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Using AI to Discover the JTDB Part I

Considering the Angle of Approach

Welcome to Using AI to Discover the Job to be Done. This sounds very easy, but this mini-course will show you how much easier it is using artificial intelligence, and actually gives you more research power. The two angles we’ll take would require quite a bit of effort and time if done the traditional way.

In this series we’ll be taking a look at the ways we can identify end user Jobs from different angles using artificial intelligence, e.g., ChatGPT, Claude.io, etc. Before we dive into that it’s worth reviewing what we are looking for, and how we have done that in the real world for decades.

🏫 The History

The first thing we typically do when planning our interviews is to identify the End User. End users have Jobs-to-be-Done, products don’t. Without end users it’s almost impossible to frame a Job because we have no one to interview.

I wrote about this in some detail in the following essay:

How To Get Results From Jobs-to-be-Done Interviews | by Mike Boysen | JTBD + Outcome-Driven Innovation

While I’m using the term end users, this is actually one of the three types of customers (or Job Executors)…

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End users — These are the people who use a product or service to get the core functional job done. The end user can provide you with the performance metrics (desired outcomes) that you need in order to understand how to design better products and services. These metrics are the inputs you need to help end users get their jobs done better, more predictably, and more efficiently.

If the goal of the initiative is to create a product that gets the job done better, then the end user is the right customer to target.

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People on the product lifecycle support team — These are the people who install, set up, store, transport, maintain, repair, clean, upgrade, and dispose of products. These are what we call consumption chain jobs because they relate directly to a solution (and its consumption). Not all of these jobs are relevant in every situation, but the people that perform these jobs can help you find ways to improve the overall customer experience.

If the goal of the initiative is to simplify the execution of the consumption chain jobs, then the people on the support team are the right customers to target.

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Purchase Decision Makers — These are the people responsible for seeking out and evaluating alternative offerings, and then deciding which to buy. These are the people to talk to when you need to understand how to improve the buying process, and also to understand the financial metrics used to make the buying decision.

If the goal of the initiative is to sell more of what you have to the purchase decision maker, then defining a go-to-market strategy for the purchase decision maker is the right choice.

Basically, if you’re focused on core product innovation and customer journeys you’ll want to identify end users. If you’re studying the provider side of the equation, you’ll study the product lifecycle support team, which are service providers (which sometimes includes end users if they’re doing it themselves). And if you’re interested in learning about how the purchase decisions are made you need to focus on people who make those decisions (which could also be the end user if it’s a consumer product).

I’ll let you read the essay for more details on the end to-to-end process. Essentially, the entire collection of lessons and prompts I’m making available will 100%, and without a doubt, eliminate everything you will learn in my prior writings. Sorry. 🤷

The exercise of identifying the end user is still important before generating Jobs-to-be-Done frameworks. But, you may also be interested in learning

What Jobs-to-be-Done could a product help end users with (those jobs could expand beyond the intended job by the brand)?
What core jobs would you expect to find in an industry, sector, or subsector for a specific end user. That is what the rest of this series will focus on

In both cases, you can determine the end users for each of the jobs you identify as we may not always want to call them consumers. So, AI helps us to work backwards.

Solution Angle

If you’re on a product team and you’ve gotten the Jobs-to-be-Done bug, you’re probably trying to determine exactly what the Job-to-be-Done is of your product.

🚨🚨🚨 Products do not have jobs! People have jobs that products enable (sometimes).

Actually, I’ve found that many consumer products support multiple jobs that consumers (the end user) are trying to get done. Therefore, getting a list of those jobs could be helpful. For example, maybe the core job is highly competitive, and you need to find opportunities with niche groups that are using your product for something else, or multiple things.

The next installment will show you exactly how to develop an AI prompt that gives you a list of those jobs, so stay tuned and don’t forget to check your spam folder!

Industry Angle

As with most processes and procedures, things tend to explode into an array of value-destroying activities…at least not value-producing. Maybe you’d like to simplify things so you can focus on the core purpose of your industry. Abstracting your study away from current solutions is a powerful innovation tool and this is one approach that might help.

Once you’ve done that, you can broaden your scope to find new opportunities (higher context jobs). I’ll share a couple of prompts to help you with that as well.

More to come…