Journey mapping to understand customers’ emotions

We know that as people and as consumers, our decisions are colored by emotions. As marketers, we’re interested in giving the people making decisions about our products a great experience. To do that, we turn to research. Our questions: How could our products help people’s lives? What problems are people facing adjacent to the problems our products solve? What context are people using our products in, and how could we better meet them where they are? And who are the people using our products? What are their daily lives like, and where does our product fit in their lives?

Questions like these are the core of customer and user research. But it’s so easy to jump around — should we research our customers’ demographics? Should we research their buying habits, their goals, their opinion of our product versus others on the market? Where do we even begin to ask questions when there are so many angles to approach from?

I often use a framework called the Customer Decision Journey to map the consumer’s experience end to end — how did they become interested in products like ours, where does our product fit in their lives, and once they have it, how well is our product helping them reach a goal? By conducting research around the whole experience of using our product and understanding those experiences as phases or stages, we can draw a map of the highest and lowest points. The lowest points give us a clearer roadmap toward improvement.

What’s the Customer Decision Journey?

Let’s back up to a (short, I promise) description of the Customer Decision Journey. In 2009, McKinsey published an article calling for marketers to re-evaluate how they define the buyer journey and establishing the Customer Decision Journey. McKinsey said to stop thinking of the buyers’ decisions as a linear funnel that ends in a purchase, and instead see these decisions as the culmination of interactions with different channels that they really are.

An example of this multichannel experience: For today’s consumer, it wouldn’t be uncommon to stand in a store’s makeup aisle (physical location visit) while reading reviews on a smartphone (competitor research) and half-listening to a makeup ad over the store’s speakers (traditional advertising). This consumer’s journey, from realizing they wanted makeup, to standing in the aisle & reading reviews, to buying it, can be chronicled through the Customer Decision Journey. And for marketers and experience strategists alike, doing research at each of those stages would help us understand how to help the customer make a decision more quickly, how to save her time in the aisle, and even help us target her with more appropriate or contextual advertising.

Since the McKinsey article introducing the Customer Decision Journey, its implementation as a framework has been widespread (examples include TripAdvisor, eBay, Google, and AirBnB). Brands have restructured their marketing approach to serve prospects through the stages of considering what they need, evaluating brands against each other, and encouraging loyalty. “By using audience insights to identify the areas that need more attention, you can dedicate more time and content to the right stages and deliver a consumer experience that really works.” Source

Mapping the Customer Decision Journey and the Experience

The meat of a Customer Decision Journey research project is often the mapping deliverable that comes from the research. In mapping the experience through each of the stages that a customer travels, we:

  • Investigate what the consumer is doing, thinking, and feeling
  • Identify barriers to their end goal and brainstorm solutions
  • Map out the brand’s role in serving the consumer to reach their goal
  • Discover the best way to connect and help the consumer reach their goal

Below is a product-neutral example of journey mapping (source).

The Importance of Research in the CDJ

The Customer Decision Journey framework is not without its barriers, though. Watch out for an all-too-common mistake of CDJ mapping: Assumptions. It can happen to many executives, product managers, marketers, or anyone who focuses on serving a customer. We serve the customer every day; we assume that we know them deeply. We know their common pain points, and we know their end goals. We make the mistake of trying to build out a CDJ map based on what we already know.

What’s that overused cliche? The definition of insanity is doing the same thing over and over again and expecting different results? This is the problem with relying on institutional knowledge about our customers’ experiences. We are operating on old data, and we’ll likely come up with stale solutions to stale problems.

We are operating on old data, and we’ll likely come up with stale solutions to stale problems.

A Refresher: Common Marketing Research Methods to Build On

Conducting new research is vital to developing a timely and enlightening Customer Decision Journey map. I broke down the most common research methods in marketing in “Should you be focusing on qual or quant research?” but let’s review a quick summary of those foundational methods before we can expand into a focus on emotion research.

The richest insights come from a paired approach to research, one that seeks both statistically significant findings to define our product’s place in the market as well as a deep understanding of how our product fits into a single consumer’s life.

Common quantitative methods like surveys and data analysis can lead to the following findings and deliverables:

  • Market segmentation
  • Pricing projections
  • Net promoter scores
  • Customer satisfaction ratings
  • Recommendations about product launch, pricing, messaging
  • Changes in sales efforts to increase customer satisfaction and target market segments

Common qualitative methods like interviews, usability tests, focus groups, and contextual inquiry can help:

  • Make human-centered decisions across the entire business, not just in the marketing department, leading to a better customer experience overall
  • Understand context around quantitative data — like why bounce rates are so high off of one page on your site
  • Predict how your product or service would fit in and impact the consumer’s life
  • Understand the emotions your target population feels in relation to your product or market