Ad Testing Guide

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Your Guide to Scientific Ad Testing

Ad Testing is comprised of both math and creative elements.

At a high level, the steps to ad testing are quite simple:

  1. Determine your hypothesis
  2. Decide the test’s scale & testing type
  3. Choose how you will pick winners
  4. Set up your tests
  5. Wait for data
  6. Take action

However, it’s easy to use non-statistically relevant data or incorrect testing metrics if you don’t understand exactly what you want to know and how to measure how users interact with your ads.

In this guide, we’ll walk you through how to ensure you are using the correct metrics, data, and math so you are confident that your ad testing results will improve your account and that you aren’t making changes due to pure randomness or testing metrics that don’t help you reach your goals.

Table of Contents

Creating Your Ad Testing Hypothesis

When you are ‘scientifically testing’; you are testing a hypothesis or idea.

The hypothesis is generally formed around an idea you have and something you want to learn about your customers.

For instance, you might try adding a 10% discount to your products. However, when you sell at a discount, you need to make up for it in more total orders to offset the lower price. So your hypothesis could be as basic as:

We believe that adding a 10% discount to our goods will increase conversion rates by 15% and the net revenue increase will be greater than $10,000. To test this, we will start off by offering a discount on a limited selection of
产品和回音的折扣在广告和登录页。

这一假设可能基于一个新的商业里程碑:我们现在已经售出了100多万张门票。我们想测试在我们的广告中增加“售出100多万张”的可信度是否比我们目前的表现更好
行动呼吁“呼吁迅速提供个人援助”。

可能性是无限的;但以下是一些让您开始的想法:

一旦确定了要测试的内容,下一步就是确定测试的规模。

单Ad组与多Ad组测试

在你开始检验你的假设之前;你需要知道测试的规模。

这就引出了两种不同类型的广告测试:

通过单个广告组测试,您可以只检查该广告组的广告数据。即使您在数千个不同的广告组中进行测试,您也只会检查广告组本身中的广告数据。

使用多广告组测试,您可以在假设级别(可以是广告行、模板、标签、模式等)检查您正在运行测试的所有广告组的数据。

当你考虑你的广告数据时,你应该考虑从任何广告测试中获得的见解,以及这些数据是否可以在你的账户中的其他地方使用。

例如,如果您在单个ad组中运行测试;您将知道该广告组中针对目标的最佳广告(目标可以是关键字、列表、位置等)。然而,你不知道这则广告是否会在
another ad group until you test it in the other ad group.

WIth multi-ad group testing, you are testing an idea across many ad groups and therefore, you will understand what line (or concept) is best across all the ad groups used in that test.

Single ad group testing

Advantages:

Disadvantages:

Multi-ad group testing

Advantages:

Disadvantages:

Which to use?

If you are testing very high value targets, such as brand terms or your hero keywords; then it is best to use single ad group testing as you will find the best ad for each targeting type.

If you are testing ideas, templates, or massive accounts and want insights that can be applied to many ad groups, and even landing pages or other marketing channels, then multi-ad group testing is best.

Once you have determined your hypothesis and where you will test, the next step is to choose what metrics will tell you that your ad tests are winners and losers.

Overview of Testing Metrics

一旦你确定了测试的假设;接下来,您需要确定如何挑选获奖广告。

我们将在这里简要介绍这些指标;如果您想了解有关每个指标的更多信息,请参阅详细文章。

我们建议大多数广告商使用基于印象的指标。

当你进行广告测试时,通常有六个不同的指标可以用来确定胜利者;然而,它们的使用方式可能非常不一致,一些指标被误解。了解所有测试指标的基本知识及其总体优缺点非常重要。

指标

点击率(CTR):

CTR是点击与印象的比率。使用此指标可确保收到尽可能多的单击。
快速优点:

快速缺点:

转化率(CR)

转换率是转换与单击的比率。此指标可确保您收到的点击次数最多。
快速优点:

快速缺点:

每次收购成本(CPA)

每次收购的成本是支出与转换的比率。这个指标仅仅是您为获得转换而支付的金额。
快速优点:

快速缺点:

每个印象的转化率(CPI)

每个印象的转化率是转化率和印象之间的比率。它可以确保您获得尽可能多的转换效果。

快速优点:

快速缺点:

广告支出回报(ROAS)

ROAS是收入与支出的比率。它确保您保持最低的销售利润率。它最常用于电子商务网站。

快速优点:

快速缺点:

每印象收入(RPI)

每个印象的收入是收入与印象的比率。它可以确保您收到的印象获得尽可能多的收入。它最常用于电子商务网站。

快速优点:

快速缺点:

组合指标

很多时候,在测试时,你应该使用两个指标来确保你的广告测试帮助你实现目标。

例如,如果您是一个具有以下简单目标的电子商务帐户:

在这种情况下,您需要同时检查两个指标以确定赢家:

这一简单的过程将确保您实现在目标ROA内实现最大化的目标。

在开始测试之前,您应该选择如何挑选优胜者,以便了解要监控的指标。详细阅读特定指标;或者要了解所有指标的详细信息,请继续阅读本指南。

Testing Metric Details: Click Through Rate (CTR)

CTR is the metric that Google pushes you to use the most as their ad rotation default is set to optimize for clicks, which is the highest click through rate ad. This metric is useful to use for ad testing when you want to increase traffic or one of your primary goals is visitors. However, as it does not take into account conversions or revenue goals, it is often not a great for sites that are trying to gain new customers from PPC advertising.

What is CTR?

CTR is simply the ratio of impressions to clicks.

How CTR is Calculated

CTR is calculated by diving the number of clicks by your impressions:

CTR = clicks/impressions

It is generally displayed as a percentage. Here are some examples:

Ad 点击次数 印象 CTR
1 45 243 18.52%
2. 97 1023 9.48%
3. 56 840 6.67%
4. 32 230 13.91%

In this case, ad 1 has the highest CTR and ad 3 has the lowest CTR.

The Advantage of using CTR as Your Testing Metric

There are two main reasons to use CTR as your testing metric:

If your goal is to get more traffic, have more people see your site, then CTR is the best metric to use for testing. This is a common metric to use for brand departments who want to make sure that people are seeing their offer. It is also common to see companies use CTR for their branded keywords and another metric for their other keywords.

If you are struggling with Quality Score, then using CTR as an ad testing metric can often help in increasing Quality Score. As CTR is one of the most important factors in Quality Score, having high CTRs often correlates to higher Quality Scores (and often lower CPCs). It is common to see an account where there is a direct correlation between CTR and Quality Score.

For instance, here’s a chart for one account where the metrics are broken up by Quality Score ranges. The trend between higher Quality Scores with higher CTRs is a very common occurrence.

Quality Score 点击次数 印象 CTR
1 0 0 0%
2. 1 143 0.70%
3. 21 3094 0.68%
4. 1036 164,582 0.63%
5 471 23,289 2.02%
6. 7563 353,377 2.14%
7. 59,593 1,530,468 3.89%
8. 68,153 1,435,300 4.78%
9 93,640 1,329,169 7.05%
10 131,586 1,472,395 9.62%
总计 372,064 6,301,816 5.90%

因此,如果您的主要目标是提高质量分数或获得最多的流量,那么CTR是一个很好的衡量标准。

使用CTR作为测试指标的缺点

而CTR有利于获得大量的流量;它没有区别好的或坏的流量。

例如,如果你有很高的CTR和很高的反弹率;那么你只是吸引了不在乎你的信息的流量。因此,即使您试图获得尽可能多的流量,也最好使用交互目标(例如每次访问的页面浏览量或在站点上的时间)来确保您获得高质量的流量。因此,当您的目标是高质量流量时,CPI(每个印象的转化率)比CTR更适合使用。有了CPI,你可以根据高质量的访问设定目标,然后优化你的广告,以吸引最合格的访客,而不仅仅是最多的访客。

提高CTR以提高质量分数对大多数公司都有好处;但不一定是全部。在许多情况下,在用户点击你的广告之前,你会使用你的广告对他们进行资格认证。如果你取消了资格认证,那么你的CTR和质量分数通常会增加,但会损害你的总体目标。

例如,在B2B(企业对企业)空间中,通常会在广告中添加资格,例如在广告中添加“为企业”的帐户或添加“工业”的大型商业销售。这些资格的目标是向用户澄清,您的报价是针对企业而非消费者的。当您取消这些资格时,您经常会看到一些指标(质量分数和CTR)增加,但您的销售人员通常会感到不高兴,因为他们没有收到那么多的潜在客户,或者他们收到的潜在客户不合格。
Examining CTR is useful when combined with other metrics in order to break ties. For instance, if you have two ads with identical metrics (such as CPI, CPA, CR, ROAS) and you’re not sure what to pick, choosing the higher CTR ad will generally result in higher quality scores and thus slightly higher positions (so more traffic) or lower costs.

结论

If you care about the quality of your traffic, the CTR is never a good testing metric to use. In those cases, you should use a goal (such as time on site) and CPI (conversion per impression) as your testing metric.

If you care about actual conversions, then CTR is never a good metric to use by itself as it doesn’t use conversions or revenue in its calculations.

If you are struggling with raising quality scores, then CTR can be a great metric to use in your testing.

CTR is important. Without clicks, you won’t receive any conversions and the other metrics are moot. However, CTR is rarely a metric you will use by itself in your testing, yet it is a great stat to use as a tie breaker when you are also testing by other metrics such as CPA.

Testing Metric Details: Conversion Rate (Conv. Rate)

Conversion Rate is commonly used for testing as the higher your conversion rate, the more conversions you have once someone clicks on your ad. The biggest downside to conversion rate is that it doesn’t take into account how many clicks your ad actually receives.

What is Conversion Rate?

Conversion rate (CR) is simply the ratio of clicks to conversions.

How Conversion Rate is Calculated

Conversions rate is calculated by diving the number of conversions by your clicks:

Conversion Rate = conversions/clicks

It is generally displayed as a percentage. Here are some examples:

Ad 转换 点击次数 CR
1 1 100 1%
2. 10 100 10%
3. 32 1045 3.06%
4. 57 1103 5.17%

In this case, ad 2 has the highest conversion rate and ad 1 has the lowest.

The Advantage of using CR as Your Testing Metric

There are two main reasons to use CR as your testing metric:

A common landing page testing method is to use two identical ads in an ad group with the exception of the destination URL. If you are testing landing pages, then ad 1 goes to landing page 1 and ad 2 goes to landing page 2.

If you are testing page templates, then you might duplicate this test across several ad group and use multi-ad group testing to aggregate the results across all of your ad groups by page template.

The other reason to use conversion rate as a testing metric is when you want the most conversions possible once someone clicks on your ad. We have to qualify this very carefully as conversion rate has an inherit weakness – it doesn’t care about the volume of clicks.

The Disadvantage of using Conversion Rate as Your Testing Metric

While conversion rate is great for landing page testing, it is not a good metric to use for increasing total conversions from your PPC ads since it doesn’t care about how often your ad is actually clicked. Consider these stats:

Ad 印象 点击次数 转换 Cost CTR Conv Rate CPA
1 1000 100 10 $200 10% 10% $20
2. 1000 10 2. $25 1% 20% $12.50
3. 1000 56 5 $126 5.6% 8.93% $25.20
4. 1000 11 4. $33 1.1% 36.36% $8.25
5 1000 156 12 $234 15.6% 7.69% $19.50

In every case, these ads all received the exact same impressions. Because CTR varies, so will the actual CPC and costs for each ad variation.

The ad with the absolute highest conversion rate is ad test 4 at a 36.36%. However, that ad only received a total of 4 conversions. The ad with the lowest conversion rate, test 5, received three times as many conversions at 12. Because ad 5 had such a high CTR, it received more traffic than the other ads and therefore, it had more opportunities to create conversions. So even though it’s the lowest conversion rate, it ends up with the most conversions.

在进行广告测试时,转换率很少(如果有的话)是一个好的指标,可以作为您决定哪种广告最适合您的PPC帐户的唯一决定。转化率是一个很好的指标,可以与CTR相结合,CTR会创建CPI(每个印象的转化率),这将是以后的一个特色指标。

对于登录页测试,转换率是一个很好的数字,因为登录页测试只关心到达页面的流量;页面本身不会吸引更多或更少的点击,它只关心实际访问您页面的用户。

结论

转换率是一个非常重要的指标——我不想低估它作为广告测试指标的重要性。然而,由于转换率根本不关心点击率,它本身并不是一个很好的广告测试指标。它与点击率结合在一起非常好,点击率随后创建了每印象的度量转换(CPI)。

其中转换率是你的go-to广告测试指标,是当你测试登录页而不是广告时。如果你的广告是相同的,而你只是测试登录页;那么转换率将是您测试中的主要指标。

不要将转换率作为衡量标准来打折,但除非您正在测试登录页,否则不要将其作为确定广告赢家的唯一衡量标准。

测试指标详情:每次收购成本(CPA)

CPA(每次收购的成本)就是您为转换支付的金额。

这通常称为每次转换的成本;然而,在PPC中,我们通常将首字母缩写CPC与每次点击的成本联系起来,因此通常有人会说“每次转换的成本,我们的CPA”,以避免混淆。

这是在几种不同类型的账户中进行测试的常用指标:

Here’s a few examples of business models that should be examining their CPAs:

Some ecommerce accounts have checkouts that are highly variable and ROAS (return on ad spend) doesn’t work as a testing method, in which case CPA is a good metric to use. For instance, I work with one ecommerce company whose average checkout is roughly $500. However, 5% of their checkouts are for more than $10,000. The keyword and ad that receives those high value checkouts are completely random and there is no pattern. Thus if they were to use ROAS as a bid or testing method the random checkouts would lead to them picking an ad winner that might not lead to the same value the following month; and thus CPA is a better metric for them to use for testing and bid management.

Often with CPA testing, you won’t use just CPA as your testing metric, it’s a great combination metric to use and we’ll address that later in this article.

What is CPA (Cost per Acquisition)?

CPA is how much a conversion costs you.

How CPA is Calculated

CPA is calculated by dividing total cost by total conversions.

CPA = cost / conversions

It is generally displayed as a percentage. Here are some examples:

Ad Cost 转换 CPA
1 $1,000.00 10 $100.00
2. £1,000.00 5 £200.00
3. ¥500.00 10 ¥50.00
4. € 429.00 11 € 39.00

If we don’t correct for the currency differences and assume these were all in the same currency, then ad 4 would have the lowest CPA and ad 2 would have the highest CPA.

The Advantage of using CPA as Your Testing Metric

The primary advantage of using CPA is to control costs and how much a conversion costs you.

例如,如果您以25美元的价格转售lead,那么您可能不想为lead支付超过15美元的价格。

如果你有一个很长的销售周期,那么通常你需要在整个周期内进行计算,以确定你的短期注册会计师。例如,假设您的销售周期为:

让我们假设我们在1美元的CPC上花费了10000美元,看看完成领先优势需要多少成本:

Conversion rate 漏斗中的人员 CPA
单击到站点 10,000
收集的电子邮件 20% 2,000 $5
接受网络研讨会邀请 40% 800 $13
参加网络研讨会 50% 400 $25
观看50%的网络研讨会 50% 200 $50
销售团队联系率 25% 50 $200
销售团队成交率 20% 10 $1000

根据这些信息,我们可以反向确定电子邮件收集的初始CPA。如果1000美元的新销售成本是有利可图的,那么我们的状况很好。如果我们想增加进入漏斗的人数,我们可以提高CPA。如果最终成本太低,那么我们可以降低CPA。

现在,在这种特殊情况下,除了广告的CPA之外,还有很多东西可以测试,例如:

在某些情况下,这要容易得多。例如,如果你以50美元的价格销售一个数字产品,你可以接受40美元的注册会计师,因为这将使你在每次销售中获得10美元的利润。CPA有时很难确定;但是,当您想要关注成本时,CPA是一个很好的指标,可以单独使用,也可以与其他测试指标结合使用。

使用CPA测试指标的缺点

虽然CPA对于控制成本很有用,但它并不总是用于测试的最佳指标,因为它没有考虑点击量或转换率。

Consider these stats:

Ad 印象 点击次数 转换 Cost CTR Conv Rate CPA
1 1000 100 10 $200 10% 10% $20
2. 1000 10 2. $25 1% 20% $12.50
3. 1000 56 5 $126 5.6% 8.93% $25.20
4. 1000 11 4. $33 1.1% 36.36% $8.25
5 1000 156 12 $234 15.6% 7.69% $19.50

For these results, each ad was served the same amount of times (1000). The lowest CPA is ad 4 at $8.25; however, it only has 4 conversions. The ad with the most conversions is ad 5 with 12; but it’s CPA is more than double the lowest CPA ad.

This is often what you fight with CPA – costs versus volume.

Where CPA is a great metric is when you combine it with other metrics.

Combining CPA With Other Metrics

In many cases, you don’t want the lowest CPA ad – what you want is to set a threshold for your target CPA and then pick the ad with the most conversions that is at or below your target CPA.

For instance, if our max CPA was $20 this would be our process:

Now, the biggest issue in the real world with this process is that all your ads won’t have the exact same number of impressions. Thus in reality what you usually do is eliminate the ads above your target CPA and then pick the highest CPI (conversion per impression) ad as that will lead to the most conversions at or below your target CPA.

In some cases, you will have a target CPA, but you want the most visitors to see your offer (landing page) and become familiar with your company. This is a common tactic for PPC accounts where many searchers will visit the site multiple times before they convert. In that case, you would use CPA as your filter and then user CTR as your winning ad metric. This is also useful if you are trying to raise quality score (higher CTRs usually mean higher quality scores) but you have a max CPA that you to optimize to at the same time.

结论

CPA对于大多数账户来说是一个非常重要的指标(某些电子商务是例外),因为它决定了你为转换支付的金额。您可以将该数据与每次转换的实际收入进行比较,并确保您的PPC帐户盈利。

CPA的缺点是它不考虑交易量(如CTR或转换率);因此,虽然这是一个了解和使用的好指标,但它很少是您在广告测试中专门使用的指标。CPA最擅长的是过滤广告测试。使用CPA作为过滤器来删除高于目标CPA的广告;然后,您可以使用另一个指标,如CPI或CTR来确定目标CPA范围内的广告的获胜者。

使用CPA作为过滤器和另一个指标来确定剩余广告的赢家,这是一个很好的方法,可以确保您的帐户盈利,并最大限度地实现您的帐户的其他目标,如最多的转化率、最多的点击率等。

测试指标详细信息:每个印象的转换(CPI)

CPI(每个印象的转化率)是显示印象和转化率之间比率的指标。

When you consider ad testing, which combination is better?

很难说哪个更好,因为这些信息依赖于两个不同的指标:CTR和转化率。

CPI所做的是将这两个不同的指标结合起来,形成一个单一的指标,它将向您显示哪个广告将从impression中获得最多的转化率。

为什么要从印象中衡量?

每次显示广告时;你有机会改变信仰。您选择了一个关键字。有人搜索了你的关键字。在这一点上,有一个转换的机会。用户必须同时单击您的广告,然后转换以接收实际转换;但是,从印象中测量可以显示可能的总转化率。

How CPI is Calculated

CPI is calculated by dividing total impressions by the total conversions.

CPI = conversions / impressions

It is generally displayed as a percentage. Here are some examples:

Ad 印象 转换 CPI
1 10,000 12 0.12%
2. 10,000 5 0.05%
3. 10,000 15 0.15%
4. 10,000 14 0.14%
5 10,000 13 0.13%
6. 10,000 10 0.10%

In this example, ad 3 has the highest CPI and ad 2 has the lowest Conversion per Impression.

The Advantage of using CPI as Your Testing Metric

The main reason to use CPI is when you want the most conversions possible. As this metric takes into account both CTR and conversion rate, it’s a simple metric that will show you which ad will lead to the most total conversions possible.

Working with CPI

There are times that when you examine the full metrics behind various ads, you might not always pick the highest CPI winners. This usually happens for a few reasons.

Let’s take a look at a full chart of data and then examine how we’d pick the various winners (click the chart to see a larger version).


If we just want the most conversions possible; then ad 3 is our clear winner. It receives 15 conversions for every 10,000 impressions. This is why CPI is such as great metric. Ad 3 is not the winner in CTR (that’s ad 4) or the winner in conversion rate (that’s ad 6). In comparison to our other ads; ad 3 has both a good CTR and a good conversion rate, but it is not a winner or loser in either metric. However, when you use both CTR and Conversion rate to calculate the most conversions possible for and ad; then ad 3 is our clear winner.

如果我们正在与质量分数作斗争;然后,我们可能会选择广告4,因为它的CTR比其他广告高得多,这也是为什么它的CPC比其他广告低,而且它的CPI也离我们的优胜者不远。

如果我们的目标是30美元的注册会计师,我们希望30美元以下的转化率最高;然后,我们将消除所有CPA高于30美元的广告,并从剩下的那些广告中选择CPI最高的广告作为我们的赢家;这是公元5年。

如果我们一个月只想要10条线索,那么就尽可能少地支付这10条线索;那么广告6将是我们的赢家,因为它拥有所有广告中最低的CPA,每月可以达到10次转换(假设这是每月的广告数据)。

使用我们的数据进行下一次广告测试

假设我们想要尽可能多的转换,或者在32美元的注册会计师目标下,甚至是尽可能多的转换,那么广告3就是我们的明显赢家。然而,我们应该在下一组广告测试中学习其他广告。在这一点上,检查在总体指标中失败但在单个指标中获胜的广告是有用的。

例如,广告4显然是CTR的赢家。为什么?广告中有没有一句话对用户很有吸引力?我们可能想在下一次广告测试中使用这一行。我们可以复制ad 3,添加该行,然后运行另一个测试。

为什么广告6的转化率如此之高?它的CTR确实很低。很有可能,这则广告是“预认证”用户,其广告文本旨在过滤掉用户。我们可以看看这个限定条件是什么,在新的广告3副本中使用它,然后测试这个组合。

最后,ad 2是转换率失败。为什么?我们可能想添加一条关于线路的注释以避免,因为这条广告显然吸引了错误类型的点击。

何时不使用CPI

CPI的一个缺点是它不关心收入或订单总额。如果您有一个电子商务网站,并且希望根据ROA或收入目标进行转换,那么CPI不是一个很好的数字。

CPI is great for lead generation, or the most conversions possible. However, since revenue and ROAS are not numbers used in its calculation, there are other metrics, such as ROAS or RPI/PPI (revenue/profit per impression) metrics that are better to use for ecommerce companies. We’ll cover these additional metrics later.

结论

Conversion per impression is one of the best ad testing metrics you can use since it is a simple number that lets you see which ad will lead to the absolute most conversions.

The largest downside of CPI testing is that it does not take into account revenue per conversion. So while it’s a great metric to use for lead generation companies, it might not be suitable to ecommerce companies.

If you have hard CPA targets, then you can use CPA as a filter to remove ads that are above your target CPAs and then pick your highest CPI ad as your winner; so many companies should use both CPA and CPI testing metrics to choose their winners.

If you are not taking into account revenue for your testing metrics, then you should always evaluate CPI when determining your winners – it’s that good of a metric to use for your testing needs.

Testing Metric Details: ROAS vs ROI vs Conv. Value / Cost

The next two metrics we need to discuss, ROAS and RPI (revenue per impression) rely on tracking revenue and often on talking about ROAS and ROI.

Before we get into those metrics, we need to examine how data is passed back and forth to your PPC accounts in order to use terminology that is somewhat in line with marketing and economic terms.

There is a lot of confusion about ROAS, ROI, and Google’s Conv. Value/Cost metric, we’re first going to dig into these metrics before proceeding to how to use them in your ad testing.

The History of ROI vs ROAS in Search Marketing

Return on investment (ROI) has been long misused in search. The true formula for ROI is ROI = (revenue – cost) / (cost).

这个公式被许多营销人员扭曲为ROI=(收入)/(成本)(请注意,公式不正确,我们稍后将介绍正确的公式)。他们选择使用这个错误的公式,因为投资回报率可能是负数,而负数会使投标计算更加复杂。错误公式中的100%ROI是您的盈亏平衡点(假设您没有考虑硬商品的成本),因此计算变得很容易。对此的简单解释是,由于您正在计算营销成本,因此您只需从计算ROI的公式中删除这些相同的成本。

当搜索营销在早期主要由非营销人员进行时,网页设计师或IT部门经常进行付费搜索,这种定义上的细微变化通常对公司并不重要。然而,随着搜索业务发展成为一项价值数十亿美元的业务,并在大学市场营销课程中教授,必须努力纠正这些术语的使用,以便公司各部门之间保持一致。

ROAS公式为ROAS=(收入/广告成本)。ROAS公式与许多搜索营销人员使用的扭曲或错误的ROI公式相同。

虽然这种差异对每个人都不重要,但如果你遇到一位CFO审核你的数字,他们会非常关心ROI与ROA的差异。

ROAS vs ROI示例

让我们简单地看一下ROI和ROA之间的区别。

运动 PPC成本 收入 ROAS 投资回报率
1 $1000 $2000 200% 100%
2. $1000 $1000 100% 0%
3. $1000 $500 50% -50%

在本例中,为了使活动3达到收支平衡,需要将其出价降低50%。

通过使用ROAS作为我们的出价乘数,可以在Excel中轻松计算,因为ROAS总是一个正数(或0);因此,大多数营销人员都使用ROAS来设定出价。如果您使用ROI,因为这个数字可以是正的,也可以是负的,所以您需要建立一个更复杂的公式来计算您的出价。最后,答案是一样的:将出价降低50%以达到收支平衡。

This is why most PPC marketers actually use ROAS even if they say they are using ROI. Please note, this isn’t everyone – many people know the difference and are calculating these numbers correctly. However, at every conference I attend, at least one speaker uses the ROI term incorrectly.

ROAS is not Always ROAS

If you are ignoring hard costs such as salaries and manufacturing, and if you are selling a digital good – then ROAS is usually a good number to work from and your ROAS is your actual ROAS.

However, if you are selling physical goods then you need to remove the cost of those goods from your revenue to calculate bids and determine ad test winners.

Please note, this cost of physical goods does not always have to be physical goods. If you are selling hosting packages, then you’d want to remove your costs for servers, bandwidth, etc as they are hard costs. However, there’s not an easy way to do this in Google Ads, hence why we’re going to stick to physical good examples since that can be programmatically accomplished.

Google Ads allows you to pass dynamic variables to your account based upon the sale. (Information on how to do that here).

Most advertisers are passing along the total sale of goods (excluding shipping) to Google Ads who are using this feature. In this case, ROAS is not true ROAS since the cost of goods is not being removed before the metric is calculated. This is why a lot of companies do not have a 100% break even ROAS. They might have a 200% ROAS target to break even since they have to accommodate for the cost of goods in their calculations. In these cases, the company might have a 400% ROAS target for the account to be profitable.

Some companies are passing total cost of goods sold minus cost of hard goods to Google Ads. In this case, ROAS really is ROAS (again, assuming you’re only talking goods and no other fixed costs).

盈亏平衡点

如果您正在计算实际ROA,那么,如果您在计算数字之前有100%的利润或扣除商品成本,那么100%的ROA就是盈亏平衡。如果您销售的是产品,而没有扣除这些产品的成本,那么100%的ROAS意味着您在每次销售中都会损失产品的成本,并且可能会损失运输成本。

200%的ROAS意味着你每花一美元,就能带来两美元的收入。50%的ROAS意味着你每花一美元,只赚50美分。换句话说,50%的ROAS意味着你在亏损。

这就是计算ROA和ROI更为棘手的地方,因为我们假设我们只讨论商品成本和营销成本。一些公司通过计算所有成本来计算收入和利润,这些成本可以包括管理费用、工资等。因此,即使在一家公司内,对于相同的指标,您也可能有两种不同的计算方法。

谷歌也很困惑

如果你将收入金额转入谷歌广告,那么你可以在谷歌广告账户中看到你的“转换价值/成本”数字。

Google Ads界面中的转换值列

此列的计算方法是将总转换值(即您传递给Google的该数据点(即广告、关键字等)的总收入数字)除以这些相同点击的成本。

转换值/成本=总转换值/成本。

如果您将鼠标悬停在?在谷歌广告中,您将看到以下谷歌工具提示:

每成本转换价值(“转换价值/成本”)衡量您的投资回报。它是转换值除以所有广告交互的总成本。此指标中的成本不包括不能导致转换的交互,例如不使用转换跟踪时发生的交互。。

谷歌表示,这个数字是您的投资回报率(ROI)。然而,这并不准确,因为使用的公式是ROAS公式,而不是ROI公式。

Please note, most people show ROAS and ROI as percentages. Google shows it as a whole number. So a 2750% ROAS is displayed in Google Ads as 27.5. These are the same number, only the display changes.

A High ROAS Does Not Always Mean More Profits

ROAS and ROI are simple ratio metrics. It is possible for one ad to have a higher ROAS than another ad, but have less profits.

Here’s a very simplistic look at two ads:

Ad Cost 收入 ROAS Profit
1 5000 10,000 2. 5,000
2. 3000 7,000 2.33 4,000

In this example, ad 2 has a higher ROAS but less profits. Ad 1 has a lower ROAS and higher profits.

It’s useful if you can to calculate profits along with ROAS for your campaigns. This is another reason that we like using revenue or profit per impression in our ad testing; and we’ll cover that metric soon.

Wrap Up

When you are going to say ROI or ROAS, think back to what math which you are using for the basis of that statement. Is it your actual ROAS, your ROI, or some version of ROAS you use inside your PPC department for bidding that might not be your actual ROAS?

If your team has a 200% break-even ROAS, then you aren’t calculating ROAS. You might internally use the term ROAS as a way to describe your numbers, but this number is more akin to cost of revenue calculations (although, that’s not quite right either).

We’re going to discuss how to test by ROAS and Revenue/Profit per impression metrics. These are two great metrics to use for ecommerce accounts. However, we needed to first define ROAS and its various permutations before we can easily discuss how to use ROAS and RPI/PPI for testing purposes.

Testing Metric Details: ROAS & ROI

ROAS (return on ad spend) and ROI (return on investment) are two common methods of ad testing for ecommerce accounts.

If you are dynamically passing your conversion values to Google Ads; then you’ll have a column known as Conv. Value/Cost in your account. This stands for Conversion Value / Cost.

Google Ads界面中的转换值列

该值是根据您将数据从系统传递到谷歌广告的方式计算的。如果您传递的是全部结帐金额(希望减去运费);那么这个值通常是ROAS。如果您通过结帐金额减去硬商品;那么这个值通常是ROI。

由于这些指标可能会令人困惑,您可以参考前一篇文章,了解如何在PPC中计算ROA和ROI。

因为谷歌广告中的这个数字并不总是ROAS或ROI,我们将使用转换价值/成本,因为这是您在帐户中看到的。

转换价值/成本的计算方法

转换值/成本的计算方式与您的想法完全一致:它取一个数据点(如ad)的整个转换值,然后除以该数据点的成本。

转换价值/成本=(总转换价值)/(成本)

而ROA和ROI通常以百分比表示;谷歌将其显示为一个整数。以下是一些示例:

Ad 换算值 Cost 转换价值/成本
1 100 300 0.3
2. 500 500 1
3. 1000 700 1.4
4. 10,000 1000 10
5 15000 3500 4.3

在本例中,ad 4的转换价值/成本最高,ad 1的转换价值/成本最低。

使用转换价值/成本作为测试指标的优势

公司喜欢使用ROA作为测试指标有两个主要原因。

第一个是投标一致性。许多电子商务公司根据ROA或ROI进行投标;因此,在他们的广告测试中使用相同的指标可以确保他们的广告测试与他们的投标目标一致。

第二个原因是它确保了支出是有利可图的。许多公司要求该帐户具有正ROA,例如400%以确保该帐户正在赚钱。通常,这些数字高于其真实目标,因为他们可能没有从账户中扣除商品成本或其他成本,因此通过将目标ROA或转换价值/成本高于其真实目标,他们知道账户或广告测试正在赚钱。

The Disadvantage of using Conv. Value / Cost as Your Testing Metric

The downside of using Conv. Value / Cost as a testing metric is that it doesn’t care about volume. For instance, what winner would you pick from this chart:

Ad Cost Conv. Value Conv Value
/cost
Profit
(conv value – cost)
1 100 1000 10.0 900
2. 1000 5000 5 4000
3. 1200 1000 0.8 -200
4. 800 5000 6.3 4200
5 5000 12,000 2.4 7000

If you picked the ad with the highest conv. value/cost, ad 1 at a 10; then you’re only making 900 in profit (assuming there’s no other hard costs).

If you picked ad 4, the second highest conv. value/cost then you’d make 4200.

If you picked ad 5, one of the lowest conv value/cost; then you’d make 7000.

So while ad 5 is best for the company, the highest conv. value over costs is actually one of the least profitable ads.

Using Conv. Value / Cost as a Filter

In many cases, our conv. value / cost isn’t actually all profit, its total revenue but hard goods aren’t removed (again, this depends on the data you’re passing to Google Ads) so your profit might not be profit, it’s really just revenue minus marketing costs. Therefore, you might have a conv. value target of 5 and your breakeven point is a 3.

In that case, ad 5 would lose you a lot of money since it’s actually below your breakeven point. Therefore, you have to filter out any words below a 3 Conv. Value/cost and then take the highest profit word after the filtering is completed, which would be ad 4.

The other option would be to first remove all hard costs, and then work from profit in picking your ad tests. Just note, that the highest conversion value/cost or even highest ROI/ROAS ads might not be the most profitable ones for the company. This is common when you place emphasis on high volume low margin ordering versus lower volume higher margin products.

无论如何,Conv.Value/Cost可以是一个很好的过滤器,用来删除没有达到目标的广告,然后你可以使用其他指标来挑选赢家。

结论

如果你想让你的出价方法与广告测试方法保持一致,那么使用转换值/成本是一个不错的测试指标。

请记住,转换价值/成本是谷歌广告中的一个指标,它可能与ROI、ROA甚至其他指标相关,具体取决于其配置。

转换价值/成本的下降在于它是收入与支出的比率。它不考虑利润或数量。

因此,这是一个很好的筛选指标,在使用另一个指标来确定您的获奖广告之前,可以用来删除无利可图的广告。

在下一篇文章中,我们将讨论使用RPI(每个印象的收入)作为测试指标。对于电子商务账户来说,这通常是比选择赢家的转换价值/成本更好的衡量标准。

然而,即使使用RPI,您可能仍然会首先使用Conv.Value/cost作为筛选指标,然后使用RPI来挑选赢家。

测试指标详细信息:每个印象的收入/利润(RPI/PPI)

RPI(每个印象的收入),有时也称为每个印象的利润(PPI),是一个很好的测试指标,可用于电子商务账户或具有可变结帐金额的账户。

RPI或PPI之间的差异不在您的PPC帐户中的度量计算中。区别在于你如何将数据传递给你的谷歌广告账户,以及你是否在数据中使用ROA或ROI,我们之前已经讨论过了。

In this article, instead of constantly saying revenue/profit per impression (depending on how you are passing data) – we’re going to be consistent and just use RPI and revenue. However, if you are taking out the cost of goods (or don’t have any hard costs) before you pass your revenue data to Google Ads; then you can substitute the word profit instead of revenue throughout this article.

RPI (revenue per impression) is a metric that shows you the ratio between your impressions and the amount of money you make. This is very similar to conversion per impression (CPI) with the exception that we are adding actual revenue into the equation and not just using conversion data.

When you consider ad testing, which combination is better?

It’s impossible to say which is better since that information relies on three different metrics: CTR, Conversion Rate, Revenue (or RPS – revenue per sale).

When to use Conversions instead of Revenue

When you have variable checkout amounts, instead of using conversions, using revenue gives you a more accurate picture of how much money you are making and lets you accurately determine ROAS and Conv. Value/Cost. For items that are consistently sold – this is the best metric in most cases to use as its your actual sales data.

There is a time when using CPI or plain conversion data is better than using revenue in your testing and management: when you have random outlier sales that skew the data drastically and are not repeatable.

例如,我们的一个早期电子商务客户每月约有300笔销售额。他们的平均销售额约为500美元。然而,在这300起销售中,大约有10-20起是针对超过10000美元的订单。月复一月–他们收到10-20份高价值订单,远高于其网站上几乎任何其他销售。带来这些销售额的广告和关键词从来都不是一个月比一个月。他们将从关键词或广告中获得销售的事实是可以预测的;然而,出售的金额是不可预测的。因此,将收入用于投标或广告测试指标是一个坏主意,因为一个月的数据与下个月的数据不一致。然而,由于他们将获得销售的事实是可以预测的,而不是销售收入,因此他们最好在广告测试和投标管理中使用CPI(每个印象的转化率)。

另一个例外是,当你想要尽可能多的客户时,不管他们的结帐金额是多少。例如,如果你正试图建立一个客户群,那么1000个销售额为10美元(收入1万美元)比500个销售额为30美元(收入1.5万美元)更让你高兴。这也是一个例外情况,不是大多数公司的常见管理方式。

在这些边缘案例场景之外,如果您从事电子商务或拥有可变的结帐金额(如托管公司、域名,甚至咨询包),那么使用您的实际收入可以让您最大限度地提高广告测试的收入,而不仅仅是转化率。
我们应该明白,对大多数公司来说,衡量收入和实际收入比衡量转化率更重要。由于你的广告可能会影响平均订单价值、追加销售、交叉销售等–你要衡量的是广告实际为你带来了多少收益,而不仅仅是它们给你的PPC账户带来了多少转化。

对大多数人来说,问题是:为什么我们要从印象中衡量?

为什么要从印象中衡量?

如果你仔细想想,每次你的广告被显示出来,你都有机会转换。您选择了一个关键字。有人搜索了你的关键字。在这一点上,有一个转换的机会。用户必须同时单击您的广告,然后转换以接收实际转换;但从印象中衡量,可以显示出总的转化率和可能的收入。

如何计算RPI

RPI的计算方法是总印象除以总收入。

RPI=收入/印象

它通常显示为货币类型。以下是一些示例:

Ad 印象 转换 收入 平均销售额 RPI
1 10,000 12 1200 100 0.12
2. 10,000 5 2500 500 0.25
3. 10,000 15 1500 100 0.14
4. 10,000 14 8400 600 0.84
5 10,000 13 7200 900 0.72
6. 10,000 10 500 50 0.05

为了便于说明,我们对每个广告使用了完全相同的印象数。这种情况很少发生。然而,由于我们使用了相同的印象,最高的收入(广告4)是最高的RPI(0.84)。

该广告不是最高的转化率(广告3)或最高的平均销售额(广告5)。广告4是每个印象的最高收入,这意味着当广告4出现时,你比其他任何广告都赚得多。

如果你的重点是最大化你的收入,那么你会想用广告4作为你的赢家。

使用RPI作为测试指标的优势

使用RPI的主要原因是您希望获得尽可能多的收入。由于这一指标同时考虑了CTR和实际收入,因此这是一个简单的指标,可以告诉您哪一个广告将带来尽可能多的总收入。

Working with RPI

There are times that when you examine the full metrics behind various ads, you might not always pick the highest CPI winners. This usually happens for a few reasons.

Let’s take a look at a full chart of data and then examine how we’d pick the various winners (click the chart to see a larger version).


If we just want the most conversions possible; then ad 3 is our clear winner. It receives 15 conversions for every 10,000 impressions. If our goal is the most conversions – this is our winner. However, it has a lower ROAS and RPI than some other ads.

If our goal is ROAS; then ad 1 is our winner. It’s also our highest converting ad. However, it has a low CTR and thus is going to have a poorer quality score than some of the other ads. It has a lower RPI and makes less money than some other ads. This is why ROAS is a good metric for bid management, but rarely for ad testing.

If we want the most revenue possible, then ad 4 is our clear winner. It’s the highest revenue and highest RPI (because the impressions are equal among all the ads).

A common way to also use RPI, since it doesn’t care about ROAS, is to use ROAS as a filter. For instance, you might have a goal of 500% ROAS. Therefore, any ads underneath that ROAS target can’t be a winner and you eliminate them. Among the ads that are left, the highest RPI would be your winner. If your goal was a 600% ROAS, then you’d eliminate ad 4 and of the ads left, ad 1 becomes the winner since it has the highest RPI among ads with at least a 600% ROAS.
使用我们的数据进行下一次广告测试
你不想为所有的失败者丢掉你的数据。您总是想检查它以找到其他想法进行测试。例如,我们的转化率最高的广告是6和1,甚至广告3也高于最高的RPI广告。因此,我们想看看这些广告,看看它们能带来更好的点击率。

我们想看看ad 5,因为它的平均订单价值最高,并了解原因。它是否在登录页上有不同的交叉销售或追加销售项目,或者它会影响平均订单价值。

广告2是一个明显的转化率失败者。它给我们带来了如此可怕的点击,这是怎么回事?我们想把这则广告和它的创意记下来,作为未来的一个警告,即该广告的创意或推广效果不佳。

一旦我们检查了数据,我们就可以暂停所有失败者并创建一个新的广告来测试获胜的广告。

找到科学广告测试指南确定测试指标:选择符合目标的指标测试指标详细信息:每印象收入/利润(RPI/PPI)
测试指标详细信息:每个印象的收入/利润(RPI/PPI)
RPI(每个印象的收入),有时也称为每个印象的利润(PPI),是一个很好的测试指标,可用于电子商务账户或具有可变结帐金额的账户。

RPI或PPI之间的差异不在您的PPC帐户中的度量计算中。区别在于你如何将数据传递给你的谷歌广告账户,以及你是否在数据中使用ROA或ROI,我们之前已经讨论过了。

In this article, instead of constantly saying revenue/profit per impression (depending on how you are passing data) – we’re going to be consistent and just use RPI and revenue. However, if you are taking out the cost of goods (or don’t have any hard costs) before you pass your revenue data to Google Ads; then you can substitute the word profit instead of revenue throughout this article.

RPI (revenue per impression) is a metric that shows you the ratio between your impressions and the amount of money you make. This is very similar to conversion per impression (CPI) with the exception that we are adding actual revenue into the equation and not just using conversion data.

When you consider ad testing, which combination is better?

A high CTR and a low conversion rate
Lots of people click on your ads, so your page gets a lot of visibility, but not many of those users turn into customers
A low CTR and a high conversion rate
Not many people click on your ads, but of those that do, many of them convert
A high conversion rate, but the average order is low
A low conversion rate, but the average order is high
It’s impossible to say which is better since that information relies on three different metrics: CTR, Conversion Rate, Revenue (or RPS – revenue per sale).

When to use Conversions instead of Revenue
When you have variable checkout amounts, instead of using conversions, using revenue gives you a more accurate picture of how much money you are making and lets you accurately determine ROAS and Conv. Value/Cost. For items that are consistently sold – this is the best metric in most cases to use as its your actual sales data.

There is a time when using CPI or plain conversion data is better than using revenue in your testing and management: when you have random outlier sales that skew the data drastically and are not repeatable.

例如,我们的一个早期电子商务客户每月约有300笔销售额。他们的平均销售额约为500美元。然而,在这300起销售中,大约有10-20起是针对超过10000美元的订单。月复一月–他们收到10-20份高价值订单,远高于其网站上几乎任何其他销售。带来这些销售额的广告和关键词从来都不是一个月比一个月。他们将从关键词或广告中获得销售的事实是可以预测的;然而,出售的金额是不可预测的。因此,将收入用于投标或广告测试指标是一个坏主意,因为一个月的数据与下个月的数据不一致。然而,由于他们将获得销售的事实是可以预测的,而不是销售收入,因此他们最好在广告测试和投标管理中使用CPI(每个印象的转化率)。

另一个例外是,当你想要尽可能多的客户时,不管他们的结帐金额是多少。例如,如果你正试图建立一个客户群,那么1000个销售额为10美元(收入1万美元)比500个销售额为30美元(收入1.5万美元)更让你高兴。这也是一个例外情况,不是大多数公司的常见管理方式。

在这些边缘案例场景之外,如果您从事电子商务或拥有可变的结帐金额(如托管公司、域名,甚至咨询包),那么使用您的实际收入可以让您最大限度地提高广告测试的收入,而不仅仅是转化率。

我们应该明白,对大多数公司来说,衡量收入和实际收入比衡量转化率更重要。由于你的广告可能会影响平均订单价值、追加销售、交叉销售等–你要衡量的是广告实际为你带来了多少收益,而不仅仅是它们给你的PPC账户带来了多少转化。

对大多数人来说,问题是:为什么我们要从印象中衡量?

为什么要从印象中衡量?
如果你仔细想想,每次你的广告被显示出来,你都有机会转换。您选择了一个关键字。有人搜索了你的关键字。在这一点上,有一个转换的机会。用户必须同时单击您的广告,然后转换以接收实际转换;但从印象中衡量,可以显示出总的转化率和可能的收入。

如何计算RPI
RPI的计算方法是总印象除以总收入。

RPI=收入/印象

它通常显示为货币类型。以下是一些示例:

广告印象转换收入平均销售额RPI
1 10,000 12 1200 100 0.12
2 10,000 5 2500 500 0.25
3 10,000 15 1500 100 0.14
4 10,000 14 8400 600 0.84
5 10,000 13 7200 900 0.72
6 10,000 10 500 50 0.05
为了便于说明,我们对每个广告使用了完全相同的印象数。这种情况很少发生。然而,由于我们使用了相同的印象,最高的收入(广告4)是最高的RPI(0.84)。

该广告不是最高的转化率(广告3)或最高的平均销售额(广告5)。广告4是每个印象的最高收入,这意味着当广告4出现时,你比其他任何广告都赚得多。

如果你的重点是最大化你的收入,那么你会想用广告4作为你的赢家。

使用RPI作为测试指标的优势

使用RPI的主要原因是您希望获得尽可能多的收入。由于这一指标同时考虑了CTR和实际收入,因此这是一个简单的指标,可以告诉您哪一个广告将带来尽可能多的总收入。

Working with RPI
There are times that when you examine the full metrics behind various ads, you might not always pick the highest CPI winners. This usually happens for a few reasons.

You are struggling with Quality Score and you want to pick a high CTR ad if it leads to similar total conversions in order to raise QS
In general, the higher the CTR, the higher your quality score will be
You have a hard cap on how low your ROAS can be and therefore, you have to pick an ad that is over your target ROAS
Let’s take a look at a full chart of data and then examine how we’d pick the various winners (click the chart to see a larger version).

image

If we just want the most conversions possible; then ad 3 is our clear winner. It receives 15 conversions for every 10,000 impressions. If our goal is the most conversions – this is our winner. However, it has a lower ROAS and RPI than some other ads.

If our goal is ROAS; then ad 1 is our winner. It’s also our highest converting ad. However, it has a low CTR and thus is going to have a poorer quality score than some of the other ads. It has a lower RPI and makes less money than some other ads. This is why ROAS is a good metric for bid management, but rarely for ad testing.

If we want the most revenue possible, then ad 4 is our clear winner. It’s the highest revenue and highest RPI (because the impressions are equal among all the ads).

A common way to also use RPI, since it doesn’t care about ROAS, is to use ROAS as a filter. For instance, you might have a goal of 500% ROAS. Therefore, any ads underneath that ROAS target can’t be a winner and you eliminate them. Among the ads that are left, the highest RPI would be your winner. If your goal was a 600% ROAS, then you’d eliminate ad 4 and of the ads left, ad 1 becomes the winner since it has the highest RPI among ads with at least a 600% ROAS.

使用我们的数据进行下一次广告测试

你不想为所有的失败者丢掉你的数据。您总是想检查它以找到其他想法进行测试。例如,我们的转化率最高的广告是6和1,甚至广告3也高于最高的RPI广告。因此,我们想看看这些广告,看看它们能带来更好的点击率。

我们想看看ad 5,因为它的平均订单价值最高,并了解原因。它是否在登录页上有不同的交叉销售或追加销售项目,或者它会影响平均订单价值。

广告2是一个明显的转化率失败者。它给我们带来了如此可怕的点击,这是怎么回事?我们想把这则广告和它的创意记下来,作为未来的一个警告,即该广告的创意或推广效果不佳。

一旦我们检查了数据,我们就可以暂停所有失败者并创建一个新的广告来测试获胜的广告。

何时不使用RPI

不使用RPI的主要时间是在不考虑平均订单值的情况下。在这些情况下,您可以将CPI作为主要测试指标。

结论

每个印象的收入或利润是您可以使用的最佳广告测试指标之一,因为这是一个简单的数字,可以让您看到哪个广告将带来绝对最大的收入。

RPI测试最大的缺点是,它不考虑客户或广告级别的ROAS目标,如果您的收入在不同订单之间差异很大,那么它可能会被异常值所扭曲。如果你有硬ROAS目标,那么你可以使用ROAS作为过滤器来删除低于目标的广告,然后选择你的RPI最高的广告作为赢家;因此,许多公司应该使用ROA和RPI测试指标来选择他们的赢家。

The other issue with RPI is that it relies on consistent data. If your orders are highly inconsistent or you have random outlier orders, then CPI may be a better testing metric for you.

Determine Your Testing Metrics: Choose a Metric that Fits Your Goals

There is not a ‘best’ testing metric for everyone.

There is a best testing metric based upon what you are trying to accomplish.

We’ve put together a quick reference chart to easily let you see what testing metric you should be using:

What do you want to do? The metric you should use
Increase conversions Conversion per Impression (CPI)
Increase visitors Click Through Rate (CTR)
Increase engaged visitors Conversion per Impression (CPI)
Get the most revenue possible Revenue per Impression (RPI)
Improve quality scores Click Through Rate (CTR)

There are two noticeable metrics missing from this list: ROAS and CPA.

Those two metrics should be filtering metrics and not winning metrics.

For instance, if you want the most conversions possible at a $35 target CPA; then you would use CPA as a filter and remove any ad that is above the $35 CPA target and then of the ads left, the highest CPI would be the winner.

These are the cases to use filtering metrics:

What do you want to do? Filtering metric Winning metric
Highest revenue above a specific ROAS ROAS Revenue per Impression (RPI)
Most conversions under a target CPA CPA Conversion per Impression (CPI)

Working with Statistical Significance: How confident should you be in your test results?

In layman’s terms, statistical significance is the how likely a result is caused by something other than random chance. Essentially, this is how confident you are in the data that random chance didn’t cause winners and losers.

统计显著性和最小数据之间存在关系(稍后我们将介绍)。

例如,如果你把一枚硬币掷4次,有1/16的几率硬币的正面会全部出现4次。然而,在第五次投掷时,你仍然只有50%的机会获得另一个头。这是因为每次你掷硬币,你都有一半的机会看到正面或反面。但是,在连续投掷时,需要考虑之前投掷的变量,以确定连续5次看到头部的几率(即32分之一)。这就是为什么我们在计算置信因子之前需要一定数量的最小数据。

最终,赔率迎头赶上,在100次翻转后,假设这是一枚普通硬币,你可能会有47-53个头像。如果在100次投掷后,你看到了90次头部,你要么是在一个非常奇怪的趋势上(应该去维加斯),因为这是非常不可能的结果,要么是统计数据表明你的硬币不符合规定,你玩的是一枚重量不正确的硬币。

事实上,如果你投掷一枚硬币20000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000。然而,如果您查看的是整个样本集,而不是任何一个连续的数字,那么您将看到正面和反面都有50%的时间出现。

当你为任何一个广告测试结果选择信心因素时,你实际上是在说,“我对这些结果有多大信心,这个结果是有意义的,不是偶然的?”
由于你的广告是搜索者看到的账户中唯一的一部分,当你选择成功和失败的广告时,你要确保你对结果有信心,并且你不会因为偶然而选择赢家。

我们经常被问及信心因素,以及在采取行动之前,人们对自己的结果应该有多大的信心;因此,我们根据关键字类型制作了一个方便的参考图表:

术语类型 最小置信度
长尾关键字 90%
中期数据术语 90% – 95%
您销售的第三方品牌 90%(小品牌)至95%(大品牌)
热门关键词(你每天看的那些) 95% – 99%
您的品牌条款 95%(未知品牌)–99%(知名品牌)

总的规则很简单:一个词对你的账户越重要,在你采取行动之前,你希望信心系数越高。

根据专家统计学家的说法,在采取行动之前,你永远不想对自己的结果信心不足90%。

很可能,您已经将您的帐户细分为各种活动。有些活动是品牌化的,有些是长尾的,还有一些是信息术语、“英雄术语”、竞争对手等等。因此,只需按活动类型记录您的最低信心水平就很有用了。

现在,下次有人想讨论信心因素时,在谈话中只需要记住几个规则:

与统计显著性和置信因子密切相关的另一个数据点是最小数据。这是您在确定结果是否重要之前要使用的最少信息量。

使用最小数据

最小数据是计算统计显著性之前应使用的最小数据集。

If your ad tests don’t have enough data, then you shouldn’t pause ads or make adjustments based upon the data since there is a high likelihood any differences you see are due to chance and not actual patterns within the data.

For instance, this is a test result after 97 impressions:

Ad

印象

点击次数

CTR

Confidence

Control

40

1

2.5%

Ad 2

33

5

15.15%

97.03%

Ad 3

24

0

0%

15.57%

In purely math terms, we do have a 97% confidence that ad 2 will be a winner. If this was a static data environment where the data that comes later is similar to the data that came before, we might take an action. However, search is a dynamic environment and it’s obvious that 97 impressions is not enough data (although, any online calculator will tell you it is).

Here’s the exact same test after 3163 impressions:

Ad

印象

点击次数

CTR

Confidence

Control

1023

23

2.25

Ad 2

993

29

2.92%

82.9%

Ad 3

1147

56

4.88%

99.96%

In this case, all of our ads have almost 1000 impressions, and we’re 99.96% confident in our winner (a different winner than at 97 impressions) and thus we can be confident that we can take actions on CTR based testing at this point in time.

At the low data levels, what you really want to avoid is having just one or two people significantly affect your data. For instance, if you have 100 impressions and 1 click, then you have a 1% CTR. If the next 2 people click your ad, your CTR goes from 1% to 2.91% CTR; which is a huge change and can completely affect which winning or losing ad you would have chosen.

When the data starts to grow, then you want to ensure that you have a sample size that is large enough so that a small percentage of searchers can’t significantly affect your data, which is why you want a larger and larger sample size the more impressions that an ad test generates within a given time frame.

Part of a minimum data consideration that does not exist within the realm of purely mathematical analysis is the variance of time.
例如,设想以下三种情况:

那只是周一,但你周一晚上的搜索可能发生在手机上,你的转换将给自己发送一个工作提醒,在周二早上检查结果。你周一早上的转换可能是下载白皮书或打电话。

现在,那只是星期一。如果你在寻找度假邮轮,周一的搜索会考虑你有多想逃离办公室,而周六下午的搜索可能会与你计划购买的邮轮度假的配偶一起进行。

随着时间框架的变化,搜索行为也会发生变化——这就是为什么我们不仅需要考虑数据,还需要考虑数据的时间框架。您应该始终使用至少一周的数据。然而,在采取行动之前,可以使用一个月甚至三个月的时间收集数据。
在确定最小数据时,有两个考虑因素:

你的测试指标是什么

在您知道要定义哪些数据点之前,我们需要确定测试指标。

例如,如果您是通过CTR进行测试,那么您的转换并不重要,因为CTR在计算中不使用转换数据。

大多数指标都有一个必需的数据点(因为这是机会)和一个用于计算该指标的辅助数据点(操作)。

例如,点击率是印象与点击的比率。你必须有一个印象才能点击。因此,印象是强制性的,但点击是可选的。

In some cases, you might not want to define the optional metric. For instance, let’s say we’re running two ad tests with this data set:

In this test, we’re confident that ad 1 is the better ad and has achieve over a 90% confidence interval. However, if we defined a minimum of 25 clicks, we’d still be waiting for results since ad 2 hasn’t hit that number yet. When you define the optional data points, you might wait longer to achieve results if one of your tests is significantly below average (in this case a 10% vs 1% CTR).

With minimum data, every ad in the test should hit the minimum data before you look at the information – not the test combined. As there are two ad rotation options, which we will cover later, it is common that not all ads within a test have the same opportunity, and thus each ad should meet the minimum requirements before you examine your confidence levels.

As timeframe is highly important to any test, all metrics should be using a timeframe minimum of at least a week; although, using monthly data works just as well.

Here’s the minimum data that you should define by testing metric:

Metric

印象

点击次数

转换

Timeframe

CTR

Yes

Optional

Yes

CPA

Yes

Yes

Conversion rate

Optional

Yes

Yes

CPI

Yes

Optional

Yes

ROAS

Yes

Yes

RPI

Yes

Yes

How Much Data Do You Generate each Month

We’re often asked to suggest minimum data amounts. There are times I’m hesitant to give out numbers because not everyone should be using the same numbers.

If you have a brand term that is searched 1 million times a week, you should be using at least a million impressions as your minimum. For many brands, they aren’t searched 1 million times in a year, and should be happy with 10,000 – 100,000 impressions before they examine their confidence levels.

These are MINIMUM DATA recommendations. It is OK to use higher numbers than these.

大多数公司的最低数据建议:

印象

点击次数

转换

低流量

350

300

7.

交通堵塞

750

500

13

高流量

1000

1000

20

知名品牌术语

100,000

10,000

100 – 1000

由于您的活动通常按品牌、产品术语、长尾等进行细分,因此每个活动中的广告通常可以使用相同的最小数据。您经常会对帐户的不同部分使用不同的指标、最小数据和统计显著性因素。

定义最大数据量

有时您将运行ad测试;但是测试太相似了,或者用户对测试变化的反应没有太大的不同,你永远不会达到统计显著性。

如果仅定义最小数据和最小置信因子;这些类型的测试可以运行数年,您将失去进一步提高转化率的机会。

因此,您不仅要定义最小数据,还需要定义最大数据。

如果你的广告达到了你的最大数据,但还没有达到你的最低置信水平,那么你需要结束广告测试,继续前进。

定义最大数据通常有两种方法:

  1. 使用最少10倍的数据
  2. 使用3个月的时间框架(假设您的测试高于最低数据)

定义广告测试的最小和最大数据可以确保你正在努力寻找可操作的信息,即使该操作只是为了结束测试,因为结果无效,而是从不同的假设开始。

对于Adalysis用户,我们会自动提醒您测试结果高于最低数据阈值,并且已经运行了至少3个月,但尚未达到您的最低置信水平。无需担心定义此信息。如果您在Excel或其他系统中进行测试,请确保您定义了最大数据量,这样您就不会运行不会产生任何结果的ad测试,这样您就一直在努力提高性能。

Ad旋转设置

如果一个广告组中有多个广告,则广告轮换设置将决定每个广告的显示频率。根据您的测试和您最喜欢的指标,您应该考虑您正在使用的轮换设置,以及它如何影响您接收统计显著性数据以做出测试决策的能力。

Ad旋转设置

2017年,四个轮换选项中的两个退出后,现在只有两个广告轮换设置可供您选择用于谷歌广告活动:

谷歌广告账户中的广告轮换设置

广告服务百分比

广告送达百分比显示每个广告在您的帐户、活动或广告组中送达的频率。

谷歌广告中的广告服务栏

在检查这些数据时,务必记住您正在查看的时间范围。如果您暂停或删除了在检查时间段内处于活动状态的广告,则除非您显示这些广告,否则您的广告服务百分比总和可能不会达到100%。

此外,只有在所有广告同时运行时检查数据才有用。如果您在一个月前创建了一个广告;但你看到的是过去三个月的数据;当然,看起来新的广告没有合适的广告服务百分比;它不能,因为在你检查的三个月中,有两个月它没有活动。

Ad轮换如何影响最小可行数据

任何广告测试都应该有最少的可行数据量,例如最少的时间、点击、印象和转换。根据您用于广告测试的指标类型和您正在测试的关键字类型(如品牌与产品),这些指标可能会有所不同。

Adalysis中的帐户测试阈值

When your ad served percentages are skewed towards a single ad, the other ads receive fewer impressions. Since they have fewer impressions, these other ads also receive fewer clicks and conversions. Since these ads are receiving less data, it takes longer for those ads to build up enough minimum viable data to make statistically significant decisions. You can collect the data faster with the right ad rotation setting.

Which Setting to Choose?

Optimize: Prefer best performing ads

If you use Google automated bidding, this is the only option you have. Even if your campaign doesn’t have this setting chosen explicitly in the settings, Google uses the optimize setting and chooses how to serve your ads.

Due to how ads are served unevenly, using this setting generally makes your ad tests take longer to reach statistical significance. This setting will sometimes display the incorrect ad the most, which can lower your clicks and conversions. Thus, you want to ensure you are testing ads, choosing winners, and pausing losers when using this setting as the worst-performing ad can end up with the most impressions.

This example shows how the ad with the best data in every metric was served 55,656 times versus the ad that is a statistically significant loser in every metric being served almost 6 times as often at 299,221 impressions.

Ad测试示例

If the company just pauses the losing ad, they’d see their clicks and conversions immediately increase. This is why you need to watch your ad tests when using optimize as once Google’s machine learning decides which ad to show the most often if the data shows it was an incorrect decision, the machine rarely fixes the ad serving problem.

Do not optimize: Rotate ads indefinitely

If you are bidding manually, meaning you are setting bids by hand, using a script to set your bids, or using a third party bid manager, then you should use ‘Do not optimize: Rotate ads indefinitely’.

这是用于广告测试的最佳广告轮换设置,因为所有广告都有更高的机会获得同等份额的印象。

让我们看另一个例子。在这个广告测试中,有一个广告是CTR的赢家,另一个广告是其他指标的赢家。如果你真的被优化了,那么每个印象转化率最高的广告应该是显示频率最高的广告。

在这种情况下,CTR最高的广告显示频率是转化率和每次印象转化率最高的广告的3倍。

当你有一个广告的点击率高于另一个广告,而另一个广告的转化率或每个印象的转化率更高时;谷歌通常默认CTR高于其他指标。

获奖广告示例

在这种情况下,切换到“不优化”将确保您的广告或多或少获得相似的曝光。这一变化将引导您快速找出哪些广告将为您提供更多的转换,以及哪些广告需要暂停,因为在大多数指标中,这要糟糕得多。

此外,如果你在一个广告群中引入5个或5个以上的广告,谷歌的广告服务可能会变得非常混乱,而且广告似乎是随机提供的,而不是确定要提供的最佳广告和最频繁地提供该广告。

例如,在本次广告测试中,印象最低的广告(图表按印象从高到低的顺序排列)是CTR或我们正在测试的其他指标的优胜者。然而,总体数据最差的广告被服务的频率更高,在任何指标中都不是最好的广告的印象(107335)明显高于转化率最高的广告(15107印象)。当你在一个广告群中有太多的广告时,谷歌会感到困惑,甚至不会在使用优化的广告服务时依靠CTR或每个印象的转化率。

AB测试中的优胜者广告示例

This is also a common issue when new ads are introduced. With optimize ad serving, sometimes the new ads rarely get impressions and a chance to show what they can achieve.

In all of these cases, if you are serious about ad testing, you should be using ‘Do not optimize: Rotate ads indefinitely’ in campaigns with manual bidding (i.e., not using Google automated bidding strategies). With this ad rotation option, you get faster ad testing results, and across ad groups your ads are served more evenly making multi-ad group testing very accurate for getting insights into large sets of ads.

However, if you are ignoring your ad tests and not adding many new ads, then using the ‘Optimize: Prefer best performing ads’ can be OK to use as Google making some good and bad choices is better than doing nothing.

If you are using Google’s automated bidding, then you don’t have a choice over which ad serving option to use. Therefore, you want to watch your ad tests closely to ensure that your favorite ads are being served the most often.

Ending Your Ad Tests

Taking action is fairly simple. Once you have defined:

Then you can follow a simple flowchart to see if your action is to wait or take action:


Taking action involves:

Further insights is a vague notion; however, there is much to be gained by ad testing.

Here are some examples:

Ad tests give you an amazing amount of insight about how users interact with your ads. These insights can be used for other parts of your marketing. It is more common to leverage insights from multi-ad group tests than single ad group tests in these ways since multi-ad group tests include a lot more keywords and ad group than single ad group tests do.

The actions themselves are not very difficult. The trick is to first determine your criteria for winning and losing ads so that you know when to take an action.

The overall steps to ad testing are:

Once you start testing your ads, you can learn amazing things about how your visitors interact with you creatives and constantly improve your overall PPC performance.

If you want to automate many of these tasks and make ad testing incredibly simple, try Adalysis for free.

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