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Introduction to the Client Interaction Problem

Recently, a discussion sparked in our Slack chat about how we can enhance our client interaction model. One of the developers raised the issue that the success fee model leads to uncertainty for startups, especially in their early stages. This prompted us to think about how we could make interactions more transparent and predictable.

Context: Why This Matters

The startups we work with often operate under challenging conditions, where every penny counts. The success fee model, based on a percentage of successful project completion, creates uncertainty. Founders do not always understand what the final costs will be, leading to mistrust. We realized that to build honest and long-term relationships with clients, we needed to change our approach.

The Problem in Detail

One notable example involved a startup that approached us for help in finding candidates. We proposed a success fee model, but during the process, it became clear that the startup could not afford high commissions in case of failure. This led to disappointment and dissatisfaction on both sides, negatively impacting our collaboration.

Initial Attempts

Before arriving at the contact credits model, we considered several alternatives. One of the first ideas was simply to reduce the percentage of the success fee, but this did not address the core issue—uncertainty in costs. We also tried fixed rates, but these did not account for project variability, which also caused dissatisfaction among clients.

Technical Approach to Contact Credits

Eventually, we developed the contact credits model. This allows startups to purchase credits in advance, which they can use to access services. This creates a more predictable cost model. For example:

class ContactCredits:
    def __init__(self, credits):
        self.credits = credits

    def use_credit(self):
        if self.credits > 0:
            self.credits -= 1
            return True
        return False

This model not only improved financial transparency but also strengthened trust between us and our clients.

Changes in the Product

With the introduction of contact credits, our clients began to experience less stress and more control over their budgets. We noticed an increase in repeat inquiries from startups, indicating a positive experience. In particular, startups began to engage more actively with our services on the /jobs and /for-companies pages, which increased their involvement.

Lessons Learned

• Honesty and transparency in payment models build trust.
• Simplifying financial processes helps startups focus on their business.
• Not all clients fit one model—unique needs must be considered.
• Testing ideas in early stages helps avoid major issues later.
• Contact credits can lead to long-term client relationships.

What This Means for Candidates

For candidates, this means that we can now offer more flexible and transparent terms. The contact credits system allows startups to manage their budgets more easily, which in turn increases the likelihood of successful project completions. This creates a more stable environment for job searching and collaboration.

What This Means for Recruiters

For recruiters, this opens up new opportunities to present startups that can offer their clients more predictable terms. The contact credits model allows recruiters to assess client needs more accurately and propose suitable solutions, increasing the chances of successful collaboration.

Next Steps

Despite the success, we understand that the contact credits model still requires refinement. We continue to monitor how it affects client relationships and are ready to adapt based on their feedback. If we had to choose, we would perhaps focus on improving client feedback mechanisms to further enhance trust and satisfaction. ---