How to Build a Product from Zero to One Using Interviews and Kano Analysis

#kano #surveymethods #generativeresearch #ux

May, 2024 | Christopher Nguyen

Contents

Intro
Research Process
In-depth User Interviews
Ideation Workshop
KANO Model
Concept Testing
Conclusion

Overview

In this document, I provide a walkthrough of my experience building a product from zero to one through the use of mixed-methods research and multi-team collaboration.

Disclaimer: This document serves more as a how-to piece and focuses less on the actual project insights.

Defining a research process

Exploring new product opportunities came with little direction and lots of uncertainty. What I found useful in this situation was to break down the steps required to build a new product experience.

Breakdown of steps:

Identify customer pain points
Get the product and design team onboard to solving pain points
Find a way to generate solutions for pain points
Assess and prioritize which solutions to work on
Evaluate concept solutions with customers

Each step serves as a funnel that re-evaluates the validity of the pain point and proposed solution where multiple iterations take place.

Exploring untapped areas in the product experience

As a team we didn't want to exclude any parts of the product experience where customer problems may be arising. So we decided that it would be best to evaluate the entire end-to-end journey using in-depth customer interviews. We decided to use interviews over other methods because it offers greater flexibility in asking open-ended questions as well as asking clarifying questions. The goal of the in-depth interview was straightforward, which was to identify at what points do customers experience any challenges.

Recruiting: Our team utilized an internal recruiting tool where customers could opt into research studies. This tool worked well for recruiting participants who had experienced the end-to-end journey at least once as the opt-in was presented to customers at the end of their project engagement. When it came to sample size, this study had 12 participants. Customer were categorized into two groups being a non-technical and technical group. These two groups consists of the largest dispersion of our customers so it made sense to split them up in this manner. Regardless of segment, research questions were administered the same way across groups.

Experimental design: Preparing exploratory research questions were organized in chronological order based on the end-to-end journey. As mentioned earlier, the script contained open-ended questions where customers could freely speak about their experience. There was some context setting when transitioning from one stage to the next. Active listening and rigorous note taking were also key during study moderation. Additionally, knowing background information on the participant helped prepare tailored questions.

Sharing research: Research findings were presented to product and design (roughly 25+ team members). The goal was to get the team to understand the full-scope of the key findings and to ultimately have them participate in an ideation workshop in the following weeks. Keeping the presentation focused on 3-4 key findings helped the audience pay attention to what really mattered, which was to get everyone on board to solving these customer problems. Allowing enough room during and at the end of the presentation allowed for open discussion, brainstorming, and resolvement of any objections. The final outcome of the in-depth interview presentation was excitement for the research team to host an ideation workshop with product and design.

Collectively ideating on solutions

The ideation workshop took place remotely and over the course of 1 session. Miro was used as the creative canvas for ideation.

Preparation: One week prior to the workshop, team members were added to a group Slack channel detailing the instructions for the ideation workshop. Team members were asked to review the presentation report on their own and familiarize themselves with the Miro board that contained 3 How Might We questions.

HMW Ideation: During the workshop, team members were given roughly 8 minutes per HMW to add their own sticky notes on how they might solve a customer problem outlined in the interview report shared weeks prior. Here is a resource on how to structure HMW questions by dscout.

Collaborative Synthesis: After all the sticky note solutions were added to their HMW the team collectively grouped similar sticky notes and labelled them. Each HMW ended up with a cluster of around 8-10 solutions (roughly 60+ sticky notes per HMW).

Voting: All team members were given 3 red dots to vote on their favorite ideas. Within the workshop we also had a Principle Designer, Director of Product and Director of Research that acted as the final decision makers where they voted on ideas they felt were important to solve. These ideas were then transformed into 7 product features that were later evaluated by customers using the KANO model.

Outcome

Overall, the ideation workshop provided team members the opportunity to contribute ideas on problems outside of their product area. Additionally, the workshop inspired collective collaboration, alignment between teams and most importantly it generated 7 new product ideas to further test and explore.

Kano Analysis and Impact

The Kano Model was used for gathering feedback on customer's sentiment towards the presence or absence of a new feature. The benefit of using the Kano at this point is that we had already conducted prior research with the in-depth interviews and had uncovered customer problems. And now we needed a way to evaluate whether these problems are impactful problems to solve on a larger scale. The sample size for this study depends on the number of customer segments. For this study, there was a total of n=68 responses.

The model functions as a survey and works well as a product prioritization method. Here is a resource detailing the kano model by folding burrito.

Each feature is evaluated by two sets of questions. For example,

If you had the ability to _______, how do you feel?

I like it
I expect it
I'm neutral
I can live with it
I dislike it

If you did not have the ability to _______, how do you feel?

I like it
I expect it
I'm neutral
I can live with it
I dislike it

In figure 2, we can reference

Based on the combo of responses, the model classifies the feature into six categories (Figure 1).

P = Performance: The more a user has of this, the more satisfied they become. Users like having them and dislike not having them
M = Must be: These are services or features that are expected by users
A = Attractive: When a user likes a feature that was unexpected (new and attractive)
I = Indifference: When the presence of absence of a feature does not make much of a difference
R = Reverse: Like not having the service or dislike having it
Q =Questionable: When responses are conflicting (like it and like it)

Features are then plotted onto an x (dissatisfaction) and y (satisfaction) plane based on their scores. For example, feature 3 is plotted as a performance feature, indicating that the more a user has of this, the more satisfied they become (Figure 2). Imagine feature 3 being mileage range on a single charge for an electric car. The more mileage range an electric car owner has on a single charge, the further they will be able to travel, increasing satisfaction.

Figure 2 (Feature plotting)

My team considered performance and must-be features as a high priority. In the example above, product priorities went to feature 3 and feature 2. This means they move into the product backlog as an upcoming features to build. The process for high value features post Kano was to build out concepts for the feature idea with the design team. Further evaluation and iterations of the features were then tested in either a concept or usability test.

From product analytics to interviews to evaluating 1 feature to 4+ at a time, the impact Kano has brought to my team was 13 evaluated proposed solutions with 4 products deemed high-value (categories performance and must-have). Three out of the four features were built by 2023.

Kano Disadvantages and Advantages

Disadvantage: Can take awhile to come up with product solutions, difficult to use if prioritizing a large list of solutions because each solution has 2 questions (absence/presence), Customers can misinterpret feature description

Advantage: Use for building a product from scratch,use for prioritizing unrelated and related features, can segment customers post survey

Final Thoughts

In this document, I've outlined how I used Kano to help my organization better understand customer needs and problems.

When my team needed to build a product from scratch, incorporating Kano in the product development process provided a comprehensive path towards that goal. As such, Kano helped my team develop 4 completely new product features, all led by research.