103: Case Studies: Paid Media and CRM – Closing the Attribution Gap (Office Hours)

Danny Gavin: 0:04

How much are you spending on pay media this quarter? A hundred thousand? A million? Now for the tough question. How much of that is actually driving revenue? For too many businesses, that answer is just a shrug. 

You pour money into Google Ads, you see clicks and impressions, but when you look at the sales data, there’s a massive black box in between. 

The connection is broken. 

Today we’re talking about the attribution gap, that critical yet often severed link between your advertising platforms and your internal CRM system. 

It’s the reason why so many marketing leaders can’t definitively prove their ROI, and it’s a problem that keeps CEOs up at night. I’m Danny Gavin, founder of Optidge, Marketing Professor, and the host of the Digital Marketing Mentor. And today we’re pulling back the curtain with the team at Optidge, a digital marketing agency that specializes in closing this exact loop. We’re going to walk through examples with two completely different businesses, a home services company and a massive real estate firm, each with a unique version of the same black box problem. 

Our first case takes us to Houston, Texas, a well-known family-owned moving and storage company. This was a client with high expectations. They knew their business, they knew their numbers, and they needed to see a clear return on their investment. 

The moving company uses a specialized CRM for the moving industry called Smart Moving, which is excellent for managing operations, scheduling jobs, and tracking leads. But the true challenge here was to move beyond simply counting leads and start measuring true return on ad spend based on actual closed one revenue. 

The problem was that Smart Moving, for all its operational strengths, was not designed with marketing attribution in mind. It was a data silo. It could tell you who became a customer and how much they paid, but that crucial information couldn’t easily flow back to Google Ads. This made it impossible to optimize campaigns for high-value customers versus low-value leads. Without a connection to revenue, every form fill or phone call looked the same. 

This is where Optidge’s data team, led by our analyst Alejandro, stepped in to build a permanent feedback loop between sales and advertising, a true marketing intelligence engine. It was a methodical step-by-step process. Step one was data extraction and enrichment. They worked directly with the client Joe, who played a hands-on role in exporting the raw sales data from Smart Moving. This gave them the raw material, a list of leads, and their final sales value. 

Then Alejandro set up automations to enrich these records with the original UTM parameters, tying every dollar of revenue back to the specific campaign, ad group, and keyword that generated it. Step two, advanced analytics in BigQuery. 

Next, they exported this newly enriched sales data into Google’s BigQuery. This unlocked a whole new level of analysis. 

They could now model the data to create a month-over-month accumulative sales report. This didn’t just show monthly revenue, it revealed the average sales cycle, allowing them to measure funnel speed and understand how long it takes for a lead to become an actual paying customer. 

With this system in place, the moving company finally had a holistic view of their marketing performance. They gained visibility into over 2,000 leads, achieving an average return on ad spend of 2.8, with the data showing a clear path to reaching 3.5. But the real strategic win was the ability to align their campaign optimizations with tangible business outcomes. They could now confidently shift budget toward campaigns that didn’t just generate leads, but generated faster, higher value customers. 

By building a data bridge, Optidge gave the moving company a unified view of their marketing funnel from click to cash. 

Optidge connected a single purpose-built CRM back to its ad platforms. But what happens when the data isn’t just in one silo, but fragmented across multiple enterprise-level systems that were never designed to speak to each other? That brings us to the complex world of high-volume real estate. 

Our second case study features an impressive, 100% digital, single-family rental company managing a portfolio of nearly 11,000 rental homes. 

Their entire business model relies on a seamless online experience, but their internal technology was a strategic liability. They operated with a fragmented stack where their marketing platform, HubSpot, and their property management, ERP, Entrada, were not properly synchronized. 

This created a massive attribution blind spot right in the middle of their lead-to-lease journey. As Optidge investigated, they uncovered a tangle of technical and procedural failures. They learned that for a lead to be properly worked by the leasing team, it had to be an Entrada. However, a previous vendor had only automated the data transfer for one specific form, the Contact Us for Future Residence form.

For every other lead form on the website, the marketing director Lauren had to follow an incredibly inefficient workaround. She’d have to manually download a list of leads from HubSpot and email it to the leasing team for manual upload. This process wasn’t just slow, it created significant data latency and integrity issues. Once in Entrada, every single one of these leads, whether from the single automated form or the dozen manual uploads, was classified under the same generic source, website. It was impossible to distinguish a lead from a paid search campaign from one that came from an organic search or even a direct visit. 

To show the real estate company team what was possible, Optidge created a proof of concept. We took a manual export from Entrada, the one that just said website, and merged it with the data from HubSpot using the prospect’s email addresses as the common key to stitch them together. For the first time, the real estate company could see the true origin of their leases. The data showed that, for example, 20 leases in quarter one came directly from Paid Search. Seeing this connection, the client’s reaction was immediate and enthusiastic, calling the insights pretty freaking cool. And that’s the moment the game changes. It’s when marketing data stops being a spreadsheet of clicks and becomes a ledger of signed leases. 

That’s a language the entire C-suite understands. This small manual proof of concept opened the door to a much larger strategic initiative. 

Optidge scheduled a meeting with the integration vendor to map out a path forward. The plan was twofold. First, to explore automating the data transfer for all the forms, from HubSpot to Intrada. And second, to begin the even more important work of creating a connection to pull final lease and revenue data back from Intrada into HubSpot, closing the attribution loop once and for all. 

This brings us to the core lesson of today’s episode. Two different businesses, two different industries, two wildly different tech stacks, but one universal problem. So what’s the common thread here? 

We looked at home services with smart moving and real estate with a fragmented HubSpot and Entrada system. 

On the surface, these problems look completely different. But fundamentally, these clients, like many of our other clients in other industries, were facing the exact same business challenge, a critical disconnect between their marketing spend and their business outcomes. They were flying blind, unable to prove what was working, what was broken, and where to invest for growth.

 What I find so compelling is that our solution in each case followed a repeatable strategic methodology. It wasn’t about a single piece of software, it was about a way of thinking. You can distill it down to three core principles. 

Number one, diagnose the real bottleneck. This is about going beyond surface-level metrics like clicks or even leads. It’s about finding the true point of failure. For some clients, it’s a high-friction user experience or low-to-no tracking visibility. Specifically for the moving company, it was the lack of revenue data, and for the real estate company, it was a broken system integration. 

Two, build the data bridge. Once you find the bottleneck, you have to connect the data. This means creating the necessary data pipeline to link marketing actions to business results. Sometimes that requires a scrappy manual process to prove the concept, and other times, it requires custom development. But the bridge must be built. 

And number three, prove the value and drive strategy. Finally, you use that newly visible data to do two things. First, you prove marketing’s ROI in a way that’s undeniable. And second, you deliver executive level insights that justify strategic investments in better technology, better processes, and ultimately smarter growth. 

The black box between ad spend and revenue is one of the most persistent problems in business today. But as these stories show, it is solvable. It requires curiosity, technical skill, and a relentless focus on connecting marketing activities to the metrics that the C-suite truly cares about: appointments, revenue, and leases. Closing that attribution gap isn’t just a marketing exercise, it’s a fundamental requirement for any business that’s serious about sustainable, data-driven growth. 

That’s all the time we have for today. To learn more about how you can connect paid media and CRM to equal performance, visit Optidge.com and be sure to subscribe wherever you get your podcasts for more deep dives into mentorship and solving complex digital marketing challenges. Thank you for listening to the Digital Marketing Mentor Podcast. Be sure to check us out online at thedmmentor.com and at the DM Mentor on Instagram. And don’t forget to subscribe on Apple Podcasts, Spotify, or wherever you listen to your podcasts for more Marketing Mentor magic. See you next time.