The Two Types of Mentor Matching Every Accelerator Program Needs to Master

Most accelerator managers agree that mentorship is the backbone of a successful program. Yet despite universal recognition of its importance, many programs struggle with what seems straightforward, connecting the right mentors with the right startups.

Our work with hundreds of accelerators reveals a critical insight: There isn't just one type of mentor matching. There are two distinct types, each serving a different purpose in startup development.

The Two Types of Mentor Matching Every Accelerator Program Needs to Master

Type I: Expertise-Based Matching

When we match mentors based on industry knowledge, technical skills, or network connections, we're engaging in Type I matching. These relationships are practical and task-oriented:

• Industry alignment: A fintech startup paired with a payment processing veteran
• Stage-specific guidance: Early-stage founders connected with mentors who've navigated pre-seed challenges
• Functional expertise: Technical founders matched with marketing or sales experts to fill skill gaps

The value is immediate and measurable. AcceleratorApp data shows that startups matched with domain-expert mentors hit product-market fit 30% faster on average.

But something crucial is often missing.

Type II: Chemistry-Based Matching

The entrepreneurial journey is emotionally demanding. Founders face uncertainty, rejection, and immense pressure. This reality requires a different kind of mentorship based on trust and personal connection.

Type II matching creates relationships where founders can:

• Process fears and anxieties in a safe space
• Build confidence through authentic encouragement
• Find alignment between business challenges and personal values

These relationships are deeper and more nuanced. They require mentors who listen more than they talk. In a recent mentor software study, 78% of mentors said they'd mentor again after participating in programs with these meaningful connections, compared to just 45% in purely transactional arrangements.

Why You Need Both Types

Consider what happened at the UK Data Science Accelerator. They faced the challenge of pairing analysts across government departments with experienced data scientist mentors for complex projects requiring multiple specialized skills.

When the pandemic forced remote work, they turned this challenge into an opportunity by developing a data-driven approach to mentor matching:

1. They identified six key categories of expertise:
   • Programming languages (Python, R)
   • Tools (RShiny, Dash)
   • Programming environments (Azure, Google Cloud)
   • Data types (health data, video, text)
   • Themes (COVID-19)
   • Data science techniques (NLP, deep learning)
2. They tagged each project with relevant keywords and had mentors rate their expertise in each area.
3. Rather than simply matching the highest-scoring pairs first (which would leave some pairs with poor matches), they used linear programming optimization to maximize the average strength across all matches.

The results were impressive. They found out that 50% of mentors were matched to their first project preference, 25% to their second, and 12.5% to their third. The process allowed them to create optimal matches more quickly and confidently than their previous approach, with positive feedback from participants.

Implementing Dual-Type Matching

Here's how to build both types of matching into your program:

For Type I matching:

• Map specific mentor expertise against concrete startup needs
• Look beyond broad categories to specialized knowledge areas
• Consider stage-relevance (pre-seed vs. growth mentors)

For Type II matching:

• Survey communication styles and working preferences
• Create opportunities for informal, chemistry-based connections
• Allow both parties freedom to select their own matches

The Accelerator Program Manager's Role

As a program manager, you're the architect of these relationships. Your job isn't just administrative matching, it's creating the conditions for both types of mentorship to flourish.

This means:

1. Using structured data to inform Type I matches
2. Creating space for organic Type II connections to form
3. Building feedback loops to continuously improve both types

The right technology makes this possible at scale. AcceleratorApp doesn't just help you match based on industry codes, we take the following into consideration to help you: communication preferences, availability patterns, and session feedback to continuously improve match quality across both dimensions.

The most successful accelerators intentionally design for both types of mentorship.

So I'll be leaving you with these questions. Is your program designed to foster both types of mentorship? Or are you leaving half the value of mentoring on the table?

AcceleratorApp is the leading management platform for accelerators, incubators, and innovation programs worldwide.