In search for a data-informed way to build product vision and positioning: part 1
The 3-part series is oriented towards building one more skill in your toolset: creating product vision and positioning based on customer research. The series will outline steps that can take you from having basic intuitions about what will speak to users/buyers to a completely research-based positioning and product vision.
Focusing on a customer decision to build positioning and product vision
One of the most memorable working experiences came from significant research undertaken with my colleagues at one of the companies I worked for and a consulting firm MarketFit, led by Alan Albert. It was about product vision and positioning — a not-so-easy topic for even the most experienced product managers.
Many product managers and product marketing managers do not realize how they should tackle crafting product vision and positioning in their company. The problem seems to be covered with mystique.
At best, companies run internal workshops and brainstorms to devise product vision and subsequent positioning based on their understanding of the market, customers, and product they are building.
Business books, including Blue Ocean Strategy, describe the same way to get at positioning or product vision. The implication is that people working on a product should know enough collectively to devise a product positioning. While this approach is better than a top-level manager making a sole decision, we could do much more to get product vision and positioning that reflects what our market segment truly needs.
We typically position what we create instead of creating what is easy to position
In general, positioning follows a product vision. After all, we start with a vision and only then get to the level of details: what features do we build, what positioning our product will have, how will we appeal to the needs of the user, how do we make sure our potential audience realizes that we fit their needs.
However, we should not start working on positioning after we deliver a product or a version of it. If we start with both product vision and positioning, we will be able to focus our efforts on features that the target audience will appreciate. Some features will not make the cut, and that is fine.
The typical way to do product vision and positioning isn’t optimal
Product vision, positioning, and value proposition often come as a result of a sole or group decision. Managers write positioning statements and documents and then push those documents to GTM teams.
A sole decision-maker introduces too many biases
Industry, market, and client knowledge is nothing to sneeze at, but our experiences within an industry or even insights from tangential interviews introduce biases to our thinking, and they shape the way we see our product and the needs of our existing or potential customers.
A group comes to a compromise between multiple biases
Collaborative work, when multiple people exchange opinions and provide ideas on product vision and positioning, is a much better alternative to making a decision based solely on the gut feeling of one person. Triaging multiple data points results in a much more consistent and relevant output, although the biases are still present. You just remove the most egregious outliers by doing the work together. The result is a compromise between the biases of different people.
Sometimes the typical way works — we nail the positioning, product vision, and value proposition. The problem is not that we can’t get to an effective state with this approach. The problem is that the typical way is not consistent and depends significantly on luck, even when we include experts. So many products fail despite the names behind them.
A data-informed way to build positioning
Within this series we will go through a series of steps towards getting a data-informed product vision and positioning.
What’s so different from the ‘typical way’ described above?
First of all, instead of guessing what points we should highlight for our target audience, we’ll take those points directly from those who have recently made a decision on selecting a solution like the one we are building.
Secondly, we will have to say ‘no’ to things that don’t align with the decision-drivers of our audience. Cool ML algorithm that you can build and introduce that will make you stand out (as it covers some specific need), but that’s not relevant for the audience you are building your application for? That’s a no. However, you might want to think about finding an audience that cares about that but the burden of validation is still present.
Thirdly, we will not just do the interviews to get the decision-drivers, we’ll also quantify them — through interviews.
As the main idea of the series is to show you how to get a product vision and positioning based on the decision-drivers, that’s where we’ll spend the most time on. For target audience definition, ICPs, roles within B2B I suggest you read an additional article or two if that’s not defined or used within your organisation.
Step 1: What decision does your target audience need to make?
Define an ICP first
At the outset, you need to have an idea of what the most fitting segment looks like for your new product introduction. You may be wrong at that point, and potentially the interviews will show you that you can’t cover decision drivers of the audience that you have thought of as the best for you, but a rough image of an ideal customer profile is necessary.
A problem you are solving with your product is felt the most by a specific category of people. Who are they? What do they do day-to-day? What kind of job role within the company do they have, if that’s relevant? Create a portrait and try to screen participants through it in the next steps. For B2Bs you’ll start with the company description first, and person description second — you will need both.
If you have no experience in defining a persona or ICP, I suggest you find an article about that or a person within the organisation that can help you. Don’t skip that part just because you think you know your audience. A preliminary research on segments of your target audience may be necessary, or you may use existing data to build your ICP.
Segment definition will impact all the work you are going to do next! Different segments will have different decision-drivers.
Restate the decision into a question
The more important point is to know what kind of decision your audience needs to make. A decision can generally be restated into a question, a simple example for B2B SaaS would be: “What product from [product category] do we want to select?”
Specific needs, values, criteria, and motives drive an answer to this question. The next steps will shed light on the specific decision drivers that help your target audience answer that question.
Restating the decision into a question is my preference, not a hard rule. Knowing the decision is enough, I just feel like it’s much easier to empathise with the audience a bit more when the decision is restated into a question.
Define the role to talk
There are multiple roles within B2B SaaS solutions: decision-makers, evaluators, end-users, and others. Sometimes they overlap, sometimes they do not — for our purposes, we need to select which roles drive finding the answer to the above-mentioned question.
For one research, you might realize that evaluator and decision-maker will be different people within the company, but evaluator will be much more crucial than a decision-maker, just because decision-maker approves or rejects what evaluator suggests. In other cases, an evaluator will provide a selection of options a la carte for a decision-maker to select from, and in this case, you need to decide: do we want to get on the list or do we want to get selected from the list that we will be a part of.
An imaginary example for the series
For example, you are creating a B2B SaaS application that allows your clients to accept payments on a website / in an application.
The decision of the target audience, in this case, is related to a question: “Which payment provider should we introduce to our product?” I am omitting a lot of details, such as the specific segment of the target audience, ideal customer profile, vertical or exact use case for getting payments, etc, that I described previously. In your research, you’ll need to have much more clarity on those points.
This concludes the first part. In the next chapter we’ll go about actually gathering decision-drivers and their rankings as a foundation of the positioning and product vision.
By that point we know:
– What our Ideal Customer Profile (ICP) is for the product we are considering (or for a problem we are trying to solve)
– What is the decision to be made by an ICP or a representative of ICP (or what question they are answering)
– What role should we talk to (for B2B)
In part 2, we will cover:
– Ways to come up with the list of decision-drivers (fast and dirty vs. long and robust)
– How to perform interviews that are aimed at ranking decision-drivers and getting deep context on each important decision-driver
– How to rank decision-drivers with supporting context across all interviews
– How to build a product vision and positioning based on all the data you will have gathered by that point
