As we discussed in Part 8 – “The Hypothesis Under Test”, our objective for conducting our VoC research is to gain insights into the level of satisfaction our test subjects are achieving in executing their jobs. What are the specific outcomes and desired results they want to achieve and why aren’t they getting the results they desire? What’s constraining them? Under what circumstances? And what is their ultimate definition of success?
In early stage research we are both exploring what the customer wants as well as confirming that they indeed do have a pain (i.e. losing tools and bringing the wrong tools and equipment on to the jobsite is a pain worth solving). By asking the right questions with the right subjects we can assess if there is a pain out their worth solving and/or if there is another set of pains out there associated with the jobs-to-be-done (the job trees) that might be an even bigger issue worth solving.
And of course whether our preliminary customer value proposition hits the mark at all. It might just be a “solution looking for a problem” – hopefully that’s not the case but better to discover this early and make adjustments versus launching a product dud. (The quintessential essence of iterative discovery and design – test early, test often, test cheaply – refine, refute, pivot or abandon as evidence guides us).
Here’s an example of research objectives that we would want to discover and learn for Teknovantage’s product concept:
Concept appeal of location aware tools
Perceived pain of losing tools at construction sites
Attractiveness of self-finding tools
Understand jobs to be done related to managing tools at construction sites
Satisfaction level
Requirements and constraints in getting Jobs-done
Location aware tools success will depend on the wide spread adoption of wireless sensor technologies in industrial settings (i.e. construction sites).
What’s the adoption rate to date and
What are the drivers, constraints and barriers enabling and/or impeding wide spread adoption?
Consumption chain and market landscape
Buying process
Competitors and alternative solution
Research questions are formulated to gain insights into these core learning objectives. How we ask the questions is critical. We don’t want to introduce cognitive bias (i.e. questions that will yield answers we want to hear vs. what customer’s really believe.)
Equally important we need to select the right set of people to act as our test subjects. We want research true “job executors” and other “real” people involved in the consumption chain (i.e. the decision makers – technical buyers, influencers, peers, channel members, etc.). It’s the jobs people are trying to do and their satisfaction levels in executing the jobs that we care about – not whether they like the product concept of location aware tools.
In the next blog I’ll discuss how to structure the questions using a combination of quantitative and qualitative questions to get the best results from the research data.
Talk with you soon,
Kevin
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