Evaluating Melissa vs ZeroBounce: Validation Accuracy, Result Transparency, and Performance 

When choosing an email validation service, businesses often balance three priorities: how accurately it confirms deliverable email addresses, the level of detail they can present about an email, and responsiveness of the service.

Both Melissa’s Global Email API and ZeroBounce’s Email Validation API offer strong capabilities in this space. However, they differ in how they present their results and in the overall scope of the information they provide.

Below are the functional differences between the two solutions, followed by findings from our study which compares how they each perform against real-world data.

Feature and Capability Comparison

Study: Testing Real-World Email Deliverability

We conducted a study evaluating how each Email Validation API performs in a trial of randomly selected email addresses.

The focus of the study is on identification of valid and deliverable addresses, differences in input handling, and the level of detail with which emails are profiled by each API.

Sample Selection

100k records were randomly selected from publicly available datasets intended for research use. A few constraints were used to ensure that the random sample contained a good mix of:

• Different types of corrections needed
  e.g., typos, poor syntax, invalid characters.
• Valid/Invalid addresses
  e.g. fake domains/mailboxes, domains without mail servers, and pre-verified emails.
• Special cases
  e.g. spamtraps, disposable domains, catch-all mail servers.

Though test cases were distributed among many domains, the record selection was naturally proportional to how often domains are actually queried; popular domains such as gmail.com, hotmail.com, yahoo.com, and icloud.com will have greater weight than others. This ensures the results are relevant to the most common use cases.

Disclaimer

These results are based on tests conducted in January 2026 using the production API versions available at that time. Since both APIs are updated intermittently, results should be viewed as time-specific observations, not permanent benchmarks.

Service Specific Categorization

For this comparison, we grouped Melissa and ZeroBounce’s results into 4 different categories: Deliverable, Undeliverable, Risky, and Unknown.

This is intended to simplify the interpretation of results, but it’s important to keep in mind that both APIs offer more granular results. The granular results for each category will be explored deeper where needed.

ZeroBounce
Results are classified based on two fields: Status and Substatus.

• Status defines the primary result and includes:
• Valid/Invalid
• Catch-all, Spamtrap, Abuse
• Do_Not_Mail
• Unknown
• Substatus provides more specific insight into why a particular Status was assigned.
  For example, an email marked Invalid may have a SubStatus of failed_syntax_check.

All results are boiled down to a single Status and SubStatus combination. ZeroBounce offers 7 primary Statuses, and 4 of them have SubStatuses associated with them (5-10 per Status).

Melissa
Results are classified based on two fields: Deliverability Confidence Score (DCS) and Result Codes.

• DCS is a numeric value between 0-100 which represents the likelihood of successful email delivery.
• Result Codes provide further context about the email address.
  For example, an email with a low DCS score may have result codes signifying it’s a role address (ES08) and a complainer (ES09).

Melissa offers 29 unique result codes that can be returned in varying combinations.

1. ZeroBounce definitions retrieved from: https://www.zerobounce.net/docs/email-validation-api-quickstart/#status_codes__v2__
2. Melissa definitions retrieved from: https://docs.melissa.com/cloud-api/global-email/result-codes.html#globalemail-resultcodesfull

Quantitative Results

Validation Results (Percentage of Emails In Result Set)

Service Speeds

Key Findings for ZeroBounce Address Validation API

Lack of Granular Results

ZeroBounce returns a single status and substatus per email. In contrast Melissa’s DCS (Deliverability Confidence Score) presents deliverability on a scale, allowing users to make decisions based on their risk-tolerance level.

Our test reveals a wide range of DCS values and result codes for emails with the same ZeroBounce designation.

Expanded Results

Valid Emails Marked Undeliverable Due to Syntax and Typos

Melissa standardizes/corrects syntax and domain misspellings before attempting a validation. This led to the identification of more deliverable addresses than ZeroBounce. While ZeroBounce does provide a corrected email address suggestion, a second validation request would need to be sent for it.

In our test, about 15% of all addresses ZeroBounce marked as Undeliverable were deemed deliverable by Global Email after Syntax or Domain Corrections.

Domain Correction: baliminimalist@uahoo.com → baliminimalist@yahoo.com

Expanded Results

Higher Rate of Unknowns

Melissa showed a slightly lower rate of “unknown” responses. However, Melissa showed a much higher likelihood to validate addresses that ZeroBounce marked unknown, compared to ZeroBounce validating emails that Melissa marked unknown.

Melissa was able to determine validity for roughly 70% of unknown emails from ZeroBounce, while ZeroBounce was able to determine validity for roughly 48% of unknown emails from Melissa.

Unknown from ZeroBounce: interruption@weaken.net

Expanded Results

Unknown from Melissa: ian@kutatownhouses.com

Expanded Results

Surface Level Catch-All Results

Catch-all addresses are notoriously difficult to validate because their mail servers are configured to claim deliverability regardless of a mailbox’s actual status. ZeroBounce marks such emails as catch-all but attempts no further validation. Melissa will attempt to predict the liveliness of such addresses by gauging historical patterns, activity signals, and other factors.

In our test Melissa marked roughly 65% of emails that ZeroBounce marked as catch-all/accept-all as being deliverable. In contrast, ZeroBounce marked about 7% of accept-all results from Melissa as deliverable.

Catch-all address: perdana@balioffice.com

Expanded Results

No Support for Mobile Email Identification

Mobile email addresses are heavily regulated by the FCC. Sending unauthorized messages to these emails can incur fines. Melissa detects such email addresses and marks them as undeliverable to protect against that.

In our test, ZeroBounce marked 57% of detected mobile emails as deliverable.

Mobile email address: johndoe@139.com

Expanded Results

Interpreting Conflicting Results

With both Melissa and ZeroBounce sporting high accuracy rates, disagreements can raise an important question: Which result reflects the truth?

Examples

While we can’t speak to ZeroBounce’s methodology, we can illustrate how Melissa determines validity. Below are two real-world examples where the services returned conflicting results, alongside the live SMTP responses returned by the destination mail server.

Example 1:

During verification, the recipient mail server returned: 550 5.1.1 recipient address rejected

A 550 5.1.1 response is a permanent failure, indicating that the mailbox does not exist on the domain. Because the receiving mail server explicitly states the recipient was rejected due to nonexistence, this address can be confidently classified as undeliverable.

Example 2:

During verification, the recipient mail server returned: 250 2.1.5 OK

A 250 2.1.5 response means that the mail server accepted the recipient address with no policy blocks or mailbox errors, indicating that the mailbox exists and is accepting mail.

Layers of Validation

It’s important to note that SMTP verification is just one component of Melissa’s validation process. Melissa combines protocol-level checks with domain analysis, mailbox behavior signals, risk heuristics, and reputation intelligence to form a comprehensive check.

SMTP provides direct insight from the receiving server, but it is interpreted within a broader validation framework to ensure consistent and defensible results.

Other Considerations

Another factor that can contribute to discrepancies is caching. Melissa continuously refreshes its validation cache to ensure results remain current while minimizing unnecessary repeat checks.

Other services, including ZeroBounce, may also use caching, though their refresh and retention approaches are not publicly documented.

Summary

This study compared ZeroBounce’s Email Validation API and Melissa’s Global Email API using a large set of real-world email addresses to evaluate deliverability results, result depth, and service responsiveness.

Both solutions demonstrated strong core validation capabilities and reliably identified clearly invalid or deliverable addresses.

• ZeroBounce performed well in flagging high-risk and restricted emails through its straightforward status and substatus framework, which makes it easy to interpret results at a glance. Beyond core validation, the platform also offers a broad spectrum of supporting tools including email activity data, scoring insights, list evaluation, blacklist monitoring, and more. Together, these capabilities help support an ecosystem for managing email quality and risk deliverability.
  
  
• Melissa’s Global Email distinguished itself by providing greater transparency and flexibility in how deliverability is represented. Through its Deliverability Confidence Score and expansive set of result codes, Melissa enables users to assess email addresses along a spectrum of risk rather than relying on a single categorical outcome. This approach proved especially valuable for handling catch-all domains, and cases where mail servers returned limited or ambiguous responses.

Overall, both ZeroBounce and Melissa deliver reliable email validation performance. ZeroBounce offers a simple and direct classification model suitable for organizations with low risk-tolerance and broad classification needs. Melissa provides a more nuanced and risk-reward centric framework suitable for organizations that want greater visibility and control over how deliverability decisions are made.