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To improve Google Ads recommendations, fix the data foundation before accepting more automated suggestions: select the conversions that represent the real business outcome, connect website, app, CRM and offline sources, send accurate events and transaction values, add consent-aware first-party customer signals, and check diagnostics. Once those signals are reliable, consider value-based bidding and audience features. Optimization score and recommendations can help prioritize account changes, but neither proves incremental profit by itself.
What “data strength” means in Google Ads
Google Ads can only recommend settings and optimize bids from the information it receives. “Stronger” data is not simply a larger number of events. It is data that is connected to the correct account, represents the intended customer outcome, includes meaningful values when value matters, and is collected in a way that respects consent.
Google’s Data Strength Best Practices guidance describes a sequence rather than a single switch:
| Stage | What to do | Why it matters |
|---|---|---|
| Connect | Implement sitewide Google tagging; link relevant Analytics and Google Ads accounts; connect CRM and other offline sources through Data Manager or the API; connect app data through the appropriate Analytics/Firebase setup. | Recommendations need a joined view of interactions and outcomes rather than isolated events. |
| Improve signals | Send accurate conversion events, transaction values, consent signals and suitable first-party customer data, including enhanced conversions where applicable. | More relevant, correctly formatted signals help Google match interactions to outcomes and distinguish high- and low-value results. |
| Activate | After validation, consider Maximize conversion value, Target ROAS, customer-acquisition or retention goals, first-party audiences, Customer Match and Performance Max. | Automated bidding and audience features should optimize against trustworthy goals, not incomplete or arbitrary data. |
| Measure | Use conversion and campaign diagnostics, eligible consent-impact reporting, experiments and, where appropriate, Meridian for marketing-mix analysis. | Measurement tests whether changes help the business instead of treating a platform score as proof of causal growth. |
Step 1: Make conversion goals and values match the business
Choose the outcome you actually want to buy
Start by listing the outcomes that should influence bidding: for example, a completed purchase, a qualified sign-up or a subscription. Then check each Google Ads conversion action’s definition, event firing and inclusion in optimization. Google’s optimization-score documentation says advertisers can control the performance objective through strategies such as Maximize conversions, Maximize conversion value, Target CPA, Target ROAS and Target impression share, and can choose which conversions are included for optimization. If a campaign is optimizing toward an unqualified form fill while the business values a completed sale, adding more events will make the recommendation engine more confident in the wrong direction.
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Use values that represent economic differences
When orders, leads or subscriptions have different economic outcomes, pass transaction values that reflect what the business wants to optimize. Google connects transaction signals with ROAS and profit and recommends considering value-based Smart Bidding only after those signals are available. A value should not be an arbitrary number inserted merely to unlock a bidding option. Document how each value is calculated, whether it is revenue or profit, and which currency and region it represents so reporting remains interpretable.
Check the goal before changing the bid strategy
- Confirm the conversion action fires once for the intended event and does not count page reloads or duplicate tags.
- Confirm the campaign’s selected conversion goals are the actions the business can fulfill and value.
- Confirm values are present when the chosen strategy depends on value.
- Keep the current strategy until event quality and volume are validated; changing bidding and tracking simultaneously makes diagnosis harder.
Step 2: Connect every relevant data source
Website conversions
Use a sitewide Google tag foundation, then define conversion events for meaningful actions such as purchases, sign-ups and subscriptions. Link the relevant Google Analytics property and Google Ads account so event definitions and reporting are consistent. Verify that the conversion event is sent on the success action, not merely when a user opens a form or reaches an intermediate page.
CRM and offline outcomes
A website lead may not become valuable until a sales team closes it. Connect the CRM or another offline source through Data Manager or the Google Ads API, and import the later conversion with its value. Matching requires a stable identifier captured at lead creation and preserved through the sales process. Reconcile imported counts and values with the CRM so an accepted import means the same thing in both systems.
Apps and cross-channel journeys
For app conversions, Google’s data-strength guidance mentions the Google Analytics for Firebase SDK. Link the relevant Analytics and Google Ads properties, define app events consistently, and add CRM or offline sources when the customer journey continues outside the app. An app install, an in-app purchase and a later subscription are different outcomes; do not collapse them into one event unless they truly share the same business value.
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| Customer journey | What to send or connect | What to verify |
|---|---|---|
| Online purchase or website conversion | Sitewide tags, the conversion event and suitable user-provided data for enhanced conversions. | Correct conversion action, event firing, received-data diagnostics and consent behavior. |
| Website lead that later becomes an offline sale | Lead-capture data plus an imported offline conversion event and value. | Lead-to-sale matching, import receipt, conversion value and goal settings. |
| App or cross-channel journey | Relevant Analytics/Firebase and Google Ads connections, plus CRM or offline sources where applicable. | Linked properties, event definitions, account goals and reporting continuity. |
These paths are alternatives based on where the actual conversion occurs. A web purchase does not need the same implementation as a lead that closes weeks later, and neither should be evaluated with app-install goals.
Step 3: Add enhanced conversions correctly
Choose the appropriate implementation
Google describes enhanced conversions as supplementing existing conversion tracking with hashed first-party customer data. The web path uses user-provided information from a website conversion to improve measurement of online events. The leads path pairs user-provided website data with imported offline lead conversions, such as a later sale. Enhanced conversions supplement an existing conversion action; they are not a replacement for defining and firing that action.
Prepare the data before transmission
Google’s Enhanced Conversions Best Practices technical guidance calls for consistent normalization before hashing:
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Follow Google’s customer-data policies and the consent requirements that apply to your jurisdiction. Correct normalization and hashing improve matching mechanics, but they do not decide whether your collection or use is lawful.
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Use meaningful events and preserve identifiers
Prioritize purchases, qualified sign-ups and subscriptions over low-intent interactions. For lead enhanced conversions, preserve the lead identifier or matching data from the form through the CRM and the eventual offline import. If the identifier is lost, an otherwise valid sale may not be attributed to the original ad interaction.
Read enhanced-conversion diagnostics
After deployment, check the relevant enhanced-conversions diagnostics. A “Good” state can mean the setup is active while additional user data could still improve matching. “Needs attention” indicates an issue requiring review. These labels describe implementation status, not a guarantee of improved return on ad spend.
Step 4: Implement Consent Mode without promising a universal uplift
Consent Mode adjusts Google tag behavior according to each user’s consent status and can enable conversion modeling to fill eligible measurement gaps. The implementation must pass the relevant consent signals to the tags; it should not silently treat an unknown choice as consent.
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- Map each consent state in your consent-management platform to the Google tag behavior required for your regions.
- Test both consent-granted and consent-denied journeys.
- Check that tags receive the intended state before the conversion event fires.
- Review impact reporting only for eligible domain-and-country combinations and within the stated reporting window.
Step 5: Validate data before enabling value-based automation
Use a staged validation checklist
- Trigger a test conversion in the website or app and confirm the event appears in the expected property.
- Verify that the Google Ads conversion action receives the event once, with the intended value and currency.
- For leads, confirm the offline import is received and matched to the correct original lead.
- Review enhanced-conversion diagnostics for received data and implementation errors.
- Test consent-denied and consent-granted paths and record the resulting tag behavior.
- Compare Google Ads totals and values with the source system over a defined period, allowing for normal reporting delays and modeled conversions.
Use campaign diagnostics to find account-level problems
Campaign diagnostics checks more than 90 signals across campaign components. It can surface issues involving business data, goals and conversion tracking. Treat it as a fault-finding view: investigate the specific signal, correct the underlying implementation and then watch whether the conversion data becomes more coherent.
Step 6: Activate bidding and audience features in the right order
When Maximize conversion value or Target ROAS makes sense
Consider Maximize conversion value or Target ROAS after transaction values are consistently received and represent the economic outcome you care about. If values are missing, delayed, duplicated or arbitrary, a value-based strategy can optimize toward measurement artifacts. Start with a target that reflects observed performance and change one major variable at a time so you can distinguish tracking effects from bidding effects.
Customer acquisition, retention and first-party audiences
Google’s data-strength guidance also describes customer-acquisition and retention goals, first-party audiences, Customer Match and Performance Max. These are options, not universal recommendations. Use them only when the audience definition, consent basis, exclusion logic and business goal are clear. For example, a retention objective needs a reliable definition of existing customers; otherwise acquisition and retention signals can be mixed.
Do not activate every feature at once
A practical rollout is to stabilize conversion tracking first, add enhanced conversions and consent signals, validate imported outcomes, then introduce one bidding or audience change. This gives the account enough time to reveal whether a recommendation addresses a real data gap or merely changes settings.
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How to use optimization score and recommendations without being misled
What the score measures
Google describes optimization score on a 0–100% scale. It is calculated in real time from account and campaign statistics, settings, available recommendations, their estimated impact and recent recommendation history. The score can change when settings, ecosystem trends or available recommendations change. Google also states that optimization score is not used by Quality Score; the two are separate diagnostics. A higher percentage means the account aligns with more of Google’s suggested settings, not that profit or incremental conversions have been proven.
Prioritize guided recommendations by category
Guided recommendations organizes suggestions around account setup, serving issues, growth and optimization, and Google AI. The interface surfaces up to three recommendations per category based on impact, while the full recommendations view can contain others. For each suggestion:
- Read which campaign, conversion action or setting it changes.
- Check whether the recommendation’s objective matches the business goal and selected conversions.
- Estimate operational and measurement risk, including budget, brand, consent and data-quality effects.
- Apply it only when the prerequisite data is present, or dismiss it with a documented reason.
- Measure the business outcome with an appropriate comparison rather than relying on the score change.
Measure incrementality separately
Google’s data-strength guidance points to experiments for incrementality measurement and Meridian, its open-source marketing-mix model, for budget optimization. Use an experiment or another defensible comparison when you need to estimate causal lift. An optimization-score increase, more modeled conversions or a recommendation marked “applied” does not establish that the campaign generated additional profit.
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Online purchase
- Define the purchase conversion and decide whether value means revenue, margin or another business measure.
- Install and test sitewide tagging, then fire the purchase event after the confirmed transaction.
- Enable the web enhanced-conversions path with normalized, consent-appropriate customer data.
- Check event count, value, currency, consent state and enhanced-conversion diagnostics.
- Only after stable data is visible, evaluate Maximize conversion value or Target ROAS.
Lead-to-sale business
- Define the website lead event separately from the later qualified or closed outcome.
- Capture the permitted first-party data and a durable matching identifier at form submission.
- Send the lead through the CRM without changing the identifier.
- Import the offline sale and its value through Data Manager or the Google Ads API.
- Confirm matching, import receipt and campaign goal inclusion before changing bidding.
App or cross-channel journey
- Link the relevant Analytics/Firebase and Google Ads properties.
- Define app events that distinguish installs, meaningful engagement and purchases.
- Connect CRM or offline outcomes when the customer completes the journey elsewhere.
- Check event definitions, linked properties, consent behavior and reporting continuity.
- Use audience or value-based features only after the cross-channel outcome is measurable.
Troubleshooting common data-strength failures
| Symptom | Likely area to inspect | Corrective action |
|---|---|---|
| Recommendations focus on low-quality leads | Conversion goals or included actions | Change optimization to the qualified outcome and verify the goal is included for the affected campaigns. |
| Value-based bidding has little useful differentiation | Missing, delayed or arbitrary values | Repair transaction-value logic and wait for validated values before relying on value-based bidding. |
| Enhanced conversions show “Needs attention” | Field formatting, tag implementation or policy/consent handling | Review normalization, hashing, event firing and consent behavior, then recheck diagnostics. |
| Offline conversions are not appearing | CRM identifier, import configuration or event definition | Trace one lead from capture to import, confirm the identifier and value, and verify the import receipt. |
| Consent impact results are absent | Thresholds, domain-country eligibility, reporting window or implementation | Check eligibility and timing, test consent signals and avoid interpreting missing reporting as a performance result. |
| Optimization score falls after an account change | Real-time recommendation inventory or settings | Review the specific recommendation and setting; do not reverse a sound business decision solely to restore the percentage. |
A practical rollout sequence
Use this order when several parts of an account need work:
- Inventory: list campaigns, conversion actions, included goals, values, data sources and consent requirements.
- Correct: remove duplicate or misleading events, fix values and align goals with the intended business outcome.
- Connect: implement sitewide tagging, link Analytics and Google Ads, and connect CRM, offline or app sources.
- Enrich: deploy the appropriate enhanced-conversions path and pass consent signals.
- Validate: use event checks, enhanced-conversion diagnostics, offline-import checks and campaign diagnostics.
- Activate: introduce value-based bidding or audience features only when their required signals are stable.
- Measure: assess business outcomes with experiments or other incrementality methods, not optimization score alone.
Google’s interface labels, eligibility rules and feature behavior can change. Verify the current account screens and policy requirements before giving a production implementation to a client or deploying code.
What stronger data can—and cannot—do
Accurate, connected data gives Google Ads a better basis for matching ad interactions to the outcomes you selected and for distinguishing outcomes by value. It can make recommendations more relevant to the account’s configuration and give automated bidding more useful signals. It does not guarantee lower costs, higher profit or a particular conversion lift. Results depend on the customer journey, data volume, consent, event quality, business economics and the strategy chosen.
The safest standard is therefore operational: a recommendation is worth considering when it addresses a verified account problem, fits the intended goal and can be evaluated with outcome-based measurement. A recommendation that raises the score but weakens data quality, consent compliance or business alignment should not be accepted.
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