Solved: Higher CPC on Meta Ads After Creative Change

Hi there,

Thanks for reaching out!

Happy to give you some initial thoughts on your Meta ads. It's a really common problem to see costs shoot up when you test a new creative, and it's usually not as simple as just one thing being 'wrong'. You've hit on a classic advertising puzzle, and the answer is usually a mix of audience perception, ad platform mechanics, and your offer.

Let's get into what's likely happening and what you can do about it. It’s not just about the creative, it’s about the entire message you’re sending.

We'll need to look at why the algorithm is punishing your second ad...

First off, let's clear up a common misconception. You mentioned a higher CPC, but since you're running a messaging campaign, the key metric is your Cost Per Message, or more broadly, Cost Per Result (CPR). While related, they aren't the same. The real issue is that Meta is charging you more for each conversation started with your second ad. Why does this happen?

You have to remember you're not just buying ad space; you're entering an auction. Meta’s job is to show the most relevant ad to the right person at the right time, both to keep its users happy and to make money. It decides who wins the auction based on three main things:

1. Your Bid: How much you're willing to pay. In your case with an ABO (Ad Set Budget Optimisation) campaign, this is managed automatically.
2. Ad Quality: How good Meta thinks your ad is, based on feedback, engagement, and comparisons to other ads targeting the same audience.
3. Estimated Action Rates: This is the big one. Meta predicts the probability that a person will actually take the action you want them to take (in your case, send a message).

When you launched your second ad set, the only thing you changed was the creative and the price mentioned in it. Your audience was the same. The algorithm showed this new ad to a small slice of your target audience and saw that people were less likely to click and message you compared to your first ad. They hesitated. Maybe they scrolled past faster. The engagement rate dropped.

The algorithm learns from this instantly. It concluded: "This ad is less likely to get a message than the other one." Because the 'estimated action rate' for the second ad is lower, Meta has to charge you more to deliver that same result (a message). It has to show the ad to more people to find the one person willing to message you, and that costs more. So, your 45 MAD cost per message isn't a punishment out of nowhere; it's a direct reflection of the audience's lukewarm reaction to your new offer. The creative isn't just a picture; it's the entire pitch, and this new pitch isn't landing as well.

This tells us the problem isn't a technical glitch. The problem is a human one. Your target customer is looking at the 750 MAD fabric and thinking, "I'm not so sure about that." Our job is to figure out why and fix it.

I'd say you need to diagnose the real problem: a value mismatch...

Your first ad for the 550 MAD fabric clearly hits a sweet spot. The price and the visual of the fabric align perfectly, creating a perception of good value. The customer sees it and thinks, "That's a fair price for that beautiful fabric." The decision to message you is easy.

Your second ad, however, breaks this harmony. You've increased the price by nearly 37%, which is a significant jump. The fatal mistake is assuming that simply showing a different fabric is enough to justify that higher price. For the customer, the question isn't "Is this fabric nice?" but rather "Is this fabric 200 dirhams *nicer* than the other one?" Your ad, as it stands, is failing to answer that question with a convincing "YES".

This is what I call a 'value mismatch'. To fix it, you can't just show the product; you have to build a compelling story around it that justifies the premium price. Forget selling "fabric". You're selling a feeling, a result, an identity. You need to move from showing a product to promising a transformation.

Let's use a framework for this: Before - After - Bridge.

• Before: The customer feels ordinary. She's looking for an outfit for a special event (a wedding, Eid celebration) but worries she won't stand out. She's seen similar fabrics everywhere.
• After: She imagines herself at the event, wearing a stunning, unique caftan made from your fabric. She feels elegant, confident, and receives compliments all night. She feels like the best version of herself.
• Bridge: Your 750 MAD fabric is the bridge that takes her from her 'before' state to her 'after' state.

Your ad creative and copy need to paint this 'After' picture vividly. Instead of just a flat photo of the fabric, your creative needs to scream "premium". Here are some ideas to test:

• Professional Videography: Show the fabric in motion. How does it drape? How does it catch the light? A slow-motion video of the fabric flowing can look incredibly luxurious and imply higher quality.
• Show the End Result: Don't just show the raw material. Show a beautifully designed dress or caftan made *from* the fabric. This helps the customer visualise the potential and makes the price seem more reasonable, as they're not just buying cloth, they're buying the potential for a masterpiece.
• Focus on the Details: Use macro shots to highlight the intricate weaving, the quality of the thread, or any unique patterns. This provides tangible proof of its superior quality.
• Use Storytelling in Your Copy: The ad copy needs to do the heavy lifting. Don't just state the price. Justify it.

Example of weak copy (what you're probably doing now):

"New exclusive fabric. 750 MAD. DM to order."

Example of strong, value-driven copy:

"For the woman who doesn't blend in. Our limited edition 'Royal Fes' silk is woven with a technique passed down through generations. The result is a lustre and depth of colour that simply cannot be replicated. Be the one everyone remembers. 750 MAD. Message us for a private consultation."

Notice the difference? The second version sells exclusivity ("limited edition"), heritage ("passed down through generations"), superior quality ("lustre and depth"), and an emotional benefit ("Be the one everyone remembers"). It reframes the 750 MAD not as a cost, but as an investment in status and confidence. This is how you close the value gap and convince the algorithm—and your customers—that your ad is worth paying attention to.

You probably should rethink your audience targeting...

The second major issue I see is your audience selection. "Moroccan women" is not a target audience; it's a demographic. It's incredibly broad and unfocused. You are almost certainly wasting a significant portion of your budget showing your ads to women who have absolutely no interest in buying premium fabrics. They might be students, or women who prefer ready-to-wear fashion, or simply not be in your target income bracket. You're paying for their impressions, and their lack of engagement is hurting your ad's quality score and driving up costs.

To get better results, you must become an expert in your ideal customer. Who is she *really*? She isn't just "a woman in Morocco". She's a woman with a specific problem, a specific desire, and a specific lifestyle. Your job is to find her on Meta's platform.

We need to move from broad demographics to layered, interest-based targeting. Let's build a picture of your Ideal Customer Profile (ICP). Let's call her Fatima.

Fatima is 35, lives in Casablanca, is married with children, and has a high disposable income. She attends several formal events a year (weddings, family gatherings) and takes pride in her appearance. She doesn't buy off-the-rack; she has a trusted tailor and loves the process of creating a unique garment. She follows high-end fashion designers, luxury brands, and Moroccan fashion influencers on Instagram.

Now, how do we target Fatima? We use Meta's detailed targeting to find people who have shown interest in:

• Luxury Brands: Dior, Chanel, Gucci, etc. (People who like these are comfortable with premium pricing).
• High-End Moroccan Designers: Target followers of famous Moroccan caftan designers.
• Related Interests: "Haute Couture", "Fashion Design", "Sewing", "Textiles".
• Life Events & Behaviours: You can even target women with an anniversary coming up, or who are 'Engaged Shoppers' (a behaviour Meta assigns to people who frequently click 'Shop Now' buttons).

The key is to layer these interests. For example, you could create an ad set that targets: Women in Morocco who are interested in "Haute Couture" AND are also "Engaged Shoppers". This immediately creates a much smaller, but far more qualified, audience than just "Moroccan women".

I usually structure audiences in a prioritised way, especially for eCommerce. The people most likely to convert are those who already know you. The next most likely are people who *look like* your existing customers. The hardest to convert are complete strangers (cold traffic). Your current strategy is only focused on the last group, which is the most expensive.

Here’s a simplified funnel you should aim to build:

1. Top of Funnel (ToFu - Cold Traffic): This is where you find new people. You'd test your detailed interest audiences here (like the 'Fatima' profile we just built).
2. Middle of Funnel (MoFu - Warm Traffic): This is for people who have shown some interest but haven't messaged you. You can create a retargeting audience of people who have watched 50% of your ad videos or engaged with your Instagram/Facebook page in the last 90 days. Show them different ads, perhaps testimonials or behind-the-scenes content.
3. Bottom of Funnel (BoFu - Hot Traffic): These are people who are very close to buying. For a messaging campaign, this is harder to track, but you could retarget people who have visited your website if you have one. In eCommerce, this is where we retarget 'Add to Carts'.

By starting with highly specific ToFu audiences, you gather data. This data then feeds your MoFu and BoFu campaigns, which are almost always cheaper and more effective. You're spending your money more intelligently by focusing on the people most likely to buy.

You'll need a proper testing structure...

Your current approach of testing one ad set against another is a good start, but it's not very efficient or scalable. To really figure out what works, you need a more systematic approach. The goal is to isolate variables so you can learn what's truly driving performance. Are people responding to a specific message? A specific visual style? A specific audience?

I would suggest moving away from ABO and trying a CBO (Campaign Budget Optimisation) campaign for your testing. Here’s how it works:

1. You set the budget at the campaign level, not the ad set level.
2. You create multiple ad sets within that campaign, each one targeting a different audience (e.g., Ad Set 1 targets 'Haute Couture' interest, Ad Set 2 targets 'Luxury Brands' interest, Ad Set 3 is a retargeting audience).
3. You place multiple ads (creatives) within each ad set. You should have at least 3-4 different ads. These could be different videos, images, or carousels, each with slightly different copy.

The magic of CBO is that Meta’s algorithm will automatically distribute your budget to the best-performing ad set and ad in real-time. It does the heavy lifting for you, pushing money towards what's working and away from what's not. This is a much faster and more effective way to test than manually managing budgets for each ad set.

Here's what a simple testing campaign could look like for your 750 MAD fabric:

• Campaign: CBO Messaging Campaign - 750 MAD Fabric Test - [Your Daily Budget]
• Ad Set 1: Audience - Fashion Lovers (Targeting interests like Haute Couture, Fashion Design, etc.)
• Ad 1A: Video showing the fabric draping and flowing. Copy focuses on the 'Luxury' angle.
• Ad 1B: High-quality image of a finished caftan made from the fabric. Copy focuses on the 'End Result' angle.
• Ad 1C: Carousel ad showing close-up shots of the weave, followed by a lifestyle image. Copy focuses on the 'Craftsmanship' angle.
• Ad Set 2: Audience - Luxury Shoppers (Targeting interests in brands like Dior, Chanel, and 'Engaged Shoppers' behaviour)
• Ad 2A: Video showing the fabric draping and flowing. Copy focuses on the 'Luxury' angle.
• Ad 2B: High-quality image of a finished caftan made from the fabric. Copy focuses on the 'End Result' angle.
• Ad 2C: Carousel ad showing close-up shots of the weave, followed by a lifestyle image. Copy focuses on the 'Craftsmanship' angle.

After running this for 3-5 days (or until each ad set has had enough spend to get some results), you can look at the data. You'll quickly see which audience is responding better and which creative angle is generating the cheapest messages. Maybe you'll find that 'Fashion Lovers' respond best to the craftsmanship angle, while 'Luxury Shoppers' prefer the end-result angle. This is invaluable information. You can then turn off the losing ads/ad sets and scale up the winners, or use your learnings to create even better ads for your next test. This iterative process of testing, learning, and optimising is the only reliable way to acheive and maintain good performance on paid ad platforms.

Let's talk about the numbers and what you should expect...

It's good that you're already paying close attention to your cost per result. Your initial cost of 18-20 MAD per message is actually quite decent. The 45 MAD you're seeing now is on the higher side, but it's not catastrophic, especially for a higher-priced item. The key is to understand what's achievable and how your ad performance metrics influence your final cost.

The cost per message is a result of two main metrics: your Cost Per Click (CPC) and your Click-to-Message Rate (the percentage of people who click your ad and then actually send a message).

Cost Per Message = CPC / Click-to-Message Rate

Let's break down your two scenarios:

• Good Ad (18 MAD Cost): You might have had a CPC of 3 MAD and a very high Click-to-Message rate of 16.7% (3 / 0.167 = ~18 MAD). This tells me the ad was highly compelling; people who clicked were very motivated to talk to you.
• Bad Ad (45 MAD Cost): Here, the problem could be twofold. Your CPC might have gone up to 4.5 MAD because of lower engagement. And your Click-to-Message rate might have dropped to 10% because people were less convinced after clicking (4.5 / 0.10 = 45 MAD).

As you can see, even small changes in these two metrics can have a huge impact on your final cost. Your goal when optimising is to lower your CPC by making your ads more engaging (better creative, better targeting) and to increase your Click-to-Message rate by having a very clear and compelling call to action.

To help you get a better feel for these numbers, I’ve built a simple calculator below. You can play around with different CPCs and Click-to-Message rates to see how they affect your final cost per message. This can help you set realistic targets for your campaigns.

So, where do you go from here?

The advice I've detailed above—fixing the value perception, narrowing your audience, and building a proper testing structure—is the foundation of a successful paid advertising strategy. It moves you from just 'boosting posts' to being a sophisticated advertiser who makes data-driven decisions.

However, implementing all of this correctly and consistently takes time, effort, and experience. You've seen yourself how a small change can double your costs overnight. The world of paid ads is complex, and the platforms are constantly changing. Keeping up with best practices, analysing data correctly, and knowing when to scale a winner or kill a loser is a full-time job.

This is where expert help can make a huge difference. While you're an expert in fabrics, we're experts in finding customers for businesses like yours. For instance, one campaign we ran for a women's apparel eCommerce store generated a 691% return on ad spend. We know the patterns, the pitfalls, and the strategies that drive real growth, and we could help you not just fix this one ad, but build a predictable and scalable system for acquiring new customers profitably.

If you're interested in seeing what that might look like for your business, we offer a completely free, no-obligation initial consultation. We'd take a look at your ad account together, review your strategy, and give you some more specific, actionable advice you can implement right away. It's a great way to get an expert second opinion and see if working together might be a good fit.

Hope this detailed breakdown has been helpful for you!

Regards,

Team @ Lukas Holschuh