Solved: Best Way to Switch to Bid Caps in Google Ads?

Hi there,

Thanks for reaching out! Happy to give you some initial thoughts and guidance on your question about changing bid strategies in your Facebook Ads campaign.

So you're looking to move from a 'lowest cost' approach to using 'bid caps' on an existing campaign and you want to do it without messing up the performance you're currently seeing, especially the engagement you've got on your ads. That's a smart thing to be concerned about, honestly. It's really easy to accidentally tank a working campaign with changes.

My immediate thought, based on how these platforms work – and we've run quite a few campaigns across Meta for various clients, including software (seen campaigns dip significantly with big changes!), ecommerce, and even things like events and recruitment – is that changing the bid strategy directly on a live, performing campaign is quite a risky move. When a campaign is running well on a certain bid strategy (like lowest cost), the algorithm has effectively 'learned' the best way to deliver your ads to get results based on that goal and constraint. It's built up data and found its groove, so to speak. It sounds like your campaign is in a good place right now if you're worried about losing engagement, which suggests it's delivering and finding people who interact with your ads.

Introducing a bid cap is a fundamentally different instruction for the algorithm. Instead of just finding the cheapest conversions within your budget, you're now telling it "okay, go find conversions, but don't pay more than X for the *opportunity* to show the ad". This is a massive shift in how the system needs to evaluate ad auctions and decide who to show your ads to. It effectively needs to start learning all over again how to operate under this new constraint while still aiming for conversions.

Think of it like this: the campaign has been trained to run a marathon (lowest cost, find the cheapest way to get to the finish line). You're suddenly telling it to run a sprint instead, but with the same training and conditioning. It's going to struggle to adapt instantly. This kind of change is highly likely to knock your campaign right out of its stable delivery phase, and it will almost certainly reset or severely disrupt the learning phase. The learning phase is where the system is exploring to find the best audiences, placements, and times to show your ads. When you make a significant edit like changing the bid strategy, all that acquired knowledge becomes less relevant to the *new* objective/constraint, and the system has to enter a period of exploration again to figure out how to perform with the bid cap.

During this relearning period, performance almost always dips. You could see costs go up temporarily, conversion rates drop, and yes, crucially, engagement might decrease because the system is prioritising finding conversion opportunities within the bid cap limit rather than optimising for engagement which it was maybe implicitly doing effectively before on lowest cost to find those cheap conversions.

So, directly changing the bid strategy on your existing campaign to a bid cap carries a significant risk of performance loss and disruption. It's the advertising equivalent of changing the engine mid-race. You might get it done, but it'll probably cost you time and performance.

The recommended approach, and what we always do in these situations when testing something as fundamental as a bid strategy change, is to *duplicate* the campaign (or at least the ad set containing the ads you want to test with the bid cap). This approach has a couple of major advantages:

• -> Safety Net: Your original campaign continues to run uninterrupted with its current bid strategy (lowest cost). If it's performing well and getting you the engagement you value, great! Let it keep doing its thing. This ensures you maintain your current results while you experiment.
• -> Clean Test: The duplicated campaign starts fresh. It enters the learning phase from the beginning with the new bid cap strategy applied. This allows you to see how the bid cap performs without the interference or baggage of trying to retrain a campaign that was optimised for a different goal. You get a much cleaner test of whether the bid cap strategy can work for you.
• -> Direct Comparison: By running the original and the duplicate side-by-side (with the original on lowest cost and the duplicate on bid cap), you can directly compare their performance over a testing period. Which one delivers conversions at a better CPA? Which one maintains the desired engagement levels? This data is invaluable for making an informed decision about which strategy is best for your specific goals long term.

When you duplicate, make sure everything else is the same – targeting, creatives, ad copy, placements, landing page – so that the *only* significant variable you're changing is the bid strategy. This is basic split testing really, just applied at the campaign level. It's how you figure out what works best without guessing.

Set up the duplicate campaign with the bid cap you want to test. What bid cap should you set? That's a whole other question and depends on your target CPA and what you're willing to pay. A common starting point is to look at your historical CPA on the lowest cost campaign and set the bid cap slightly above that initially, then adjust based on performance. But again, I can't give specific numbers without seeing your data.

Run both campaigns for a sufficient testing period. How long is enough? It needs to be long enough for the duplicated campaign to get through the learning phase (usually a few days to a week or two, depending on conversion volume) and gather enough conversion data to make a statistically sound comparison. Don't make decisions too early based on just a day or two of data; performance often fluctuates initially.

Once you have sufficient data (say, a couple of weeks, or once each campaign has generated a decent number of conversions), you can analyse the results. See which campaign delivered conversions closest to your target CPA, which one maintained better engagement if that's important to you, and which one looks like the better strategy going forward. Based on this, you can then decide whether to pause the original and scale the duplicate, adjust the bid cap on the duplicate, or stick with lowest cost if it's still outperforming.

Here's a quick overview of the recommended actionable solution:

Testing different strategies like bid caps versus lowest cost is definitely part of optimising campaigns, especially as you try to scale or gain more control over your CPA. We see this often with software clients aiming for a specific cost per trial or signup, where they might start with lowest cost but then test bid caps or target cost to get more predictable acquisition costs once they have enough data.

Ultimately, while it might seem simpler to just flip a switch in the existing campaign, the way advertising algorithms work means you're almost always better off introducing significant changes like bid strategy shifts through controlled testing, and duplication is the standard way to achieve that on platforms like Facebook Ads.

Figuring out the right testing methodology, interpreting the data, and continuously optimising campaigns to scale efficiently can be complex and time-consuming, especially with B2B offerings or when aiming for specific cost targets like you might be with a bid cap. Having experience with different niches and campaign types helps navigate these challenges.

If you'd like a more in-depth look at your specific campaign setup, goals, and data, we're happy to hop on a free consultation call. It's a good way for us to understand your situation fully and give you tailored advice based on your specific metrics and account history.

Regards,
Team @ Lukas Holschuh