Introduction

Crewhu Echo has an automatic match engine, so you can attribute online reviews to the right contacts and employees without manual work. By using the Match Confidence Level, you can change the matching level according to your needs.

In this article, you’ll learn how to configure the match confidence level and understand how each option affects future review attribution.

How to Use the Match Confidence Level

To configure the match confidence level, first go to Echo > Settings. The confidence level setting is available in the same area as the automatic contact and employee match settings:

Match Confidence Level

The match confidence level determines how much evidence Crewhu Echo needs to check before automatically attributing a review. By default, the initial confidence level is set to Conservative. You can change this setting at any time based on your team’s needs.

Once updated, the new confidence level will be used for future automatic matches. Changing the confidence level does not reprocess reviews that were already attributed. Existing attributions will remain unchanged.

After selecting the desired confidence level, click Save. Crewhu Echo will apply the new setting to future reviews that arrive after the configuration is saved.

Note:
The selected confidence level applies individually to contact matching and employee matching. 

How Confidence Levels Work

Crewhu Echo analyzes different signals before automatically attributing a review. Based on those signals, Crewhu Echo classifies each possible match into an internal confidence level, using one of the following three options:

• High confidence (Conservative): strong signals indicate a reliable match.
• Medium confidence (Balanced): a relevant signal was found, but with less certainty.
• Low confidence (Aggressive): only a weak or ambiguous signal was found.

The more conservative the level, the more evidence Crewhu Echo requires before attributing a review. The more aggressive the level, the more flexible Crewhu Echo will be when creating automatic matches.

Conservative

With this level, Crewhu Echo only creates an automatic match when it finds strong matching signals. In practice, only matches classified internally as high confidence are applied automatically.

This level is recommended when accuracy is more important than match volume.

Examples of matches that may be applied at this level:

• A recent survey is associated with the review, and the employee name in the review comment confirms the same employee.
• A recent survey is associated with the review, even when no employee name is mentioned in the comment, as long as the temporal signal is strong.
• A recent survey is associated with the review, and the comment mentions a different active employee, allowing Echo to resolve the match with a high level of confidence.

Balanced

With this level, Crewhu Echo applies high confidence matches and medium confidence matches. This helps increase the number of automatic attributions while still keeping reasonable accuracy criteria.

This level is recommended when you want to capture more matches automatically while still avoiding highly ambiguous cases.

Examples of matches that may be applied at this level:

• All matches applied at the Conservative level.
• No recent survey is associated with the review, but the review comment mentions a unique active employee name in the database.

For example, if the review says “Davi was amazing” and there is only one active employee named Davi, Crewhu Echo may apply that match automatically with medium confidence.

Aggressive

With this level, Crewhu Echo applies high, medium, and low confidence matches. This maximizes the number of automatic matches, but it can also increase the risk of less precise attributions.

This level is recommended when the main goal is to capture the highest possible number of automatic attributions.

Examples of matches that may be applied at this level:

• All matches applied at the Conservative and Balanced levels.
• Cases where the system finds only a minimal matching signal.
• Cases where the name mentioned in the review may be ambiguous, such as when more than one active employee has the same name.

For example, if the review says “Lucas was great” but there are two active employees named Lucas, this is a weaker signal. With Aggressive, Crewhu Echo may consider this type of match to maximize automatic attribution volume.

Best Practices

If you are not sure which level to choose, start with Conservative. This gives your team the highest confidence in automatic attributions while you evaluate how well your account data supports automatic matching. 

After reviewing the results, you can move to Balanced or Aggressive if your team wants Crewhu Echo to capture more matches automatically.

Retroactive Auto-Match

The automatic match engine starts processing reviews from the moment automatching is enabled.

However, reviews received before the automation was turned on may still be unattributed. The Run Retroactive Auto-Match option lets Admins and Managers run the automatic match engine, helping older reviews get attributed to the correct contacts and employees.

Use this option when you want Crewhu Echo to review past unmatched Google reviews and apply automatic attribution based on your current match settings.

How to Run Retroactive Auto-Match

To run retroactive automatching, go to Echo > Settings.

The Run Retroactive Auto-Match button is available in the same area as the automatic employee and contact match settings.

Click Run Retroactive Auto-Match to run the process.

What Happens During Retroactive Auto-Match

When the retroactive process runs, Crewhu Echo checks eligible reviews and applies the automatic match engine to them.

The system uses the same automatching logic and matching sensitivity configured in your Echo settings.

This means the result depends on:

• Whether employee automatching is enabled.
• Whether contact automatching is enabled.
• The selected Match Confidence Level.
• The data available for each review, contact, company, and employee.

For example, if your match confidence level is set to Conservative, Crewhu Echo will only apply matches with stronger confidence. If it is set to Balanced or Aggressive, Crewhu Echo may apply matches using more flexible criteria.

Attention: If you have configured Echo to automatically recognize employees who receive reviews, the auto-match will send review badges to all matches it finds. If you do not want to do this retroactively, disable this option before running the auto-match, and re-enable it after the process has run.

Retroactive Auto-Match Results

After the process finishes, Crewhu Echo displays a results modal with a summary of what happened.

The modal shows:

• How many reviews were attributed during that execution.
• How many reviews already had previous attribution.

This gives you visibility into what the retroactive run changed and which reviews were skipped because they were already attributed.

Reprocessing Rules

You can run retroactive automatch more than once.

There are no restrictions on how many times the button can be used.

Crewhu Echo will not overwrite existing attributions. This applies to both:

• Manual attributions.
• Previous automatic attributions.

If a review already has an attribution, the retroactive process skips it and keeps the existing attribution unchanged.

Best Practices

If you are not sure which level to choose, start with Conservative.

This gives your team the highest confidence in automatic attributions while you evaluate how well your account data supports automatic matching.

After reviewing the results, you can move to Balanced or Aggressive if your team wants Crewhu Echo to capture more matches automatically.

Run Retroactive Auto-Match after enabling employee or contact automatching for the first time. This helps your team attribute older reviews that arrived before the automation was active.

Before running the retroactive process, review your Match Confidence Level setting. A stricter level gives you fewer but more reliable matches, while a more flexible level may capture more historical matches.