By Iyiola Obayomi and Danielle Adler

— Iyiola Obayomi and Danielle Adler are senior directors, Marketing Analytics & Consulting, at Ogilvy Healthworld, part of OCHWW.

 

Smart integration of data can now help identify and predict customer location and movement along the customer journey continuum. Mapping the customer journey is a vital planning tool.

Mapping out customer journeys is a well-established phase of communications planning. At Ogilvy, this represents the third step in the well-regarded planning platform: FUSION. The customer journey lays out the different phases consumers migrate through toward a desired behavioral change destination. The journey phases will differ in each planning effort as the preferred consumer action and marketing objective are all project-specific.

Improved understanding of the different stages customers should pass through en route to the ultimate desired location helps planners marshal the right channels, messages, and content to aid the customers along their journey.
The construct around the journey-based plan addresses key questions like:
• What is our ideal behavioral perception for audiences in a particular stage?
• What are the perceptual challenges that may hinder getting our audience to think in a particular way?
• What are the positive levers that can enhance the likelihood of our audience to think in a desired way?
• How do we then move our consumers along to the next phase of the journey?
• What channels do we deploy and at what time to get our key messages across?

When these key questions are well identified, the output helps make the ubiquitous, overused, but still aspirational goal of “right message, right channel, at the right time, to the right audience” a possibility.

The customer journey can be complex. Recent studies such as McKinsey’s The Consumer Decision Journey have shown that the customer journey has grown more complex. As Iyiola has alluded to in a previous article, The Marketing Funnel Is Not Dead: A Website Analogy, customers may take several detours, but they still have to pass through well-defined phases to proceed with their conversion. The typical phases of the customer journey start with awareness of the brand or message, and proceed to stimulating interest, trial, usage, commitment, and advocacy. Customers may get caught up in a phase, or proceed rapidly across phases, or even recede at times. However, consumers generally need to be aware of a product before considering purchasing it.

Communication Planners currently produce robust and well-laid-out plans to engage and usher customers down the behavioral change voyage. A desired enhancement to this process is to map real customers to each phase and reach or “touch” these customers appropriately to improve the journey. In the absence of good consumer mapping knowledge, marketers have applied satisfactory approaches such as contextual marketing, which aligns messages to media content as a proxy for customer journey phase. Another approach is sequential messaging, which starts with early phase messaging and shifts to later stage messaging based on the estimated average time a customer is expected to spend at each phase. Lastly, one could always deliver broad messages, with the hope that the audience will self-select, and engage with the messages most applicable to their phase of the journey. The application of customer mapping using empirical data provides a significant boost to communication effectiveness.

The availability of customer-level data and the ease of pooling previously unconnected data is making customer mapping a reality. Now we can identify when a customer traverses a specific phase of the journey so that we can execute well-laid-out communication plans against these customers. Data can now help us answer questions such as: who are these customers? What is the likelihood that they will consider or try the product? How quickly will they progress along the journey? How likely are they to become a highly valuable customer? Once the customer journey has been identified, planners and analysts can identify attributes and traceable behaviors that correspond to each journey phase. Analysts then pool together the vast available customer-level data, create new variables as needed, recommend new proxy measures, and categorize customers into their corresponding phase. This is the essence of marketing smart: integrating consumer mapping (segmentation) and targeting with planning from the start.

We conducted a similar exercise for a healthcare client. We categorized HCPs into key journey phases using a combination of data including scripting volume (current value), category share (opportunity), trajectory of prescription change over time (momentum), and other behavioral and attitudinal markers (attributes). We identified “Trialists” as customers who have low volume of recent activities, or have remained static in usage patterns. “Adopters” are users on an upward momentum who over-index on usage. “Advocates” have large usage volumes and are still increasing their volume. The advocates typically indexed well with regard to brand share as a function of category share. We were able to quantitatively identify “Dabblers” and “Regressors” as occasional brand users or HCPs who have regressed in their brand and/or category usage.

We then proceeded to layer on geographic, demographic, contextual situations (payer access), recent communication contacts, and other attributes. This layering helped us understand the drivers and potential triggers for HCPs’ location in a journey phase as well as the triggers or motivation for recent momentum. For instance, we hypothesized that recent exposure to empirical studies from peer-to-peer gatherings is a driver for transitioning from the inactive to trial stage within a two-month period. These triggers and predictors proved useful in informing personalized and trigger-based messaging and testing, which we will discuss further.

In addition to attributes, we were able to apply our knowledge of the customers’ location along the journey, as well as their observed momentum or speed of brand adoption. Our pooling of this vast available data helped us develop tactical communications that were most likely to resonate with our target. We were able to set behavioral change goals for clusters of customers, as well as project the economic impact of tactics, ideas, and programs aimed at moving customers toward a more valuable phase of the journey.

One of the previously mentioned healthcare clients’ campaigns was designed to enhance HCP understanding of the compelling attributes of the marketed brand. This campaign entailed having HCPs with recent brand adoption share their experience with comparable HCPs who could benefit from similar treatment decisions. This tactic required recruiting advocates to share their experiences with similarly profiled beneficiaries through targeted non-personal promotion tactics. In preparation for campaign optimization, we used our knowledge of the various behavioral change drivers and indicators to initiate triggered communication such as emails and direct mail. This tactical segmentation and differential targeting allowed for individualized engagement based on different stages of the customer journey. The fact that we can put a face to every target HCP within these important stages of the customer journey allows us to map the communication plan (as well as behavioral change targets) to specific customers.

A journey infused with data makes evaluating and optimizing for marketing effectiveness easier. Goals and targets should be set with regard to behavioral outcome objectives for each customer segment, which makes tracking, assessment and adjustment more feasible. When customers move from one phase of the journey to the next, the speed and momentum can be quantified and the effect of channels and messages can be realized. A/B testing experiments are also possible and beneficial to identify and amplify drivers (e.g. tactics, content, execution) that have proven more effective in engaging and moving customers from one phase to the next.

In conclusion, data (and the attendant analysis) can enhance our understanding of audiences along the customer journey, thereby enhancing more relevant communication, engagement, and desired responses from our customers. Clients can also use the data and insights amassed from the journey-based analysis to better actualize personalized marketing. Marketers who put the customer mapping capability to better use will reap results in terms of customer velocity along the journey, deeper customer experience with the brand, and higher value per customer.