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Solution · Other solutionsA monitor that sits between the platforms, because no single platform can see the funnel
Traffic drops and burning campaigns flagged the same day
Robots collect ad, analytics and order data daily and test every live funnel, so a broken form or a campaign running ahead of plan reaches its owner in Teams with the numbers attached.
Executive summary
Your ads are running, your page is loading, your analytics is counting, and nothing converts.
The design starts from an admission: no platform can monitor this, because each of them only sees its own segment.
Incidents are caught in hours instead of days, because the funnel is tested end to end rather than watched platform by platform.
the reporting dataset in Azure SQL; the Power BI semantic model and report
Business problem
Marketing
Campaign data lives in four places that each see one section of the journey. The ad platform counts the click, analytics counts the visit, the shop or the CRM counts the order, and the agency's slides count whatever they were asked to. Nothing counts the distance between them, which is exactly where the expensive failures happen: a form that stopped posting, a tag that did not survive a release, a landing page returning an error to one country, a campaign pacing at three times plan.
Each platform alerts on its own metrics, which is why an incident of this kind sets off nothing at all. Traffic is normal, so analytics is calm. Spend is normal, so the ad platform is calm. Orders fall, but the shop has no idea a campaign exists. The one system that would have noticed, a check that walks the whole funnel, is the one nobody owns.
Meanwhile two analysts spend most of the week exporting from each source, reconciling in Excel and pasting into a deck that is read on Friday about a week that ended. The report is accurate and late. Decisions to scale or cut wait for it, so a good campaign is underfunded for days and a bad one overfunded, and the marketing director defends the budget with numbers the agency supplied and finance does not recognise.
How it works today
This is the weekly rhythm in most marketing teams running more than a handful of campaigns.
- PersonAn analyst exports platform data on Monday and reconciles it against analytics and orders in Excel
- PersonThe weekly deck is built and circulated on Friday, describing a week that has ended
- Risk of errorA website release changes a form or removes a tag, and no system reports the change
- WaitingAds keep spending and visits keep counting while conversions sit at zero
- WaitingSales notices the missing leads several days later and asks marketing
- PersonThe analyst investigates across four systems to find which step actually broke
- Risk of errorThe campaign is paused after the budget is gone, and the incident is discussed at the next weekly meeting
Why the current process costs more than it appears
Time that disappears before anyone measures it.
- Analyst hours are the visible cost. Budget burned during an undetected incident is the larger one, and it never appears as a line item, because the spend was planned and only its uselessness was not.
- Lead flow that stops for a week arrives in the sales pipeline as a gap a quarter later, by which time nobody connects the two, and the conversation between marketing and sales is about trust rather than about a form.
- Agencies report on their own performance using their own definitions, so channels cannot be compared on equal terms and the budget gets cut where it is least understood rather than where it works least.
- Website releases go out without anyone confirming that tracking survived them, which means the measurement of every campaign depends on a step nobody checks.
Cost of inaction
The spend during an incident was budgeted; only its uselessness was not, which is why none of it is ever questioned afterwards. Campaign count grows with markets and product lines, website releases become more frequent, and browser and privacy changes break tracking more often, so the number of incidents rises while the detection method stays what it has always been: somebody in sales will notice.
There is a slower cost behind the spend. Analysts recruited to find insight spend their weeks assembling decks, and the good ones leave for places where they do analysis. Marketing keeps defending its budget with late numbers that came from an agency, so when the CFO looks for something to cut, the cut lands where the evidence is thinnest rather than where the performance is worst.
A plausible organisation with realistic proportions. The figures are there to be recalculated on your data; they are not a client result.
An online retailer of home and garden products, 480 employees, selling in Poland, Czechia and Germany, with a marketing team of 26. Microsoft 365 and Teams are in daily use, Power BI exists for finance reporting but not for marketing.
About 14 campaigns running at any moment across Google Ads, Meta and marketplace advertising, with Google Analytics for web analytics and an e‑commerce platform holding the orders.
Two analysts assemble a weekly deck by exporting from each platform and reconciling in Excel. Incidents are found by sales or by chance.
Two analysts at 12 hours a week each on collection and reporting, and roughly three incidents a month, each running for about 4.5 days before anyone notices, at an assumed €1,400 a day of misdirected spend.
Robots collect ad, analytics and order data daily into one dataset with agreed definitions; Power BI shows campaign economics by channel, country and campaign and raises data alerts on conversion, cost and pacing; a second robot walks every live funnel several times a day and posts a card in Teams to the campaign owner when something fails.
In the modelled case an incident is caught in hours rather than days, the budget behind it is paused the same day, and the Friday deck becomes a digest nobody has to build. The figures are a model, not a measured result.
Proposed solution
The design starts from an admission: no platform can monitor this, because each of them only sees its own segment. So we build the layer between them. UiPath robots collect daily data from the ad platforms and web analytics through connectors built with UiPath Integration Service Connector Builder, and orders and leads from the e‑commerce platform and the CRM through their APIs. Everything lands in a reporting dataset in Azure SQL with one agreed set of definitions for spend, clicks, sessions, conversions, cost per acquisition and return on ad spend, agreed with finance so the numbers survive the budget meeting.
A Power BI semantic model and report then give the marketing director campaign economics by channel, country and campaign, refreshed daily rather than weekly. Power BI data alerts fire when a conversion rate falls below its baseline, when cost per acquisition passes its target, or when spend pacing runs ahead of plan, and the thresholds behind them are documented and owned by marketing operations rather than buried in a report.
The part that catches the incidents no metric would show is a separate robot. Several times a day it loads every active landing page, confirms the tracking tag is present, submits a test lead through the form under an identity the CRM recognises and excludes from reporting, checks that the lead actually arrived, and confirms that campaign URLs do not return errors in any market. A failure becomes an Adaptive Card in the marketing channel in Microsoft Teams naming the campaign, the check, the numbers and a link, assigned to the campaign owner. A weekly digest arrives by Power BI subscription and replaces the Friday deck. No AI is involved anywhere, and that is the point: every threshold and every check is deterministic, so an alert that pauses somebody's campaign can always be explained.
Power BI semantic models, data alerts and subscriptions to Microsoft Teams and Outlook; Adaptive Cards posted into a Teams channel through the UiPath Microsoft Teams connector, or the Workflows app webhook trigger where the card is raised from an HTTP call; UiPath Orchestrator triggers, credential store and run log
The shared metric definitions agreed with finance; the daily collection and consolidation robots; the reporting dataset; the semantic model and report; the alert thresholds and baselines; the synthetic funnel checks; the card content, its assignment to an owner and the weekly digest
Connectors to Google Ads, Meta, marketplace advertising and Google Analytics built with UiPath Integration Service Connector Builder; orders and leads from the e‑commerce platform and the CRM through their APIs
How the automated process works
- AutomationRobots collect spend, clicks, sessions, conversions and orders from every platform each day and load them under one set of definitions
- AutomationThe Power BI semantic model refreshes and the report shows economics by channel, country and campaign
- SystemA second robot walks every active funnel several times a day: page loads, tag present, test lead submitted, lead arrived, URLs healthy
- AutomationA data alert fires when conversion, cost per acquisition or spend pacing crosses its threshold
- AutomationThe failure or breach becomes an Adaptive Card in the marketing channel in Teams, with the campaign, the numbers and a link, assigned to its owner
- PersonThe owner pauses, fixes with the web team, or judges it seasonal and adjusts the baseline
- AutomationA weekly digest goes to marketing and sales leads by subscription, and every alert is logged with its detection time
Human-in-the-loop model
Automation handles
- Daily collection and consolidation of ad, analytics and order data under shared definitions
- Threshold monitoring on conversion rate, cost per acquisition and spend pacing
- The synthetic funnel checks: tag presence, form submission, lead arrival and URL errors
- Alert cards with the numbers attached, assigned to a named owner, and the weekly digest
People decide
- Whether to pause, scale or reallocate a campaign, which is a commercial judgement and stays one
- What to fix, and with whom, when the failure is a page or a tag rather than a campaign
- The thresholds and baselines themselves, and when a seasonal pattern should move them
- Whether an anomaly is a problem at all, which is the judgement no threshold can make
Before and after
Systems and integrations
We do not add technology to make an architecture look serious. Every element below has a specific job in this process.
Inputs
- Google Ads, Meta and marketplace advertising accounts
- Google Analytics
- orders and leads from the e‑commerce platform and the CRM
Automation layer
- UiPath Orchestrator
- UiPath Robots
- UiPath Integration Service with Connector Builder
- the threshold and funnel-check rules
Target systems
- the reporting dataset in Azure SQL
- the Power BI semantic model and report
Human touchpoints: alert cards in the marketing channel in Microsoft Teams; the weekly digest by Power BI subscription; the threshold list owned by marketing operations
Technologies used
daily collection, the funnel checks and the alert cards, scheduled with a credential store and a full run log
Aconnectors to the ad platforms and web analytics, where no packaged connector exists
Athe reporting dataset holding spend, sessions, conversions and orders under one set of definitions
Asemantic model and report for campaign economics, with data alerts on thresholds and the weekly digest by subscription
Athe alert card in the marketing channel carrying campaign, metric, numbers and link
Achannel membership and the service identities the robots run under
AIllustrative economic model
What it is worth, with the arithmetic shown.
Two of the four inputs below are worth arguing about, and both are the incident ones: how often a funnel actually breaks, and what a day of misdirected spend costs. We reconstruct both from your own campaign history before anything is concluded. The rest is simpler: two analysts at 12 hours a week each on collection and reporting, of which 0.7 is automatable at €40 an hour; three incidents a month, each running about 4.5 days, at €1,400 a day of misdirected spend, of which 0.7 becomes avoidable once detection is same-day. Because hours and wasted spend are unlike quantities, this is a value pool rather than a per-transaction calculation, and none of it was measured at a client.
Business benefits
- Incidents are caught in hours instead of days, because the funnel is tested end to end rather than watched platform by platform
- Budget that would have been spent on a broken funnel is paused or redirected the same day, which is the largest single item in the model
- Campaign decisions move from weekly to daily, so a winner is scaled and a loser cut days earlier than the deck allowed
- Channels and agencies are compared on one set of definitions that the company owns, which changes the budget conversation from faith to allocation
- Analysts stop assembling decks and start explaining results, and sales hears about a lead-flow problem from marketing rather than finding it
The management view
- Every incident carries its own detection time, so "we were unlucky" becomes an operational number that somebody owns
- Alert history shows which campaigns, pages and releases cause problems, which lets the web team's release process be improved on evidence
- Spend and return by channel are reported on the same definitions finance uses, so the marketing budget is discussed as an allocation
- Thresholds are written down and owned, so an alert is never a matter of opinion about whether it should have fired
Board-level KPIs
Security and governance
An auditor should be able to reconstruct every decision.
- Advertising, analytics and shop credentials belong to read-only service identities and are held in a managed store rather than in a workflow, with every collection run and every alert logged in Orchestrator
- The funnel check submits its test lead under an identity the CRM recognises and excludes from reporting, so monitoring never contaminates the pipeline
- No customer personal data is collected: the dataset holds aggregated campaign metrics and order counts, which keeps the whole solution outside the scope of the arguments that usually delay marketing reporting
- Alerts go to a standard Teams channel whose membership is managed in Microsoft Entra ID, threshold changes are versioned in a list owned by marketing operations, and processing stays in the Microsoft 365 EU Data Boundary and the EU region of UiPath Automation Cloud
Why now
Tracking breaks more often than it used to, as browsers restrict cookies and consent layers change what analytics records, so the funnel now needs a monitor of its own rather than a quarterly audit
Every advertising and analytics platform exposes an API, Connector Builder covers the ones without a packaged connector, and Power BI data alerts and subscriptions deliver numbers to people instead of waiting for a login
Marketing budgets are being asked to justify themselves against finance's definitions, and the modelled cost of the present arrangement is about €16,110 a month, most of it spend rather than hours
Relevant executive roles
Incidents are caught the same day, the budget is defended with the company's own numbers, and the analysts do analysis
Campaign economics by channel on finance's definitions turn the marketing budget into an allocation decision rather than an act of faith
Lead flow is monitored end to end, so a broken form becomes marketing's alert instead of a sales discovery a week later
Common questions and objections
Each alerts on its own metrics, to whoever configured it. None can see the form, the tag or the CRM, and that is where most incidents live: a campaign spending normally on visits that convert nowhere is invisible to every platform involved.
Weekly is the problem, and the report uses the agency's definitions. This gives you a daily dataset of your own, which is also what lets you hold every agency to the same standard.
It flags traffic anomalies. It does not submit a test lead, confirm the tag survived last night's release, or tell the campaign owner in Teams with the numbers attached and a name against the task.
When this is not the right solution
- Advertising spend is small and campaigns are few, where a person opening the platforms each morning is genuinely enough
- Conversion tracking is not set up at all, in which case measurement comes first and monitoring second
- No one owns campaigns day to day, because an alert without an owner is noise that trains people to ignore the channel
A question for the next management meeting
Fourteen campaigns, three platforms and one form on the pricing page: which of them would we hear about first if it broke tonight, and from whom?
Implementation approach
What we deliver, and what we need from you to start.
We deliver
- A metric definition workshop with marketing, sales and finance, so the dataset holds up in the budget meeting and not only in the marketing meeting
- Connectors to the ad platforms, analytics and orders, plus the daily collection robots and the reporting dataset
- The Power BI semantic model, the report pages, the data alerts and the weekly digest
- The alert thresholds and baselines, set with the campaign owners rather than for them
- The funnel-check robot for landing pages, forms and campaign URLs, tested on live campaigns before it is trusted
We need from you
- API access to the advertising, analytics and shop accounts for read-only service identities
- A test-lead route in the CRM that the funnel check can use and that reporting excludes
- A marketing-operations owner for thresholds and a named owner per campaign
- A contact in the web team, because half of what the checks find is fixed there
Stages
Definitions
Metrics, baselines and thresholds agreed with marketing, sales and finance
Build
Connectors, collection robots, dataset, semantic model and report
Checks
The funnel checks written and proved against pages that are known to be healthy and known to be broken
Pilot
One market's campaigns and its main landing pages, alerting into one channel
Rollout
Remaining markets and platforms, the full page set, the weekly digest and the retirement of the Friday deck
Quick win in scope, provided conversion tracking already exists. Effort is driven by the number of advertising platforms without a packaged connector and by how many landing-page variants must be checked.
If the pricing-page form breaks tonight, sales will tell you about it on Wednesday.
Send us last month's campaign report and the list of your active landing pages. We define the ten alerts that would have caught your last three incidents, and what each one was worth.
Test ten alerts on your last three incidentsThe neighbouring process usually has the same problem
The version that went live in Romania was not the one legal approved, and nobody could prove which one it was.
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View solutionIndustries we deliver this in most oftenRetail & e‑commerceFinance & insurance