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We've been running a marketing campaign called Hospital Partnership, how is it performing so far?

Analyzed for 35s

First, let me find information about how this campaign is performing, then I'll compare it to other campaigns.

Query:

lookup-hospital-partnership-performance

Query:

compare-hospital-partnership-to-recent-campaigns

Hospital Partnership Campaign Analysis


Overall the campaign delivered 91 tracked sign-ups in the last 60 days. Activation into the product is concentrated in a small, fast-adopting subset while the cohort as a whole shows a long tail of delayed or no activity. Conversion to free trial is 30.8% and conversion to paid is 24.2%. This campaign performed favorably compared to other recent campaigns (details below).


High-level performance


  • Total cohort: 91 users acquired via the Hospital Partnership campaign

  • Conversion to free trial: 30.8% (28 / 91)

  • Conversion to paid user: 24.2% (22 / 91)


Comparison to other campaigns


Sample of recent campaigns during the same time frame:


  • Clinical Pilot: 115 sign-ups; free trial conversion 22%; paid conversion 15%

  • Trade Show: 78 sign-ups; free trial conversion 18%; paid conversion 12%

  • Partner Referral: 62 sign-ups; free trial conversion 25%; paid conversion 16%


Hospital Partnership outperforms recent campaigns on paid conversion rate and time-to-value. It converts a larger share of signups into paying users and does so faster.

View explanation

Ask Indent anything..

We've been running a marketing campaign called Hospital Partnership, how is it performing so far?

Analyzed for 35s

First, let me find information about how this campaign is performing, then I'll compare it to other campaigns.

Query:

lookup-hospital-partnership-performance

Query:

compare-hospital-partnership-to-recent-campaigns

Hospital Partnership Campaign Analysis


Overall the campaign delivered 91 tracked sign-ups in the last 60 days. Activation into the product is concentrated in a small, fast-adopting subset while the cohort as a whole shows a long tail of delayed or no activity. Conversion to free trial is 30.8% and conversion to paid is 24.2%. This campaign performed favorably compared to other recent campaigns (details below).


High-level performance


  • Total cohort: 91 users acquired via the Hospital Partnership campaign

  • Conversion to free trial: 30.8% (28 / 91)

  • Conversion to paid user: 24.2% (22 / 91)


Comparison to other campaigns


Sample of recent campaigns during the same time frame:


  • Clinical Pilot: 115 sign-ups; free trial conversion 22%; paid conversion 15%

  • Trade Show: 78 sign-ups; free trial conversion 18%; paid conversion 12%

  • Partner Referral: 62 sign-ups; free trial conversion 25%; paid conversion 16%


Hospital Partnership outperforms recent campaigns on paid conversion rate and time-to-value. It converts a larger share of signups into paying users and does so faster.

View explanation

Ask Indent anything..

We've been running a marketing campaign called Hospital Partnership, how is it performing so far?

Analyzed for 35s

First, let me find information about how this campaign is performing, then I'll compare it to other campaigns.

Query:

lookup-hospital-partnership-performance

Query:

compare-hospital-partnership-to-recent-campaigns

Hospital Partnership Campaign Analysis


Overall the campaign delivered 91 tracked sign-ups in the last 60 days. Activation into the product is concentrated in a small, fast-adopting subset while the cohort as a whole shows a long tail of delayed or no activity. Conversion to free trial is 30.8% and conversion to paid is 24.2%. This campaign performed favorably compared to other recent campaigns (details below).


High-level performance


  • Total cohort: 91 users acquired via the Hospital Partnership campaign

  • Conversion to free trial: 30.8% (28 / 91)

  • Conversion to paid user: 24.2% (22 / 91)

View explanation

Ask Indent anything..

Answers without waiting for the data team

Ask a question in plain English and Indent goes to work—giving you the answer right away.

A

How many users signed up in Japan from our Facebook campaign last week, and how were the signups distributed throughout the week?

Indent handles complex questions. Just like a good colleague, Indent will clarify your intent and break large questions into manageable pieces.

Analyzing...

Referenced 12 observations related to users and marketing

Read:

users

Read:

analytics.marketing

I'll help you analyze the signup data from last week's Facebook campaign in Japan. Let me query the users table and examine the daily distribution.

Query:

overall-signups

Query:

japan-facebook-signups

Reasoning...

Indent shows every step of its work. See exactly how Indent got to its answer, so you can audit and trust the final output.

342 users signed up last week in Japan from the Facebook campaign.


The signups were distributed throughout the week, with the earliest on October 6th and the latest on October 12th. The data is current through October 15th, so this count is complete for the requested period.

342 users signed up last week in Japan from the Facebook campaign.


The signups were distributed throughout the week, with the earliest on October 6th and the latest on October 12th. The data is current through October 15th, so this count is complete for the requested period.

View explanation

View explanation

I queried the users table filtering by created_at between October 6th, 2025 and October 12th, 2025. I filtered for users from Japan (country = 'JP') and acquisition source as Facebook (utm_source = 'facebook'). Following standard practice for user metrics, I excluded bot users (bot_user = false OR NULL) and the Indent internal organization (organization_id != 3) as specified in the observations.


I verified data recency with a second query which confirmed that user signup data is current through October 15th, 2025, ensuring the last week count is complete and accurate.

I queried the users table filtering by created_at between October 6th, 2025 and October 12th, 2025. I filtered for users from Japan (country = 'JP') and acquisition source as Facebook (utm_source = 'facebook'). Following standard practice for user metrics, I excluded bot users (bot_user = false OR NULL) and the Indent internal organization (organization_id != 3) as specified in the observations.


I verified data recency with a second query which confirmed that user signup data is current through October 15th, 2025, ensuring the last week count is complete and accurate.

Indent's answers are thorough. Indent uses multiple queries, visualizations, and explanations to give you a complete picture.

Integrates with dashboards and codebases

Indent understands your entire data stack. Context from dashboards and codebases allow Indent to improve answer quality beyond what's possible with tables alone.

While working on a question, Indent references your dbt lineage, checks your Airflow logs, and validates against your BI definitions. This context is the difference between a guess and an answer.

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chris

Today at 10:42 AM

@Indent

who should I reach out to before their trial ends this week?

1 reply

Indent

APP

Today at 4:48 AM

27 trials ending this week. Here's your priority list:

Hot leads (high product engagement):

  • founders@acme-data.com - connected 4 communication channels, ran 89 insight queries, flagged 12 upsell opportunities in their customer data

  • team@buildco.io - 3 users active daily, analyzing 2,400+ customer messages/day, already found $340k in hidden pipeline

  • ceo@growthventures.com - integrated Slack + Intercom, discovered 7 churn risks in first 48 hours, actively sharing with exec team

See more

I queried

user_trials

high_intent

product_events

joined with

to find all trials ending

this week. The result shows 27 accounts with varying engagement levels.

The

queries, meaning these users are actively extracting value and match

flag indicates accounts with 3+ integrations and 40+

See more

View chat here.

Request review

Also send to 

chat-analytics

Reply…

chris

Today at 10:42 AM

@Indent

who should I reach out to before their trial ends this week?

1 reply

Indent

APP

Today at 4:48 AM

27 trials ending this week. Here's your priority list:

Hot leads (high product engagement):

  • founders@acme-data.com - connected 4 communication channels, ran 89 insight queries, flagged 12 upsell opportunities in their customer data

  • team@buildco.io - 3 users active daily, analyzing 2,400+ customer messages/day, already found $340k in hidden pipeline

  • ceo@growthventures.com - integrated Slack + Intercom, discovered 7 churn risks in first 48 hours, actively sharing with exec team

See more

I queried

user_trials

high_intent

product_events

joined with

to find all trials ending

this week. The result shows 27 accounts with varying engagement levels.

The

queries, meaning these users are actively extracting value and match

flag indicates accounts with 3+ integrations and 40+

See more

View chat here.

Request review

Also send to 

chat-analytics

Reply…

Indent never forgets a thing.

Just like onboarding a new colleague, you'll teach Indent a thing or two about what makes your data unique. The difference is, you never need to tell Indent twice.

2 new observations

2 new observations

Review now

Review now

Analysis complete!


Key findings for users signed up in the last 2 months:

Conversion Rates:

• 30.8% of users created their first chat (28 out of 91 users)

• 24.2% of users reached code generation (22 out of 91 users)


Time to First Chat:

• Average: 78.2 hours (3.3 days)

• Median: 1.6 hours (much faster than the average, some users start immediately while others take much longer)


Time to First Code Generation:

• Average: 108.7 hours (4.5 days)

• Median: 21.6 hours (0.9 days)


The visualizations show the distribution patterns and user journey stages. Most users (69%) haven't created any chats yet, while about 7% created chats but haven't generated code. The timing distributions are right-skewed, with medians much lower than averages, indicating many users engage quickly while others take significantly longer.

Analysis complete!


Key findings for users signed up in the last 2 months:

Conversion Rates:

• 30.8% of users created their first chat (28 out of 91 users)

• 24.2% of users reached code generation (22 out of 91 users)


Time to First Chat:

• Average: 78.2 hours (3.3 days)

• Median: 1.6 hours (much faster than the average, some users start immediately while others take much longer)


Time to First Code Generation:

• Average: 108.7 hours (4.5 days)

• Median: 21.6 hours (0.9 days)


The visualizations show the distribution patterns and user journey stages. Most users (69%) haven't created any chats yet, while about 7% created chats but haven't generated code. The timing distributions are right-skewed, with medians much lower than averages, indicating many users engage quickly while others take significantly longer.

Indent is constantly improving itself. Every time Indent comes across new information, it proposes updates to its knowledge base for you to review.

"Premium signups"

"Premium signups"

"Premium signups"

users.tier = 'premium'

users.tier = 'premium'

users.tier = 'premium'

"Conversion rates"

"Conversion rates"

"Conversion rates"

SUM(paid_users) / SUM(trial_users)

SUM(paid_users) / SUM(trial_users)

SUM(paid_users) / SUM(trial_users)

Indent learns to speak like you. Indent will adapt to concepts like the steps of your onboarding funnel so you can talk to it as naturally as a teammate.

Analysis complete!


Key findings for users signed up in the last 2 months:

Conversion Rates:

• 30.8% of users created their first chat (28 out of 91 users)

• 24.2% of users reached code generation (22 out of 91 users)


Time to First Chat:

• Average: 78.2 hours (3.3 days)

• Median: 1.6 hours (much faster than the average, some users start immediately while others take much longer)


Time to First Code Generation:

• Average: 108.7 hours (4.5 days)

• Median: 21.6 hours (0.9 days)


The visualizations show the distribution patterns and user journey stages. Most users (69%) haven't created any chats yet, while about 7% created chats but haven't generated code. The timing distributions are right-skewed, with medians much lower than averages, indicating many users engage quickly while others take significantly longer.

Analysis complete!


Key findings for users signed up in the last 2 months:

Conversion Rates:

• 30.8% of users created their first chat (28 out of 91 users)

• 24.2% of users reached code generation (22 out of 91 users)


Time to First Chat:

• Average: 78.2 hours (3.3 days)

• Median: 1.6 hours (much faster than the average, some users start immediately while others take much longer)


Time to First Code Generation:

• Average: 108.7 hours (4.5 days)

• Median: 21.6 hours (0.9 days)


The visualizations show the distribution patterns and user journey stages. Most users (69%) haven't created any chats yet, while about 7% created chats but haven't generated code. The timing distributions are right-skewed, with medians much lower than averages, indicating many users engage quickly while others take significantly longer.

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We're Hiring

Privacy policy

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X.com

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