Smart Match is Mentorloop's algorithmic matching tool built on your bespoke matching criteria. It is a powerful, proven method to guarantee equitable, quality matches for everyone on your program at scale. Program Coordinators can instantly run Smart Match themselves.
Program Coordinators can refine or modify matching rules to power Smart Match, and create Loops for the entire program, segmented groups or cohorts in a matter of minutes.
Smart Match is available on Mentorloop Enterprise. If you want to learn more about how you can upgrade to Enterprise and unlock Smart Match, reach out to us at support@mentorloop.com
What is Smart Match?
Mentorloop Smart Match uses a purpose-built algorithm to simultaneously evaluate your entire cohort in one go, and ensure everyone receives the best chance of a quality match.
It considers a range of criteria from the information provided by mentors and mentees when they sign up for your program, such as skills and goals. It ensures equity, scalability and efficiency both in administration and cost.
Smart Match evaluates all participants simultaneously, eliminating the "first come, best served" dynamic. By optimising across your entire cohort rather than matching sequentially, it ensures everyone receives quality pairings, not just early registrants. This whole-program approach removes unconscious bias, giving every participant an equal opportunity for a transformative experience.
The algorithm processes hundreds of profiles in seconds, considering all possible pairings simultaneously — something impossible to achieve manually. It handles complex multi-variable criteria that would overwhelm any Program Coordinator, allowing you to scale from 50 to 5,000 participants while actually improving match quality.
Smart Match transforms matching from a days-long process into minutes, freeing you to focus on strategic program activities. It delivers higher match quality while surfacing valuable pairings you'd never spot manually: those transformative "unlikely" connections that become your program's success stories.
Keeping participant profiles up to date
Smart Match scores pairs on the information in participant profiles, so accurate, complete profiles directly improve match quality. Encouraging participants to review and update their profiles before you run a matching round helps ensure the best results. For a ready-to-use approach and message ideas, see How do I ask participants to review and update their profile.
How do I use Smart Match?
The below video takes you through a simple demonstration. For detailed training, see Smart Match Bitesize Training.
Read on for how to create effective, equitable Smart Matches in an instant. The Smart Match flow walks you through 5 steps: Matching rules → Select mentees → Select mentors → Participants in both lists → Review drafts.
Step 1: Configure your matching rules from the Smart Match page, found in the "Manage program" menu
Configuring your rules:
- Toggle: turn a rule on or off
- Dropdown menu: defines how the rule works (for example, same location vs different location)
- Scale: weight the rule from low priority (nice to have) to required (must be met to return a match)
When you're happy with your rules, click Save and begin Smart Match to move to participant selection, or Save to save your rule configuration without running a match.
What are conditional matching rules?
At the bottom of the matching rules page you'll find an Other matching rules section. This is where conditional rules live — rules that only apply when a participant has expressed a particular matching preference.
For example, a "Department preference (same)" rule will only activate when a participant has indicated they want to be matched within the same department. If they haven't expressed that preference, the rule is skipped for them entirely. Each conditional rule is labelled: "Conditional matching: This custom rule will apply when certain conditions are met, such as when a participant has a particular matching preference."
Common conditional rules include department preference (same or different) and gender preference (same or different). These give participants more agency over their match without making the criteria rigid for everyone.
Modifying rules:
- For detailed guidance on matching rules, see designing your sign-up form and matching criteria.
- For complex rules, reach out to your Customer Success Manager.
Key tip: Assigning too many 'required' rules can reduce the number of matches made. If this occurs, reconfigure some rules to 'low priority' and re-run Smart Matches. If you're unsure, reach out to your Customer Success Manager for advice.
✦ AI-powered matching for free-text fields
Smart Match can use AI to match participants based on free-text fields such as their biography and program expectations. This means the rich, unstructured information participants share in open-ended sign-up form responses can now directly contribute to match quality — something that was previously only possible with structured fields like dropdowns and checkboxes.
How it works:
Smart Match uses AI to analyse and compare the meaning of free-text responses across your participant pool. Rather than looking for exact keyword matches, it understands the intent and themes in what participants have written, and uses this to find alignment between mentors and mentees. Free-text matching rules are scored and weighted alongside your other matching rules. They don't replace your existing criteria — they enrich them.
Which fields are available?
Two standard free-text fields are available as matching rules by default on all Enterprise programs:
- Expectations — matches participants with similar expectations based on what they hope to get out of the program.
- Bio — matches people through similarity and alignment in their personal stories, including interests, hobbies, experiences, and what makes them unique.
These fields appear automatically in your Smart Match rules page if your sign-up form includes fields named expectations and bio. They are indicated by a blue sparkle icon to show they are AI-matched fields.
Configuring free-text rules:
Free-text matching rules work the same way as other matching rules. You can:
- Toggle them on or off
- Choose Same values from the dropdown to match participants with similar responses
- Weight the rule from low priority to strongly preferred using the scale
By default, these rules are toggled off. Enable them when you want Smart Match to factor in participants' free-text responses alongside your other matching criteria.
Custom free-text fields:
If your sign-up form includes additional free-text fields beyond Bio and Expectations that you would like to include in matching, reach out to your Customer Success Manager. Custom free-text fields can be enabled as AI-matched rules on your Smart Match page.
Note: For AI-powered free-text matching to work, the field must use the same field name for both mentors and mentees on your sign-up form. If your form uses different field names for each role (e.g. menteeBio and mentorBio), contact your Customer Success Manager to discuss a field name migration.
Steps 2 & 3: Select who you will include in Smart Match
Participant selection is split into two separate steps — Select mentees and Select mentors — so you can filter each role independently before running the algorithm.
a) Review or update your filters.
For example, if you wanted to run matching for a specific department, you would add a 'department' filter, and select the required department.
You can edit, add, or remove any of the below default filters:
- Mentoring Role
- Availability (participants who are available will appear)
- No Active Loops (participants without a loop will appear)
- No Draft Loops (participants without an existing draft loop will appear)
b) Select your Mentees, then select your Mentors.
c) Assign the correct role for Eithers in your program.
We recommend an equal number of Mentors and Mentees. You can use Eithers to appropriately balance the ratio, whilst taking into consideration their experience level to ensure the assigned role makes sense for them.
Running additional matching rounds with Maximum Matches
If you have more mentees than mentors, or simply want some participants to be matched more than once, the Maximum Matches setting can help you run additional Smart Match rounds effectively.
What is Maximum Matches?
When enabled, Maximum Matches allows mentors and mentees to define a maximum number of mentoring relationships they are able to participate in. This is a participant-level setting that each person controls from their own profile.
How does it work with Smart Match?
When a participant reaches their maximum number of matches, they are automatically marked as unavailable and will no longer appear in Smart Match. This is helpful because:
- If you have more mentees than mentors, Maximum Matches helps you identify which mentors are willing to take on more than one mentee. You can run multiple rounds of Smart Match — in each round, mentors who haven't yet reached their maximum will still appear as available.
- It gives you visibility into participant capacity, so you can plan your matching rounds strategically.
- Between rounds, you can check who still has capacity by using the 'Maximum matches: has max set' filter in your participant list.
Tips for running multiple rounds:
- Before running additional rounds, remove the default 'No Active Loops' filter in Steps 2 & 3 — otherwise, participants who already have a match from a previous round will be excluded.
- Consider prioritising specific groups or segments in your first round, then matching the remaining participants in subsequent rounds.
- Encourage mentors who are happy to take on multiple mentees to enable Maximum Matches and set an appropriate number on their profile.
Steps 4 & 5: Review and approve your Smart Match results
With your participants selected, you're ready to Create!
Once you select 'Create', your Smart Matches will appear in Draft mode, allowing you to review before either approving or dismissing them. Step 4 shows any participants who appear in both the mentor and mentee lists for you to resolve, and Step 5 is your draft review.
What happens on the results screen?
The results screen summarises your run and gives you three options for what to do next:
- Review and approve draft loops — takes you directly to your draft matches to review and approve them. See how to review and dismiss draft matches in bulk.
- Add more participants — return to the participant selection step to include additional mentors or mentees before approving.
- Delete and start again — discard the current draft results and restart the matching process from scratch.
The results screen also shows how many participants were placed into draft loops and how many remain unmatched. If a significant number are unmatched, review your rules and filters before approving — see the FAQs below for common causes.
How do I review an individual match?
Each draft match in the results list has a View button and a delete button. Clicking View opens the match detail, which shows:
- Dismiss pairing and Approve match — action the pairing directly from this view.
- Fields used in matching rules — a side-by-side comparison of each participant's profile values for every field your algorithm considered. This lets you quickly sense-check whether the data looks right before approving.
- ✦ See why this Smart Match works — generates an AI-written rationale explaining why these two participants were paired. See Smart Match Rationale below for more detail.
You can also navigate between draft matches using the arrow controls in the match detail view, so you can step through pairings without returning to the list each time.
What is Smart Match Rationale?
Mentorloop now provides an AI-generated rationale that explains why each Smart Match has been made. This can be incredibly useful for:
- Helping you quickly understand the logic behind matches — the rationale summarises how your matching rules and participant profile data contributed to the pairing.
- Providing context to participants who may be curious about their pairing.
- Building confidence in matches that might seem unexpected at first glance.
How to use it:
- From a draft or active Smart Match Loop, click the 'See why this Smart Match works' button to generate the rationale.
- The rationale is opt-in — it is only generated when you click the button.
- Once generated, the rationale persists in your view of that Loop. You can return to it at any time by expanding the 'Why this Smart Match works' section.
- Rationale can be generated for any Smart Match Loop, whether it is still in draft or already active.
Can participants see Match Rationale?
Yes, the participant-facing version of Match Rationale allows participants to see a plain-language explanation of why they were paired with their mentoring partner, directly from their Loop home page. The explanation is drawn from your matching rules and their profile data, without naming either participant directly, so it reads as an objective summary of the pairing.
The more complete a participant's profile (goals, skills, bio, and any other fields), the more meaningful their Match Rationale will be. Encourage your cohort to keep their profiles up to date before matching runs. Learn how to update a profile →
Smart Match masterclass
What are Recommended Matches?
Recommended Matches is a self match functionality powered by an algorithm that suggests good matches to participants. It is available on both Mentorloop Pro (using Mentorloop's simple algorithm) and Enterprise (using the bespoke algorithm).
How do I manage match quantities?
Two features in Mentorloop help you manage how many matches participants can have. They serve different purposes and are often confused, so here's a side-by-side comparison to help you understand when and how to use each one.
| Maximum Matches | Limit Open Match Requests | |
|---|---|---|
| What it controls | The maximum number of active mentoring relationships (Loops) a participant can have at one time. | The maximum number of pending match requests a participant can have open at one time. |
| Who sets it | The participant — they enable and configure this from their own profile. | The Program Coordinator — this is a program-level setting found in Program Settings. |
| Where to find it | Participant's profile (participant-facing). PCs can view capacity via the 'Maximum matches: has max set' filter in the participant list. | Program Settings > scroll to 'Limit open match requests'. |
| What happens at the limit | The participant is automatically marked as unavailable. They will no longer appear in Smart Match or Self Match. | The participant cannot send additional match requests until a pending request is accepted or declined. |
| Applicable matching methods | Both Smart Match and Self Match. | Self Match only. |
| Default setting | Off by default. When enabled, the default number may display as 5 on participant profiles. | Pro: 2 requests. Enterprise: Unlimited. |
| Best for | Ensuring participants are not overcommitted with too many active mentoring relationships. Useful for running multiple Smart Match rounds where some mentors take on more than one mentee. | Preventing participants from overwhelming potential matches with too many pending requests at once in Self Match programs. |
In summary: Maximum Matches limits how many relationships someone can have. Limit Open Match Requests limits how many requests they can send while waiting for responses. Both features work together to help you manage match quantities across your program.
To learn more about how to manage Self Match programs, check out our Self Match best practice guide here.
FAQs
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Why am I not getting any (or many) matches?
- Your rules might be too rigid.
Assigning too many 'required' rules can reduce the number of matches made. Reconfigure some rules to 'low priority' and re-run Smart Matches. If you're unsure, reach out to your Customer Success Manager for advice.- Filters may be excluding people. For example, if you are giving people a second match, you would need to remove the default filter 'No Active Loops'.
- Participants may have reached their Maximum Matches limit. If a participant has enabled Maximum Matches and reached their limit, they will be automatically marked as unavailable and won't appear in Smart Match. Check the 'Maximum matches: has max set' filter in your participant list to identify these participants.
- Profiles may be out of date. Send a bulk message encouraging your participants to review and update their profiles. See How do I ask participants to review and update their profile for a ready-to-use approach.
- Run multiple rounds: If you have different rules for various groups of people, you will need to run multiple match rounds. See Running additional matching rounds with Maximum Matches for guidance.
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Can I run Smart Match for just one person?
You can run Smart Match with all unmatched and available participants, but you may not get the result you want due to numbers and profiles not aligning.
If this happens:
- Run it against the whole program, just to see who their best match would be. If their best match is already mentoring, reach out and ask if they can take on another one before approving the Smart Match.
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What happens once I have approved my draft Loops?
Participants will receive an email from the system introducing them to each other, encouraging them to book their first session. See here for a description of all System Emails.
They will also receive the New Match Email Notification, which is fully customisable from your program settings.
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Should Smart Match replace my chosen matching method?
Not necessarily! The best matching method will vary based on your program's goals and requirements. Here's a quick recap:
Manual Match: You, the program coordinator, manually pair mentors and mentees by filtering participants and creating relationships.
- Best for: Programs where the coordinator's expertise is critical for pairing or when participants need direct assistance.
Self Match: Participants find and connect with each other based on their profiles.
- Best for: Empowering participants and encouraging autonomy.
Smart Match: Mentorloop's equitable algorithm automatically matches participants based on skills, goals, and experience to remove bias.
- Best for: Matching large groups or when you want to remove unconscious bias.
Blended: A combination of Smart / Manual matching and participant-driven, where the platform provides recommendations to support participants who are self-matching.
- Best for: Programs that want to offer flexibility, allowing participants to take ownership while still providing support from the coordinator / Mentorloop's algorithm.
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Why aren't the participants I want to match appearing in the Smart Match list?
Your filters are likely incorrect. For example, if you are giving people a second match, you would need to remove the default filter 'No Active Loops'. Additionally, check whether the participant has reached their Maximum Matches limit, which would automatically mark them as unavailable.
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How do I know who wants to be matched?
This depends on your mentoring strategy (for example, always-on mentoring can differ from cohorts), but the general rule is anyone who is 'available', in 'No Active Loops', and has not met their 'maximum match capacity'.
If you need help achieving a different matching strategy, reach out to your Customer Success Manager (Enterprise) or support@mentorloop.com (Pro).
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What's the difference between Maximum Matches and Limit Open Match Requests?
These are two separate features that both relate to match quantities but work differently. Maximum Matches limits the number of active mentoring relationships a participant can have (set by the participant). Limit Open Match Requests limits the number of pending requests a participant can send in Self Match programs (set by the Program Coordinator). See Managing match quantities above for a full comparison.
Smart Match is a great way to save time and remove bias, without compromising equitable quality matches. Watch our Bitesize Training for an in-depth product demonstration. Reach out to your Customer Success Manager for support, or support@mentorloop.com to include Smart Match in your subscription.