Is marketing working? Without this data, you can't know.
Many companies invest in advertising, analyze the leads generated, and ask whether the campaigns are working. But they often don't track what happens to those leads after they've been received.
"How are the campaigns going?"
It's one of the questions we hear most often from the companies we work with.
The answer usually comes from the reports: how much we invested, how many people we reached, how many contacts we generated, and how much each one cost.
This is important data, but it rarely answers the question that truly matters to entrepreneurs: are these investments generating commercial results?
And above all: should we increase our Google Ads budget? Is Meta driving better customers? Which campaigns should we boost and which ones should we scale back?
To answer this question, we need information that advertising platforms alone cannot know.
And here we encounter a rather common paradox: many companies want to know if their marketing is working, but they don't record the information necessary to find out.
Summary
The problem is not how many leads come in, but what happens next
Let's imagine a company that invests in Google Ads and Meta Ads simultaneously.
At the end of the month, the report shows that Meta generated more leads at a lower cost than Google. The most immediate conclusion might be: let's increase our Meta budget.
But what if we discovered that contacts from Google schedule more appointments, request more quotes, and become customers more frequently?
Or that customers acquired through Google have a higher average value?
The decision could change completely.
This doesn't mean Google is better than Meta, of course. It depends on the industry, the product, the type of query, and many other factors.
It simply means that cost per lead is only the first indicator of a much longer process.
To evaluate the investment, we should also know how many contacts are actually reached, how many are qualified, how many lead to a deal, how many become customers, and the value of the sales generated.
Information that, in most cases, is not found in the campaign panel.
They are found in the CRM.
CRM is essential. But it must be used.
CRM should be the point where the company records the business history of each contact.
Did the request arrive? Did the salesperson call? Did the customer respond? Was an appointment scheduled? Was an offer sent? Was the deal won or lost?
In theory, it's simple. In practice, much less so.
Customer service people have other priorities: calling back, preparing quotes, scheduling appointments, and selling.
Updating your CRM can seem like an additional administrative burden, especially when the system is complicated or requires too much information to be entered.
It can happen that a contact is handled correctly, perhaps even transformed into a customer, but remains recorded in the CRM as a simple request for information.
From a marketing analytics perspective, that sale becomes invisible.
And if we don't know which contacts convert into customers, we can't even know with sufficient precision which campaigns contribute most to sales results.
The problem is not necessarily solved by purchasing a more sophisticated CRM.
Above all, a sustainable process is needed that allows salespeople to update a few essential pieces of information, possibly minimizing manual labor.
Even a relatively simple CRM, if well configured and used consistently, can provide valuable insights.
Reporting should help you decide where to invest
Connecting advertising data and business data changes the way we understand performance.
Instead of focusing on how much it costs to get a contact, we can start thinking about how much it costs to get an appointment, a qualified opportunity, or a customer.
We can compare channels not only by lead volume, but also by sales progression and value of closed deals.
This allows us to address the questions that really matter with more information:
Is it worth increasing the budget for a campaign that generates many leads but few sales?
Is a seemingly expensive channel actually generating more valuable customers?
If leads arrive but few become appointments, is the problem with the quality of the contacts, the response times, or the sales process?
Not all of these questions have an automatic answer.
An analytics system is no substitute for the experience of someone who understands the market and the customer. Furthermore, sales attribution to campaigns can be incomplete, especially when the purchasing journey involves multiple channels or spans several months.
But having commercial information related to investments allows for discussions on a much more concrete basis .
And this also improves collaboration between company and agency: both can observe the same process, compare the results and identify where to intervene.
How we're addressing this problem at Hangler
To make this analysis easier in our daily work, we developed Hangler Data Hub , a tool we use to integrate advertising campaign data with customer CRM data.
The system collects information from Google Ads, Meta Ads and Google Analytics 4 and links them, when available, to the business opportunities recorded in the CRM.
The goal is to observe the path from contact to the subsequent sales stages.
For example, we can analyze how many leads were generated, how many were contacted, how many arrived at an appointment, and how many were acquired as customers.
When the CRM also records the value of won deals, we can add a particularly important piece of information: how much business value is associated with the campaign results .
It's not a perfect measurement. Some contacts are reliably attributable, others only partially, and still others can't be definitively linked to a specific campaign.
For this reason, the Data Hub also highlights the level of data reliability.
We see it as a tool to improve decisions, not a machine that produces infallible answers.
Example of analysis in the Hangler Data Hub: the connection with the CRM allows you to observe the contact path even after the advertising conversion.
The Data Hub wasn't created to be sold as standalone software. We developed it to support our work and make it available to clients as part of our lead generation service .
In some projects, we use CRMs like Brevo, which allow us to manage business opportunities without having to resort to expensive and complex systems. In others, we integrate tools already used by the company.
The principle is the same: try to collect the necessary data without unnecessarily complicating the work of salespeople.
An integrated analysis of investments and commercial phases helps compare channels based on results, not just the number of contacts.
Business data can also improve campaigns
There is an additional benefit to connecting CRM to advertising activities.
Google Ads and Meta Ads use conversion signals to optimize campaigns.
If a platform only receives information that a user filled out a form, it knows that result, but not necessarily what happened next.
If, however, it is also possible to transmit reliable information about subsequent conversions, such as qualified leads, appointments, or sales, the platform can use signals that are closer to the company's commercial objectives.
This is the principle of offline conversions , which can help refine campaign optimization.
Of course, simply enabling an integration isn't enough: you need correct data, adequate volumes, consistent configurations, and compliance with privacy requirements.
But the point is important: correctly recording sales doesn't just help produce better reports. It can also create the conditions for improving future campaigns.
What about artificial intelligence?
AI introduces another possibility.
When campaign and sales data is organized, an analytics system can help identify anomalies, variations in conversion rates, differences between channels, and signals that deserve further investigation.
This is one of the developments we are working on for our Data Hub.
The goal is to complement traditional KPI reading with an analysis capable of examining multiple pieces of information simultaneously and suggesting where to focus attention.
But there is one limitation worth remembering.
No artificial intelligence can reliably reconstruct a sale that has not been recorded.
If business data is incomplete, even the most sophisticated analysis will start with incomplete information. Therefore, data quality and process organization come before AI.
Before asking for a better report, let's ask ourselves what data is missing
Today, there are accessible tools that allow even an SME to connect marketing and sales without building particularly complex infrastructures.
Technology is no longer necessarily the main obstacle.
The most important step is often organizational: determining who updates opportunities, what information is recorded, and how to connect it to campaigns.
You don't need to measure everything. You need to measure what allows you to make better decisions.
So, the next time we ask ourselves, “How are our campaigns going?” we might start with another question: Do we know what happened to the leads we generated?
If the answer is no, that's probably where you should start.
Because measuring marketing effectively isn't just about knowing how much we've spent. It means understanding the results we've achieved and having more solid evidence to decide where to invest tomorrow.
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