How to Determine the Right Paid Media Budget

One of the questions we hear most often is: “How much should we invest in paid media?”

The truth is, there’s no one-size-fits-all answer. The right budget depends on your business goals, historical performance, competitive environment, and growth plans.

The most effective paid media budgets aren’t based on gut feel or arbitrary percentages of revenue. They’re built by looking at multiple data points and understanding what level of investment is needed to achieve a specific outcome.

When determining your paid media budget, we recommend starting with these six considerations:

1. Start with historical performance

Look at what you’ve invested in previous periods and, more importantly, what those investments produced.

Did your spend generate the leads, sales, revenue, or other outcomes you were targeting? How did performance change as you increased or decreased investment?

Historical performance gives you a valuable baseline for understanding what your media budget can realistically deliver—and where there may be opportunities to improve.

2. Understand your financial guardrails

Every organization has budget realities. Before determining what you could spend, establish what you can reasonably spend.

Your budget should support your business objectives while remaining financially practical. In other words, you want a level of investment that drives growth without causing your CFO to spray out their coffee.

3. Work backward from your goals

If you have reliable historical metrics—such as cost per lead (CPL), cost per acquisition (CPA), or return on ad spend (ROAS)—use them to work backward from your objectives.

For example, if your goal is to generate 500 leads and your historical cost per lead is $100, that gives you a starting point of approximately $50,000 in media investment needed.

Of course, real-world performance isn’t always perfectly predictable. But starting with your desired outcome and applying historical benchmarks is often one of the most effective ways to estimate the investment required.

4. Improve efficiency before simply increasing spend

More budget doesn’t automatically mean better results.

Before increasing your investment, take a close look at your creative, messaging, targeting, audience strategy, media mix, and campaign structure. Are you getting as much as you reasonably can from your existing spend?

In many cases, improving efficiency can allow the same budget to generate stronger results. Once you’ve optimized what you can, you’ll have a much clearer picture of whether additional investment is likely to produce incremental growth.

5. Consider the competitive landscape

Your budget doesn’t exist in a vacuum. What your competitors are doing can influence how much investment is required to maintain or increase your visibility.

If competitors are increasing their spending, your share of voice may decline if your investment remains flat. Competitive pressure is particularly important when entering crowded markets, launching new products, or trying to gain market share.

You don’t necessarily need to match your competitors dollar-for-dollar (or tactic-for-tactic)—but you should understand the competitive environment when setting your budget.

6. Account for what’s changing

Your future budget shouldn’t be based solely on what you spent last year.

Are you entering a new market? Launching a new product or service? Supporting additional business units? Expanding your geographic footprint? Increasing your growth targets?

Any meaningful change in scope or business objectives should be reflected in your media plan. A budget that was appropriate for last year’s goals may not be sufficient for this year’s ambitions.

The Bottom Line

Determining a paid media budget isn’t about picking a number and hoping it works. It’s about balancing business goals, historical performance, financial realities, competitive dynamics, and growth opportunities.

The strongest budgets are built from data and strategy—and grounded in realistic expectations about what your investment can achieve.

If you’re trying to determine the right paid media budget for your business, we can help you work through the numbers and build a plan around your goals.

Reach out anytime at info@catalystmediadesign.com or 480-471-8390.

 

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Political Advertising’s Ripple Effect: Is Your Media Plan Ready for the 2026 Election Cycle?

Political advertising will continue to affect the paid media marketplace, and brands should be prepared for another highly competitive environment as the 2026 midterm election cycle accelerates.

The 2024 election cycle became the most expensive in U.S. history, with political advertising spending surpassing $11 billion nationwide. While Presidential election years typically generate the largest overall spend, midterm elections still bring substantial advertising activity, particularly in battleground states and competitive congressional, gubernatorial, and ballot initiative races.

Markets such as Phoenix, Philadelphia, Atlanta, Las Vegas, Milwaukee, Detroit, and Raleigh are expected to remain among the most heavily impacted by political advertising due to their importance in statewide and federal elections. Political advertisers are also beginning campaigns earlier than ever, extending the period of market disruption well beyond the traditional September–November election window.

At the same time, media consumption habits continue to evolve. While Broadcast Television remains a critical component of political advertising strategies, campaigns are increasingly investing in other media channels that allow for highly targeted voter outreach. As a result, political advertising now affects a much broader range of media outlets than ever before.

WHAT MEDIA OUTLETS WILL BE AFFECTED?

Political advertising has historically been concentrated in Television and remains a major driver of demand. However, the modern political media mix is significantly more diversified.

Today, campaigns are investing heavily across:

  • Broadcast Television
  • Cable Television
  • Connected TV
  • Streaming Video
  • Digital Video
  • Social Media
  • Search Advertising
  • Audio Streaming and Podcasts
  • Radio
  • Direct Mail
  • Out-of-Home

Streaming and Connected TV have become particularly attractive because they combine television-like viewing experiences with digital targeting capabilities. Political advertisers can now reach voters based on demographics, geography, interests, and even voting behavior models.

Radio continues to attract political spending, particularly on News/Talk formats, Sports programming, and stations serving rural communities. Podcasts and streaming audio platforms are also seeing increased investment due to their ability to reach highly engaged audiences.

Digital Out-of-Home inventory, including digital billboards and place-based media, is increasingly being incorporated into political media plans as campaigns seek additional reach and frequency.

In addition, many commercial advertisers displaced from Television begin redirecting budgets into Streaming, Radio, and Out-of-Home. This secondary demand can create inventory pressure even when political campaigns are not directly purchasing large amounts of those channels. In other words, Television often serves as the starting point for a broader marketplace squeeze that impacts multiple forms of media.

In short, virtually every advertising channel is now impacted by election spending to some degree.

WHAT DOES THIS MEAN FOR YOUR BUSINESS?

It all comes down to supply and demand.

Political advertisers often enter the marketplace with large budgets, aggressive timelines, and legal protections that can make inventory difficult to secure for commercial advertisers.

Political advertising creates more than just direct competition for Television inventory. As campaigns flood Broadcast and Cable Television with spending, commercial advertisers are often forced to shift budgets into alternative channels such as Streaming Video, Connected TV, Radio, Audio Streaming, Digital Video, and Out-of-Home.

This migration creates a ripple effect throughout the media marketplace. Demand increases not only for Television inventory, but also for the channels advertisers use as substitutes when Television becomes unavailable or too expensive. As a result, inventory constraints and rate increases can extend well beyond Television and affect multiple media channels simultaneously.

In highly contested markets, advertisers may find that premium Streaming inventory, popular Radio programming, and high-visibility Out-of-Home locations become more difficult to secure as election activity intensifies.

For businesses, this means it is more important than ever to plan early and remain flexible.

Work closely with your agency or media partners to anticipate inventory challenges and develop contingency plans before election activity peaks.

If your Television schedule is disrupted or inventory becomes prohibitively expensive, consider alternative tactics such as:

  • Leveraging broadcasters’ digital and streaming assets to reach similar audiences
  • Converting portions of Television or Radio budgets into Connected TV or Streaming Audio
  • Increasing investment in Search and Paid Social to maintain audience reach
  • Testing new media combinations such as Radio + Outdoor or CTV + Paid Social
  • Utilizing first-party customer data for targeted digital campaigns
  • Partnering with complementary brands to expand audience reach through shared marketing initiatives

Election cycles can create challenges, but they also create opportunities for advertisers willing to adapt.

HOW TO PROTECT YOUR MEDIA PLAN DURING ELECTION SEASON

If your brand prefers to avoid political environments altogether, consider channels where political advertising is limited or unavailable.

These may include:

  • Public Television
  • Certain streaming platforms
  • Sponsorship-based media opportunities
  • Direct-to-consumer channels such as email and SMS (text) marketing
  • Owned media properties including websites, blogs, and customer communities

These channels often experience less pricing volatility and fewer inventory disruptions during election periods.

For brands that rely heavily on Television, maintaining a presence remains possible with proper planning.

Strategies may include:

  • Securing inventory earlier than usual
  • Paying premium rates for guaranteed placements
  • Incorporating shorter ad units
  • Purchasing sponsorships tied to specific programming
  • Expanding into non-news programming environments
  • Utilizing dayparts with lower political demand
  • Integrating Broadcast, Cable, and Streaming inventory into a unified strategy

The key is recognizing that flexibility often becomes more valuable than perfection during election season.

SHOULD YOU PAUSE ADVERTISING DURING ELECTION SEASON?

Not necessarily.

Many advertisers assume they should reduce spending during election periods, but increased media consumption often creates valuable opportunities.

Before reducing or pausing your advertising, consider:

  • The role awareness advertising plays in your sales funnel
  • Historical performance during prior election cycles
  • The impact of reduced brand visibility on long-term growth
  • Increased audience engagement with news and media content
  • Whether alternative channels can realistically replace lost reach

For some brands, maintaining visibility during a crowded media environment can provide a competitive advantage when competitors pull back.

For others, shifting budgets into less impacted channels may be the smarter approach.

The answer depends on your objectives, audience, and tolerance for marketplace volatility.

WHY YOU MUST PIVOT DURING AN ELECTION YEAR

Running the same advertising plan implemented in a non-election year can be risky.

Political spending fundamentally changes the marketplace by increasing competition, raising costs, reducing inventory availability, and creating uncertainty around campaign delivery. The impact often begins with Television, where political advertisers command significant inventory, but it rarely stops there. As brands seek alternative ways to maintain reach and frequency, additional demand flows into Streaming, Connected TV, Radio, Audio, Digital Video, and Out-of-Home, creating broader marketplace pressure across multiple channels.

To remain effective, advertisers may need to:

  • Increase budgets to achieve the same communication goals
  • Expand beyond traditional media channels
  • Be more flexible with placements and scheduling
  • Test emerging tactics and platforms
  • Spend more time monitoring and optimizing campaigns
  • Develop contingency plans for inventory disruptions

Brands that adapt quickly typically outperform those that attempt to force a business-as-usual approach during election periods.

TOP FIVE TAKEAWAYS

Here are our five key recommendations for maximizing your advertising investment during an election cycle:

  1. High political spending does not mean you should stop advertising.

Many brands continue to achieve strong results during election periods by adapting their strategies rather than retreating from the marketplace.

  1. Communicate early and often with your agency and media partners.

Develop contingency plans and alternative inventory options before political demand reaches its peak.

  1. Be flexible and willing to test new channels.

Political demand often starts in Television but can quickly affect Streaming, Radio, and Out-of-Home inventory as advertisers shift budgets. Election years frequently create opportunities to discover media tactics that can improve performance long after the election ends.

  1. Stay informed and adapt quickly.

Political advertising is dynamic. Market conditions, inventory availability, and pricing can change rapidly.

  1. Plan earlier than you think you need to.

The brands that secure inventory, negotiate rates, and develop backup strategies well in advance are typically the best positioned for success when political spending intensifies.

Election cycles create challenges for advertisers, but they also create opportunities. With thoughtful planning, strategic flexibility, and a willingness to explore new media options, brands can continue to reach their audiences and achieve their goals—even during the most competitive political advertising environments.

And if you need help, reach out to the team at Catalyst Media Design at 480-471-8390 or info@catalystmediadesign.com.

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Why Many AI Results Feel Generic (And What Better Teams Do Differently)

One of the most common reactions to AI is also one of the most telling: “It’s fine… but it’s kind of generic.”

The outputs are clean. Grammatically correct. Even directionally helpful. But they lack depth. They lack specificity. And they don’t feel particularly tailored to your situation.

That’s not a limitation of the tool—it’s a reflection of how it’s being used.

AI Doesn’t Work Like Traditional Tools

Part of the disconnect comes from how people think AI works. Most software tools we’ve used for years—Excel, Word, PowerPoint—have predefined capabilities. Their functions are fixed. You input data, and the tool performs a specific, predictable action.

AI doesn’t work that way. It combines what it was trained on with the context you provide and generates something in between. That means the output isn’t fixed—it’s shaped by the interaction with you.

Which also means the quality of the output is highly dependent on the quality of the input.

The Real Issue With AI Isn’t the Output—It’s the Input

AI will respond to whatever you give it:
If the input is broad, the output will be broad.
If the input is vague, the output will be generic.

That’s where most teams get stuck. They’re interacting with AI the way they would a search engine: short request, minimal context, expectation of a complete answer. Then AI fills in the gaps the only way it can—by generalizing.

What Better Teams Do Differently Working With AI

The teams getting real value from AI approach it differently. They don’t just ask for answers—they set it up to succeed. That usually means being more intentional about a few key things, making sure to tell AI the answers to the following when providing your prompt:

– Role – Who should the AI “be” in this scenario?
– Goal – What are you actually trying to accomplish?
– Audience – Who is this for?
– Context – What information matters here?
– Output – What does a useful response look like?

This also helps you to be clear on what it is you’re asking for; to provide that level of input, you have to know what you’re actually trying to do.

One additional shift we’re seeing with more advanced users is how they interact with AI after the initial prompt. Instead of expecting a perfect answer on the first try, they use AI as part of a back-and-forth process. This might look like:

  • Asking AI what additional information would improve the response 
  • Having it identify gaps or assumptions in the original input 
  • Prompting it to ask follow-up questions before providing a final answer 
  • Or even asking it to challenge the direction entirely


In other words, they’re not just giving AI instructions—they’re collaborating with it. That tends to produce much stronger outcomes, because it forces more complete thinking on both sides of the interaction.

This Isn’t About Writing Better Prompts

It’s easy to reduce this to: “You just need to learn how to prompt better”, but that oversimplifies it. The real skill isn’t typing better instructions—it’s thinking more clearly, by clarifying the problem, defining success, understanding what information matters, and communicating that effectively. If the thinking is vague, the output will be too.

Why This Matters More Than It Seems

When teams rely on generic outputs, ideas start to sound the same, strategies become less differentiated, and decisions become easier—but not necessarily better. This can create the illusion of progress: things move faster, but not necessarily forward.

The Bottom Line

AI isn’t inherently generic. But it will produce generic results if it’s given generic input.

And as these tools become more widely used, the real differentiator won’t be access to AI—it will be how effectively it’s used.

Closing Thought

If your experience with AI has felt underwhelming so far, you’re not alone. In many cases, it’s not the tool—it’s how it’s being applied.

It’s an evolving skill set, and one that’s becoming more important quickly. If your team is working through what that looks like, you’re not alone.

 

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently

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What AI Can’t Replace (And Why That Matters)

There’s a lot of conversation right now about what AI can do. The list is long: it can analyze data, generate ideas, summarize information, produce polished outputs, and even help plan your Girls’ Trip to Napa.

But as AI becomes more capable, the more important question isn’t just what it can do—it’s what it can’t. 

AI Can Process Information. It Can’t Fully Understand Context

AI works off patterns and inputs—but it doesn’t understand what’s happening around those inputs. It doesn’t know what’s changed internally, what conversations have already happened, what constraints are in play, or what tradeoffs matter most.

That gap matters more than it seems. Most real decisions aren’t made in isolation—they’re shaped by shifting priorities, internal dynamics, and context that lives outside the data.

For example, AI might recommend reallocating budget based purely on performance data. On paper, it makes sense. But it doesn’t know that the channel supports a broader initiative, or that leadership has already aligned on a different priority. That context lives outside the model—and without it, even the most logical recommendations can lead in the wrong direction.

AI Can Generate Ideas. It Can’t Make Judgments

AI is very good at producing options. But deciding between those options requires a human lens. Judgment comes from experience—knowing what’s worked before, understanding tradeoffs, and recognizing when there isn’t a clear right answer. It also comes from context, intuition, and, at times, simply knowing when something doesn’t feel right.

AI can generate multiple campaign directions, each with a clear rationale. But it can’t weigh long-term versus short-term impact in a meaningful way, align those ideas with broader business priorities, or make a call when the data isn’t definitive.

AI Can Analyze Patterns. It Can’t Build Relationships

Marketing doesn’t happen in a vacuum, it involves clients, internal teams, partners, and stakeholders who all bring different priorities, perspectives, and expectations.

AI can’t navigate those dynamics. It can’t build trust over time, read the room in a meeting, or understand how a recommendation will land with a specific audience. It also can’t account for the nuances that come from long-standing relationships or institutional knowledge. These things don’t show up in a dataset—but they influence outcomes in very real ways.

AI Can Move Fast. It Doesn’t Know When to Slow Down

Speed is one of AI’s biggest advantages. It can analyze, generate, and respond in seconds. But not every decision should be made that quickly.

AI might push toward optimizing performance based on recent data. But experienced teams know when to pause, gather more context, or avoid overreacting to short-term signals. They’ve seen patterns before. They understand the difference between a real trend and a temporary fluctuation. Sometimes the best decision isn’t the fastest one—it’s the one that takes a step back.

What This Means Going Forward

AI isn’t replacing the need for expertise—it’s changing where that expertise shows up.

As more execution becomes automated, the real differentiator becomes how decisions are made, how tradeoffs are evaluated, and how strategy is shaped. In other words, the value shifts from doing the work to directing that work effectively.

The Bottom Line

AI is a powerful tool. But it doesn’t replace context, judgment, or experience—and those are the things that ultimately determine whether a strategy works.

Closing Thought

As AI becomes more integrated into how teams work, the goal isn’t to remove the human element—it’s to apply it more intentionally.

If you’re thinking through what that balance should look like for your team, you’re not alone. It’s an evolving space—and one worth navigating thoughtfully.

 

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently

 

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Using AI Is Easy. Using It Well Is Not.

After the initial wave of excitement around AI, most teams are now asking a more practical question: Where does this actually add value? Because while using AI is easy, using it well is something else entirely.

The difference isn’t between teams that are using AI and those that aren’t. It’s between teams that are using it intentionally and those that are using it indiscriminately.

The Biggest Mistake: Treating AI Like It Has the Answers

One of the most common patterns is using AI as a shortcut to conclusions.

Ask a question → get an answer → move forward.

When it’s used this way, you tend to get generic recommendations, overconfident conclusions, and outputs that reflect the prompt more than reality. Over time, that leads to an erosion of strategic quality.

AI wasn’t designed to replace thinking—it works best when it’s pushing your thinking further.

 

Where AI Actually Adds Value

Used well, AI isn’t a decision-maker—it’s a thinking partner. It can act like a virtual roundtable of perspectives, helping you expand, challenge, and organize your thinking.

AI can be particularly effective in these three areas:

  1. Generating Possibilities

AI is excellent at helping you explore options you may not have considered. Instead of asking for “the answer,” strong teams use it to widen the field.

Example: Instead of asking AI to write your email or proposal, you ask it to generate 5–7 different approaches based on different priorities or audiences. The value isn’t in choosing one—it’s in seeing options you may not have initially considered, and using that as a starting point for your own thinking.

  1. Refining and Stress-Testing Ideas

Once you have a direction, AI becomes more valuable as a challenger than a creator.

Example: You can upload an idea or point of view and ask AI to poke holes in it—what assumptions you’re making, what perspectives might be missing, or how different stakeholders might react. You can even have it respond as if it were a CFO, a customer, or an internal team member.

This is where AI helps remove blind spots—especially when you’re too close to the work.

  1. Structuring and Organizing Information

AI is also very effective at turning unstructured thinking into something more usable.

Example: After a brainstorming session or rough draft, you can have AI organize the information into a clear framework, summarize key themes, or structure it into a more polished outline. Instead of starting from a blank page, you’re refining something that already exists.

Where AI Falls Short

AI struggles in areas that require context, prioritization, and real-world experience.

It doesn’t know what’s changed internally, what conversations have already happened, or what matters most to your organization. It can’t fully understand tradeoffs or long-term implications.

And without that context, even strong outputs can lead in the wrong direction.

The Shift: From Doing the Work to Directing It

AI doesn’t eliminate the work—it changes where the value sits.

Historically, a lot of time has gone into execution: building, analyzing, refining. AI can now handle pieces of that faster and at greater scale. But that doesn’t reduce the need for expertise—it raises the bar for it.

Because someone still has to decide what the right problem is, provide the context AI doesn’t have, interpret what comes back, and ultimately make the call.

That’s where the value is shifting. AI can play the instruments, but you’re still responsible for how the song comes together.

What This Looks Like in Practice

In practice, strong teams don’t hand work off to AI—they work alongside it. They use it to explore options before deciding, to challenge their own thinking, and to organize ideas more efficiently. But they remain firmly in control of the strategy, the decisions, and the outcomes.

AI is involved in the process—but not in charge of it.

The Bottom Line

AI can absolutely improve speed, efficiency, and output quality. But it is only as good as the context you give it, and needs to be used with thoughtfulness and intention.

In practice, that often comes down to how you prompt it. Vague inputs lead to generic outputs, while specific inputs—clear goals, audience, and context—lead to something much more useful. That’s one of the biggest gaps we see today.

The teams seeing the most value aren’t the ones using it the most. They’re the ones using it most thoughtfully.

Closing Thought

We’re continuing to test where AI meaningfully improves how we work, interact, plan, analyze, and execute—and where it doesn’t.

If your team is working through similar questions, you’re not alone. It’s an evolving space—and one worth navigating thoughtfully. We’re always happy to compare notes.

 

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently

 

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AI Is Confident—Even When It’s Incorrect. Here’s What That Means for You.

AI is very good at sounding right—even when it isn’t.

It sounds confident, never uncertain, and very, very smart. The word “intelligence” is in its name, and it has all of the data the internet can hold at its fingertips. It’s easy to type in a question or request and take what it gives you at face value. But confidence and correctness are not the same thing—and that gap is where risk starts to show up.

As more teams begin using AI in their day-to-day work, the biggest issue isn’t outputs that are obviously wrong; those are easy to spot and to correct. The bigger concern is outputs that are incorrect, but convincingly so—meaning the data looks accurate, has citations that sound real, and the response logically sounds like it would be the answer. But it’s still not accurate, and if you’re moving quickly, that can be easy to miss.

The Real Risk of Relying on Exclusively on AI: “Plausible” Answers

When AI makes a mistake, it rarely looks like a mistake. It looks like:
– A well-written recommendation
– A clean summary of “insights”
– A logical next step

If something is missing, outdated, or misunderstood, the output can still sound polished while being directionally off. That’s what makes this tricky. You’re not spotting obvious errors—you’re trying to find the mistakes in something that inherently sounds right.

Where AI Goes Wrong Most Often

There are a few consistent patterns when working with AI tools:

1. Hallucinations (aka invented information)

AI can generate statistics, examples, or even citations that don’t actually exist. They’re presented clearly and confidently, which makes them easy to trust at a glance.

Example: Asking AI for industry statistics and receiving something like: “According to a 2023 Nielsen report, 68% of consumers prefer brands that advertise consistently across multiple channels.”

It sounds credible, cites a well-known source, and uses a precise statistic—but when you try to track down the report, it either doesn’t exist, or the number provided is incorrect or tied to a different claim.

2. Overconfidence

AI rarely says, “I’m not sure.” It tends to present answers as complete—even when they should come with caveats or uncertainty.

Example: AI presenting a recommendation as “the most effective strategy” without acknowledging tradeoffs, limitations, or alternative approaches.

3. Bias and Framing

AI often simplifies complex decisions or presents one path as the “best” option, without fully exploring tradeoffs or alternatives.

Example: Suggesting that “older audiences don’t engage with digital channels like podcasts or streaming,” and recommending shifting budget away from those platforms—using a broad overgeneralization (bias) without exploring how different segments within that audience and that market actually behave.

Why This Matters in Practice

These gaps aren’t just theoretical—they show up in real AI responses, whether it’s Gemini, GPT, Claude, or other tools, and affect real decisions being made by individuals, companies, and team members.

For example:
– Relying on AI-generated research that includes outdated or inaccurate sources
– Making decisions based on analysis that sounds complete but is missing key context
– Acting on recommendations that optimize for the wrong outcome

These aren’t always dramatic failures. More often, they’re subtle misalignments—and those are harder to catch. In a marketing and media context, for example, this can look like:

– AI recommending publications or channels that no longer exist or aren’t relevant in their current form
– Prioritizing short-term performance without accounting for seasonality or long-term brand strategy
– Suggesting budget shifts that make sense in isolation but conflict with broader campaign goals
– Missing nuances in performance data that aren’t visible without deeper context

How We Pressure-Test AI Outputs

The goal isn’t to avoid AI, it’s to use it with the right level of scrutiny. One of the most effective ways to evaluate AI outputs is to ask the tool itself questions like::

– “Where might you be wrong?”
– “What assumptions are you making?”
– “What context could change this recommendation?”
– “What should I verify before acting on this?”

These prompts don’t just improve the output—they shift how you engage with it. Instead of treating AI as an answer engine, you start treating it as a thinking partner.

The Bottom Line About Using AI

AI is a powerful tool. But it’s still a tool, and a relatively new one that is still evolving and growing. The more capable it becomes at generating answers, the more important it is to evaluate those answers critically.

Because, in most cases, the risk isn’t that AI gives you something obviously wrong. It’s when it gives you something that sounds right—and moves you in the wrong direction entirely.

Closing Thought

We’re actively building this kind of thinking into how we use AI within our agency, for ourselves and our clients.

If your team is navigating similar questions, please reach out. It’s a conversation worth having.

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently

 

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AI Is Changing the Work. It’s Not Replacing It.

I recently completed the Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” with the goal of better understanding how to use AI and how AI tools actually fit into the way we work—not just in theory, but in practice. As part of that process, I’ve been translating those learnings into real-world application for our team and our clients, while also pressure-testing them against day-to-day realities. This blog series is a reflection of those takeaways—shaped by the Masterclass teachings, hands-on use, practical experience, and, fittingly, collaboration with AI tools like ChatGPT to help organize and refine the thinking.

AI has quickly become part of the conversation in almost every industry, often framed in best case or worst case extremes—either as a transformative breakthrough or a looming replacement for existing roles. But most of those conversations focus heavily on what AI can produce, rather than on how those outputs are actually created or evaluated.

At this point, there is some general agreement on what AI is capable of. It can analyze data, generate ideas, summarize information, and produce structured outputs at speed. However, focusing only on those capabilities misses the more important shift underneath. Unlike traditional tools, AI does not operate within a fixed set of functions. It combines what it has been trained on with the context it is given, producing outputs that are shaped by that interaction.

As AI takes on more execution, the value of the work shifts. Less value sits in producing outputs, and more value sits in defining problems, providing context, asking better questions, and making educated final decisions. AI can support thinking, but it does not replace the need for it.

This shift is about redefining what good work looks like. Speed alone is no longer the differentiator. Thoughtfulness and relevance drive value.

What we are seeing is not a gap in access—it is a gap in approach. Some treat AI as a shortcut; others treat it as a collaborator. The difference in outcomes is significant. AI is powerful, but not strategic on its own. It requires direction, context, and judgment. As adoption grows, the advantage will come from how intentionally these tools are used. This perspective will be explored across the rest of this series.

If you are working through what that balance looks like, you are not alone!

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently

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Television Advertising in an Election Period

by Liz Scott, CEO at Catalyst Media Design

 

Every election cycle, we get asked if advertisers should change up their strategies, particularly when it comes to Television advertising. And the answer is, of course, it depends. 

But let’s start by first taking a step back. Television, in particular Broadcast TV, has historically been the highest spend category with political advertisers. This is due to the quick and broad reach that Television is able to provide, particularly among voters, who skew older, as well as in part due to the access and protections provided to these advertisers by the Federal Communications Commission. This includes eligibility for a station’s lowest unit charges (LUCs) during an election period, which is defined as the 45-day period prior to a primary election and the 60-day period prior to a general election.

For non-political advertisers running during these time periods, this creates a challenge, as it generally translates into the reduced availability of spots and higher rates than they are used to paying. It also means that their schedules are much more susceptible to pre-emption, which is when their ads are “bumped out” to allow political and/or higher paying advertisers’ spots to run.

So why would a general advertiser want to advertise during an election period?

For several reasons, including if:

  • Your target audience skews older: Viewer interest in certain programming, such as news content, is usually higher during an election period, especially for the older audience, where Television viewership is already extremely high. 
  • You’d like to stand out from your competition: By advertising during an election period, you may be the only advertiser in your category running during a particular program, allowing you to stand out from the competition while increasing brand affinity by providing viewers a nice break from the back-to-back political ads.
  • Your product or service is a hot topic: Certain topics, including healthcare, are a big concern for voters and many are “waiting to see what happens with the election” to decide what they are going to do; being there with your message during a time when this is very much on their minds can be very impactful.
  • You don’t want to get lost in the sea of post-election advertising: Holding out to advertise on Television or (gasp!) marketing altogether until after an election isn’t a great strategy, as this can negatively impact your overall business, especially if this is a key time period for you. Inventory is also generally still tight after the election period as:
    • There are a high number of advertisers that do that very thing, i.e. they wait to start their schedules until after the election, causing increased demand for that time frame.
    • Television stations are replacing the spots that were pre-empted during the election, reducing available inventory.
    • The end of general election period comes right at the start of the holiday period, with retail and other related advertisers now entering the market.

So again, there are many factors to consider when planning your advertising schedule during an election period. The key is having the right partner in place to successfully navigate you through, a team who will not only apply the same principles utilized when managing the buys outside of election periods, but will also ensure there is much more frequent communication with the stations and very proactive management of the schedules to reallocate any pre-emptions. Your partner should be having conversations with the stations up front in regard to rate tolerance as well, i.e. how much you are willing to increase a spot rate to maintain the schedule during the tightest periods. And finally, you want a partner who has strong relationships with the stations, who will be on the short list of people they call when a new political buy comes into the market which could affect your schedule. 

Still looking for some guidance? Give us a shout and we’d be happy to help. Email us at info@catalystmediadesign.com or call 480-471-8390.

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Are You Ready for GA4?

July 1st is quickly approaching: Are you ready?

Effective July 1st, Universal Analytics (UA) will be replaced by Google Analytics 4 (GA4). Below are some FAQs concerning the change, along with details on what you need to do to protect your past and future data.

What does this mean?

Starting July 1st, all new data will only flow into your GA4 properties. Until that date, you can continue to use and collect new data in your UA properties. Although there will be some familiar reports and features in GA4, you will need to convert your campaign performance tracking from UA goals to GA4 events. This change will ensure that metrics are more consistent with what you’re seeing in your Google Ads reports. Beginning on January 1, 2024, Google will be deleting all historical UA data.

Why is this a good thing?

  • GA4 provides more advanced cross-device tracking capabilities (website and app), allowing you to better understand the customer journey across multiple devices and touchpoints
  • GA4 offers more data protection and privacy controls
  • GA4 includes built in machine learning algorithms that automatically identify trends, generate insights and provide recommendations

What do I need to do, so I don’t lose my old data?

You can do one of the following to ensure that your historical data is accessible:

  • Export individual reports
  • Use the Google Analytics Reporting API to export data
  • Export to BigQuery (Google Analytics 360 users)

How do I know if I currently have UA or GA4 set up?

  • If your property IDs start with a UA and end with a number (UA-XXXXXXXX-1), you are using UA
  • If your property IDs have only numbers (XXXXXXXX), you are using GA4

Helpful reminders about Google Analytics:

  • Keep UA and GA4 running at the same time. It will not impact your metrics to have both collecting data from the site in the interim period, and this will help provide you access to some historical data when UA is no longer available.
  • Once you have UA and GA4 running on your website, remember that there are differences in how the data is being collected and reported in each, so the metrics are not an apples-to-apples comparison. Run parallel testing now to review any differences if possible.
  • Adjust your data retention setting to ensure that you can save your data as long as possible by going to Property Settings > Tracking Info > Data Retention. Next to User and event data retention, there is a drop-down menu where you can select a retention period of your choice (select 14 months, the maximum window available).

The deadline is July 1, 2023! Don’t forget to convert your account! And please free to reach out with any questions.

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What’s the Deal with Cookies?

There has been so much coverage over this past year surrounding the death of 3rd party cookies, and although the “end date” keeps getting pushed further and further out (we are now looking at some time in 2023), the topic keeps cropping up.  Even with all of the coverage, it’s still hard to follow exactly what the issue is or what effect this change will have on advertising.  With that in mind, we took some of the top questions from our clients and our team, and (hopefully) answered them in a way that is a little less technical and a little more accessible.  See below!: 

  • What even are cookies?
    • Cookies are tags, or pieces of code, that are placed on someone’s device (cell, laptop, etc) when they visit a website, for the purpose of gathering data.  Think of cookies kind of like a VIP wristband at a concert—the bouncer checks it any time you move in and out of the VIP areas, backstage, etc, but he can’t use it to track all of your movements within any of those areas.  When you visit a website, a cookie is placed on your browser, and this code is then utilized by advertising networks and analytics platforms to see what you go in and out of. If a cookie is present, these networks and platforms can then serve relevant ads and track your behavior accurately.
  • What are 3rd party cookies?
    • There are 3 parties to the conversation:
      • 1st Party:  Your brand & your brand’s website
      • 2nd Party:  The audience member/consumer
      • 3rd Party:  Your browser (Google Chrome, etc), which currently is relied upon to place cookies to gather data
  • How do 3rd party cookies affect my campaigns?
    • 3rd party cookies can also be used to help monitor a consumer’s path after they engage with an ad. With this path, an advertiser is able to attribute future actions (purchases, etc) to the original ad the consumer clicked. 
      • Example:  You see a display banner for a flip flop sale at Target and click through, but after browsing some of their inventory you decide to come back later when you can devote more time to your search for the perfect flops.  You X out of the Target website, but go back to the site a few days later and end up making a purchase.  3rd party cookies on the Target site can trace your path back to the original banner ad you clicked on, even though you didn’t buy something at that time. 
    • 3rd party cookies also help create a picture of who that person is; this behavioral information is then used to match against the targets when setting up a digital campaign.
      • Example:  Cookies have shown that you are a frequent visitor of vacation sites, tropical destination hotel sites, and shoe store sites.  These behaviors can be used to help determine that you would be some of the lower hanging fruit for advertising sales on flip flops.
  • How are 1st party cookies different?
    • 1st party cookies are data a site collects from a consumer directly.  Both Google and Facebook have a wealth of 1st party data, used to target ads on their own platforms. Because of this, while the life of the 3rd party cookie is coming to an end, this does not mean the end of tracking.
    • Google has also created their own method of targeting called Privacy Sandbox.  Consumer data is still collected, but rather than allow ads to target specific individuals, the individuals are lumped together into like groups and ads will be served to the group.   
  • Can I still do retargeting?  Has it changed in any way?
    • Cookies are currently used in retargeting as a method of determining which consumer devices will be served ads.  A consumer visits your website, where a cookie is placed on their device.  After that, your retargeting campaign is set up to only deliver ads to the people who have those cookies attached to them.
    • When 3rd party cookies disappear, the specifics of retargeting will also change.  Instead of relying on a browser (Google) to place the cookie, website owners will now be the ones placing the cookies on site.  The end result will not change, just the process leading up to it.
  • Can we still track foot traffic attributed to getting served ads?
    • Foot traffic tracking currently relies on the opt-in location data from mobile devices; with the new iOS Update (see next item) this decision to opt-in (or opt-out) is now in the consumers’ hands, rather than set as an opted-in default.  Because of this, fewer Apple devices are opted in, which means that the ability to track them from the moment they are served an ad to the moment they walk through your doors is limited only to those Apple devices who have opted in to location tracking.  NOTE:  This does not currently affect non-Apple devices, so complete foot traffic tracking for Samsung, etc, is still possible. 
    • Work arounds and long term solutions are currently being worked on by digital vendors, and we expect to have some answers soon.
  • What role does Apple/iPhone play in this whole thing?
    • The iOS Update that has been getting so much attention is similar to the 3rd party cookies issue, but is not the same thing.  With the new App Tracking Transparency feature, iPhone users will see a new pop-up asking them if they want to be tracked by allowing the app they’re in to access their unique device ID for advertising purposes.  (Up until now, this type of tracking happened automatically, and users weren’t given the opportunity beforehand to opt out.)  This change throws a wrench in Facebook’s ability to target, especially, as in-app Device ID tracking is one of the biggest ways they gather their targeting information.
    • Does it affect other phones, like Galaxy etc?  No….not yet.
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