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How Long Does it Take Before Paid Advertising Campaigns Deliver Results?

Waiting for the results of a paid ad campaign can be tense. 

Hitting that refresh button. Obsessing over the dashboard. Sending emails: “Nothing’s happening — should we change the ad?”

We get it, the pressure is on, and you’re eager to see results. 

Yet making data-driven strategic choices about paid ads requires patience. An ad needs the time to collect a substantial amount of quality data, including impressions, clicks and conversions, to be able to receive consistent results. Having that data is essential for making meaningful performance assessments and driving a long term, sustainable ad strategy.

So how long does it take to get meaningful results? How much is all this going to cost? And what data is needed to drive a long term strategy?

A Question of Time

An ad needs time for data to be generated. The ad must be seen, read, clicked on, or ignored by a sufficient number of people and at different times of the day for a proper understanding of how it is performing.

We’ve found that it’s important to have two months’ worth of data or a minimum of one million impressions to identify macro trends.
Take a swimwear brand, as an example. Our swimwear clients’ sales season is generally from late February to August, which includes festival season, spring break and summer vacations, with the majority of sales coming in from June to August. Another example is our clients who sell beauty products. Although the products experience no seasonal demand fluctuations, beauty businesses experience high sales during holiday promotions such as Black Friday and Cyber Monday, as well as during seasonal promotions, such as around Christmas or spring break.

Taking this into account, having a complete view of two months’ data helps us optimize for the best results. This period gives us a wealth of data upon which to base strategic decisions.

The Learning Phase

The initial period after the ad goes live is the ad’s “learning phase.” This is time needed for the algorithm to experiment with delivering the ad and gather data on how users interact and engage. This data informs how we adjust the ad campaign going forward.

Although data is visible as early as 24 hours after launching an ad, the length of the learning phase varies by platform. Google advises that an ad needs a minimum of seven days in this learning phase before any minor optimizations and bidding decisions are made. Meta ads, on the other hand, typically require a minimum of 15 days of data to make meaningful campaign adjustments. On both platforms, it generally takes at least two months of quality data to see consistent results.

During those initial weeks, ad performance is less stable and the performance data may hit peaks and troughs. It’s tempting to respond to a drop in performance by making edits to the ad or requesting changes. Instead, we urge you to close the campaign monitoring window and focus on other tasks at hand. Remember, day-to-day results in the learning stage aren’t always indicative of future performance.

In fact, editing an ad in this phase resets the clock, which delays the amount of time needed for optimization and puts the campaign right back at the beginning. It’s vital that edits to the ads only occur when there’s reason to believe that doing so should improve performance — and to prove that, there must be data.

Trust in the process. Many hours of thought and labor have gone into crafting an ad before it goes live, so there’s seldom a need to make emergency, reactive changes once the ad is live. Simply sit back and wait as the impressions tick up.

Budgeting for Ad Campaign Results

Considering a realistic duration for an ad is critical in setting an accurate budget and seeing results.

There’s no magic number when it comes to a budget, and budget varies relative to the industry, competition, and ad spend. Even with a small ad budget, it’s possible to see outstanding results, and conversely, a considerable ad budget doesn’t necessarily mean an ad will conquer the internet.

It’s also important to set a realistic budget that factors in the testing and learning period. Setting a tiny budget for the learning phase will mean having less data as a foundation on which to build a strategy. Over-inflating a budget gives the delivery system an inaccurate indicator that will affect performance.

Our general rule is to set a budget large enough to reach at least 50 total “optimization events,” generally defined as 50 leads or sales, for the learning period, depending on the goal of the ad campaign. A budget this size will give visibility across the whole of a funnel and enough data to spot the leaks.

Setting a sound budget from the beginning and avoiding significant budget changes is essential. Changing a budget during the learning phase resets the clock and re-starts the learning process.

Laying a Foundation Marketing and Sales Strategy

So far, we’ve spoken about the time it takes to see results from a paid ad campaign after an ad has gone live. Is that it? Does an ad just need two months to get set up and begin generating results?

In short: no. The most successful ad campaigns are supported by an informed strategy, comprehensive analytics, and solid marketing and sales funnel architecture.

Developing a robust paid media strategy before launching paid ad campaigns is crucial. This means getting the basics right: optimizing the site for analytics, having a dedicated landing page for each ad, performing keyword and competitor research, and adjusting each ad to the customer and how they behave online, to name a few. The strategy should integrate into and support an overall marketing and sales strategy.

To optimize an ad’s chances of success, our recommendation is to plan for one month of strategy and alignment, a second month of data collection and then a further month for ad optimization. This three-month time frame allows time to deliver a polished, performance-driven ad campaign that makes the most of the ad spend budget.

The Value of Ad Campaign Data

The data from a comprehensive learning phase is illuminating and has the power to change the entire campaign strategy.

Take, for example, a florist client we had. They specialized in roses for the US market and thought they knew their audience: In previous ad campaigns they performed, they segmented their audience by gender and age and targeted women and older men.

But why? Our client had no data to back up this decision. When we began planning our first ad campaign with them, we included demographic testing within the learning phase of the campaign.

The learning phase revealed that men aged 18–24 were, in fact, one of their top performing demographics. Their previous sales data was a self-fulfilling prophecy: Young men were less likely to buy their roses — in large part because they couldn’t see any ads.

Shifting their strategy to include this demographic has meant that sales are increasing weekly.
The data from the learning phase is often surprising. It reveals opportunities missed, new audiences and overlooked holes in the sales funnel. It’s valuable and allows for informed, strategic decisions to be made. Alternatively, it could reveal that a campaign is on the right track — knowledge that is just as valuable. Either way, it’s an investment worth the wait.

Ready to hand over your ad campaign setup and monitoring to a professional team? Book a call with our founder to see how running an ad with a serious strategy can increase performance in three short months.

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