Deliverability Issues?

davidh_braze

Hi there,

I have an email campaign that has the following metrics in email performance section:

Unique Recipients: XX,XXX
Sends: XX,XXX (same as above)
Deliveries: 90.79% (XX,XXX)
Bounces: 0.08% (XX)
Spam Reports: 0.01% (X)

The Deliveries tooltip suggests this number and the rate are "sends minus bounces".

However, my bounces are very low. There is certainly a gap of data that's not being accounted for.

Is it likely that the reality is that the Bounce volume being presented is too low and actually there are lots, or could it be that the deliveries volume is higher?

Is there a place in the dashboard where more detailed bounce information is available?

Ideally I'd like to see a breakdown into hard/soft bounces and ideally a breakdown into domains and failure reasons.

Thanks

David

Nirnay

Hi @davidh_braze ,

Great question - this is a common point of confusion, and you’re right to flag the gap you’re seeing.

What’s going on with Deliveries vs Bounces

The Bounce metric shown in the campaign/canvas performance view represents hard bounces only. Soft bounces are not included in that number, which is why:

• Deliveries = Sends − Hard Bounces
• Soft bounces can be substantial, but they don’t reduce the Delivery count shown in the UI

This explains why your hard bounce rate looks very low, while the delivery rate still appears meaningfully lower than 100%.

How I validated this

To confirm, I tested this directly using segmentation:

• I created a segment with:
  • Last received email with tag in last 2 days AND
  • Hard bounced in last 2 days
• The resulting user count matched the hard bounce count shown on the campaign/canvas metrics exactly.

I then ran the same test using:

• Soft bounced more than 0 times in last 2 days AND
  
• Last received email with tag in last 2 days 

That segment was significantly larger and did not match what’s shown in the dashboard — which aligns with soft bounces not being surfaced in campaign-level bounce metrics.

Where to find more detailed bounce data

If you’re looking for a deeper breakdown (hard vs soft bounces, domains, failure patterns, etc.), the best place is Analytics → Query Builder, using the shared Snowflake tables.

Below is an example query that pulls:

• Hard and soft bounces
• Sends and deliveries
• Opens, clicks, unsubscribes, and spam reports
• broken down by email domain over the last 30 days (you can adjust the date window as needed).

This should give you the level of visibility you’re looking for, including hard vs soft bounces and domain-level patterns.

-- Email bounces and sends per domain

WITH hard_bounces AS (
    SELECT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_BOUNCE_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
soft_bounces AS (
    SELECT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_SOFTBOUNCE_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
sends AS (
    SELECT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_SEND_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
delivered AS (
    SELECT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_DELIVERY_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
unique_opens AS (
    SELECT DISTINCT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_OPEN_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
unique_clicks AS (
    SELECT DISTINCT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_CLICK_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
unique_unsubscribes AS (
    SELECT DISTINCT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_UNSUBSCRIBE_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
mark_as_spam AS (
    SELECT DISTINCT email_address,
           RIGHT(email_address, LENGTH(email_address) - charindex('@', email_address)) AS domain
    FROM USERS_MESSAGES_EMAIL_MARKASSPAM_SHARED
    WHERE date_trunc('day', to_timestamp_ntz(time)) >= dateadd('day', -30, date_trunc('day', CURRENT_DATE()))
),
total_bounces AS (
    SELECT * FROM hard_bounces
    UNION ALL
    SELECT * FROM soft_bounces
),
hard_bounce_counts AS (
    SELECT domain, COUNT(*) AS bounces
    FROM hard_bounces
    GROUP BY domain
),
soft_bounce_counts AS (
    SELECT domain, COUNT(*) AS bounces
    FROM soft_bounces
    GROUP BY domain
),
total_bounce_counts AS (
    SELECT domain, COUNT(*) AS bounces
    FROM total_bounces
    GROUP BY domain
),
send_counts AS (
    SELECT domain, COUNT(*) AS sends
    FROM sends
    GROUP BY domain
),
delivered_counts AS (
    SELECT domain, COUNT(*) AS delivered
    FROM delivered
    GROUP BY domain
),
unique_opens_counts AS (
    SELECT domain, COUNT(*) AS unique_opens
    FROM unique_opens
    GROUP BY domain
),
unique_clicks_counts AS (
    SELECT domain, COUNT(*) AS unique_clicks
    FROM unique_clicks
    GROUP BY domain
),
unique_unsubscribes_counts AS (
    SELECT domain, COUNT(*) AS unique_unsubscribes
    FROM unique_unsubscribes
    GROUP BY domain
),
mark_as_spam_counts AS (
    SELECT domain, COUNT(*) AS mark_as_spam
    FROM mark_as_spam
    GROUP BY domain
)

SELECT total_bounce_counts.domain,
       total_bounce_counts.bounces AS total_bounces,
       COALESCE(hard_bounce_counts.bounces, 0) AS hard_bounces,
       COALESCE(soft_bounce_counts.bounces, 0) AS soft_bounces,
       COALESCE(send_counts.sends, 0) AS sends,
       COALESCE(delivered_counts.delivered, 0) AS delivered,
       COALESCE(unique_opens_counts.unique_opens, 0) AS unique_opens,
       COALESCE(unique_clicks_counts.unique_clicks, 0) AS unique_clicks,
       COALESCE(unique_unsubscribes_counts.unique_unsubscribes, 0) AS unique_unsubscribes,
       COALESCE(mark_as_spam_counts.mark_as_spam, 0) AS mark_as_spam
FROM total_bounce_counts
LEFT JOIN hard_bounce_counts ON total_bounce_counts.domain = hard_bounce_counts.domain
LEFT JOIN soft_bounce_counts ON total_bounce_counts.domain = soft_bounce_counts.domain
LEFT JOIN send_counts ON total_bounce_counts.domain = send_counts.domain
LEFT JOIN delivered_counts ON total_bounce_counts.domain = delivered_counts.domain
LEFT JOIN unique_opens_counts ON total_bounce_counts.domain = unique_opens_counts.domain
LEFT JOIN unique_clicks_counts ON total_bounce_counts.domain = unique_clicks_counts.domain
LEFT JOIN unique_unsubscribes_counts ON total_bounce_counts.domain = unique_unsubscribes_counts.domain
LEFT JOIN mark_as_spam_counts ON total_bounce_counts.domain = mark_as_spam_counts.domain
WHERE total_bounce_counts.domain IS NOT NULL
ORDER BY total_bounces DESC
LIMIT 100;

Thanks! 
Hope this helps!