If you find the above title a little intimidating, don’t worry. We’ll simplify this entire process. Using voice of customer (VOC) data techniques and employing a Kano analysis can be daunting. However, while the tasks themselves are involved and the process of gathering data somewhat laborious, they are very straightforward methods of quantifying those product features and benefits that customers want, versus those they don’t need. Every company has its internal and external customers. Each push their own solutions and their own initiatives. As a product manager, your must isolate those VOC data points that dictate what your product must have for market entry.
The Kano Analysis and Voice of Customer (VOC) Data
Before going forward with the process of accumulating VOC data, it’s important to get a general overview of the damage that can be inflicted when one party has too much influence on a product’s scope. Companies that manufacture custom-made designs understand these issues very well. They know that to leave an engineer on his or her own to decide the product’s scope, is a recipe for disaster.
While companies rely upon engineering for product advancements, the reality is that all engineers want to design a better mousetrap. Given the opportunity, they can eschew protocol and blow a product’s budget out of the water. That’s ultimately why companies use voice of customer data points. Companies aim to maintain the product’s overall budget, mitigate the impact of delays, identify critical versus non-critical paths to product introduction, and ultimately push their product to market at the right time and for the right reasons. Voice of customer data is needed for the following:
- Determine what customers truly want & care about
- Balance customer needs with the product’s budget (what can you afford to meet?)
- Establish the principles of a cost/benefit analysis on product upgrades.
Step 1: Collect Voice of Customer Data at Initial Product Scope Stage
No one approach to VOC collection will provide all the answers you’re looking for. To be successful requires a multipronged approach. First, companies typically start with customer interviews that are focused on identifying “pain points” versus “happy points”. Companies look for reactions and issues that immediately point to problems by focusing on how customers react to a product’s potential features. Second, companies follow up these interviews with surveys and questionnaires that quantify those aforementioned pain points and happy points from initial interviews. Third, employing focus groups often weeds out inaccurate data and brings together likeminded individuals to corroborate ideas and product features.
1. Customer Interviews: Be specific, to the point and upfront about the intention of the interview. Too long an interview and you’ve lost your audience. Stick to your most important questions and don’t veer off on tangents. Measure the benefits of one-on-one interviews relative to phone and email interviews. Face-to-face is more accurate but sometimes more expensive, while phone & email is less expensive, but much less accurate and reliable.
2. Surveys: Use data from customer interviews to substantiate customer needs through surveys. Your surveys are meant to further expand upon your findings in those initial customer interviews, and to provide a larger sampling portion with which to establish the necessary statistical data to make a decision.
3. Focus Groups: Using focus groups allows you to maximize information gathering relative to time. In essence, you gather multiple data points from a single focus group gathering. Somewhat less accurate and personal than one-on-one interviews, focus groups are far more cost-effective – given the right circumstances.
Cascade your voice of customer data collection into the following stages:
- Initial Product Scope: Use interviews to establish initial customer needs.
- Midpoint & Before Product Launch: Justify product’s scope & timeline.
- Future Product Upgrades: Customer specific or market specific?
Step 2: Use a “Kano” Analysis to Isolate Most Important Customer Needs
Use the Kano analysis for the “Midpoint or Before Product Launch” or “Future Product Upgrades” portion of your product’s market introduction. The Kano analysis is applied post product scope stage.
In this second step, you will classify those customer needs uncovered from the VOC data above and classify them into the following criteria:
- Those customer needs that are…. 1) Essential to Market Dominance
- Those customer needs that are…. 2) Essential to Market Entry
- Those customer needs that are…. 3) Me-too Product Features
- Those customer needs that are…. 4) Unnecessary Product Cost Drivers
To accomplish the above, you’ll use what I refer to as a single line/single focus “Kano” analysis. A Kano analysis is typically employed in large scale product introductions for consumer applications, one where companies require large sampling sizes, cross-referenced questions and conjoint analyses across multiple geographical locations. Granted, it sounds quite involved. However, it is nothing more than a tool to quantify or segregate VOC data in terms of its importance. We’ll simplify our analysis by asking customers to provide four possible answers on the product’s existing features.
- Exceptional Feature = Essential to Market Dominance
- Expected Feature = Essential to Market Entry
- Indifferent Either Way = Me-too Product Features
- Disliked Feature / Not Needed = Unnecessary Product Cost Drivers
Step 3: Assess Costs of Possible Upgrades & Savings of Downgrades
The answers above will provide you with the ability to identify those expected features that are essential to entering the market. However, you must now understand how your product performs relative to these features. Customers may tell you that the RF leakage tracking is an expected feature, but they may also be telling you it doesn’t work on the current version of your product! This requires further data collection.
Your customer may provide a Kano answer of "It's a fantastic feature - if you can make it work!"
For instance, if a prevailing theme resulting from customers is the claim that the product’s RF leakage tracking stalls and that the temperature tracking is faulty, then the next question is what happened in the manufacturing or design stage, and how does the company meet this expected feature in order to enter the market? It’s somewhat similar to a CE matrix (cause & effect). Your focus must be on meeting the minimum market entry requirements for your product – that being any "expected feature" from your Kano analysis (step 2).
What have we accomplished?
We’ve identified those customer needs from our VOC data and have classified them in terms of their importance to the product’s success in its market. This was done in our initial product scope stage where we used interviews, surveys and focus groups. Next, during the midpoint & before product launch stage, we’ve used a simple Kano analysis to test our product’s features relative to those needed for market dominance, market entry, me-too product features and unnecessary product cost drivers.
Finally, we’ve identified those expected features that are essential to market introduction and have determined costs to upgrade/repair versus the savings from eliminating disliked or unnecessary features.
Gathering voice of customer data can be a time-consuming and involved process. However, the input it provides is immeasurable and essential when performing a Kano analysis. The focus must be on voice of customer gathering techniques (interviews, surveys, focus groups) at initial product scope stage.
Once you’ve a product ready for testing, use the Kano analysis to distinguish those expected features your product must include, versus those features that will distinguish it versus its competition and ultimately, those features that offer no benefit to the customer and are simply unnecessary cost drivers. FInally, sum up the total costs of upgrades for expected features your product isn't meeting and account for those savings on product features you can remove.
The above video explains how to measure inventory holding costs against large volume purchases. It is taken from the post: Inventory Carrying Costs Versus Higher Volume Purchases
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