Giorgio Gnoli builds and implements CRM, data-integration, and marketing-automation systems. Gnoli's LinkedIn posts show hands-on work connecting customer data and creating practical sales and marketing workflows, including WhatsApp and SMS automation.
Giorgio Gnoli is most useful for hands-on CRM, data integration, and marketing automation implementation pilots.
Best for
B2B SaaS or CRM consultancy needing a scoped implementation pilot, not a broad media buy.
Not for
Consumer brand wanting paid LinkedIn sponsorship or broad creator-style awareness campaign with fixed media package.
Key takeaways
They reconciled 105,169 automotive dealer records into 98,146 unique customers.
They link records only when identifiers provide enough certainty and set CRM rules.
Their SMS system included opt-out and duplicate-send checks, plus a disclosed logging bug.
Check first: Confirm system access, consent-compliant data, named commercial use case, and measurable pilot outcome.
Main ideas
Companies should buy working revenue flows, not another tool · Build from your own operating needs first · Clean customer data and write the rules before automating
Giorgio Gnoli’s LinkedIn posts feature practical CRM, data-integration and marketing-automation systems.
The work ranges from reconciling an automotive dealer’s customer records and defining CRM rules to automating appointments through WhatsApp and building SMS and email campaigns.
They explain the mechanics with concrete examples, figures and operating rules, making their posts useful to readers who want to understand how business data and marketing workflows fit together—not just which tools to buy.
Gnoli connects implementation detail to the business process it is meant to improve.
In the automotive CRM example, they describe matching customer records only when identifiers provide enough certainty and setting explicit rules for leads and sales opportunities.
In messaging examples, they pair automation with safeguards and tracking: their SMS system included opt-out and duplicate-send checks, and they disclosed a logging bug that had undermined its daily limit.
They also share limits rather than presenting every result as a win: the early win-back campaign had a 2% reply rate, which they called low, and they described the CRM rebuild as unfinished.
Readers can follow their work for grounded examples of CRM design, data quality and automation in practice.
Giorgio Gnoli argues that CRM, messaging and outbound matter only when built into a working revenue process.
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They start with messy operational data and explicit commercial rules, build low-cost infrastructure the company controls, and measure flows by bookings, replies and pipeline.
They test ideas in the studio and show detailed build logs.
AI is central as a builder and auditor, but they also describe it as a source of unease.
They quote practitioners and conference speakers separately, not as claims of their own.
Companies should buy working revenue flows, not another tool
Gnoli argues that WhatsApp and CRM are useful only as revenue levers, not standalone products.
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A tool leaves the operator to invent the use case; a tested flow changes a business number. They say their own tool grew from their needs as a demanding user and propose a 30-day go-live with monthly optimised use cases.
Gnoli lists automatic appointment check-ins to reduce no-shows, review requests for credibility, and “bring a friend” referral flows for low-cost acquisition. In one post, they say up to 40% of cold contacts completed a booking through WhatsApp Flows.
Gnoli starts with a problem they live with, not a product category.
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They built a CRM around their personal WhatsApp, extended it to SMS, automated part of their own studio's appointments, and created a win-back sequence whose working file they published. Testing on their own operation, they argue, produces validated use cases and public numbers.
The SMS system came after the WhatsApp CRM.
Gnoli loaded 837 consented numbers from the address book and set a 100-message daily cap.
The win-back sequence targeted about 2,000 dormant customers.
Clean customer data and write the rules before automating
In an automotive CRM case, Gnoli argues the foundation is secured data, standard CRM objects, certain matching and explicit business rules—not a dashboard.
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They reconcile records only when a tax code, VAT number, or email or phone plus name match is certain. Leads convert only with a quote; leads on existing customers become campaigns; deals without a win after 60 days are treated as lost.
Gnoli turns 105,169 records into 98,146 unique customers, makes 2,371 automatic links, maps 682 fields, and ties vehicles and workshop spending to customer lifetime value.
Gnoli argues for building on infrastructure the company controls instead of paying gateway or agency fees.
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The SMS example uses an eSIM connected to a self-built Lovable app, at a reported €0.002 per message; the win-back sequence runs on MailerLite, Claude Code and a cheap sending domain.
They say the asset remains with the company.
That ownership argument fits custom builds more than the subscription product they also sell.
More than 3,000 SMS a month run with duplicate, opt-out and reply filters, A/B testing and a live dashboard. The win-back build costs about €25 for MailerLite, €100 for Claude Code, €3 for verification and €12 for a domain.
The same cost-control logic underpins Lead Scraper, sold as a €17 starter plan and a €99 done-for-you service—a productized option alongside bespoke integration.
Outbound is a system, and pipeline gives the founder freedom
Gnoli treats lead generation as a sequence: build pipeline and a fallback alternative, then an offer that solves a category pain, followed by scraping, copy, sending, A/B tracking and CRM.
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Without pipeline, they argue, a founder takes any deal and cannot negotiate. They also argue for separating judgement from execution as tools such as Salesforce's Apollo agent and Hunter absorb more of the execution.
An agency test with about €15 of setup produced 13 positive replies in a week. For accountants, Gnoli suggests an AI app that catalogues PEC messages and updates clients on tax rules as an irresistible offer.
Gnoli uses AI to build and audit: Claude Code and Lovable inside workflows, AI to read replies and prepare reports, and AI to generate a management-system audit.
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They argue this speeds up solo delivery and can reveal hidden problems. They also describe a shift from wonder to anxiety after AI produced 100 graphs in seven minutes, about 70% of which they judged relevant, while the studio grew 12% year on year but had underlying problems.
The audit took seven minutes and produced more than 100 charts and practical recommendations. Gnoli offered readers the working file and video access.
Gnoli says their own reaction shifted from amazement to anxiety over a year.
A channel only works if the company can operate the CRM behind it
Gnoli uses quoted practitioners to argue that adoption depends on support and operational competence, not channel hype.
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They quote a Meta country leader at NetComm saying Italy is one of the top countries for WhatsApp adoption and citing interaction rates of 98% for WhatsApp, 50% for email and 60% for SMS.
The same speaker says the company must be good at CRM and that agentic use will be the focus over the next 18 months.
Separately, they quote a CRM manager at a B2B company on Salesforce and Google saying commercial teams need support—almost a carer for salespeople—to manage work more fluidly.
The two quotes come from different posts: the Meta speaker supplies the channel-adoption numbers, while the CRM manager describes the daily support gap inside a sales team.
This is the strongest starting point for judging technical depth.
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It shows whether Giorgio Gnoli can handle messy, multi-source CRM data and turn it into a usable customer view, not just talk about automation.
The post walks through a CRM and data-integration project for an automotive dealer.
Giorgio Gnoli describes extracting data from Qlik, a dealer management system and other portals, then building a customer 360 on Salesforce standard objects.
The reconciliation example is concrete: 105,169 records become 98,146 unique customers, with 2,371 automatic links made only where a tax code, VAT number, or email/phone plus name match is certain.
The post also sets business rules: a lead becomes a customer record only with a quote, leads on existing customers become campaigns, and deals are treated as lost after 60 days without a win.
The final console maps 682 fields and links vehicles, workshops and customer lifetime value.
For brands planning a campaign
A CRM consultancy could use this as the anchor for a paid discovery: audit source systems, reconcile customer records, define conversion and deal rules, then build a 360 view. The record counts and matching rules give a practical scope for a pilot rather than a generic “CRM cleanup” proposal.
This shows how Giorgio Gnoli turns a messaging channel into a working mini-application, with a stated booking outcome.
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A newcomer can see the implementation and the service-business problem being solved.
The post explains WhatsApp Flows as mini-applications inside messages.
Giorgio Gnoli says the feature was used to automate appointment follow-up, with up to 40% of cold contacts completing a booking.
The post lists practical uses: bookings, lead-generation forms, order handling, feedback surveys and account access.
It also describes the build path: WhatsApp Manager inside Meta Business, a drag-and-drop or JSON-based flow builder, text fields and date pickers, and webhooks that send collected data to a CRM or database.
For brands planning a campaign
For a service-business pilot, scope one appointment or reactivation flow with consent, webhook delivery into the CRM, and a booking-rate baseline. This is a contained automation project with measurable outcomes such as fewer no-shows or more completed bookings.
This shows how Giorgio Gnoli approaches owned infrastructure and cost control.
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It helps assess whether the work is a one-off script or an operating system with safeguards, reporting and fixes.
The post describes sending more than 3,000 SMS per month through an API connected to a phone with an eSIM and a self-built Lovable app.
Giorgio Gnoli lists 837 contacts loaded with marketing consent, a 100-messages-per-day limit, safeguards against duplicate sends and opt-outs, AI-based reply recognition, A/B testing and SIM selection.
The dashboard shows sent, replied, cancelled and queued messages, with a per-message history and a campaign stop button.
The post also notes a fixed bug where messages were sent but not logged, so the daily limit was not actually working.
For brands planning a campaign
This fits a pilot where messaging volume and cost matter and WhatsApp is constrained.
Scope consent verification, daily caps, suppression rules, reply handling and a live dashboard.
The logging bug gives a partner a concrete evaluation point: can they show that limits and records are enforced, not just that messages go out?
This shows the campaign structure behind the tooling: segmentation, a multi-step journey, testing and CRM follow-up.
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It shows what a practical reactivation project looks like when Giorgio Gnoli builds it.
The post describes a win-back sequence for dormant customers, built in about two hours.
It includes segmentation, A/B testing, email warm-up, a five-email journey with different paths, daily reporting on sends, click-through and unsubscribes, and reply tracking that feeds reactivation into the CRM.
The target was around 2,000 customers not contacted for a long time.
After one day, two people replied and one new appointment was booked, a 2% reply rate that Giorgio Gnoli calls low.
The stated costs are €25 for MailerLite, €100 for Claude Code, €3 for Million Verifier, €12 for a Hostinger sending domain, plus four or five working hours.
For brands planning a campaign
A reactivation pilot could use the same structure: segment dormant accounts, run a short email journey, and track replies and CRM reactivation. The stated cost base makes comparison with agency quotes easy; the 2% early reply rate is a baseline to improve on, not a promised result.
This is the clearest view of a packaged offer rather than a bespoke build.
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It helps a B2B SaaS or agency reader judge whether Giorgio Gnoli can turn implementation work into a repeatable product.
The post lists ten features of Lead Scraper: unlimited Google Maps scraping through Outscraper or Apify, automatic email enrichment, multi-channel email and SMS workflows with rate limits, SMS sending through an Android phone API gateway, A/B testing, a unified IMAP inbox, multiple Gmail SMTP accounts, a daily 08:00 summary, team roles with row-level security, and a done-for-you service.
Pricing is stated as a €17 monthly starter plan and €99 for done-for-you.
The post positions the tool for GTM engineers and agency owners.
For brands planning a campaign
For a B2B SaaS partnership, this offers a productized layer with clear pricing and a managed service option. A pilot could test integration with the partner's CRM and data stack and clarify who supports scraping, deliverability and account security.
Salesforce-adjacent B2B sales and marketing operations3
Low-cost SMS and email reactivation systems2
CRM and customer-data cleanup as the foundation1
CRM and customer-data cleanup as the foundation
A long automotive case study walks through securing a database, extracting data from Qlik, a dealer management system and other portals, and building a 360-degree customer view.
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The post reconciles 105,169 records into 98,146 unique customers, splits private customers from companies, sets lead-conversion rules and a 60-day deal cut-off, and links vehicles and workshop spending. It presents the work as a consultancy a big firm would sell for more than €10,000.
Gnoli works from source systems, secures the database, applies standard CRM objects, reconciles records only when identifiers are certain, and defines lead and deal rules.
For brands planning a campaign
Useful for a CRM or data-integration pilot on one messy database. Scope a data audit, define matching and conversion rules up front, and ask for before-and-after record counts and a working customer view—not a slide deck.
Across several posts, Gnoli treats WhatsApp as a revenue channel rather than a standalone tool.
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They describe automated appointment check-ins, review requests and referral flows, and say cold contacts booking through WhatsApp Flows reached 40% in one case. Another post reports on a Meta country leader's NetComm talk citing 98% interaction for WhatsApp versus 50% for email and 60% for SMS, and predicting that agentic use will be the focus over the next 18 months.
The approach starts with Gnoli's own studio needs, tests use cases there, and proposes a 30-day go-live plus monthly use-case improvements.
The 40% booking figure and interaction rates are reported claims; the Meta figures are attributed to a conference speaker, not independently measured in the posts.
For brands planning a campaign
A WhatsApp pilot could target no-shows, reviews or referrals, with clear consent and booked-appointment KPIs. For a B2B SaaS partner, the strongest fit is an implemented workflow with reported results—not another messaging tool.
Two build logs show small, low-cost lifecycle systems.
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One sends more than 3,000 SMS a month through an API connected to a Lovable app and an e-sim, with safety filters, AI reply recognition, A/B tests and a dashboard; the reported cost is €0.002 per message. The other is a five-email win-back sequence with segmentation, warm-up, A/B testing, daily reporting and CRM reactivation, built for about €25 in MailerLite, €100 in Claude Code and small tool and domain costs.
The builds assemble low-cost tools into a working stack, document setup costs, and add controls such as suppression lists, sending limits and reply handling.
The costs and results are reported figures from specific builds, not benchmarks buyers should assume will repeat.
For brands planning a campaign
Suitable for a tightly budgeted reactivation or appointment-reminder pilot. Ask for the working flow, consent and suppression rules, and a measured reply or booking rate; keep the initial scope to one segment and one offer.
Gnoli maps outbound as a system: pipeline and a fallback alternative first, then an irresistible offer, scraping, email scripts, A/B tracking and a CRM.
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In one agency example, the post describes a €15 setup that produced 13 positive replies in a week.
A separate post lists a lead-scraper product with Google Maps scraping, email enrichment, email-plus-SMS sequences, Gmail rotation, a unified inbox and a done-for-you plan at €99 a month.
The post also discusses Salesforce's outbound agent with Apollo and argues for separating judgement from execution as Hunter becomes generally available.
The approach starts with pipeline economics and the offer, then assembles scraping, outreach, testing and CRM tracking into a repeatable process.
The €15 setup and 13 replies come from one reported test, not a guaranteed outcome. The lead-scraper pricing is a product offer, not an independent assessment.
For brands planning a campaign
A fit for B2B SaaS or agency lead-generation partnerships where the brand can supply a product or offer. Scope a pilot around one target segment and one offer, and require deliverability, suppression, reply handling and CRM reporting before scaling.
AI serves as both an analysis tool and a build accelerator.
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In one post, AI reviews management-system data and produces more than 100 charts in seven minutes, with about 70% judged relevant for decisions and recommendations for hidden problems. Other posts mention using Claude Code, Claude's ecosystem and Lovable to build CRM, CDP and automation workflows, and using AI to read replies and prepare reports.
The work uses AI to generate audits and recommendations from operational data, and AI coding and workflow tools in builds.
The seven-minute audit and 70% relevance are Gnoli's account of one audit; ask for independent validation before relying on the analysis.
For brands planning a campaign
A possible pilot is an AI-assisted audit that ends in a prioritised automation roadmap, not just charts. Test the recommendations against your own data and ask which parts were automated, which were reviewed by a person, and what implementation would cost.
Salesforce-adjacent B2B sales and marketing operations
Several posts sit close to the Salesforce and B2B GTM world.
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One quotes a CRM manager at a B2B company describing the commercial need as a carer for salespeople who helps them work more fluidly.
Another analyses Salesforce's Apollo-powered outbound agent and the Hunter alternative.
A webinar post lists a stack covering outreach, Claude, OpenSEO as an Ahrefs and Semrush replacement, Google Ads and Meta Ads automation, and the essentials of a CRM that converts.
The content uses tool comparisons, conference material and practitioner quotes to frame B2B sales and marketing problems, then points to implementation or a webinar.
The quoted CRM manager is from another company; the post reports that person's view, not an audit by Gnoli.
For brands planning a campaign
Best suited to a Salesforce-adjacent or B2B revenue-operations partnership. A brand can co-market around CRM adoption, outbound tool comparisons or a webinar, but should check whether the content is a genuine evaluation or a route to Gnoli's own implementation offer.
Posts use numbered walkthroughs, feature lists, before-and-after record counts, conference quotes, webinar agendas and comment or DM requests for files and access.
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Several walkthroughs read like a consultancy teardown; others are direct product or webinar promotion. The practical detail makes some technical work inspectable, but the call to action is usually part of the same post.
Gnoli uses step-by-step lists and specific counts to make technical work inspectable, then attaches a call to action.
The webinars and files are promotional routes to Gnoli's services or community; the posts do not establish independent attendance or results.
For brands planning a campaign
A brand can commission a build-log teardown or co-host a webinar, but should specify the deliverable and whether a resource is genuinely usable. Treat comment and DM offers as lead capture, not editorial endorsement.
The examples span automotive dealers, dental practices, medical consultations, ecommerce, agencies and B2B software.
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In each case the pitch changes to the workflow: vehicle and workshop data for a dealer, appointment reminders for a clinic, win-back for ecommerce, and pipeline systems for an agency. The breadth shows applied work across local service and commerce settings, not only B2B SaaS.
For brands planning a campaign
A brand should choose the vertical where it can supply a real product or data set, then ask for a matching case. Do not assume a B2B SaaS pilot will draw on the dental or automotive examples without translation.
Recommends Salesforce admin certification in a CRM integration post.
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In a post about Salesforce’s Apollo integration, they tell readers to contact their account executive “or me.” No employment or partner status is stated.
Start with the automotive CRM teardown for its data-cleanup method and business rules, then read the WhatsApp, SMS and win-back posts for messaging systems and reported costs.
For outbound, read the agency pipeline example and the Salesforce/Apollo/Hunter analysis.
The AI material appears in the audit post and the webinar stack.
Similar creators offer different entry points: Michele Sciabarrà on AI and software futures, Ivan Canovese on consulting and economic risk, and Alessandra Salimbene on marketing systems in optics.
Both draw on direct technical and managerial experience to explain how software and AI change business practice.
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Sciabarrà's posts focus on company leadership and broad AI and software futures, while Gnoli shares hands-on CRM, messaging and outbound build logs with reported campaign numbers.
Both offer consulting-style advice to B2B decision-makers on improving commercial and operational performance.
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Canovese's posts center on consulting relationships, cost and supply-chain strategy, and economic uncertainty; Gnoli focuses on specific CRM, automation and messaging implementations.
Both argue that marketing tools and AI need to work as a coherent system, not as isolated actions.
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Salimbene writes from a marketing-strategy and optics-sector perspective, emphasizing continuity and brand coherence; Gnoli shares technical build logs for CRM, messaging and outbound, with campaign metrics.
Giorgio Gnoli’s posts are most relevant to buyers considering practical CRM, customer-data integration, and marketing automation work.
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Examples include a detailed automotive CRM and data-reconciliation project, WhatsApp appointment flows, and SMS and email reactivation campaigns. For a campaign targeting CRM decision-makers at B2B SaaS companies, ask for recent LinkedIn reach and engagement results on comparable posts, plus documented audience data on occupation, seniority, and industry, such as survey results.
Giorgio Gnoli’s posts show implementation-led collaborations: hands-on CRM and customer-data integration, WhatsApp/SMS/email automation builds, deployment of a custom lead-generation tool, and technical webinars or community content.
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They emphasise go-live, tested use cases and ongoing iteration. Plan around system access, consent-compliant data and a named commercial use case rather than a media kit; confirm commercial terms and sponsorship availability directly.
Hands-on CRM and customer-data integration
Buyer requirement
Provide access to the CRM and surrounding systems, such as Salesforce, a DMS, Qlik or portals.
Agree in advance how leads, deals and duplicates are defined, who owns acceptance, and what data volumes and go-live date are in scope.
Work can include database clean-up, a customer 360 and standard-object setup.
Name the systems and the commercial decision the integration must support.
WhatsApp, SMS and email automation builds
Buyer requirement
Bring a specific commercial use case, such as appointment booking, no-show reduction, review requests or win-back, plus a consent-compliant contact list and API or CRM access.
Expect safety filters, A/B testing and reporting, and plan for iteration: the posts describe monthly new use cases and a 30-day go-live.
Confirm who owns the resulting assets and how message consent is documented.
Custom lead-generation tool or stack deployment
Buyer requirement
Specify lead sources, outreach channels, sending accounts and data rules before scoping.
The documented product supports Google Maps scraping, email enrichment, email and SMS sequences, a unified inbox and multiple Gmail accounts.
Published product pricing is a starter plan from €17 per month and a done-for-you service at €99 per month.
Confirm current pricing, service limits and data-compliance responsibilities before contracting.
Webinar or technical content collaboration
Buyer requirement
Agree the topic, audience, registration route and whether the session is educational or commercial.
The posts advertise webinars and a Growth Express community.
Ask directly about sponsor-slot availability, fees and booking terms; none are published.
Good fit: a B2B SaaS company or CRM consultancy wants a hands-on partner to clean a messy Salesforce or multi-source data estate and prove one automation use case in about 30 days.
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Giorgio Gnoli is a credible fit for a scoped implementation pilot, not a broad media buy.
The strongest example is the automotive CRM rebuild: extracting data from Qlik, a dealer management system and other portals; reconciling 105,169 records into 98,146 unique customers; linking records only where identifiers are certain; setting lead-conversion and 60-day deal rules; and mapping 682 fields into a customer 360.
That is directly relevant to a CRM and data-integration project.
The WhatsApp, SMS and email builds add examples for the activation half: appointment follow-up, safety filters and reporting in the SMS build, and a five-email win-back journey with segmentation and CRM reactivation.
The lead-generation product and the Salesforce, Apollo and Hunter analysis show commercial awareness of the B2B tool landscape.
Fit is strongest when the buyer supplies system access, a named commercial decision, consent-compliant data and a measurable pilot outcome.
The posts report results such as a 40% booking rate and a 2% early reply rate; treat these as reported baselines to test, not guaranteed outcomes.
If reach is part of the buy, ask for audience demographics and independent performance data.
When to choose a specialist
Poor fit: a consumer brand wants a paid LinkedIn sponsorship or creator-style awareness campaign aimed at a broad consumer audience, with reach, engagement and a fixed media package.
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The content is mostly implementation-led B2B operations: CRM data reconciliation, Salesforce-adjacent tool analysis, outbound systems and messaging workflows.
Some examples are consumer-facing verticals, such as dental appointments and ecommerce win-back, but the posts are written for operators and buyers of implementation work, not for mass consumer discovery.
A brand could still commission a build log or technical webinar, but should not treat this as a proven consumer reach buy.
Ask for a sponsorship rate card and audience demographic data before considering a media package.
A worked campaign example
Worked campaign angle for the good-fit brief: a 30-day 'clean data before AI' pilot and build-log series.
The partner is a B2B SaaS company with a Salesforce instance and a dormant-account problem.
Phase 1: a paid discovery with Giorgio Gnoli to audit lead sources and account and contact records; agree matching rules, a lead-conversion definition and a deal cut-off.
Phase 2: build a customer 360 view on standard objects and document before-and-after record counts.
Phase 3: run one controlled reactivation flow to a consented dormant segment, using email or WhatsApp with suppression rules and reply handling, and report sends, replies, bookings and CRM reactivation.
Content angle: three LinkedIn build-log posts and one technical webinar for the partner's audience.
Post 1 covers the data audit and what was messy.
Post 2 covers the reconciliation and business rules.
Post 3 covers the activation flow and measured results.
The webinar turns the build into a practical checklist for CRM managers.
Deliverables to the brand: a working pilot, a documented rulebook, a measurement dashboard and a reusable case study.
Guardrails: name the systems and data owner, confirm consent and data-protection responsibilities, fix the KPI before launch, and publish only results the partner can verify.
Do not promise that the reported 40% booking or 2% reply figures will repeat.
For a scoped CRM/data integration and automation pilot, Michele Sciabarrà is the better conversation if the buyer needs technical leadership and product-strategy judgment before committing to a build.
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The posts show a founder who moved from CEO to CTO to focus on product and technical decisions, and who argues that AI changes what software teams can attempt.
Sciabarrà is more useful when the real blocker is deciding what the product should become, who owns technical choices or how AI fits the roadmap.
A CRM consultancy could use that perspective to pressure-test whether a data-integration pilot is solving the right problem before assigning engineering time.
The tradeoff is distance from hands-on CRM delivery.
The posts do not show data reconciliation, Salesforce field mapping, lead-conversion rules or campaign execution.
Sciabarrà writes about company governance, technical focus and AI’s long-run effect.
If the buyer needs someone to clean records, connect systems and run a 30-day activation test, this is strategic cover, not implementation capacity.
Use Sciabarrà to sharpen the technical and product case, and keep a builder like Giorgio Gnoli for the pilot itself.
For the same partner-selection decision, Ivan Canovese is the better alternative when the CRM or automation pilot has to be sold internally as a cost, procurement or supply-chain resilience move.
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The posts show a Senior Partner at ERA Group framing client work around listening first, building tailored paths and linking cost analysis to commercial decisions.
One post uses the Bab el-Mandeb shipping risk to argue that uncertain conditions should make companies more selective and rigorous about costs and supplier contracts.
That is relevant if the buyer’s CRM pilot is tied to renegotiating supplier terms, reducing commercial waste or giving a CFO and procurement team a defensible business case.
The tradeoff is that Canovese’s posts are advisory, relationship-led and focused on costs and supply chains, rather than CRM data integration or marketing automation build work.
He can help frame the commercial rationale and align stakeholders, but the posts do not show him reconciling customer records, mapping Salesforce objects or running WhatsApp, SMS or email flows.
For the hands-on pilot, that execution capacity sits with Gnoli.
Canovese is better for the cost-transformation wrapper than the technical build.
For the same decision, Alessandra Salimbene is the better alternative when the buyer is a retail, optical or multi-brand consumer business and the real problem is marketing operating-model coherence rather than raw data cleanup.
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The posts show work connecting campaigns, CRM, social, AI and customer relationship into one sustainable system, with an explicit warning that disconnected actions waste value.
A second post reads the GPT-6 launch through the lens of which office tasks are structured enough to delegate to an AI agent for 40 minutes.
Salimbene is more useful when the buyer needs to decide which marketing processes to standardize, which to automate and how CRM fits the customer experience across channels.
The tradeoff is technical depth in data integration.
The posts show marketing strategy, brand coherence and AI task selection, rather than large-scale record reconciliation or Salesforce-adjacent data engineering.
Salimbene can help define the customer journey and automation use case, but the posts do not show the hands-on data plumbing of Gnoli’s automotive CRM rebuild.
Use Salimbene when success depends on marketing adoption and cross-channel coherence; keep Gnoli when the pilot’s first job is cleaning and connecting the data estate.
Giorgio Gnoli's 13 LinkedIn posts cover CRM and customer-data integration, WhatsApp, SMS and email automation, lead generation, Salesforce-adjacent tools, AI-assisted analysis and webinars.
No publication dates are given in the posts; the account was observed on 8 October 2026.
Reported metrics are the figures given in the posts.
The posts do not establish a complete career history, audience demographics or sponsorship terms.
