To understand why the users feel a certain way about an experience, we must understand it through the eyes of the user. To achieve this, I designed a template and process for synthesizing customer friction in a digital experience. My multiple award winning friction map template encourages team collaboration by bringing together multi-discipline insights from content strategy, UX design, copy writing, research, business, analytics, and the voice of the customer (VoC).
The friction map template aggregates screen shots from each page in the existing user experience and pairs each with the relevant quantitative data. This becomes the baseline for the multi-disciplined resources to layer in their insights (qualitative data) in context.
The content strategist layers in their insights from the content audit and analysis
The designer layers in insights of the design audit (accessibility)
The researcher layers in insights from relevant studies (user study results, survey results, A/B testing results, etc.)
Business client layers in insights from competitive and marketplace analysis, sales numbers, business goals, objectives and key results (OKRs), key performance indicators (KPIs), etc.
All of the insights are accumulated into a single template and culminated to give us a more complete view of the user friction and the impacts of that friction to the business. For the best results, this is done in phases.
Phase 1: Define the use case
Set the stage by writing a statement that describes the scenario of this user's session; i.e., existing wireless customer leverages the native app to upgrade their mobile device and plan while taking advantage of a trade-in offer. It’s important to be clear and crisp in order to query data analytic systems for accurate metrics.
Phase 2: Data aggregation
Now that your use case is defined, analysts can create the needed queries to pull accurate data around the user experience.
Note: the data you see in the following examples is for educational purposes only. The metrics are not true or accurate to any journey, flow, business, nor use case.
Step 1: Funnel data
The analyst will level set on the segment, the date range, the sample size, and interpret the metrics for task completion for the use case defined in phase 1. In this example, our sample size is 1.1M sessions, where +88K occurrences converted at ~40% and there is a high number of abandoned carts where the total value lost from abandoned carts creates an annual opportunity of approximately $134M for the business.
The analyst will interpret each funnel the customer must go through to complete the task for this scenario. And will make call outs to conversion steps that take a significant amount of time. In this example, we see that the average total time to task completion for the user was approximately 17.6 minutes. The analyst has noted that the average user spends approximately 8 minutes on the checkout step. This is a significant amount of time that may warrant a deeper analysis on that funnel step.
Step 3: Traffic data
The analyst may then pull in traffic volumes to better understand to how the overall traffic is moving through the same funnel, which conversion steps show significant traffic drops. Is there a correlation between the drops and the time spent in checkout? Next, we will want to discover why so much time is being spend in the checkout step for this particular use case.
Step 4: VoC data
Analyst will level set on the VoC data that is applicable to this use case. They may pull in Customer Satisfaction Scores (CSAT), Net Promoter Scores (NPS), JD Power results, App ratings, Google reviews, and/or user verbatim, etc. to understand what the your users are saying about this experience. Understanding customer sentiment for this experience helps us discover, through this mapping, exactly when, where and why the users feel a certain way about the experience. In this example, we can see that for our use case, product CSAT is 55% and we only have 43% promoters. We have yet to understand why.
Step 5: Research results
At this time, the UX research team may have some insights to layer in regarding past user studies or research results that are relevant to the experience and use case. The insights may come from past market trend research, user studies, A/B testing results, user survey results, "known knowns," etc.
For our example narrative, there has not been studies conducted in this area for a couple of years. That is ok. We will see later how the friction mapping can drive hypothesis for user studies to gain additional insights.
Step 6: User sessions
In this step, the content analyst provides a user session that matches the use case defined. The content analyst may make some key call outs to the users behavior metrics prior to converting; i.e., this user visited the site 68 times, built and abandoned a cart with a value of $324.24 prior to returning to the site and converting for $153.62. Since we know that the total revenue lost from abandoned carts for our uses case is around $134M, this user session may be a solid one for our friction mapping exercise! The analyst may publish user sessions For the working team to access and watch. In this example, the analyst published the session where the customer builds and abandons their cart, as well as the session where the user later converts.
Phase 3: User engagement
Through the user session identified above, screen captures are taken to level set the working team on the content displayed to customer at each step in the journey. These screen shots become the basis from which the working team will complete the friction map exercises for the use case.
NOTE: The user session above was leveraged to map this flow providing visibility into the CX itself. Screen grabs are provided to orient us to the step in the experience where the metrics apply.
The friction mapping is achieved by providing:
Full screen captures for each page displayed to the user
Each corresponding page URL
Documents the content flow diagram below each page. Each step in the user flow is represented by a shape. These shapes are taken from traditional UX flow diagram models.
Digital sticky notes are used to describe the action the customer took in the each step of the flow.
Provides engagement metrics for each page, showing user decisioning in terns of click through rates, page scroll rates, time spent on page, page load times, or performance issues—as relevant. This helps the teams not only to see the user behavior at each step in the flow, but to understand it in context of the content and design.
Content analyst calls out any areas of concern within the data to draw the team to investigate the UX and content closer.
Additional data is layered in at request in the next phase.
The content analyst will then do a read out to the multi-disciplined project/product team of the data findings. Explaining the any concerns noticed. This sets the stage for the working team to begin layering in the multi-disciplined insights.
In our example, we see that the average user places 5-6 products in their cart. They configure each device 3-4 times. We see that in the checkout out phase, >60% of customers abandon their carts. We still don’t know why our users are doing this.
Phase 4: Multi-disciplined insights
In phase 4, the multi-disciplined project team members and any stakeholders are invited to layer in their insights, thoughts, and questions.
Each participating discipline will be assigned their own color for mapping stickies.
The pink stickies are reserved for placing requests at certain points where supplemental data is needed to better understand an engagement. All disciplines use pink stickies to requests more data.
Analyst responds to pink stickies, layering in the requested data, and providing analysis on that data, to satisfy the questions
In this example, the content strategist places a pink sticky asking what are the top 5 Google People Who Ask for wireless customers searching to upgrade their device with trade-in. This is supplemental data. The analyst gathers that information and layers it into the friction map. It is here that we learn customers top questions are around pricing, trade-in credits, and discounts. It is only in the checkout phase that the customer is able to see these calculated costs. Our hypothesis is that customers are using the cart/checkout to complete their research and compare activities. This leads our UX researcher to set up a user survey to validate our hypothesis.
Once the team is satisfied with insights discovered and data to reinforce them, we move to the next phase--friction themes.
Phase 5: Friction themes
In this phase, a working session is held across disciplines to identify the frictions and assign friction themes. In the legend, there are pre-defined themes and icons for this exercise. As a working team,
Discuss all of the insights and come to consensus on whether a sticky poses to be an impactful friction in the experience as backed by the quantitative and qualitative data.
Talk through categorization of those frictions and drop the corresponding icon onto stickies.
Phase 6: Friction synthesis
In phase 6, all of the icon stickies from phase 5 are copied into their respective themes. They are synthesized into Key Friction Statements that can be consumed in content strategy brief, executive summaries, epic writing, testing hypothesis, production defect ticket creation, production content changes, and/or requests for pointed user research studies, or targeted survey questions. Their uses are really ENDLESS!
In our example, the biggest area of opportunity for this use case was to address the need for the user to conduct research and compare complete with accurate pricing, trade-in credit and discounts applied, so they could understand final costs between devices.
Once the customer friction has been identified through the Friction Map exercise, you'll need to benchmark that friction. Your content strategy SHOULD contain goals and KPIs specific to alleviating the user friction in the flow. And it makes it easy pull the best metrics to measure those KPIs because those metrics told you the story of that friction!
In this example, we can now
Write our epic for the product team; i.e., Create a robust digital device upgrade with a trade-in experience, which allows users to compare multiple devices with personalized pricing reflected before entering the checkout.
We could define our goal as “decrease the abandoned cart value for upgrade with trade-in experience by 30% in Q1.” This goal defined in this way is relevant, clear and measurable.
We can then set our tracking and measurements for reporting our attainment toward this goal; i.e.,
Baseline: abandoned cart value metric of $134M
Target: abandoned cart value to be $93.8M by the end of Q1
Now that we have our baseline and our target scores, we can measure the abandoned cart value at the end of Q1 to see how much we attained toward that goal.
Summary
The magic of the friction map is that it really acts as a one stop shop for product, business, and UX/CX teams to unite, collaborate, and come to understand where, together, they can make the most impactful changes to an experience. This framework empowers all impacted parties to understand the friction within the digital experience, through the eyes of the user, and in context of their journey. And all impacted teams and stakeholders have this map to follow when, where, why and how those frictions are arising in the UX.
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