I'm Scot Dubert. For 20+ years I've helped companies decide where their ad dollars go, figure out whether the numbers behind those decisions can be trusted, and fix the systems when they can't.
Get in touchIn most companies this work is split across silos: someone runs the ads, someone else owns analytics, a developer owns the tracking, and nobody owns the question of whether the whole thing makes economic sense. I work across all of it. Most of the job comes down to helping you structure your campaigns and your measurement so you can choose what you're optimizing for, whether that's the best return on your spend or maximum volume at a target profit margin, and then actually hit it. Right now that adds up to several million dollars a year in ad spend for a handful of clients.
Campaign strategy and hands-on management across Google Ads and Microsoft Ads, plus ChatGPT, Meta, and LinkedIn when they make sense for the business. I handle account structure, bidding, and budgets, and I manage them against cost per qualified outcome and margin.
Buyers call, fill out forms, talk to sales, go quiet, and come back through a different door. The revenue usually lands in a CRM or a warehouse the ad platforms never see. I build the attribution layer that stitches those paths together, with reports and dashboards that show where the incremental value is coming from. Then I feed that data back into the ad platforms so the bidding optimizes for revenue instead of traffic.
All of this depends on the plumbing. Conversion tracking that actually fires, product feeds, analytics, and the data connections between your website, CRM, call tracking, and warehouse. I read the code, write the SQL, and give your developers specs they can implement without a lot of back and forth. Lately I've also been building automated systems that watch the plumbing and the performance data as it comes in, catching problems and opportunities that would be too labor-intensive to monitor by hand.
We spend a lot, but we're not sure how much we should trust the numbers.
I reconstruct the measurement chain from click to revenue and reconcile it across every system it touches. Usually that turns into an attribution report that ties ad spend to actual CRM revenue, an audit of what the platform's conversion numbers really count, and dashboards the whole team can trust.
Conversions are up, but revenue isn't.
Usually the bidding system is being trained on the wrong signal. I trace lead quality through the CRM and sales outcomes, then redesign the conversion feedback so the algorithm learns from customers instead of form fills.
We're paying for the traffic, but the site isn't converting it.
Conversion rate optimization is where my consulting practice started 20 years ago, and it's still part of the job. I look at landing pages, forms, calls, and checkout to find where visitors stall, then test changes and measure the wins in qualified leads and revenue instead of soft metrics. It pairs naturally with the media work, because improving the site raises the return on every ad dollar you're already spending.
How much of this would have happened anyway?
This is one of the most common requests I get. I design and run tests to estimate the true incremental value of paid channels, using holdouts, controlled comparisons, and honest before-and-after analysis. And when the data can't support a causal claim, I'll tell you that plainly.
Something changed, and every team has a different explanation.
One investigation across the ad account, the website, the tracking, and the warehouse, ending in a mechanism and a decision. Part of the value is that I'm a neutral party. I don't own any team's version of events, so I can follow the data wherever it goes. A recent example was a lead drop that looked like lost demand but turned out to be junk traffic getting cleaned out. The right move was to change nothing.
How much should we spend, and where should the next dollar go?
I build spend models that connect budget to marginal profit, then set targets and implement the changes necessary to hit them. It's the difference between "our CPA looks fine" and knowing where growth stops paying for itself.
My ideal client has meaningful ad spend and a business that's too complex for dashboard-level answers. Long sales cycles, buyers who arrive through several doors, revenue data that lives in a CRM or a warehouse instead of the ad platform. Almost all of my work comes through referrals, and most relationships run for years. Here's what a few of those clients say:
JES has been working with Scot for about 5 years now and in every one of those years he's added millions of dollars in revenue. He manages many types of projects for us, including traffic purchases, SEO, shopping cart migrations, content creation and promotion, and conversion rate optimization.
We gave Scot and his team an extremely aggressive goal: to increase online revenue by 1,000% within a year. They were able to accomplish that and more within 8 months. Scot is world class at conversion rate optimization, AdWords, web analytics analysis, and working with shopping cart technologies.
Dubert Consulting helps us to generate high quality leads and increase our eCommerce sales. Our business is very specialized, so a lot of the normal best practices don't work. Scot is great at creating and implementing strategies tailored to our customers that measurably increase sales.
Behind the consulting work is software I built for the job. Dubert Consulting Ads Manager is our internal tool for managing client Google Ads accounts through the Google Ads API: daily performance reporting, search-term mining to cut wasted spend, and account snapshots for auditability. Every proposed change is staged for human review before it touches a live account. The tool is used only by Dubert Consulting on accounts we manage, and how it handles data is covered in our privacy policy.
The same approach runs my Microsoft Advertising work and campaigns on newer platforms like ChatGPT Ads, and it's part of a larger set of AI-assisted systems I've built for research, analysis, and automation.
I work with no more than five clients at a time and take on one or two new engagements a year. That's what lets me go deep instead of wide. I don't ask for long-term contracts either. The work has to keep proving itself, month after month. New work usually starts as either an ongoing paid media and measurement engagement or a fixed-scope project, like an attribution rebuild, a tracking audit, or a spend model. If your situation sounds like the problems above, tell me about it.
The most useful first message tells me what you're seeing. What the numbers say, what you think is actually happening, and what decision you're trying to make.
I read everything myself and I'll tell you honestly if I'm not the right fit.