Published on 7/31/2025 Staff Pick

Solved: Meta ads bidding strategy: Conversions vs. Value?

Inside this article, you'll discover:

Wich Meta ads bidding strategy is better, you think? Maximizing number of conversions or maximizing conversion value? I have daily budget around 300€ on conversion based campains. What you think?

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Hi there,

Happy to give you some initial thoughts and guidance on your Meta ads bidding question. It’s a really common point of confusion for a lot of advertisers, so you're not alone in asking. Deciding between maximising conversions and maximising conversion value is a big one, and the right choice really depends on your specific buisness goals and where you're at with your advertising.

With a daily budget of €300, you're in a good position to get some serious data and make an informed decision. Let's break it all down.


First, let's break down what each strategy actually does...

It's easy to see them as similar, but they tell Meta's algorithm to do fundamentally different things. Understanding this is the first step.

Maximising Conversions (or 'Highest Volume'):
When you select this, you're essentially telling Meta: "Get me the most purchases you possibly can for my €300 budget." The algorithm will then go out and find the people within your target audience who are most likely to convert, full stop. It doesn't care if they buy a €10 item or a €200 item. A conversion is a conversion. It's focused purely on the quantity of sales.

This is often a great stragegy for businesses that need to acquire a high volume of new customers quickly, perhaps to build up their email list or pixel data for future retargeting and lookalike audiences. If all your products are in a similar price bracket, this can also work really well because the value of each conversion is roughly the same anyway.

Maximising Conversion Value (or 'Highest Value'):
This strategy is a bit more sophisticated. When you choose this, you're telling Meta: "Get me the highest possible total revenue for my €300 budget." The algorithm's job now is to find people who are not just likely to buy, but are likely to spend more when they do. It will prioritise showing your ads to users who have a history of making larger purchases or who show interest in your more expensive products.

This means you might get fewer individual sales compared to the 'Maximise Conversions' strategy, but your Average Order Value (AOV) and, crucially, your Return On Ad Spend (ROAS) should be higher. This is the go-to for businesses with a wide range of product prices, where a €200 sale is far more valuable than a €20 one.


I'd say you need to be clear on your business goal...

So, the choice isn't about which one is 'better' in a vacuum, but which one is better for you right now. Your overall business objective should dictate your bidding strategy.

Consider using Maximise Conversions if:
-> You're a newer store and your main goal is customer acquisition and data collection. You need to feed your Meta Pixel with as much conversion data as possible to build powerful retargeting and lookalike audiences for later.
-> Your products all have a similar price. If the difference between your cheapest and most expensive product is small, then there's not much 'value' for the algorithm to optimise towards, so focusing on volume makes more sense.
-> You have a strong backend process (like email marketing) to increase the lifetime value of a customer. In this case, getting them in the door, even with a small purchase, is the main thing.

You should lean towards Maximise Conversion Value if:
-> Your primary Key Performance Indicator (KPI) is ROAS. If your boss or your bottom line only cares about how much revenue you generate for every euro spent, this is the strategy for you.
-> You have a catalogue with a wide range of prices. If you sell both €15 accessories and €300 premium products, you definately want Meta to find the people who are more likely to buy the expensive stuff.
-> You have a mature ad account with plenty of historical purchase data. The algorithm needs this data to understand what a 'high-value' customer looks like for your specific business.


You'll need enough data for either to work well...

This last point is really important. Both bidding strategies rely on Meta's machine learning, and that machine needs data to learn. For value-based bidding, it's even more critical. If your pixel has only recorded a handful of purchases, and they're all for similar amounts, the algorithm will have no idea how to find 'high-value' customers. It has no reference point.

Generally, you want an ad set to get around 50 conversions a week to exit the 'learning phase' and perform stabley. For a value-based campaign, you not only need that volume but also a healthy variety in the conversion values being reported. Without it, the algorithm is flying blind and you might get poor results.

If your account is newer or has inconsistent sales, I'd almost always suggest starting with 'Maximise Conversions'. Get the volume up, build that data foundation, and once you have a steady stream of several hundred purchases with varying values under your belt, you can then test moving over to 'Maximise Conversion Value'.


You probably should run a proper test...

Theory is great, but the only way to know for sure what works for your account is to test it. With your budget, you're in a perfect position to do this cleanly. Don't just switch the bidding strategy in your existing campaign – that can reset the learning and mess up your results. I'd set up a proper A/B test.

Here’s a simple way you could structure it:

  1. Duplicate Your Existing Campaign: Create an exact copy of your best-performing campaign. Keep the creative, copy, and targeting identical. The only thing you will change is the bidding strategy.
  2. Set the Bidding Strategy: In Campaign A, use 'Maximise Conversions'. In Campaign B, use 'Maximise Conversion Value'. If you want to be extra cautious, you can set a ROAS goal for Campaign B, but to start, just letting the algorithm aim for the highest value is fine.
  3. Split the Budget: Give each campaign half of your daily budget, so €150/day for each. This ensures a fair test.
  4. Let It Run: Allow both campaigns to run for at least 2 weeks, or until each has generated at least 50 conversions. This gives the algorithms time to get through the learning phase and stabilise.

After the test period, you need to analyse the results properly. Don't just look at which one got more sales. Compare teh key metrics side-by-side.

Metric Campaign A (Max Conversions) Campaign B (Max Value) Analysis
Amount Spent €2,100 €2,100 Should be the same for a fair test.
Purchases 105 75 Which one achieved higher volume?
Cost Per Purchase (CPA) €20 €28 Which one was more efficient at acquiring a customer?
Total Conversion Value (Revenue) €4,200 €6,300 Which one generated more total money?
Return On Ad Spend (ROAS) 2.0x 3.0x Which one was more profitable?

In the example above, Campaign A got more customers, but Campaign B was significantly more profitable. If your goal is profit, Campaign B is the clear winner, even with a higher CPA and fewer sales.


We'll need to look beyond just the bidding strategy...

It's also worth remembering that your bidding strategy is just one piece of the puzzle. The most advanced bidding in the world can't save a campaign with poor creative or bad targeting. I've seen many accounts where fiddling with bidding is just a distraction from the real problems.

-> Targeting: Are you reaching the right people? We structure campaigns based on a funnel (ToFu, MoFu, BoFu). Your top of funnel (ToFu) might use broad or interest-based audiences, while your bottom of funnel (BoFu) retargets cart abandoners. A 'Maximise Value' strategy will likely work best on a warm audience that already knows you, like website visitors or past purchasers.

-> Creative: Is your ad creative stopping the scroll? Does it clearly show the value of your product? We've worked on eCommerce campaigns where just switching from static product shots to simple user-generated style videos or carousels showing the product in use has had a massive impact on results, far more than a change in bidding.

-> Offer & Landing Page: Is your website converting the traffic you send it? A high bounce rate or low add-to-cart rate could indicate problems with your product page, pricing, or the overall trust and professionalism of your site. Ads can only do so much.


This is the main advice I have for you:

Recommendation Actionable Step
1. Define Your Goal Decide if your immediate priority is max customer volume (for data/growth) or max profitability (ROAS). This choice dictates everything.
2. Assess Your Data Look at your Meta Pixel data. Do you have at least 50-100+ purchases a week and a good spread of different purchase values? If not, start with 'Maximise Conversions'.
3. Run a Clean A/B Test Set up two identical campaigns, one for each bidding strategy. Split your €300/day budget between them and run for 2-4 weeks.
4. Analyse Holistically Compare CPA, total revenue, and ROAS. The winning strategy is the one that best meets the goal you set in step 1.
5. Don't Forget the Fundamentals Continuously review and test your audience targeting, ad creative, and landing page experience. These are often where the biggest gains are found.

I know this is a lot to take in, but getting this right can be the difference between a campaign that just breaks even and one that is wildly profitable. While you can certainly implement these tests yourself, managing it all, analysing the data correctly, and knowing what levers to pull next takes time and experience.

This is where working with a specialist can make a huge difference. For example, I remember one women's apparel client where we hit a 691% return largely by overhauling their creative to be more relatable. We spend all day, every day inside ad accounts like yours, running these kinds of tests and optimising funnels from top to bottom. If you'd like to have a chat and a look at your account together, feel free to book in a free consultation with us. We can walk through your current setup and give you some more specific advice.


Regards,
Team @ Lukas Holschuh

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