In search of a data-informed way to build product vision and positioning: Part three
This is the final installment of a three-part series on building a product vision and positioning by researching decision drivers – factors that influence your customers’ decisions when choosing a solution. Here I wanted to discuss some of the questions that haunted me after we had completed the process for ourselves.
If you haven’t read parts one and two yet, you can go and do that now – I’ll wait. Otherwise, read on for a quick recap.
Recap of the first two parts
There are five steps to crafting a product vision and positioning based on data you’ve gathered from prospects
Step one: Describe a decision your target audience has to make
The first step has to do with who you’re building your product for and the decisions they need to make. Be as specific as possible with your target audience definition, identify your ideal customer profile (ICP), then identify the role of the person who plays the biggest part in the decision to buy (or not). Then state that decision, or reframe it as a question. For example, “Which solution from [product category] should we select?”
Step two: Discover the decision-drivers
Now you’ll gather data on how prospects evaluate different solutions You’ll learn what the overall evaluation process looks like, what sources of information prospects use, and other background context. The goal is to gather decision-drivers from multiple representatives of your target audience.
Step three: Rank the decision-drivers and get context on the most important ones
Here you need to come up with a list of 10 to 15 decision-drivers and ask your interviewees to rate them on a scale from one to seven. You’ll also need to get the context on the three to five most important decision-drivers for each interviewee. You can ask for ratings either via survey, before the second round of interviews, or do it within the interview.
You also have to gather context on the key decision-drivers in a structured way. You have to ask very similar questions for each driver to get the same type of information. This shouldn’t prevent you from getting additional context, but it will help you get to the heart of the drivers.
Alex Walton
Step four: Calculate the average, median, and standard deviation for each decision-driver
This will help you get a prioritized list of decision-drivers that you can apply as you craft your product vision and positioning. Select up to five of the decision-drivers that ranked the highest.
At this stage, if you have multiple audiences you want to understand better, just calculate the numbers for them separately. Keep an eye on decision-drivers with a high standard deviation. They might signal that there’s a sub-segment of your target audience within your interviews, and they highly value a decision-driver that might be of no interest to other segments.
Step five: Make the product vision and positioning
Now you’ve got it all: ranked decision-drivers and lots of context for them, all gained through interviews. You’ll have an understanding of what you should build and what’s not important for your audience. This will guide you to a lean product vision that includes only what’s relevant.
As for positioning, use context and use the specific language your interviewees used when they described decision-drivers and how they evaluated solutions based on those decision-drivers.
Scaling it up
As your business grows, you’ll want to expand your target audience. The methodology still holds, and you can approach scaling from two different perspectives:
- Reconsider the decision-drivers you’ve gathered and start covering more of them either within the main product or as an add-on.
- Do the research again, but with a specific segment in mind.
In the first case, the idea is to use the data you’ve already gathered to see what decision drivers can unlock a bigger chunk of the market.
A simple example here is advanced compliance with different regulations. Maybe you’re in a product category with different levels of data sensitivity, and that was a decision driver for your audience but wasn’t high enough on the list. A company that values this decision driver won’t select you because it’s too great a blocker.
You need to study the companies that gave advanced compliance a high importance rating and see what else they require. Is it enough for you to cover the decision drivers you initially covered and do you just need to cover one more? In that case, you have a great opportunity.
However, if you conducted the research a long time ago, the results may no longer be relevant, so approach with care.
In the second case, you just go through the full cycle of research once again, following the outlined steps.
Alex Walton
What if you’re creating a completely new market category?
This series of articles has been dedicated to building product vision and positioning for a product in an existing market category. It’s fair to ask whether we can follow this methodology for a product so novel that it’s going to create a completely new market category.
In short, I don’t know. I haven’t tested this methodology on completely innovative products. Regardless, allow me to speculate.
In theory (I warned you I was going to speculate!) you could start with a problem for a specific target audience, rather than a product or product category. But in this case, what exactly should we research to build our product vision and positioning?
Every problem has a solution. Sometimes the solution is to do nothing, and sometimes people who feel the pain of the problem create workarounds. We can study how the problem is currently solved in two ways:
- Find decision drivers for their current solution (which you believe isn’t optimal).
- Find gaps: what exactly are the people or companies you’re researching unhappy with? What prevents them from solving the problem completely?
Essentially, the research will be split into two parts because there are now two lists to rank. You’ll follow the same steps, but in the end, you’ll build your product vision and positioning not based only on what they value in their sub-optimal solution, but also on what they miss in the current solution.
Can this work for an existing product?
The challenges of working with an existing product don’t lie in the research area. Instead, your challenge will be the many stakeholders that need to be involved, and the sheer organizational effort of using the insights to build a new product vision and positioning.
You might run into executives that dismiss your research because “we’ve already done some research” or something similar. It’s just not going to be a priority for many executives. It will be your job to prove that the research is necessary.
Going back to the research dimension, working on an existing product will provide additional insights because you’ll be able to talk to your users or decision-makers from existing accounts. You should run those interviews separately from the ones with users or decision-makers of competitive tools, or at least separately within the analysis stage. You’ll not only learn what that segment of the market cares about but also about the existing accounts’ decision-drivers.
Acknowledgments
Thanks to Alan Albert, MarketFit president, who has decades-long expertise in building products, crafting positioning, and optimizing pricing, and who led the way for me to dive deeper into discovering customer values.
Thanks to Dmitriy Amosov, Sinisa Kravarascan, Maja Blazek, and Tomislav Jus who were an integral part of the initial research that was a foundation for my learning on decision-drivers.
We let you do the talking. 📣
Consider yourself an expert in competitive intelligence or competitive enablement? Feel like this 🤐 and looking for a platform to get your voice out there?
Look no further. The Competitive Intelligence Alliance wants thought leaders like you to get in touch.
It's your insights we're after, so if you're strapped for time we'll have a quick chat, then write the article for you. 💯
