service issues in the most cost-effective channel
- The impact of pre-purchase behaviors on post-purchase journeys (true end-to-end experiences)
An understanding of customer journey data constitutes a colossal leap in the ability to create actionable levels of insight compared to that produced from customer intelligence alone. Without customer journey intelligence, it is impossible to understand what is required for customers to achieve their goals.
Practical ways Customer Journey Intelligence can help
2020 saw a rapid acceleration in digitalization investment across the board – you can read more about this in our recent blogpost on Customer Engagement Themes. This means that more than ever, people are tech-literate and comfortable with employing myriad digital touchpoints as part of a single service or purchasing experience. Given consumers’ expectations for immediacy, brands must quickly identify behaviors, deduce intentions, and empower the best outcomes to satisfy customer needs. 2019 seems eons away; in the new world, we simply cannot afford to miss opportunities to deliver in the moment and support the customer/brand relationship. So, when it comes to behavioral intelligence, agility (flexibly of information), digestibility (the ability to understand quickly) and ‘actionability’ (the ability to make an impact) are essential.
Customer Journey Intelligence can deliver in these areas, for example:
- Usefully visualize customers across all touchpoints and over time (from the beginning to ‘right now’). This will reveal journey hotspots (opportunities to improve the customer experience, or drop-offs that need a remedy) from the micro to the macro; you can read more about how this can be investigated in the Customer Journey Analytics page.
- Compare behaviors over set time periods to understand changes; exactly where and when these occur and their root causes.
- Since Customer Journey Intelligence can uncover individual customer’s journeys, it’s possible to identify exactly where and when conversations are needed (e.g. outbound call, email, app content) – and what messaging would be most appropriate to support every customer’s journey.
- The application of AI to customer journey contextual data (versus customer contextual data) is far more impactful, granting the introduction of machine learning for predictive analysis. At scale, its processing power ensures that we are predicting behavior across all (digital and physical) channels, rather than being limited to audience segments.
“ONE’s Customer Journey Intelligence led to insights that fundamentally changed the way we understood how our customers engaged with our brand. It’s been a huge revelation”Mesut Öcalan, Head of Analytics – Global D2C, BSH Hausgeräte [Bosch/Siemens Group]
By continuously monitoring every customer’s real-time behavior, it becomes possible to detect small – yet significant – behavioral changes over time. These ‘micro trends’ will often indicate new needs that are worthy of investigation or action, from personal changes of circumstances to external competitive initiatives (e.g. promotions) that could pose an imminent business threat. This then means an organization can identify the most relevant trigger or friction points, and take immediate, appropriate action for the protection of the relationship through Journey Orchestration.
The speed of this process often provides an unfair advantage: by reconnecting and demonstrating empathy, the brand will reaffirm loyalty and stem a flow of attrition.
How can a Business shift to Journey Intelligence?
Shifting from Customer Intelligence to Customer Journey Intelligence usually comes with the adoption of a Customer Journey Orchestration Platform. (If you’re not sure about what this entails, or even what questions to ask providers, it’s worth downloading our Buyer’s Guide to Customer Journey Orchestration.)
Organizational hurdles in the way of Journey Intelligence are rarely technical; actually, we’ve found the ‘cultural’ ability of a business to embrace the impact of long-term, evolving, customer-led journeys directly relates to its ability to adopt them.
Once the concept of ‘outside-in’ (i.e. customer-led) journeys is understood and embraced (ideally, across more than a single department), brands can initiate customer journey intelligence with relative ease and in minimal time.
A cross-functional working group is a great start, asking customer-focused and journey insight-driven questions, such as:
- Is our intelligence useful / where are our current insight blind spots?
- Can we unite customer journeys: across all touchpoints, and all time?
- Is our insight self-serving (business-led) or siloed (departmental) – or can it be used to increase customer engagement?
- Are we visualizing journeys over the long-term (from acquisition to win-back), and from each customer’s perspective?
- How ‘current’ is our insight (and how close to real-time can we understand and act)?
- Are we well-structured to distribute intelligence across departments and make decisions at speed?
- Are we using our customer intelligence to support customer-led growth?
Many organizations find the prospect of fully adopting customer journey intelligence across multiple channels a daunting one. This is often down to a combination of people (culture, perceptions or priorities), processes, and technological concerns. In these situations, many find connecting, visualizing, and understanding insight from just two channels can be an effective way of dipping an organization’s toe into the bathwater before getting fully submersed.
The future for Customer Journey Intelligence
The majority of medium to large businesses are already sitting on more data than they need. And although some believe that Customer Journey Intelligence creates a need to amass even more, the reality is that it actually forces an organization to mobilize only that which is relevant to deducing individual customer intent through context and relevance. Effectively, Customer Journey Intelligence is concerned with harnessing only the most important data in the creation of insight.
By coalescing around the customer (rather than being organizationally led), the understanding of customer journeys makes sense of subtle patterns and behaviors over time and provides a springboard for customer-led change. The benefits this brings includes the reduction of friction points, development of new products and services, and with in-the-moment orchestration, improved brand experiences across the end-to-end customer lifecycle. At scale, this simultaneously creates significantly better engagement and positive commercial impact. And, with the rate AI is developing, those who get on board with Customer Journey Intelligence now will be set to build on their associated successes at a staggering pace.
If you’d like to know more about the benefits of leveraging Customer Journey Intelligence, do get in touch