# Dario Zannoni

Dario Zannoni shares practical analysis of Google Ads and Meta Ads, including ecommerce campaigns, lead generation, conversion tracking, and ways to improve lead quality.

- Profile: https://b2binfluencer.marketing/creators/dario-zannoni/
- LinkedIn: https://www.linkedin.com/in/dariozannoni
- LinkedIn followers: 4,220
- Topics: artificial-intelligence, ecommerce, paid-ads, meta-ads, lead-generation, google-ads, conversion-tracking, performance-max
- Based on 15 dated posts, latest 2026-10-07

## Summary

Dario Zannoni is most useful for practical technical explainers on Google Ads and Meta Ads lead quality and conversion tracking.

- Best for: A B2B adtech company wanting practitioner content on lead-quality optimization for lead-generation marketers.
- Not for: Consumer-facing brand-awareness campaigns wanting paid partnerships, published rates, guaranteed audience, or disclosed terms.
- Check first: Confirm audience composition, engagement data, rates, and partnership terms before contacting them.

### Takeaways

- Meta performance goal may improve lead quality but reduce lead volume.
- Meta advertisers can share lead-quality updates through Google Sheets; a CRM connection is still useful.
- Google's AI image tools have limited product selection control, less useful for very large catalogs.

## Main ideas

- **Lead quality can improve without a CRM, but the tradeoff is lower volume**: Across several Meta lead-campaign posts, Dario Zannoni argues that advertisers do not need a CRM connection for the platform to optimize lead quality. Instant Form campaigns offer a 'Maximize number of conversion leads' performance goal, which they had assumed required CRM lead-scoring data; they say anyone can select it. The expected cost is volume: the system avoids cheaper, lower-quality conversions, so total leads likely fall. Later posts extend the same argument. A Google Sheets integration lets a sales team update each lead's status, and Meta reads those outcomes back into targeting. Meta's move from 'Conversion Leads' to 'Qualified Leads' introduces 'Sequenced Events', where the ad is credited only if an initial lead and a higher-value follow-up event both occur in order. A separate post describes a manual download option in the campaign results table, which they call fastest for immediate access but not a replacement for CRM integration or automatic export to Sheets. They point to Bram Van der Hallen's post on automatic collection as the better ongoing setup.
- **Read the documentation, test the setting, and say what is still unknown**: Dario Zannoni checks help pages and campaign interfaces, acknowledges earlier misunderstandings, and separates documented platform behaviour from their own assumptions. They often close by identifying what remains unclear, including whether a change is new behaviour or was simply undocumented before.
- **Extra conversion signals can help Smart Bidding, but only if the main goal stays clean**: Zannoni reports that Google help pages now say primary conversion actions not used for optimization may still enhance predictions and help a campaign ramp. Their practical argument: additional meaningful events can improve Smart Bidding, but the setup must not dilute or mislead the main goal. They list four conditions: keep only the final outcome as the account-level conversion goal; assign each extra action to the most semantically accurate conversion goal; set actions as primary because the system does not learn from secondary actions; and avoid the 'Other' category and custom conversions because they carry weak semantic meaning. Examples include adding Add to Cart or Begin Checkout alongside Purchase for ecommerce, and tracking Pricing or Contact Us page views for lead generation.
- **Campaign structure can cut out erratic placements**: Dario Zannoni argues that an underused Performance Max configuration—products feed plus Search dynamic ads only, excluding Video and Display—can make ecommerce spend more stable. They list four possible configurations for Shopping Performance Max and describe applying the feed-plus-Search setup to a campaign with erratic performance. Their argument: removing placements, not just adjusting bids, can address sudden spending peaks.
- **Convenience in tracking implementation is not the same as performance**: Zannoni explains that dynamic remarketing in Google Ads can now use ecommerce data from Google Analytics without setting dynamic events through the Google Ads tag. They list the requirements: working ecommerce tracking in Analytics, a linked account with personalized advertising enabled, and product IDs matching the feed. But they recommend the Google Ads tag where possible because its data is processed faster and covers more users. Their recurring point: an easier implementation route can carry a performance cost, and the tradeoff should be clear.
- **AI creative tools are not yet built for large catalogs**: Dario Zannoni tests two Google AI image features against a catalog of roughly 2,700 products and argues neither meets the needs of large ecommerce operations. Google Ads bulk image edits can enhance up to 100 images at once but cannot send edited images back to Merchant Center. Merchant Center's 'Generated for You' selects products automatically, which they see as its main weakness. Their argument is not that the tools are useless, but that automation without product-level selection leaves catalog teams doing manual work.
- **They send readers to other specialists**: One post, written in Japanese, recommends a session by Mike Ryan of Smarter Ecommerce on advanced Performance Max techniques for ecommerce. Zannoni describes Ryan as one of the people with outstanding insight into ecommerce PPC and Performance Max, and links to the session. They point readers to deeper specialist material when the topic calls for it, rather than treating their own posts as the final word.

## Work to read

- [Meta Instant Form Ads: changing the Performance Goal to improve lead quality without a CRM](https://www.linkedin.com/posts/dariozannoni_meta-instant-form-ads-change-performance-activity-7351189041029005312-KZL6)
- [Meta Instant Forms: sharing lead quality data with Meta through Google Sheets](https://www.linkedin.com/posts/dariozannoni_meta-instant-forms-new-option-to-share-lead-activity-7378367721585094658--sEO)
- [Meta's move from Conversion Leads to Qualified Leads and Sequenced Events](https://www.linkedin.com/posts/dariozannoni_meta-appears-to-be-changing-how-lead-campaigns-activity-7490198340958089216-34S-)
- [Google help pages now say non-biddable conversions can enhance predictions](https://www.linkedin.com/posts/dariozannoni_google-recently-updated-some-help-pages-activity-7460979874737082368-Emo9)
- [Meta Ads: downloading lead data from the campaign results table](https://www.linkedin.com/posts/dariozannoni_meta-ads-a-new-method-for-retrieving-lead-activity-7305883537751031808-InaW)
- [Google Pmax: Shopping plus Search (DSA) only campaigns](https://www.linkedin.com/posts/dariozannoni_google-pmax-shopping-search-dsa-only-activity-7259134658095820800-8U1C)
- [Two new Google AI features for bulk image editing—and where they fall short](https://www.linkedin.com/posts/dariozannoni_two-recent-google-ads-features-for-bulk-ai-activity-7348511328434606080-BA32)
- [Google Ads dynamic remarketing using Google Analytics ecommerce data](https://www.linkedin.com/posts/dariozannoni_google-ads-dynamic-remarketing-with-google-activity-7401443540171714563-hxSG)
- [A pointer to Mike Ryan of Smarter Ecommerce on advanced ecommerce Performance Max](https://x.com/DarioZannoni/status/1933529214994567298)

## Brand relationships

- **Google** (mention)
- **Meta** (mention)
- **Smarter Ecommerce GmbH (smec)** (mention)

## Partnerships

Dario Zannoni's posts offer no published sponsorship offer, media kit, rate card, or partnership inquiry route. Their technical commentary covers Google Ads and Meta Ads — ecommerce campaigns, lead quality, conversion signals — with no sponsored placements, partner tags, or disclosed brand collaborations. Brands would need to approach them directly to discuss a paid placement.

## Alternatives

- Sobia Irum: Choose Sobia Irum when the campaign needs the lead path built, not just analysed. This page needs practitioner content on lead-quality optimization, and the closest alternative work is a documented Fluent Forms to Clio Grow integration for law firms: a visitor submits a form, the data is validated and mapped by field, and the lead lands in the CRM as a contact or intake record without Zapier or manual entry. That is the intake half of lead quality: whether a form submission becomes a usable record or sits in an inbox. Irum also publishes on website accessibility to WCAG 2.2 AA, including audits, keyboard navigation, form and heading fixes, and contrast work. If the buyer task is 'make our lead capture and site usable enough that the leads we already pay for actually reach the sales team', this work is closer to that task than Zannoni's platform-side analysis.
- Aman jabeen: Choose Aman jabeen when the campaign shifts from B2B lead generation to ecommerce store quality and on-site conversion. The posts address the retail side of the same buyer decision. One walks through a Google Merchant Center score of 'Great', what sits behind it, and which weak signals, such as missing return information, slow mobile pages, thin product data, or unclear shipping, drag the store rating down. The other takes a makeup brand's dashboard—15,022 visitors, 992 orders, 626 new customers and over $60K net revenue—and asks what made those visitors trust the brand enough to buy, then lists the levers: swatches, shade guides, user content, reviews, product pages, checkout, retargeting. For a campaign about why paid traffic does not convert in a retail catalogue, that is direct material.
- Md Kamrul Islam Akash: Choose Md Kamrul Islam Akash when the buyer task is proving which campaign produced revenue and whether the tracking behind that claim still works. One post sets out the difference between traffic-source reporting, which answers where a click came from, and revenue attribution, which answers which campaign produced money. It uses a worked example of a $14.20 click that ends in a $3,500 contract 45 days later, and gives three checks: trace the conversion event back to a real business outcome, verify the attribution path across the actual customer timeline, and identify where the chain breaks. The other post is a conversion-tracking audit in steps, from defining the action and installing the tag to value tracking, test mode before launch, and a monthly check of the 'Frequently problematic tags' report, plus three failure modes such as tag manager changes silently destroying tags. For a brief about trusting the numbers before optimizing them, this is the closest fit among the three.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/