Sherlock Calls
for Google Ads + PostgreSQL
Google Ads runs your paid search and display campaigns across Google's network. PostgreSQL stores your application's core operational data and business records. When you need to investigate across both, the evidence is split between two dashboards neither of which knows the other exists. Sherlock Calls bridges them — no code, no exports, no manual joins. Ask once from Slack and get a sourced answer in under 5 seconds.
TL;DR — What beta users get access to
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Sherlock Calls connects to Google Ads, PostgreSQL simultaneously — read-only, no code changes, no webhooks — and lets you query both with a single Slack message.
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Ask questions that neither Google Ads nor PostgreSQL can answer alone. Google Ads shows ad conversions — not which campaigns actually drove calls and won deals. PostgreSQL holds every business record your app has ever created — but turning that into an answer requires a developer to write the query. Sherlock deduces the complete picture from both.
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No dashboard switching, no manual joins, no fog of uncertainty — ask in Slack and receive a sourced answer with evidence from every connected provider in under 5 seconds. The game is afoot.
<5s
Answer to any ad campaigns + database query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use Google Ads + PostgreSQL without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
PostgreSQL campaign performance is optimised without Google Ads LTV and retention data
PostgreSQL reports cost per acquisition and on-site conversion. Google Ads holds the product usage, subscription state, and retention data that reveals whether those conversions became valuable customers. True ROAS lives across both — and is rarely computed.
Your most valuable Google Ads customer segments are never activated in PostgreSQL
Google Ads holds the product usage patterns and behavioural signals that define your highest-LTV customers. PostgreSQL has the targeting tools to find more of them. But the signal from Google Ads never reaches PostgreSQL campaign audiences without a deliberate bridge.
PostgreSQL re-engagement campaigns reach the wrong Google Ads segments
PostgreSQL re-targets based on on-site behaviour. Google Ads holds the operational data that would identify which inactive customers are actually worth re-engaging — and which have already churned. Without the Google Ads filter, PostgreSQL spend is wasted on unwinnable segments.
Cross-Provider Questions
What teams ask Sherlock about Google Ads + PostgreSQL
Questions that would take hours to answer manually — answered in under 5 seconds from Slack.
- SC“Which PostgreSQL customer segments — by product usage data — produce the best Google Ads campaign ROAS?”
- SC“Show me Google Ads campaign clicks from customers with the highest PostgreSQL retention signals”
- SC“Find Google Ads ad audiences that overlap with PostgreSQL high-value customer cohorts”
- SC“Which Google Ads campaigns produce customers whose PostgreSQL application behaviour signals long-term retention?”
- SC“What's the PostgreSQL usage difference between customers acquired via different Google Ads channels?”
Beta Setup
Connect Google Ads + PostgreSQL to Sherlock in 2 minutes
No code, no webhooks, no new dashboards. Beta users get direct onboarding support.
- 1
Connect Google Ads
Add your Google Ads credentials to Sherlock Calls. Read-only access — no code changes, no webhooks, no Google Ads configuration required.
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Connect PostgreSQL
Add your PostgreSQL credentials. Sherlock indexes all relational tables, business records, operational data, and application state automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined Google Ads + PostgreSQL stack in Slack. Sherlock queries all connected platforms in parallel, correlates the evidence, and returns a sourced answer in under 5 seconds.
FAQ
Common questions about Sherlock + Google Ads + PostgreSQL
How does Sherlock Calls connect Google Ads and PostgreSQL data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries Google Ads, PostgreSQL in parallel, correlates the results by timestamp and shared identifiers, and produces a single sourced answer — the same way a good detective correlates evidence from multiple witnesses.
Do I need to set up any data pipelines between Google Ads and PostgreSQL?
- No. Sherlock Calls is entirely pull-based — it queries both APIs on demand when you ask a question. There are no webhooks, no ETL pipelines, no data warehouses, and no code changes required in any of the connected platforms.
What kinds of questions can I ask about my Google Ads + PostgreSQL stack?
- You can investigate anything that spans both platforms — ROAS, cost per conversion, and impression share, table row counts and query latency, cross-platform costs, handoff patterns, and performance comparisons. Sherlock translates your plain-English question into the right API calls and returns the deduced answer.
Is my Google Ads and PostgreSQL data stored by Sherlock?
- No. Sherlock Calls queries your data in real time and returns results directly to Slack — nothing is stored, indexed, or replicated in any Sherlock database. All data remains in Google Ads and PostgreSQL and is accessed only during an active investigation.
How long does it take to set up the Google Ads + PostgreSQL integration?
- Elementary — typically under 5 minutes total. Connect each platform with read-only credentials, install the Sherlock Calls Slack app, and ask your first question. No engineering, no dashboards, no onboarding calls required.
Apply for early access to Sherlock + Google Ads + PostgreSQL
We're accepting a select group of beta users to shape the Google Ads + PostgreSQL combination. Tell us about your stack and we'll reach out personally if you're a fit.
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