A Guide to Using Make.com with Google Ads

Google Ads is excellent at measuring what happens before and during an initial online conversion. It can report impressions, clicks, keyword performance, form submissions, telephone enquiries and cost per lead.

However, the most important business activity frequently happens elsewhere.

A prospect might submit a quotation request, receive an automatically calculated price, enter a follow-up sequence, speak to a salesperson and accept an offer several days later. Unless this information is returned to Google Ads, the platform only knows that a lead was generated. It does not know whether that lead was valuable.

This creates a significant optimisation problem.

Google Ads may favour a campaign generating £20 leads over another generating £45 leads, even when the more expensive leads produce substantially more customers and revenue. It is optimising around cost per lead because that is the deepest outcome it can see.

Make.com can help close this gap by connecting Google Ads with your CRM, forms, quoting tools, databases, spreadsheets, accounting systems and other operational software.

Instead of ending the measurement process at “form submitted”, Make can help maintain a continuous data trail:

Ad click → lead → quotation → follow-up → accepted offer → sales revenue

The commercially meaningful stages can then be returned to Google Ads as offline conversions or enhanced conversions for leads. This gives Google’s reporting and bidding systems a clearer picture of which campaigns, adverts and keywords generate actual business results.

What Is Make.com?

Make.com is a visual automation platform that transfers data and initiates actions between different applications.

An automation in Make is called a scenario. A scenario normally contains:

• A trigger that starts the automation

• One or more actions

• Filters that determine which records continue

• Routers that create different paths

• Data transformation steps

• Error-handling and retry logic

• A scenario history showing what happened during each execution

For example, a scenario could start when an opportunity reaches “Offer Accepted” in a CRM. Make could retrieve the associated contact, locate the original Google click identifier, retrieve the final sales value and send the conversion to Google Ads.

Make is especially useful when the CRM or sales platform does not have a suitable native Google Ads integration. It acts as the orchestration layer between otherwise disconnected systems.

However, Make should not automatically replace a reliable native integration. If a CRM already provides a maintained, consent-aware and properly supported connection for Google Ads offline conversions, that may be simpler and more robust. Make becomes most valuable when the required systems, fields or business rules extend beyond the capabilities of the native connection.

 Why Google Ads Needs Sales Data

A standard lead-generation campaign commonly measures:

• Form submissions

• Telephone calls

• Appointment requests

• Live-chat enquiries

• Downloads

• Email clicks

These are useful marketing signals, but they are not necessarily commercial outcomes.

A form submission may be:

• Outside the service area

• Looking for a service the company does not provide

• An existing customer

• A job applicant

• Spam

• Impossible to contact

• Unable to afford the service

• A genuinely valuable opportunity

If every enquiry is reported as an equally valuable conversion, Google Ads receives an incomplete description of success.

The objective is not to stop measuring initial leads. It is to extend the measurement framework with deeper outcomes such as:

• Quote calculated

• Quote sent

• Qualified lead

• Appointment attended

• Offer accepted

• Customer acquired

• Sales revenue received

This produces a hierarchy of conversion value rather than one undifferentiated lead total.

How Make.com Creates a Closed-Loop Data Flow

A closed-loop system connects advertising costs with lead, sales and revenue data.

Make can help coordinate the flow in both directions.

From Google Ads and the website into the CRM:

• Campaign and traffic-source data

• UTM parameters

• Google Click ID

• Keyword or search-term context where available

• Campaign ID

• Ad group ID

• Advert or creative ID

• Landing page

• Initial conversion date

• Lead contact details

• Consent status

From the CRM back to Google Ads:

• Lead qualification

• Quotation milestones

• Accepted offers

• Customer acquisition

• Conversion date and time

• Sales value

• Currency

• Transaction or order identifier

• Consent signals

• Hashed first-party customer data where appropriate

The purpose is to create an unbroken relationship between the advertising click and the eventual commercial result.

Capture Attribution Before Building the Automation

The most sophisticated Make scenario cannot recover attribution data that was never captured.

When somebody clicks a Google advert, the landing-page URL may include a Google Click ID such as a GCLID. Depending on the environment and privacy controls, Google may instead use identifiers such as GBRAID or WBRAID.

Google recommends including the GCLID where possible, even when enhanced conversions for leads are being used. Its current API documentation also supports user-provided identifiers such as normalised and hashed email addresses and telephone numbers. Google Ads offline conversion documentation

The website, form or CRM should preserve as much of the following as possible:

• GCLID

• GBRAID

• WBRAID

• UTM source

• UTM medium

• UTM campaign

• UTM content

• UTM term

• Campaign ID

• Ad group ID

• Advert ID

• Landing-page URL

• First attribution

• Latest attribution

• Contact creation time

• Marketing consent

• Ad user-data consent

These values should be stored against the contact or lead record, rather than being left only in an analytics session.

First Attribution and Latest Attribution

First attribution identifies how the contact was originally acquired. Latest attribution identifies the most recent tracked marketing interaction.

Both are useful, but they answer different questions.

First attribution can be used to understand customer acquisition. Latest attribution can be used to understand what brought an existing contact back into the sales process.

Replacing the first-touch data whenever someone returns to the website destroys part of the historical record. A better design keeps first and latest attribution in separate fields.

A Practical Sales Pipeline for Google Ads

The pipeline should reflect how the business actually generates revenue. It should not be created purely to satisfy an advertising platform.

Consider the following example:

Not every pipeline movement needs to become a Google Ads conversion.

Automatic Follow-Up and Manual Follow-Up describe internal sales activity. They do not necessarily indicate that the lead has become more valuable. Sending every operational stage to Google Ads can create unnecessary conversion actions and may confuse bidding.

The strongest conversion framework normally concentrates on genuine increases in commercial intent or value.

Scenario One: Send New Leads to the CRM

The first Make scenario can collect a lead from a form, webhook or lead-management system and create or update the corresponding CRM contact.

A simplified scenario might be:

1. Receive the form submission through a webhook.

2. Search the CRM for an existing contact.

3. Create a new record or update the existing one.

4. Store the contact details.

5. Store GCLID and other click identifiers.

6. Save UTM and campaign fields.

7. Create an opportunity in the New Lead stage.

8. assign an owner.

9. Start the speed-to-lead workflow.

10. Record the Make execution ID for troubleshooting.

The search-before-create step is important. Without it, a returning prospect may create several contact and opportunity records, fragmenting the attribution and sales history.

A robust matching hierarchy might use:

1. CRM contact ID

2. Email address

3. Normalised telephone number

4. External form submission ID

The scenario should also retain the original attribution when updating an existing contact unless there is a deliberate reason to overwrite it.

Scenario Two: Calculate the Quote

Make can be used to calculate a quotation when the pricing logic depends on form answers, products, quantities or service characteristics.

For example, a property-service quotation might consider:

• Property type

• Number of bedrooms

• Visit frequency

• Conservatory

• Extension

• Access requirements

• Location

• Optional services

• Minimum charge

• VAT

The scenario could receive the enquiry, validate the required fields and apply the appropriate pricing logic.

The result can then be written back to the CRM using fields such as:

• Four-weekly quote

• Eight-weekly quote

• One-off quote

• Optional-service value

• Total quote

• Quote calculation status

• Manual quote required

• Calculation version

Once a valid figure has been calculated, Make can move the opportunity from New Lead to Quote Calculated.

If the property or service is too unusual for automatic pricing, the scenario should route it to Manual Quote Required instead of inventing a value.

This is an important automation principle: uncertainty should create an exception for human review, not an unreliable result.

Scenario Three: Deliver the Quote

Once the quotation has been calculated, Make can assemble the information needed by the chosen communication system.

Depending on the connected applications, this might include:

• Creating a quotation document

• Creating a PDF

• Sending quote data to the CRM

• Updating an email template

• Sending an SMS or WhatsApp message

• Creating a payment link

• Assigning a salesperson

• Moving the opportunity to Quote Sent

• Recording the exact time the quote was delivered

The CRM or communication platform should normally remain responsible for the customer-facing communication where it has suitable native capabilities. Make can prepare and transfer the information without unnecessarily duplicating the entire messaging system.

The Quote Sent stage can then be returned to Google Ads if it represents a sufficiently valuable and consistently defined milestone.

Scenario Four: Automate Follow-Up

Most leads do not convert after one message. A structured follow-up process improves the probability of making contact while giving the sales team visibility over what has already happened.

An automatic sequence might include:

• Immediate acknowledgement

• Quotation confirmation

• A reminder after several hours

• A second reminder after one day

• A frequently asked questions message

• A task for the salesperson

• Escalation to manual follow-up

• Removal from the sequence when the prospect replies

Make can start, stop or route these processes based on events in the CRM.

For example:

1. Quote Sent starts the automatic follow-up.

2. A customer reply removes the contact from scheduled reminders.

3. No reply after the defined period moves the opportunity to Manual Follow-Up.

4. Make creates a salesperson task.

5. An accepted offer stops all outstanding sales reminders.

6. A declined offer moves the opportunity to Closed Lost.

The CRM should remain the operational source of truth. Make should coordinate applications, not create a second hidden pipeline that employees cannot see.

 Speed to Lead

Speed to lead describes how quickly a business responds after an enquiry is received.

When a high-intent prospect submits a form, waiting several hours gives them time to contact competitors. Make can reduce this delay by orchestrating several actions immediately:

• Create or update the CRM contact

• Assign the correct salesperson

• Send an acknowledgement

• Calculate an initial quotation

• Notify the salesperson

• Create a telephone task

• Start an SMS or WhatsApp conversation

• Escalate enquiries that have not been contacted

• Alert a manager when service-level targets are missed

Speed should not come at the cost of accuracy. A fast message containing an incorrect price or irrelevant information may damage trust.

The objective is to combine immediate acknowledgement with reliable data validation and sensible exception handling.

Send Pipeline Stages to Google Ads

Once the pipeline is working reliably, Make can trigger a Google Ads upload when an opportunity reaches a selected stage.

A conversion upload normally needs information such as:

• Google Ads customer account

• Conversion action

• GCLID, GBRAID or WBRAID where available

• Conversion date and time

• Conversion value

• Currency

• Order or transaction ID

• Consent status

• Normalised and hashed user data for enhanced conversions for leads

Google strongly recommends enhanced conversions for leads for modern offline measurement. These combine click identifiers with first-party lead data such as hashed email addresses and telephone numbers to improve matching and measurement durability. Google’s enhanced offline conversion guidance

An Important 2026 Implementation Change

New implementations should not blindly copy older tutorials based on a legacy “Upload a Click Conversion” module.

Google states that from 15 June 2026, UploadClickConversion requests can fail when the associated developer token had not previously been used for offline or enhanced conversion uploads. Google directs affected new implementations towards the Data Manager API. Google Ads API change notice

Make currently provides Google Ads campaign-management modules and an authorised “Make an API Call” action, but the correct technical route will depend on the account, developer-token history and conversion architecture. Make Google Ads Campaign Management documentation

For a new setup, confirm the supported upload route before building the complete scenario. Do not assume that a legacy Make template will remain suitable simply because it still appears in an old tutorial or account.

Recommended Google Ads Conversion Actions

A possible conversion structure is:

Lead Submitted

Triggered when a legitimate new enquiry is created.

This can remain a useful primary or secondary conversion for campaign visibility, but it should not be the only signal used to assess performance.

Qualified Lead

Triggered when the information has been validated and a quote can be calculated.

This is usually a stronger bidding signal than a raw form submission because obvious spam, duplicates and unsuitable enquiries have been removed.

Quote Sent

Triggered when a valid quotation has been delivered.

This may be valuable when a quote is only sent to commercially realistic opportunities. If quotes are generated for almost every enquiry, it may add limited information beyond Qualified Lead.

Sales Revenue

Triggered when the offer is accepted or the sale is confirmed.

This should include the actual value where possible. Sending a real conversion value allows Google Ads to distinguish between customers of different commercial importance.

The definitions must remain stable. If “Qualified Lead” means one thing this month and something different next month, reporting and bidding comparisons become unreliable.

Send Revenue Back to Google Ads

Returning revenue is the final step in closed-loop measurement.

The Offer Accepted event should ideally include:

• Final agreed sales value

• Currency

• Conversion date

• Unique transaction ID

• Original attribution identifiers

• Contact identifiers

• Consent data

If the original quotation changes, Make can use the final accepted value rather than the first estimated value.

For recurring services, the business must decide which value best reflects the commercial outcome:

• First payment

• Annual contract value

• Expected first-year revenue

• Gross profit

• Predicted lifetime value

The correct choice depends on the bidding strategy and the reliability of the financial data.

Do not send lifetime value merely because it produces a larger number. The value should represent a consistently calculated commercial measure that the business is prepared to optimise around.

Google supports conversion value and currency in offline uploads. It also strongly recommends an order or transaction ID because this helps with deduplication and future conversion adjustments. Google Ads conversion upload fields

Compare Advertising Cost with Sales Revenue

Sending revenue to Google Ads improves optimisation, but the CRM or reporting database should also retain enough information for independent analysis.

A closed-loop report could compare:

• Google Ads spend

• Clicks

• Initial leads

• Qualified leads

• Quotes

• Accepted offers

• Revenue

• Cost per lead

• Cost per qualified lead

• Cost per accepted offer

• Lead-to-sale rate

• Revenue per lead

• Return on advertising spend

• Gross-profit return on advertising spend

These metrics can be reviewed by:

• Campaign

• Ad group

• Keyword

• Landing page

• Device

• Location

• Lead source

• Service

• Salesperson

• First attribution

• Latest attribution

This reveals the difference between cheap leads and profitable leads.

A campaign with the lowest cost per enquiry is not necessarily the best campaign. The more commercially relevant questions are:

• Which campaign produces qualified leads?

• Which keywords produce accepted offers?

• Which service generates the highest revenue?

• Which campaigns produce customers quickly?

• Which campaigns produce leads that require extensive manual follow-up?

• Which advertising costs result in profitable revenue?

Keep UTM Data Against the Contact Record

UTM parameters should be visible against individual contacts, not only inside analytics reports.

A salesperson reviewing a contact should be able to see information such as:

• Source: Google

• Medium: CPC

• Campaign: Window Cleaning Kent

• Ad group: Exact Window Cleaning

• Keyword: window cleaner near me

• Landing page: /window-cleaning-kent

• GCLID: captured

• First attribution date

• Latest attribution date

• Opportunity value

• Accepted revenue

This helps marketing and sales teams work from the same evidence.

It also improves troubleshooting. If a conversion fails to reach Google Ads, an administrator can inspect the contact and confirm whether the click identifier, conversion time, value and consent data were present.

Google Ads Campaign Management with Make

Make can also support selected campaign-management and reporting tasks.

Its Google Ads Campaign Management integration includes modules for campaigns, ad groups, keywords, negative-keyword lists, account data and authorised API calls. Make Google Ads Campaign Management

Potential uses include:

• Daily performance reporting

• Budget alerts

• Disapproved advert notifications

• Keyword-status monitoring

• Negative-keyword administration

• Campaign-status checks

• Automated stakeholder summaries

• Writing reviewed data into a spreadsheet or database

• Alerting when cost rises without corresponding CRM outcomes

However, automated campaign changes require strong controls.

A scenario should not automatically increase budgets, change bids or pause important campaigns based on a small amount of data. Safeguards should include:

• Minimum conversion volume

• A defined comparison period

• Maximum permitted change

• Human approval

• Logging

• Rollback instructions

• Exclusion of brand campaigns

• Protection for learning periods

• Notification of every material change

Make is an automation platform, not a substitute for advertising strategy.

Sharing CRM Audiences with Google Ads

Make can also help prepare or synchronise CRM data for Google Ads Customer Match.

Google calls these Customer Match lists rather than Custom Audiences. They can be built from first-party customer data such as email addresses, telephone numbers and postal information.

Possible audience groups include:

• Existing customers

• Qualified leads

• Quote recipients

• Accepted offers

• Lost opportunities

• High-value customers

• Customers approaching renewal

• Previous customers

• Contacts who have not responded

• Customers interested in a particular service

These audiences can support:

• Customer exclusions

• Customer retention

• Cross-selling

• Re-engagement

• Observation and reporting

• Audience signals

• New-customer acquisition strategies

Make could update a database or file used by Google Ads, or orchestrate an approved API-based Customer Match workflow.

Google recommends using the Data Manager API for new Customer Match API workflows. It also states that Customer Match lists have a maximum membership duration of 540 days and recommends regularly refreshing them. Google Customer Match guidance

Google Ads does not use Meta’s “Lookalike Audience” terminology. Google phased out Similar Audiences as a standalone targeting method. Customer Match data can still contribute to audience signals, optimised targeting and automated bidding, but the mechanism should not be described as a conventional Facebook-style lookalike list.

Consent, Privacy and Data Governance

Offline conversion and audience automation involves first-party customer data. It must be designed around consent and data minimisation.

The implementation should define:

• Which data is collected

• Why it is collected

• Where consent is recorded

• Whether advertising personalisation is permitted

• Whether ad user data may be shared

• How long identifiers are retained

• Who can access the Make scenario

• Which applications receive the data

• How deletion requests are processed

• How failed or rejected records are handled

Google’s enhanced-conversion documentation requires sensitive customer information such as email addresses and telephone numbers to be normalised and hashed using SHA-256 before upload. Consent information is also highly recommended because missing consent signals may prevent attribution. Google Ads data formatting requirements

Hashing is not a replacement for consent. It is a security and matching measure applied after the business has established an appropriate basis for processing the data.

Avoid Duplicate Conversions

Duplicate conversion uploads can distort revenue, conversion counts and automated bidding.

A Make scenario should create a unique event key using information such as:

• Contact ID

• Opportunity ID

• Conversion-action name

• Pipeline stage

• Stage-entry timestamp

• Transaction ID

Before uploading the event, Make can check a data store, database or CRM field to determine whether it has already been sent.

After a successful upload, record:

• Upload status

• Upload date

• Conversion action

• Conversion value

• External transaction ID

• Make execution ID

• Google Ads response

• Error message if applicable

The scenario should not mark the event as successful merely because it attempted the request. It should only do so after receiving and validating the appropriate response.

Error Handling and Monitoring

A production scenario should expect occasional failures.

Possible problems include:

• Missing GCLID

• Missing customer identifiers

• Incorrect conversion action

• Invalid account connection

• Mismatched customer account

• Incorrect date format

• Missing timezone

• Expired authorisation

• Revoked consent

• Duplicate transaction ID

• API version changes

• Rate limits

• CRM field changes

• Opportunity updated before the contact record is ready

A robust implementation should include:

• Automatic retries for temporary failures

• An error queue

• Notifications for persistent failures

• A reconciliation report

• A manual replay process

• Scenario version control

• Test and production conversion actions

• Regular upload-health reviews

Google provides conversion diagnostics and recommends using upload job identifiers to help review imported data. Conversions may also take time to appear and are normally reported against the date of the original advertising interaction rather than simply the upload date.

A Recommended Make.com Architecture

A modular design is easier to test and maintain than one enormous scenario.

A practical structure could include:

Scenario 1: Lead Capture and Attribution

Capture the lead, preserve click identifiers and UTM data, deduplicate the contact and create the opportunity.

Scenario 2: Quote Calculation

Validate the enquiry, calculate the quotation and route exceptions for manual review.

Scenario 3: Quote Delivery

Prepare the quotation, update the CRM and initiate the appropriate communications.

Scenario 4: Lead Nurture

Coordinate automatic reminders, detect replies and escalate unresponsive leads to manual follow-up.

Scenario 5: Offline Conversion Upload

Listen for meaningful pipeline-stage changes and send the corresponding conversion to Google Ads.

Scenario 6: Revenue Upload

Send accepted-offer or confirmed-sale revenue with a unique transaction ID.

Scenario 7: Audience Synchronisation

Maintain compliant Customer Match groups, exclusions and customer segments.

Scenario 8: Reconciliation and Alerts

Compare CRM events with Google Ads uploads, identify missing attribution and alert administrators to errors.

This structure keeps each scenario focused. It also reduces the risk that a failure in quotation generation prevents an unrelated conversion or reporting process from running.

When Make.com Is the Right Choice

Make is a strong option when:

• The CRM does not have a suitable native Google Ads connection

• Several applications contribute to the sales process

• Quotation logic is held outside the CRM

• Custom field mapping is required

• Advanced routing or transformation is needed

• Revenue comes from an accounting or payment system

• Audience data needs to be assembled from several sources

• The business needs detailed monitoring and exception handling

• The workflow must accommodate unusual business rules

Make may not be the best option when:

• The CRM already provides a reliable native integration

• The business cannot reliably capture attribution identifiers

• Pipeline stages are not consistently maintained

• Consent data is unavailable

• Sales values are inaccurate

• Nobody is responsible for monitoring failures

• The process changes constantly without documentation

Automation amplifies the quality of the underlying system. If the CRM data is inaccurate, Make will transfer that inaccuracy more efficiently.

Final Thoughts

Connecting Make.com with Google Ads is not simply about moving data between two applications. It is about redesigning the measurement system around commercial outcomes.

The most valuable implementation creates a continuous relationship between:

• The advert that generated the click

• The keyword and campaign responsible

• The contact created in the CRM

• The quotation produced

• The follow-up activity

• The accepted offer

• The revenue generated

This allows the business to move beyond cost-per-lead reporting and begin measuring cost per qualified lead, cost per accepted offer, revenue per lead and return on advertising spend.

Make provides the orchestration layer, but successful closed-loop marketing still depends on disciplined CRM architecture, reliable attribution capture, meaningful pipeline stages, privacy controls and careful Google Ads conversion configuration.

When these elements work together, Google Ads no longer has to optimise around whichever leads are cheapest. It can receive evidence about which advertising activity produces qualified opportunities, accepted offers and revenue—the outcomes that actually matter to the business.