We need to provide job seekers and HR managers with AI solutions that
offer real added value in order to be successful in the market. The job portal Stepstone set itself this task and set out to specifically measure customer needs with CFI and then develop AI innovations that have potential in the market.
No company has too few ideas, on the contrary: good innovations are not a problem of idea production, but of idea selection. Companies are constantly looking for new market opportunities - sometimes more strongly and decisively, sometimes more randomly. And often simultaneously in different search fields that are sometimes more, sometimes less clearly defined. Search fields include digitization, sustainability, customer experience or industry-specific growth areas. Since the launch of ChatGPT 3 in November 2022, artificial intelligence (AI) is on the verge of becoming such a search field.
But a typical problem quickly arises: There are thousands of ways to use AI. Whether in internal processes for efficient service delivery, at the interface with customers for better interactions, or in the development of new products. The question always arises: where to start? We call this the ocean of possibilities . Ocean because you lose your bearings and risk drowning with all the ideas and options. With AI, there is also the fact that the resources required to really reach product or process maturity are high. It quickly becomes clear that not everything can be implemented - but how should you set priorities? According to feasibility? According to the developers' opinions? According to the HIPPO decision (Highest Paid Person Opinion)?
Innovations are inherently risky projects because they always involve something new, something that has never been done before. There is always an element of risk, no matter what the basis for the decision is. Ultimately, the customer or user (who can also be internal) decides whether an innovation is a success or a flop.
Stepstone relies on artificial intelligence
The Stepstone Group is one of the world's leading online job platforms. Stepstone has always used new technologies to help job seekers and companies find the perfect fit: the right job for job seekers, the most suitable candidate for companies. According to its own statements, Stepstone plans to invest 100 million euros in AI over the next three years.
Job search and candidate placement seem predestined for the use of AI. Many repetitive tasks are done manually on both the candidate and company side. Recruiters manually search through hundreds of CVs, candidates create application documents in Word. But beyond the obvious uses of AI, Stepstone asked itself the question: Where can AI make a real difference and become a game changer for the industry beyond the efficiency gains?
Stepstone has been facing this task for years and has received active support from Vendbridge in its implementation. In a Customer-Focused Innovation (CFI) process, the unmet needs of candidates in the market were measured and then sharp product concepts for AI solutions were developed, most of which Stepstone has already brought to market maturity.
AI products like a cover letter generator tool or an AI virtual interview trainer have a much higher chance of success because they address job seekers' needs that are proven to be unmet, reducing risk and increasing the chance of ROI from innovation.
Framing: Into the customer perspective with jobs-to-be-done
The CFI process was developed and refined in over 120 projects together with customers. It consists of four steps: Framing, Discover, Spin and Action.
Framing is about defining the right scope for the project. This is done primarily by answering three fundamental questions:
What is the business intention?
What is the target group, i.e. the source of growth?
What could be the jobs-to-be-done, i.e. the goals and motives of the target group?
While the business intention and target group are often immediately obvious – Stepstone wants to grow in its target group of job seekers using profitable AI products – the job-to-be-done is initially an empty buzzword. What does that mean?
Job seekers don't think about technological solutions or product ideas. Users use products, but not as an end in themselves. They want to achieve something with the help of the products. They want to get from A to B by car (but they could also take the train) or they read an article to keep up to date with the latest knowledge (but they could also listen to a podcast). What users ultimately want to achieve with products is the so-called job-to-be-done - the goal or purpose.
Formulating a job-to-be-done causes an immediate change of perspective away from the technical solution view (where can AI be used?) to the external view (what do job seekers want to achieve?). This change of perspective is a crucial first step in uncovering needs without distorting them with your own ideas or wishes. Customers are often unable to describe an innovative solution or correctly assess their own future use of new products: How many fitness subscriptions are lying around unused? How many initially skeptical customers now pay with their mobile phones without hesitation? On the other hand, companies are sometimes very enthusiastic when it comes to new ideas and technologies. If you look at the consistently extremely low success rates of innovations, users obviously do not always share the enthusiasm of the innovators.
Users are the experts when it comes to their job-to-be-done and their problems. Solution experts in companies are not. The concept of jobs-to-be-done allows you to switch from the internal to the customer perspective. In order to be able to assess the success of solution ideas, you must first ignore the solution.
Vendbridge has developed a tool, the so-called jobs-to-be-done hierarchy , to systematically find an initial hypothesis. The question quickly arises: How do you define the job-to-be-done? Where to start and end? Theodore Levitt once explained Jobs-to-be-done like this: people don't want a drill, they want a hole in the wall. Of course. But nobody actually wants holes in the wall either; they might want to hang up a picture or attach a shelf to the wall. But is that really the "job" that is being investigated? Isn't it more about making your home more beautiful? These questions can be raised to the highest levels. A tool is needed to define the altitude and breadth: that is what the jobs-to-be-done hierarchy is for.
Two jobs were defined for Stepstone: keeping an eye on the job market and finding a new job. This applies on the one hand to candidates who have a job but still take a look at advertisements now and then, and on the other hand to candidates who are actively looking.
Discover: Measure customer needs
The Discover phase in the CFI process often consists of a qualitative and a quantitative phase. In qualitative in-depth interviews, we uncover job metrics: metrics that users use to measure the value of solutions. For job seekers, for example, this is "updating your CV in as little time as possible" or "being as little nervous as possible in a job interview". These metrics can be found in every step of the job-to-be-done hierarchy and follow a strict syntax to guarantee methodological uniformity. As a rule, over 100 such job metrics can be found in 16 to 20 interviews, which usually last 60 minutes. These are very specific hypotheses about user problems that can then be substantiated quantitatively.
Over 8,000 job seekers and job market observers in Germany and the UK answered various jobs-to-be-done questionnaires. The result is a quantitatively substantiated insight into the problems of users , which we map in a kind of "fever curve" . It shows the importance and the degree of fulfillment for each job metric. At a glance, it becomes clear where added value is required - and where AI solutions can be used successfully. This creates the basis for the company's decision: Where is the risk of innovation the lowest? Where is it worth investing? What should you focus on?
Spin: Aligning AI with customers
With the unmet needs measured according to CFI, Stepstone can systematically go through the market opportunities and check where AI makes the decisive difference. We call this part of the CFI process "Spin" to express that ideas and technologies are to be aligned or "spun" to the user and their needs. It is therefore about sharpening the ideas so that they address exactly the measured, unmet need. We have developed two tools for this: "Pain Matching" and our own " Value Proposition Canvas ".
Pain matching enables ideas and projects to be quickly prioritized from a company perspective. The Value Proposition Canvas sharpens ideas by developing a value selling narrative based on the problem. This narrative can then be further sharpened or developed further in concept tests and other methods before resources are invested in development.
With this approach, Stepstone develops AI products to support the candidate application process. From generating the CV and cover letter to the digital AI-supported coach for preparing for job interviews, solutions are developed that set new standards for job seekers and shake up the otherwise rather conservative market. And the best part: the chances of market success are not empty hopes, but can be anticipated thanks to measured customer needs and jobs-to-be-done. This is how AI goes from being a bogeyman to a game changer: thanks to the customer perspective.
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