For businesses spending $100K+ per month in ad spend
From our Ottawa office, LGG Media manages five to six figures in daily ad spend across Google, Meta, and Microsoft Advertising for businesses with nationwide reach in the US. Every engagement begins with attribution infrastructure that reconciles platform-reported figures against actual revenue collected before a single campaign goes live.
Every owner or CMO who comes to us describes one of two problems, or both. They share the same root cause: the revenue data never reached the algorithm.
Google reports one number. Meta reports a different number. The actual revenue in the business is a third number, and nobody can reconcile them. Both platforms take credit for the same customers, so combined reported revenue can be double the actual revenue collected. Every bidding decision made from those numbers is made on fiction, and the real cost of acquiring a customer is significantly higher than the dashboard suggests.
The campaigns are spending and the algorithm is learning, but it is learning to find people who fill out forms, not people who buy. Form fill volume goes up; revenue does not move proportionally. The algorithm is doing exactly what it was told. It was told the wrong thing, because it has never been shown what a paying customer looks like.
Before a single campaign goes live, we define three numbers with every client. They are the north star for every decision we make, not cost per click, not cost per impression. The business KPIs that determine whether the advertising is actually working.
The call volume target at which the business is profitable.
The qualified lead cost the sales team can work at a positive return.
The acquisition cost at which the business grows profitably.
We then build the tracking infrastructure to measure against those KPIs accurately, before we touch the campaigns. Revenue in the tracking layer has to match revenue in your business one to one, the full build is documented under attribution tracking.
Every new account runs through the same sequence. It is the fastest path from zero to accurate data and profitable bidding.
Hyros script across all assets. Ad platform integrations. CRM connection. Phone tracking synchronization. KPIs defined and mapped to conversion events. Revenue in Hyros has to match revenue in the business before anything else happens.
Campaign structure, ad copy, and landing pages built and reviewed before going live.
No target applied yet. Max Conversions lets the algorithm spend freely and gather signal without a ROAS or CPA constraint that would restrict volume before there is enough data to learn from. Google recommends 30 conversions in 30 days to optimize a campaign; we pace toward 50 before applying a target. More signal means better optimization when the target goes on.
We verify that every conversion event is flowing correctly, that the data in Hyros reconciles with the CRM, and that click attribution is tracking at the expected percentage. If anything is broken we fix it here, before it corrupts the learning period.
Conversion volume, cost per conversion, and whether the quality of conversions matches the KPIs defined on Day 1.
If conversion volume is pacing toward 50 per month, we apply Target CPA or Target ROAS. The number is not arbitrary: we compare how closely the platform's conversion data matches the actual count in the CRM. If the platform sees 80 events for every 100 in the CRM, we adjust the target upward to compensate for the 20 events the platform is missing. The bid is calibrated to the real conversion rate, not the reported one. Try the free ROAS Target Calculator →
Target adjusted up or down based on whether actual business KPIs are being met. This is when the account starts compounding.
When the infrastructure is correct and the campaigns have enough conversion data to learn from, every additional dollar of ad spend produces a proportional return in revenue. Scaling becomes a business decision rather than a test.
Google has recognized this methodology twice: the 2026 Google Ads Impact Award, and three independently published case studies documenting 88%, 29%, and 28% conversion uplifts over 45-day windows.
$5K to $130K per day at 92% attribution accuracy. The campaign behind the 2026 Google Ads Impact Award.
Read Case StudySigned retainer events synced to Google as offline conversions, sustained on verified closed revenue.
Read Case Study93% attribution accuracy at sustained spend, verified against dispatch and payment records.
Read Case StudyGoogle Search, Performance Max, Google AI Max, Meta, and Microsoft Advertising, each with a defined job, run only where accurate attribution can be built.
We do not run channels because they look good in a proposal. We run channels where we can build accurate attribution and where the data shows incremental revenue.
Businesses spending $100,000 or more per month on paid advertising in the US. Owners and CMOs who have hit a ceiling they cannot explain, who know their campaigns are spending but cannot answer where to put more money to grow.
Businesses that have been through an agency that optimized for form fills and delivered volume without profit. Or businesses that have never had proper attribution infrastructure and are operating on platform-reported figures they know are wrong but cannot prove.
If someone referred you here, you already know what we do. The question is whether your business is the right fit for the infrastructure we build, the engagement standards are on the About page.
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We learn your business KPIs, audit your current tracking setup for free, and tell you directly whether we can help and what the infrastructure build looks like. There is no obligation either way.
Request a Discovery Call →Running paid advertising across Google and Meta simultaneously creates a structural attribution problem that neither platform is designed to resolve. Google records a conversion when a user clicks a Google ad before purchasing. Meta records that same conversion when the same user was served a Meta ad within its attribution window. Both platforms count the same customer payment, and the combined reported revenue across both dashboards consistently overstates actual collected revenue, sometimes by a factor of two.
Independent research on accounts running both platforms documents combined platform-reported revenue exceeding CRM-recorded revenue by significant margins. On a $300,000 revenue month, Google and Meta together may report $380,000. The number in the CRM is the accurate one.
Every bidding decision made from inflated platform figures underestimates what acquiring a customer actually costs. An account generating a 4x ROAS in Google Ads and a 3x ROAS in Meta simultaneously may be generating a 2x blended ROAS against actual collected revenue once the overlap is removed. Scaling spend from the inflated figures produces dashboard revenue increases that do not correspond to equivalent growth in cash collected, because the additional spend is reaching customers both platforms are already counting.
Google's Smart Bidding and Meta's Advantage+ both optimize toward whichever conversion event they receive as the primary signal. A form submission tells the algorithm to find users who fill out forms. It learns that audience efficiently. High form-fill rate and high downstream revenue rate are separate characteristics, and the algorithm cannot distinguish between them until revenue data enters the signal. Providing that revenue data changes the audience the algorithm targets and resolves the plateau.
Accurate performance marketing management requires an attribution layer that operates independently of the ad platforms being measured. Each platform applies its own attribution model to its own data in isolation, which means cross-channel overlap between Google and Meta cannot be resolved from within either platform. A third-party attribution system with access to every touchpoint, every conversion event, and every downstream revenue record produces a reconciled revenue figure that the platforms, measured separately, cannot generate on their own.
Hyros sits at the center of the attribution infrastructure built for every LGG Media client. It captures every click across Google, Meta, and Microsoft Advertising, stores the full chronological interaction history against each lead record, and appends downstream revenue events from the CRM, payment processor, and phone system. Hyros uses print tracking, a methodology combining email matching, phone number matching, and device fingerprinting, to follow customers across sessions and devices. Conversions that standard pixel tracking loses when a customer switches devices or returns after a platform attribution window closes are recovered through this process.
A proprietary data management layer sits on top of Hyros and ingests data from the CRM, payment processor, and phone system simultaneously. It deduplicates events recorded by multiple sources, validates the data structure against the conversion schema expected by Google Ads and Microsoft Advertising offline conversion imports, and pushes a single clean payload to the ad platforms. The reconciliation process runs until revenue recorded in Hyros matches revenue recorded in the business system within a 5% variance threshold over a rolling seven-day period. Campaign optimization begins only after that threshold is confirmed.
Hyros tracks customers for up to 365 days and stores the full sequence of ad interactions that preceded each revenue event. For businesses with long sales cycles in immigration law, health insurance enrollment, or high-ticket B2B services, a customer converting in month three may have interacted with a Google search ad in month one and a Meta retargeting ad in month two before responding to a direct outbound call. Hyros distributes revenue credit across that interaction sequence according to the attribution model that most accurately reflects how customers move through that specific sales cycle, so budget allocation reflects the full customer journey rather than the last recorded touchpoint.
Before the attribution infrastructure build begins, three business KPIs are defined and documented with every client. Each one maps directly to a specific conversion event in the attribution system, and every bidding target set during the engagement is calibrated against the revenue those events represent rather than against platform-reported proxies. The three figures are calculated from the client's historical CRM data before any spend goes live.
The maximum cost per inbound call from a qualified prospect at which the business remains profitable, calculated from close rate, average deal value, and cost of sales across the preceding 12 months of CRM data. This figure sets the Target CPA ceiling for call-conversion campaigns. Calls acquired above that threshold consume margin rather than generate it, so the ceiling is treated as a hard constraint throughout the engagement.
The cost per SQL at which the sales team works the pipeline at a positive return, derived from the average SQL-to-close rate and average closed deal value in the CRM. Campaigns transition to SQL-based optimization once the attribution infrastructure confirms that SQL events flowing back from the CRM accurately represent the leads the sales team is actually working, verified within the accepted variance threshold.
The all-in cost per acquired customer at which the business grows profitably, incorporating ad spend, cost of sales, and onboarding costs against average first-year customer revenue. For accounts with sufficient offline conversion volume, customer acquisition cost becomes the primary bidding target because it gives the algorithm a revenue signal that accounts for the full value of what the business is acquiring rather than the value of a lead or a call that may or may not close.
Platform metrics including cost per click, click-through rate, quality score, and impression share remain available as diagnostic tools when specific performance questions arise during the engagement. The determination of whether the campaign is working comes from the KPI targets and whether the verified conversion data shows them tracking at or below the levels defined before the first campaign went live.
Every new account runs through the same sequence in fixed order. Each checkpoint produces a verified output that the next one depends on, and the sequence is designed to reach accurate attribution data and a calibrated bidding target within 31 days of the engagement starting.
The Hyros script is deployed across all landing pages and ad destination assets, ad platform integrations are connected for Google Ads, Meta Ads, and Microsoft Advertising, the CRM and payment processor are connected to the data management layer, and phone tracking is synchronized with Hyros click records. KPIs are defined and mapped to specific conversion events in the attribution system. Day 1 is complete when revenue recorded in Hyros matches revenue recorded in the business system within 5% over a rolling seven-day baseline.
Campaign architecture is built from the KPI targets and the revenue data available in the client's historical CRM records. Search campaigns are structured around keyword intent tiers corresponding to where the prospect sits in the sales cycle. Ad copy is written to qualify prospect intent before the click, because an unqualified click that generates a low-quality conversion event enters the bidding model as signal and degrades it over time. Landing pages are reviewed against the conversion goal and the KPI targets before any spend goes live.
Campaigns go live on Maximize Conversions with no Target CPA or Target ROAS constraint applied. Applying a bid target before the algorithm has accumulated sufficient conversion volume restricts spend at the exact moment the prediction model needs maximum data throughput to build its audience and keyword probability distributions. Google's Smart Bidding documentation recommends a minimum of 30 conversions per month before Target CPA and 50 before Target ROAS produce reliable optimization. Every account paces toward 50 verified conversions before a target is applied.
Every conversion event flowing through the pipeline is verified against the CRM and payment processor records. Click attribution percentage is checked against the expected rate for the traffic volume the campaigns have generated in the first ten days. Any discrepancy between Hyros records and CRM data is identified and corrected at this checkpoint, before degraded data has had time to accumulate in the learning period.
Conversion volume, cost per conversion, and the downstream quality of conversions are reviewed against the KPI targets defined on day one. The review confirms whether the conversion events flowing through the pipeline represent the prospect quality the KPI targets were built from, or whether the campaign structure or keyword intent tiers need adjustment before conversion volume reaches the threshold for bid target application.
When conversion volume is pacing toward 50 per month, Target CPA or Target ROAS is applied. The target is set by comparing conversion data flowing through the platform against the actual count in the CRM for the same period. Where the platform records 80 conversion events for every 100 in the CRM, the bid target is adjusted upward to compensate for the 20 events the platform is not receiving, so the algorithm bids at a level calibrated to the verified conversion rate the business is actually generating.
The bid target is adjusted based on whether the verified conversion data shows actual business KPIs tracking at or below the targets defined on day one. The prediction model is now operating on a calibrated revenue signal, the attribution pipeline has been verified twice, and the algorithm has enough conversion history to refine its audience and keyword probability distributions with each new revenue event. The account enters the compounding phase of the engagement from this checkpoint.
Three of the accounts below have had their results independently documented in Google-published case studies. Each outcome follows the same sequence: attribution infrastructure verified against CRM-recorded revenue before spend goes live, revenue-based bidding applied once the conversion data meets the threshold for reliable Smart Bidding optimization, and scale applied once the cost per acquired customer is tracking at or below the KPI targets defined at the start of the engagement.
Monthly ad spend scaled from $150,000 to $3.9 million while attribution accuracy held at 92% against CRM-recorded revenue throughout the growth period. The algorithm identified profitable enrollment segments as monthly premium value data accumulated through the Hyros pipeline. Google published this account's results in a 2025 case study documenting a 23% revenue increase in 45 days during the initial optimization phase.
A 2.5x return on ad spend was sustained at over $3 million in monthly ad spend with 93% attribution accuracy against CRM-recorded bookings. Confirmed booking value flowing back through the Hyros pipeline gave the algorithm sufficient first-party revenue signal to identify and scale the query segments generating direct bookings, which eliminated dependence on third-party lead aggregators across the account. Google published this account's results in a 2025 case study documenting an 88% conversion uplift in 45 days.
A 4.2x return on ad spend was maintained continuously for four consecutive years with signed retainer value by case type pushed from Salesforce as the offline conversion event. The consistency of the revenue signal over that period kept the algorithm's spend concentrated on the keyword and audience segments producing the highest retainer values, maintaining optimization quality as spend scaled.
Daily spend scaled from $700 to $12,000 within 21 days of the attribution validation period completing, reaching a $7 million to $9 million annual revenue run rate within four months. The three-month attribution validation period preceding the scale phase was the data accumulation window that gave the prediction model sufficient verified revenue signal to absorb the spend increase without degrading cost per acquired customer as volume grew.
A 300% blended ROAS was achieved across 100 retail locations, with $340,000 per month in in-store revenue attributed to paid search and paid social campaigns for the first time in the account's history. The attribution infrastructure remained intact through two ownership changes over the engagement period, validating that a revenue attribution framework anchored to the business's own CRM and payment processor carries forward through organizational changes.
Tier 1 and Tier 2 customer share grew from 24% to 46% across 21 dealer accounts at $5 million in annual ad spend. Pushing credit-tier data from the dealer CRM back through the attribution pipeline as the offline conversion signal allowed the algorithm to identify which paid search keywords and audience segments were producing the highest credit-tier approvals and allocate bid weight toward those segments proportionally.
Results reflect accounts managed with verified attribution infrastructure and revenue-based bidding. The timeline from engagement start to the scale phase varies based on monthly conversion volume and the time required to accumulate the conversion data threshold for reliable Smart Bidding optimization.
Channel selection is determined by where the verified attribution data shows incremental revenue returns against actual collected revenue. For most accounts, Google Search carries the majority of spend because high-intent search queries produce the most direct relationship between bid strategy and revenue outcome when the bidding signal is a verified revenue event. Meta runs in a defined role in audience building and retargeting on accounts where the attribution infrastructure is in place to measure its contribution accurately against CRM-recorded outcomes.
Google Search campaigns are structured around keyword intent tiers that map to the KPI targets defined at the start of the engagement. Google's Performance Max and AI Max campaign types are evaluated on a per-account basis against the verified attribution data. Where the offline conversion pipeline confirms those campaign types are generating revenue from customer segments that Search campaigns were not reaching, they are included in the channel mix with budget allocated proportionally to their verified incremental contribution.
The channel attribution question for Google campaigns is resolved through the Hyros click history, which records which campaign type the customer interacted with first and at which stage of the sales cycle the interaction occurred. The Hyros record of the full interaction sequence allows budget allocation decisions to be made from the customer journey data rather than from campaign-level platform reporting that assigns credit to the last campaign the customer touched before converting.
Meta's default attribution window attributes a conversion to a Meta ad when the user was served that ad within seven days of clicking or one day of viewing it. For accounts running Google Search simultaneously, this creates systematic overlap because Google attributes conversions from customers who clicked a search ad and Meta attributes conversions from the same customers who received a Meta impression within the attribution window. Meta's documentation on audience overlap acknowledges that overlapping audiences affect both delivery and attribution accuracy.
Managing Meta within a multi-channel attribution framework requires measuring its contribution against the Hyros baseline, which holds the full click history for every customer across all channels. The Hyros multi-touch attribution model assigns revenue credit to Meta interactions based on their position in the verified customer journey rather than their proximity to the conversion within the platform's attribution window.
The attribution infrastructure build, the algorithm learning period, and the conversion data threshold that revenue-based bidding requires establish a defined set of conditions for this engagement. These conditions apply uniformly across every account.
The attribution infrastructure build runs on day one of the engagement and campaigns go live on day three. The day one and day two window covers Hyros script deployment across all landing pages and ad destination assets, CRM and payment processor connection to the data management layer, phone tracking synchronization, and KPI definition and mapping to specific conversion events in the attribution system. Campaigns launch on day three on a Maximize Conversions strategy once the revenue reconciliation baseline has been confirmed. The three-day setup window is achievable because the infrastructure components follow a consistent deployment pattern across all account types. The only variation that extends the timeline is a client CRM that requires custom API work beyond the standard connectors the data management layer already supports.
The 60 to 90 day period covers two sequential phases. During the Maximize Conversions data accumulation phase, campaigns spend without a Target CPA or Target ROAS constraint while the algorithm builds its audience and keyword probability distributions from the verified revenue events flowing through the Hyros pipeline. Google's Smart Bidding documentation sets 50 conversions per month as the threshold for reliable Target ROAS optimization, and every account paces toward that threshold before a target is applied.
Performance in the first 30 days is measured against attribution accuracy and conversion volume pacing. The central question during the accumulation phase is whether the pipeline is delivering accurate revenue signal at sufficient volume for the prediction model to train on, and whether that volume is pacing toward the 50-conversion threshold within the expected timeline. KPI target achievement is assessed from the optimization phase forward.
The offline conversion pipeline supports any CRM or payment processor that stores individual transaction revenue against an identifiable lead record and exposes that data through an API or structured export. Salesforce, HubSpot, GoHighLevel, and Zoho connect through native Hyros integrations. Stripe, Authorize.net, and most major payment processors connect through direct API or webhook. Custom CRM builds connect through the Hyros API provided the lead record carries the Google Click ID captured at the time of the initial form submission or call. Phone system integrations use CallRail, CallTrackingMetrics, and Ringba as the most common connectors, with call recording and disposition data feeding back into Hyros alongside the CRM revenue records.
The Google Click ID is captured from the URL parameter at the moment a prospect lands on the page from a Google Ads click and stored in a hidden field in the lead capture form. When the form submits, the GCLID is written to the lead record in the CRM alongside the prospect's contact information. When a downstream revenue event occurs, the data management layer reads the GCLID from the lead record and includes it in the offline conversion import payload sent to Google Ads. That payload ties the revenue event back to the specific ad, keyword, and audience that generated the originating click. Auto-tagging must be enabled in the Google Ads account and the GCLID must be stored within 90 days of the original click for the offline conversion import to process correctly.
The primary performance record is the Hyros dashboard, which clients have full access to throughout the engagement. It shows verified revenue attributed to each channel, campaign, keyword, and ad, reconciled against CRM-recorded revenue on a rolling basis. Formal performance reviews follow the launch sequence checkpoints at day 10, day 17, day 24, and day 31, then move to a monthly cadence once the account enters the active optimization phase. Every review is structured around the three KPI targets defined at the start of the engagement. Performance reviews are not structured around platform engagement metrics such as impressions, click-through rate, or quality score.
We work with businesses spending $100,000 or more per month, with a market big enough to grow 5x and the ambition to capture it.
The Google Ads, Meta Ads, and Microsoft Advertising accounts remain owned by the client throughout the engagement, with access granted through the standard agency manager account structure. The Hyros account is set up under the client's billing and owned by the client, with LGG Media operating as an administrator. At the end of the engagement, the client retains full ownership of the Hyros account, the historical conversion data, the CRM integration, and the offline conversion import configuration in Google Ads. The attribution infrastructure continues to function independently after the engagement concludes.
Meta's Conversions API supports server-side event transmission that sends conversion events, including purchase values and customer identifiers, directly from the server to Meta's attribution system without depending on browser-based pixel tracking. The data management layer pushes verified revenue events to Meta through CAPI using the same deduplication logic applied to the Google Ads offline conversion import, which prevents the same conversion event from being recorded twice when both browser pixel and server-side transmission are active simultaneously. The revenue figure that determines Meta's budget allocation is the Hyros-attributed figure calibrated against the CRM record, which reflects only the conversions where a Meta interaction is confirmed in the click history.
