Adverank Training and Q&A Webinar - 11-20-2025

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Table of Contents

Introduction & Speakers
What Adverank Is
Overview of the New ROAS Module
Portfolio-Level ROAS View
Location-Level ROAS View
Setting Goals, Strategies, and Modes
Social Media “Boost” Recommendations
Adding New Users to Adverank
Classic Mode vs. Search Dominance vs. AI Learning
Edward: The In-Product AI Assistant
Wrap-Up, Services, and Next Steps

1. Introduction & Speakers

My name is Mitch Briggs, and I’m the Chief Marketing Officer here at Adverank. I’m joined by our co-founder and CEO, Jason Bales – many of you probably know him and have interacted with him several times. Jason is here to help answer questions and shed some light on how to get more value out of the platform.

We also have Betsy Kuleba with us, who is joining to help with customer support, service, and overall customer experience. So we’ve got the “dream team” here to walk you through what’s new in the product, answer any questions you have, and hopefully give you better insight into how to use the tool.

2. What Adverank Is

Before I dive into the new features, I want to give a quick reminder for anyone who is either new to Adverank, or new to their internal team and just joining these calls for a refresher.

Adverank is what we call an AI advertising assistant. It’s that piece of software that brings all your data together to make your budgeting and other decision-making easier. In addition to the daily emails you receive and the digest mode many of you use, I’d encourage you to log in regularly, explore some of the new features, and use Adverank as your internal platform for understanding how your ads are performing and what adjustments you should be making.

3. Overview of the New ROAS Module

For the first part of this session, I’m going to talk about the ROAS module we’ve added. That’s a new feature inside Adverank that you may have already poked around with or seen in some of our announcements. We’re really excited about it because it helps answer the big question: “Is this worth it?”

In other words:

Is the investment you’re putting into Google Ads generating a good return?
How should that return be calculated?
How should you think about attribution and related questions?

4. Portfolio-Level ROAS View

I’m going to jump over into the product now and show you a test account we use called Kloset Storage. All of the data you’re seeing there is dummy data, so some of the numbers might look larger than normal or a little odd, but it’s just to demonstrate how things work.

When you log in, you’ll be familiar with the summary screen. This view brings together all of your locations—whether you have five or a hundred—into a single report. The new ROAS module appears there as a section you can expand.

Once open, you’ll see all the data coming from your Google Ads campaigns:

Total impressions (how many times your ad has been seen in search results)
Total clicks (how many times people clicked and were driven to your site)
Online reservations generated
Total move-ins that occurred during that same time period while those ads were running

You can adjust the time frame to one year, one month, or other ranges, and the numbers update live. This top-level view also shows your total ad spend for that period—for example, around $8,500 in this demo—and how that translates into:

Cost per move-in
Cost per click
Cost per impression

All of that rolls into the main calculator that gives you your return on that $8,500. The key variable is how many of those move-ins you want to attribute to being influenced by your ads.

We start at 50% by default, but you can:

Move that up if you want to be more aggressive (e.g., “75% of these move-ins were probably influenced by ads”), or
Move it down if you want to be more conservative (e.g., “Only 25% were influenced”).

For demo purposes, you can even drag it down to 10% and say, “Of those 156 move-ins, I think only about 15 were actually influenced by ads.” Even at that conservative level, you can see what those 15 move-ins are worth to your business from a lifetime value standpoint.

If you hover over the lifetime value section, you’ll see that those 15 move-ins are worth about $55,000 in this example. We base that on your average length of stay and your average rent. That will be different for every location and portfolio and is pulled directly from your PMS data.

In this demo:

Average length of stay: 909 days
Average monthly rent: $119

We do the math for you to calculate that $55K lifetime value. So if you spent about $8,500 and generated $55K in lifetime value, that’s roughly a 5.5x return on investment. That’s a very positive result.

Generally speaking:

Anything over a 3x or 4x return is strong, especially because there are other costs built into that $8,500.
A 5x return is a good benchmark to aim for.

Remember, that example is using a very conservative attribution level of 10%. If you slide that attribution percentage up, you can see how quickly the return grows, even at 20–25%.

All of the existing tools are still here as well:

You can change what’s charted at the top.
You can see where the top five move-ins and move-outs are across your portfolio.
You can quickly move between portfolio-level and individual-location views.

5. Location-Level ROAS View

You’re not limited to just the portfolio roll-up; you can drill down into individual locations for more granular detail.

In the detailed location view, you’ll see the same layout you’re used to from the daily emails, including:

Recommended spend adjustments up or down based on performance.
A one-click option to confirm a recommendation.
The ability to click into any location for deeper detail.

You can:

Confirm adjustments for each site individually.
Modify them and choose a different budget than what we recommend.
Review more detailed performance metrics for the last week, month, or year.

In this location view, you’ll also see the ROAS module as a dedicated tab. That tab shows ROAS information specific to that one location.

For example:

You might see that you’ve spent $1,500 in a month and had 13 move-ins.
By default, we might attribute half of those move-ins to paid search.
You can decide whether you want to treat it as all of them, none of them, 10%, 25%, or anything in between.

The point is to give you a directional sense of whether the money you’re spending is generating the kind of lifetime value and return you expect.

The original performance data is still visible as well. You can:

See exactly when move-ins and move-outs occurred.
Compare that to your advertising data.

For example, the 62 clicks you see for a specific location in Adverank should match the 62 clicks you’re seeing in your Google Ads campaign for that location. Those numbers line up, and you can look at the other supporting metrics there as well.

Each location has its own ROAS view, so you can quickly see if some locations are producing a stronger return than others. That’s where you can start making budget adjustments or other changes to improve performance.

6. Setting Goals, Strategies, and Modes

I also want to offer a couple of quick reminders while we’re in the product. These different “modes” and goal settings are relatively new as well.

If you haven’t already done this for each of your locations, make sure you’re setting your occupancy goal. That lives in the goals and strategy area for each site. The goal you set will inform the budget decisions our AI engine generates.

The closer you get to your target occupancy, the more conservative the budget recommendations will be.
If you go past that goal, the system will recommend backing down spend so you’re not wasting money on facilities that are already getting too full.

You can also set your strategy on a spectrum from conservative to moderate to aggressive. Those strategy settings influence how big the budget adjustment recommendations will be. All of that feeds into the recommendations you see:

In your daily emails, and
Inside the dashboard.

On top of that, there are three modes:

Classic Mode
Search Dominance Mode
AI Learning Mode

AI Learning Mode requires about 90 days of data before it can be activated, but once it’s ready, that’s usually our most accurate and effective mode.

You can see your active mode in the interface; if you change to Search Dominance, you’ll see that reflected at the top. Search Dominance is the most aggressive mode—it’s designed to make sure your ads show as often as possible when someone searches for storage around your location. Classic Mode is more measured and looks at several data points to bring your spend up in more incremental steps.

Once you have enough history, AI Learning Mode becomes available, and that mode uses machine learning to look at a wide range of parameters including:

All the adjustments you’ve made
Your internal Adverank data
Your Google Ads data

It then course-corrects over time based on what actually works.

7. Social Media “Boost” Recommendations

Now I want to turn to some of the live questions we’ve received.

One question is: “What drives the social media boost recommendation?”

Inside the interface, you may notice that some locations have a purple “Social Boost” recommendation. That’s triggered when the platform sees occupancy levels dipping or plateauing over a period of time, even if you’re already running search ads.

When that pattern shows up, the system recommends that you consider social media advertising as a way to change things up and give that location a different push.

If you click into the recommendation, you’ll see it highlighted there. If you’re on our Go Bananas package, you can simply click the button, and it will send us a message that you’re ready to start a social media campaign for that specific site.

If you’re not currently on that package, you can talk with Jason about:

Upgrading that location to Go Bananas, or
Exploring other ways we can get that social boost started for you.

8. Adding New Users to Adverank

Another question is about adding new users or giving new team members access.

Right now, there isn’t a self-serve option in the product for that. To add users, just email ask@adverank.ai and let us know:

Who you want to add
Whether they should receive daily alerts
Whether they should have login access

You can also email Jason directly if you’re already in contact with him, and he can get those users set up as well.

9. Classic Mode vs. Search Dominance vs. AI Learning

We also received a question asking: “What’s the main driver of Classic Mode versus Search Dominance Mode?”

One of the biggest factors we look at for each location is on the Advertising tab: a metric we call PPC Ad Shortfall.

This comes from your Google Ads campaign for that location and tells us how often your ad is showing relative to how often it could show.

For example:

It might tell you your ads are only appearing about 20% of the time because you’re running out of budget.
In that scenario, you’ll see a recommendation to increase your budget.

In Classic Mode, Adverank looks at:

Your occupancy goal (e.g., 90%)
Your current occupancy (e.g., 53%)
Your current daily budget (e.g., $108/day)
Your PPC Ad Shortfall

Classic Mode allows a bit more room and tends to recommend smaller, incremental daily budget changes—maybe $20 or $30 at a time—to gradually reduce your PPC shortfall to something like 20–30%.

In Search Dominance Mode, the system is less incremental and more aggressive. It’s trying to drive that PPC shortfall number below 10% and capture as much search traffic as possible. That’s where you’ll see bigger swings in daily budget recommendations.

Search Dominance Mode is particularly useful:

During lease-up
When you really want to go after every possible search in your area

A helpful tip:

If your location is near a big competitor—say a national REIT or a large regional operator that’s spending heavily on paid advertising—Search Dominance Mode will try to put you right next to them and beat them for search visibility.
That means it may recommend more aggressive spend.

Classic Mode will still push you toward your occupancy goals, but more conservatively.

Once AI Learning Mode is available and you turn it on, that becomes the “best of both worlds,” because it uses machine learning and our broader dataset to refine recommendations based on actual results over time.

The system:

Leans into recommendations that result in reservations and move-ins.
Course-corrects away from recommendations that don’t perform well.

This isn’t just a large language model responding to prompts. It’s machine learning that compares your data to our entire (anonymous) data warehouse to make better decisions. The system doesn’t know whose data is whose; it simply uses performance patterns to refine suggestions.

If you log into Adverank and notice that the “Learning” label has disappeared for a location, that means AI Learning Mode is available. Give it a try—start with a conservative strategy if you like, and then move up as you get more comfortable. Also, check out the cheat sheet in our knowledge base for more detail on when to use each mode.

10. Edward: The In-Product AI Assistant

Another new thing I want to highlight is our in-product AI assistant.

If you look at the lower corner of the Adverank interface, you’ll see a little chat window. When you open that, you’ll meet Edward, our AI assistant.

Edward has been trained on all of our content:

Help articles
Demos
Previous training material

He can answer a lot of frontline questions, such as:

“How do I add a user?”
“What does this metric mean?”
“How do I change a mode?”

If Edward can’t answer something, he’ll:

Direct you to email ask@adverank.ai, or
Point you to a relevant help article.

Over time, he’ll get better as we add more training data.

For those of you who’ve seen us at events or visited our website, Edward is the name of our gorilla mascot. We’ve finally put him to work helping you directly in the product.

11. Wrap-Up, Services, and Next Steps

I’m not seeing any additional questions come in, so I’ll move toward wrapping up.

As a reminder, this is a recurring webinar that we host every two weeks. We won’t be meeting next Thursday—and we probably wouldn’t have anyway with Thanksgiving—but we’ll be back the following Thursday. In those future sessions, we’ll talk about what’s coming next, what we’re working on, and how we’re continuing to make Adverank an even more effective platform to manage your ads and ad spend.

As always:

If you’re looking to get more locations onto Adverank, or
If you’re interested in additional services like retargeting or Facebook/Meta ads that may not be in your current package,

reach out to Jason and let him know what you’d like to add or upgrade.

You can always contact us at ask@adverank.ai, and don’t forget that our knowledge base is constantly growing with new articles and resources. If you have feature suggestions or ideas for knowledge base content, please share them—your feedback helps us create better tools and documentation for everyone.

We really appreciate everyone who joined today and the questions you asked. We’ll post this session in the knowledge base as well. You do need to register for each upcoming webinar individually, so we’ll share links where you can sign up and invite others on your team.

Thanks again for attending, have a great Thanksgiving, and we hope to see you in two weeks.