Planned Journey Framework: Map High-Stakes Purchases

Created by SKIM Group (publisher) - https://www.skimgroup.com/

Overview

The Planned Journey Framework is a way to map purchases that people research and deliberate over a long stretch of time, such as a car, a mortgage or a phone contract. It splits the customer journey into three stages, latent, evaluation and buying, and asks how the brands a buyer considers, and the reasons behind that consideration, change from one stage to the next. The framework was published by the market research company SKIM: in a Quirk's article from 2017, Alex Xiaoguang Zhu, SKIM's senior manager for decision journeys, set out the planned journey as one of four frameworks for mapping customer decision journeys. SKIM also republished the piece on its own site. The article does not say who first proposed the three stages, so this page credits SKIM as the publisher of the framework and claims no earlier origin.

Zhu's definition is short. A planned journey is "a longer decision journey where customers are more involved in research for products and services purchased relatively infrequently," with financial services and big-ticket items as the examples. The article says the framework "works best when consumers typically deliberate their choices over an extended period of time" and names automobiles, financial services and consumer electronics as applicable industries (Quirk's). The same article offers three other frameworks for other kinds of purchase, which the comparison table further down sets side by side.

The three stages describe what the buyer is doing. In the latent stage, as a SKIM expert Q&A puts it, "customers are not actively looking for any information but in a passive receiving information mode." Brand impressions, conversations and advertising land during this period even though the person is not shopping. The evaluation stage starts when the buyer forms an intention and begins to research, compare and ask other people. The buying stage is the final choice of a specific offer, price and place to buy. The Q&A calls the later two stages consideration and purchase, and the Quirk's article calls them evaluation and buying. The substance is the same.

The framework's central claim is that consideration moves between stages. Zhu writes that familiar or popular brands may dominate the initial consideration set in the latent stage, but that buyers who discuss their choices with others and research online may conclude that another brand better meets their needs later. Hence Zhu's instruction: "The key to this framework is to identify distinctive stages in the decision journey and connect the dots across stages" (Quirk's). The article's example is a major U.S. telecom company: network and value were the dominant drivers of brand consideration in the latent phase, while plan and data were the most important drivers in the buying phase. A team that measured only one of those stages would have optimized the wrong message for the other.

The framework is narrower than the general models it is often compared with. AIDA, credited to E. St. Elmo Lewis, is a linear hierarchy-of-effects model, and a literature review found little empirical support for hierarchical models (AIDA). McKinsey's consumer decision journey, published in the McKinsey Quarterly in June 2009 (Purchase funnel), replaced the funnel with a loop that includes post-purchase loyalty, and it has its own page on the McKinsey Consumer Decision Journey. The planned journey stays on the pre-purchase decision in deliberate categories and adds one analytical habit: comparing what drives consideration at each stage and explaining the differences.

The research behind a planned journey map usually mixes sources. SKIM describes its journey work as capturing stated and behavioral consumer data, with passive metering and digital tracking filling gaps that surveys leave (SKIM journey mapping). The mix matters because buyers reconstructing a months-long decision from memory are prone to recall bias, while behavioral data alone cannot say why a brand dropped out. The skills below cover defining the planned journey framework stages for a category and research-intensive purchase mapping from interviews and data.

Brand, insight and customer experience teams in long-cycle categories get the most from it, especially when awareness is healthy but the brand keeps losing at the final choice. In Hamster, a team can keep the stage definitions, consideration data and journey map in one shared workspace that people and AI agents read from.

Core Principles

Each Stage Has Its Own Drivers

The reasons a brand gets considered in the latent stage are often different from the reasons it wins at the buying stage. In Zhu's telecom example, network and value drove latent consideration, and plan and data mattered most at the buying stage (Quirk's). Measure drivers separately for each stage instead of averaging them across the journey. An averaged driver list hides exactly the shift the framework exists to find.

Consideration Sets Change

The consideration set is the group of brands a buyer seriously evaluates before choosing, and the literature treats it as moving: "These sets are fluid and the products in each set can change rapidly when the consumer is presented with new information" (Consideration set). Brands enter the set late through reviews, advice or a strong comparison, and long-standing favorites can drop out. Track entries and exits between stages, since both carry information. A brand that only tracks its share of the final set cannot tell whether it lost buyers early or late.

Connect the Dots Across Stages

Zhu names the connection between stages as the key to the framework (Quirk's). A finding at the buying stage, such as a competitor winning on plan terms, often has its cause earlier, in how buyers formed their criteria during evaluation. Design research so that the same buyers, or comparable segments, answer about every stage. Analysis that treats each stage as a separate study cannot show a transition.

The Latent Stage Still Shapes the Outcome

Buyers in the latent stage are not searching, yet SKIM's Q&A notes "an enormous amount of influence for consumers before they even formulate an intention to make a purchase" (SKIM Q&A). Long purchase cycles mean most potential buyers sit in that stage at any moment. For B2B services such as banking, legal, software and telecoms, a study by John Dawes of the Ehrenberg-Bass Institute reports that companies change providers around every five years, which the Institute's summary says means "only 20% are in the market for those services in a given year and just 5% in a given quarter" (Ehrenberg-Bass). Plan latent-stage work as memory building for a later decision, and judge it on consideration when buyers enter the market.

Combine What Buyers Say With What They Do

Stated data explains why buyers moved, and behavioral data shows what they actually did and when. SKIM's own approach pairs the two, using passive metering and digital tracking alongside surveys (SKIM journey mapping). Either source alone misleads: memories of a long decision drift (recall bias), and clickstreams miss conversations, dealer visits and advice from friends. Where the two disagree, treat the disagreement as a question for the next round of research.

Pick the Right Journey Framework First

The planned journey is one of four frameworks in Zhu's article, and the article treats choosing the framework as the first step in mapping a journey (Quirk's). Frequent, low-involvement purchases fit the habitual journey better, and purchases with many stakeholders fit the ecosystem journey. Forcing a quick or routine purchase into three deliberate stages produces a map that looks tidy and predicts nothing. Check the fit before any fieldwork.

Give Early Touchpoints Fair Credit

In a journey that runs for months, the touchpoint that closes the sale is rarely the one that put the brand in the set. Last-click attribution, as Google Analytics documents it, gives 100% of the credit to the last channel clicked before conversion (Google Analytics attribution). Use stage-level research, data-driven attribution where click data exists, or both, so latent and evaluation touchpoints are not undervalued by default.

Steps

1. Confirm the purchase is a planned journey Check the category against Zhu's test: infrequent purchases, heavy research and deliberation over an extended period (Quirk's). Talk to a handful of recent buyers and ask how long they thought about the purchase and what they did before choosing. If most describe a quick or routine decision, use the habitual journey instead. If several people shared the decision, consider the ecosystem journey or at least map each role separately. Write down which framework you chose and why.

2. Define the planned journey framework stages for your category Describe latent, evaluation and buying in terms of what buyers do, with the signals that mark each boundary. The latent stage ends when the buyer forms an intention, which SKIM describes as the move out of passive receiving (SKIM Q&A). Evaluation ends when a short list of offers is being priced or negotiated. Validate the definitions with recent buyers in your own words and theirs. The stage definition skill covers this step in detail.

3. Measure consideration and its drivers at each stage For each stage, record which brands buyers were aware of, which they seriously considered, and which they rejected, using the set hierarchy from consumer research (Consideration set). Ask what drove each brand's inclusion or exclusion at that stage. Include buyers who chose competitors and people who stalled, or the picture will reflect only your own customers. The output is a consideration set and a ranked driver list per stage.

4. Map touchpoints and information sources per stage List the sources buyers used at each stage and how much each influenced them. SKIM's journey work aims to identify the where, when, what and how of touchpoints and which are most impactful (SKIM journey mapping). Combine buyer accounts with analytics or CRM data where you have it. Expect latent-stage sources to be ambient, such as advertising and conversation, and evaluation sources to be active, such as reviews, comparison sites and visits.

5. Analyze the transitions between stages Compare consideration sets and drivers across stages and look for where your brand enters or leaves. The telecom example in the Quirk's article, where drivers shifted from network and value to plan and data, is the kind of finding to look for (Quirk's). For each loss point, name the likely cause and the evidence for it. The step is done when you can explain in a few sentences where your brand gains ground, where it loses it, and why.

6. Act on the weakest transition and re-measure Choose interventions for the stage or transition where the loss is largest, and match each to that stage's drivers and touchpoints. SKIM recommends socializing journey findings internally, for example through cross-functional workshops and dashboards (SKIM six steps). Set a date to repeat the consideration measurement so you can see whether the transition improved. A map that is never re-measured decays as the market changes.

Choosing Among SKIM's Four Journey Frameworks

Zhu's article presents the planned journey alongside three alternatives. Use this table to confirm the planned journey is the right one before mapping.

When to Use

• The category is bought rarely and researched heavily, such as cars, mortgages, insurance or premium electronics, which are the conditions under which Zhu says the framework works best.
• Brand tracking shows healthy awareness but a weak share of final choices, and you need to know at which stage buyers drop your brand.
• Different teams own advertising, digital, retail or sales experience, and they need one shared view of how a buyer moves from not shopping to buying.
• You are planning budget across long-lead brand work and short-lead conversion work and need evidence of what each stage responds to.
• You are entering a new market or segment for a considered purchase and do not yet know what triggers buyers there or which sources they trust.

When Not to Use

• The purchase is frequent and routine, such as groceries or over-the-counter products. SKIM's habitual journey fits these better, because the decision is about routine and switching rather than staged deliberation.
• The decision is made by many stakeholders whose roles matter more than any one person's stages, which is where SKIM places the ecosystem journey.
• You can collect data at only one point, such as a single post-purchase survey, and cannot reach stalled buyers or competitors' buyers. The cross-stage comparison would be guesswork.
• You need a tactical answer, such as which landing page converts better. A controlled test answers that faster than a journey study.