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餐飲vi設(shè)計公司轉(zhuǎn)發(fā)原文直譯：

A/B測試是網(wǎng)絡(luò)營銷的熱門話題。老實說，這是有原因的。沒有A/B測試，你的網(wǎng)上營銷永遠(yuǎn)不會發(fā)揮其全部潛力。

在破壞性的，我們親眼目睹了無數(shù)客戶的遭遇。

通過一次測試，我們在兩周內(nèi)為一個客戶賺了七萬美元。通過另一個項目，我們在幾個月內(nèi)創(chuàng)造了超過43,000美元的收入。另一項測試在幾周內(nèi)增加了數(shù)千美元的收入。

這些只是A/B測試為我們的客戶所做的幾個例子。關(guān)鍵是，如果你不進(jìn)行A/B測試，你就把錢留在了桌子上。

那么到底什么是A/B測試呢？你如何使用它？更重要的是，你如何為你的企業(yè)獲得這些結(jié)果？

嗯，你來對地方了。在這篇文章中，我們將涵蓋所有這一切，甚至更多。

現(xiàn)在，你可能會想到，這是一篇相當(dāng)長的文章，所以為了幫助你瀏覽，這里有一些文章各個部分的快速鏈接：

什么是A/B測試？

為什么A/B測試很重要

A/B測試如何工作

提出A/B測試的想法

充分利用您的A/B測試

多重變異測試

聽起來像個計劃嗎？讓我們深入了解一下A/B測試的世界。

什么是A/B測試？

A/B測試背后的想法相當(dāng)簡單。你花了很多時間和精力讓人們訪問你的網(wǎng)站或登陸頁面。為什么？因為你想讓他們轉(zhuǎn)化——做一些對你的生意有益的事情。

你希望他們填表、購物、給你打電話、參觀你的實體場所、查看某個頁面、訂閱你的時事通訊……這樣的事情不勝枚舉。

唯一的問題是，你不知道你的網(wǎng)站是幫助還是傷害你的轉(zhuǎn)化率。

幾乎不可能預(yù)測人們會如何回應(yīng)你的網(wǎng)站。不管你有多喜歡（或討厭)你的網(wǎng)站設(shè)計，你真的不知道什么對你的網(wǎng)站流量有用，什么沒用。唯一真正知道的方法就是給你的流量展示不同版本的網(wǎng)站，看看哪個版本產(chǎn)生的轉(zhuǎn)化率最好。

簡而言之，這就是A/B測試。

通過A/B測試，您可以創(chuàng)建兩個不同版本的網(wǎng)站或登錄頁面（版本A和版本B——因此得名)。然后，您在這兩個版本（也稱為變體)之間分割您的流量。

一旦有足夠多的人訪問了你的網(wǎng)站，以確定人們更喜歡哪種變體，你就和獲勝者一起去…并重新開始整個過程。

當(dāng)然，所有這些只是觸及了A/B測試的表面。老實說，我們已經(jīng)寫了幾十篇關(guān)于A/B測試的來龍去脈，如何提出測試想法和方法來改進(jìn)你的網(wǎng)站設(shè)計的博文，但是你并不需要所有這些來開始。

因此，在本文的其余部分，我們將重點關(guān)注A/B測試的基礎(chǔ)，以及如何開始使用它來從您的活動中賺更多的錢。

為什么A/B測試很重要

現(xiàn)在，你可能會想，我已經(jīng)知道我的網(wǎng)站需要改進(jìn)。難道我不能找到一些最佳實踐的文章，改進(jìn)我的網(wǎng)站，獲得A/B測試的所有好處，而不需要所有的測試嗎？

這是一個很好的問題。不幸的是，即使轉(zhuǎn)化率優(yōu)化(A/B測試的另一個名稱)專家也很難預(yù)測哪些變化會提高你的轉(zhuǎn)化率。

為了證明這一點，我們實際上在幾年前的一次會議上對營銷人員進(jìn)行了A/B測試。我們最近為一個客戶成功運行了A/B測試，表單完成量增加了146.2%。

當(dāng)然，我們知道哪個變體產(chǎn)生了最好的結(jié)果，但是我們想知道會議上的轉(zhuǎn)化率優(yōu)化(CRO)專家是否能預(yù)測出獲勝者。

這是他們必須選擇的頁面變體。你認(rèn)為哪一個產(chǎn)生了最好的轉(zhuǎn)化率？

V3是我們測試中勝出的頁面，但是猜猜我們的陰極射線示波器專家選擇了哪一頁？V2，不是V3 .

現(xiàn)在，這些都是陰極射線示波器的頂尖專家。當(dāng)談到優(yōu)化網(wǎng)站設(shè)計，這些人真的知道他們的東西。但是即使有這些專業(yè)知識，超過一半的人選擇了錯誤的變體。

為什么？因為你不是你的顧客。不管你有多喜歡某個特定的網(wǎng)站元素或設(shè)計，那也不能保證它對你的客戶有效。唯一真正確定的方法是通過A/B測試。

A/B測試如何工作

不久前，我們使用A/B測試將一個客戶的轉(zhuǎn)化率提高了22%。乍一看，你可能會想，"多么偉大的案例研究啊！你是怎么得到這些結(jié)果的？"

如果你真的想知道我們做了什么，答案很簡單：我們?nèi)∠送扑]。

這難道不令人興奮嗎？推薦降低轉(zhuǎn)化率！

如果你還沒有嘗試刪除你的推薦，你應(yīng)該走出去，試著從你的網(wǎng)站上刪除推薦。畢竟，你的推薦可能會降低你22%或更多的轉(zhuǎn)化率…對嗎？

不完全是。

平均而言，推薦通常會提高轉(zhuǎn)化率。事實上，當(dāng)我們剛開始與這個客戶合作時，如果你告訴我他們的推薦降低了他們的轉(zhuǎn)化率，我可能會和你爭論這一點。

那么，如果我們非常確定他們的推薦提高了他們的轉(zhuǎn)化率，為什么我們要試圖擺脫他們呢？

這不僅僅是一個隨機(jī)的猜測。我們首先測試了許多其他假設(shè)…

正如你從這張GIF格式上看到的，在我們最終嘗試刪除推薦之前，我們已經(jīng)研究了這個頁面的十幾個版本。

不是每個測試都提高了客戶的轉(zhuǎn)化率，但是每個測試都教會了我們一些關(guān)于目標(biāo)受眾的東西，幫助我們發(fā)現(xiàn)我們的流量真正想從他們的網(wǎng)站體驗中得到什么。

有效的測試在每次測試中都教會你一些東西。但是，如果你想從每一次測試中學(xué)到一些東西，你不能只是測試隨機(jī)的想法——你需要有策略地測試。

記住這一點，讓我們來討論一個可靠的A/B測試策略的四個基本部分：

1.你的買家角色

在你開始頭腦風(fēng)暴測試想法之前，你需要創(chuàng)建一個詳細(xì)的買方角色。

本質(zhì)上，你的買方角色給你一個定義你的測試假設(shè)的結(jié)構(gòu)和一個理解你的結(jié)果的框架。

至少，您的買家角色應(yīng)該包括以下內(nèi)容：

人口統(tǒng)計信息（年齡、性別、位置、種族等)

預(yù)算

動機(jī)（責(zé)任、目標(biāo)、興趣等)

棘手問題（恐懼、挫折、需求等)

您的企業(yè)如何解決他們的棘手問題

您可能需要與您當(dāng)前的客戶或您的銷售團(tuán)隊交談來獲得這些信息，但是了解您的目標(biāo)受眾可以幫助您更快地產(chǎn)生好的測試結(jié)果。

案例研究筆記：我們對目標(biāo)受眾的了解

由于與這位消息靈通的客戶進(jìn)行了一些詳細(xì)的討論，我們對他們的目標(biāo)受眾有了很多了解。平均而言，我們的目標(biāo)受眾是有錢投資的中年男女。

我們的觀眾想明智地使用他們的錢，但是他們也認(rèn)識到他們沒有足夠的知識來明智地投資他們的錢。

有了這些知識，我們就可以為測試定義一些目標(biāo)了。

2.你的目標(biāo)

如果你不知道你的測試要達(dá)到什么目的，就很難構(gòu)建出產(chǎn)生有意義結(jié)果的變體。

現(xiàn)在，你可能已經(jīng)很清楚你想通過測試達(dá)到什么目的了，但是讓我們詳細(xì)說明一些細(xì)節(jié)。

成功是什么樣子的？（更多線索？更多電話？更多的銷售…提示，最好的答案是更多的銷售)。

你希望你的客戶采取什么步驟？（什么將幫助他們更接近成為付費客戶？).

你的測試需要產(chǎn)生什么具體的結(jié)果才能"成功"?（參見第一個要點)。

定義你的總體目標(biāo)和你的潛在客戶在實現(xiàn)這些目標(biāo)的道路上需要采取的具體步驟，會讓你清楚地了解你應(yīng)該測試什么樣的變化。

案例研究筆記：定義我們的目標(biāo)

在這個客戶的案例中，我們將成功定義為銷售額的增加（看，我告訴過你"更多的銷售額"是最好的答案)。然而，為了實現(xiàn)這個目標(biāo)，我們需要客戶的網(wǎng)站為他們的銷售團(tuán)隊提供更多合格的銷售線索。

此外，客戶有許多不同的選項可供潛在客戶選擇，因此頁面需要確定潛在客戶最感興趣的選項。

現(xiàn)在我們知道了我們的目標(biāo)是誰，我們的目標(biāo)是什么，是時候提出一些假設(shè)了。

3.你的假設(shè)

在這一點上，你的工作是嘗試和猜測你網(wǎng)站上的哪些因素阻礙了你的目標(biāo)受眾做你想讓他們做的事情，以及你如何消除或減少這些因素。

案例研究筆記：生成假設(shè)

以下是我們提出的一些假設(shè)：

我們的提議是錯誤的。也許我們的標(biāo)題或正文沒有傳達(dá)我們的觀眾想要聽到的信息。

下一步還不清楚。也許人們想簡單地填寫我們的表格，而不是點擊一系列的信息收集頁面。

我們的內(nèi)容順序不對。也許我們的觀眾在我們的頁面中迷失了方向，或者他們一到達(dá)就想看到特定的頁面元素。

我們有太多的內(nèi)容。也許我們所有的內(nèi)容會讓我們的觀眾分心或不知所措。

我們沒有選擇正確的情感。也許我們的觀眾對我們的英雄射手配色方案沒有共鳴。

有了這些（以及其他各種假設(shè)),我們就可以開始測試了。

4.記錄和學(xué)習(xí)

測試策略不會在測試開始時就結(jié)束。你需要記錄所有的事情，并利用你所學(xué)到的知識來開發(fā)新的假設(shè)和測試。

根據(jù)您喜歡做事情的方式，您的文檔可以相當(dāng)簡單或相當(dāng)復(fù)雜，但是您的方法需要有條不紊——每個測試都需要教會您一些東西，您可以使用這些東西在下一次測試中產(chǎn)生更好的結(jié)果。

例如，以下是您如何跟蹤一系列行動號召測試的結(jié)果：

是的，記錄每件事需要額外的努力，但這比簡單地隨機(jī)測試新想法更容易也更有效。此外，如果有人問你為什么你的頁面是這樣設(shè)置的，你會得到一個可靠的、基于數(shù)據(jù)的答案。

案例研究筆記：從我們的測試結(jié)果中學(xué)習(xí)

一旦我們開始測試，我們發(fā)現(xiàn)當(dāng)我們把我們的觀眾放在駕駛座上時，他們的轉(zhuǎn)化率最高。強(qiáng)有力的銷售讓這些觀眾大倒胃口。

結(jié)果，我們最終得到了一個簡單的CTA，它允許我們的觀眾在我們要求他們提交信息之前表明他們對什么感興趣。

我們還發(fā)現(xiàn)，我們的目標(biāo)受眾想要簡單的東西，所以我們確保我們的標(biāo)題和正文強(qiáng)調(diào)客戶的服務(wù)是多么簡單快捷。

然而，在某一點之后，我們只能說這么多來清楚地表明，與我們客戶的業(yè)務(wù)合作是容易和簡單的。

因此，我們試圖消除頁面元素，看看簡化頁面是否有助于強(qiáng)化我們的客戶完全專注于為他們的客戶創(chuàng)造簡單、輕松的體驗這一理念。

結(jié)果，我們的轉(zhuǎn)化率提高了22%——但這并不令人驚訝。

在了解了我們的目標(biāo)受眾想從我們的網(wǎng)站得到什么之后，我們知道一個簡單的、有針對性的頁面會說服我們客戶的潛在客戶進(jìn)行轉(zhuǎn)化……事實也的確如此。

提出A/B測試的想法

根據(jù)經(jīng)驗，你應(yīng)該總是A/B測試一些東西。每一次點擊不僅僅是獲得另一次轉(zhuǎn)化的機(jī)會，也是了解你的受眾的機(jī)會。

但是，您不能只是為了測試而測試，您需要一種策略來確保每個測試至少回答以下問題中的一個：

這個頁面元素如何影響轉(zhuǎn)化率？

對此頁面元素的更改如何影響轉(zhuǎn)換率？

我的頁面布局如何影響轉(zhuǎn)化率？

我的副本如何影響轉(zhuǎn)化率？

我的圖片如何影響轉(zhuǎn)化率？

我的形式如何影響轉(zhuǎn)化率？

回答和優(yōu)化這些問題需要大量的計劃和測試，但是如果你是A/B測試的新手或者只是面臨"測試者的障礙",創(chuàng)建一個有效的測試策略可能是一個相當(dāng)大的挑戰(zhàn)。

考慮到這一點，我概述了一個偉大的A/B測試策略的一些關(guān)鍵組成部分，以及一些測試思路，以幫助您提高每個領(lǐng)域的轉(zhuǎn)化率。

考慮一個大的改變

有時候，你的網(wǎng)站不適合你的觀眾。也許它不適合你的廣告，也許你的價值定位不清晰，也許你的設(shè)計不適合你的流量。

在許多情況下，你可能甚至沒有意識到你的網(wǎng)站或頁面不適合你的流量，這就是為什么嘗試一些完全不同的東西會有幫助。

如果您的流量有限，這可能特別有用。變化越大，它對你的轉(zhuǎn)換率的影響就越大，這意味著獲勝的頁面設(shè)計會很明顯，網(wǎng)站訪問量會少很多。

這種方法實際上可以使用幾種不同的A/B測試策略：

1.從大到小

如果你的目標(biāo)是快速獲得大的結(jié)果，你會希望從測試你的頁面或網(wǎng)站的大的改變開始。你現(xiàn)在正在做的事情可能不起作用，所以你需要嘗試一些非常不同的事情來開始。

雖然這種方法肯定是有效的，但它也有缺點。

首先，你不知道為什么你的測試有效或者無效。有太多的變量在起作用，很難真正評估所有新元素對你的轉(zhuǎn)換率的影響。

結(jié)果，你好像又回到了起點。事情現(xiàn)在可能在起作用，但是你真正知道的是你現(xiàn)在做的比你以前做的更好。然而，一旦你有了合適的工作方式，你就可以從相對優(yōu)勢的位置著手，真正優(yōu)化你的新設(shè)計。

如果你的網(wǎng)站流量每月少于6000次，這可能是最好的方法。由于流量有限，每個測試都需要很長時間，所以試圖在前期優(yōu)化每個站點元素可能需要幾個月到幾年的時間。

2.從小到大

另一方面，如果你的目標(biāo)是真正了解你的目標(biāo)人群，以及你的網(wǎng)站的具體變化是如何影響潛在客戶的，那么最好從小處著手，逐步推進(jìn)。你的網(wǎng)站運行得足夠好，你想知道的是如何最大化它的潛力。

這種方法需要更多的時間和流量來產(chǎn)生大的結(jié)果，但它也為你提供了做出明智的未來決策所需的知識。隨著時間的推移，你的小變化的總和將累積成大的設(shè)計和內(nèi)容改進(jìn)，從而顯著提高你的網(wǎng)站的效率。

這種方法對于每月有6000次網(wǎng)站訪問的網(wǎng)站來說是非常棒的，也是像亞馬遜這樣的大型網(wǎng)站產(chǎn)生數(shù)百萬額外收入的原因。

定義您的總體目標(biāo)允許您構(gòu)建您的實際測試策略，以產(chǎn)生您想要的結(jié)果。從那里，你可以確定實際的測試參數(shù)，讓你達(dá)到你的目標(biāo)。

改變你的行動號召

讓別人響應(yīng)你的號召是你網(wǎng)站的最終目標(biāo)，所以這是A/B測試的必要條件。同時創(chuàng)造一種價值感，確定當(dāng)他們轉(zhuǎn)換時會發(fā)生什么，并敦促用戶采取你想要的行動并不是一件容易的事情。

以下是在三醋酸纖維素上進(jìn)行測試時需要考慮的一些事情：

復(fù)制

考慮將"了解更多"這樣更通用的短語改為"與專家交流"你的三醋酸纖維素越清晰，通常就越有效。測試一下就知道了！

顏色

按鈕顏色對轉(zhuǎn)化率的重要性一直是許多在線嘲笑和辯論的主題，但事實是——對一些公司來說——改變按鈕顏色產(chǎn)生了令人印象深刻的結(jié)果。這可能不是一個保證的勝利，但這就是為什么你運行測試。至少，你的按鈕顏色應(yīng)該比頁面的其他部分更突出。

位置

你把三醋酸纖維素放在哪里可能對你的轉(zhuǎn)化率有很大影響。對于某些頁面，將它放在折頁上方可能很重要。在你使用三醋酸纖維素訪問其他頁面之前，其他頁面可能需要更多的信息，所以有必要進(jìn)行A/B測試，看看低成本三醋酸纖維素如何為你的頁面服務(wù)。

設(shè)計

你的三醋酸纖維素的設(shè)計其實可以影響你的轉(zhuǎn)化率。簡單的改變，如圓角或添加陰影或漸變，很容易測試。你也可以考慮添加圖片（比如他們將要購買的產(chǎn)品的圖片)或某種信任印章，讓你的三醋酸纖維素更有吸引力。

附加三醋酸纖維素

如果你有一個很長的頁面，在頁面的下面添加一兩個三醋酸纖維素可能是值得的?；蛘撸憧梢試L試添加一個滑動側(cè)邊欄三醋酸纖維素或三醋酸纖維素到你的滑動標(biāo)題。

這不是指環(huán)王，沒有"一個三醋酸纖維素來統(tǒng)治他們。"測試不同的CTA，直到你得到一個真正適合你的聽眾的元素組合。

嘗試你的形式

如果你營銷的目標(biāo)是讓人們填寫并提交表單，那么A/B測試表單內(nèi)容和設(shè)計是另一個絕對必須的。

關(guān)于表單最佳實踐有很多爭論，但是確實沒有任何方法可以知道哪種表單最適合您的受眾。為了真正優(yōu)化表單的性能，您需要測試幾種變體。

考慮下面的測試（更多的想法，請查看本文):

縮短表單（或者，如果您有許多不合格的銷售線索，您可以考慮延長表單以添加合格字段)

左對齊表單標(biāo)簽

從垂直形式變?yōu)樗叫问剑ǚ粗嗳?

更改包含表單的框的背景

增加（或減少)必填字段的數(shù)量

將你的表格分成多個步驟

添加安全封條

嘗試燈箱形式

除了三醋酸纖維素優(yōu)化之外，表單優(yōu)化也是你在網(wǎng)站上進(jìn)行A/B測試的首要任務(wù)之一。你不希望他們點擊你的三醋酸纖維素只是為了在填寫你的表格時失去興趣！

試試新的英雄射擊

一張圖片勝過千言萬語，在這種情況下，它可能值得一千次轉(zhuǎn)換。

改變你的英雄射擊是一個可以產(chǎn)生重大結(jié)果的小改變。傳統(tǒng)上，當(dāng)用戶登陸你的頁面時，你的英雄照片會抓住他們的注意力。

以下是一些可以考慮嘗試的測試：

你的英雄鏡頭的情感。你的英雄鏡頭傳達(dá)了快樂嗎？對你的產(chǎn)品或服務(wù)滿意嗎？一個痛點的挫敗感？試著改變一下，看看會發(fā)生什么。

主題。用一個快樂的人的庫存照片？嘗試一個城市景觀，一個真實用戶或你的產(chǎn)品的快照，平面藝術(shù)甚至是純色！

種族/文化。根據(jù)您的產(chǎn)品或服務(wù)，某些種族或文化可能更容易被某些圖片所識別。例如，如果你賣的是一張溫馨的非裔美國家庭共享光明節(jié)的照片

Your hero shot and other images are relatively easy to test and they can have a big effect on your conversion rate, so try changing things up!

Your headlines and body content are?a key?part of your messaging. Essentially, there are two key areas you should look into testing.

Headlines are the part of your content that your audience is most likely to read, so these need to be succinct, compelling and on point for your messaging.

Try testing out headlines with industry buzz words against headlines advertising an offer to see which does a better job of grabbing your audience’s interest. However, if you are only changing your headline, you need to make sure that your new headline is consistent with the rest of your content—otherwise you’ll need to adjust the rest of your page, too.

How much do you really need to say? Sometimes a shorter page works better. Other times, you really need to explain more to convince people to convert. Try A/B testing various amounts of text or discussion points to see what works best.

In addition, consider changing the layout of your content to see if that affects your conversion rate. Your audience may be interested in or need to be reassured by a specific point earlier on the page, so changing where and how your information is presented can significantly affect conversion rate.

Overall, A/B testing is one of the best ways to improve the performance of your site. But, to use A/B testing effectively, you need to have a great testing strategy in play.

Just like any other aspect of digital marketing, if you want to succeed at A/B testing, you need a great strategy.?According to VWO, only 1 in 7 A/B tests produce a winning result.

That means 86% of them fail.

Fortunately, the right?testing strategy can dramatically improve your success rate. For example, using the tactics outlined in this blog post, the majority of our tests (5/7) substantially improve our clients’ conversion rates.

What makes our tests so?effective? Yes, we’ve got years of experience under our belt; but, more importantly, we start every set of tests with a thorough testing strategy that maximizes our chances for success and sets us up to learn from everything—even failure.

With that in mind, here are some of the questions we ask?while planning each?series of tests:

This question might seem obvious, but you wouldn’t believe how many people think?they are testing one thing and when they are?actually testing something else.

If your test isn’t set up to test what you think you’re testing, you won’t learn anything. For example, there’s nothing wrong with?testing to see if a new call-to-action, hero shot and page layout will improve your conversion rate;?but, if your new page content/design?performs better, you can’t assume that it was because of the new CTA.

It might have been the CTA, but it?also might have been the new hero shot, page layout or the combination of all three!

That being said, the more dramatic your?changes, the more likely they are to produce dramatic results. If?you want to know how a new design will affect conversion rates, go for it! Just don’t use the results of your test to draw conclusions about your new CTA.

If you’re new to site testing, that 86% failure rate can be daunting. After all, there’s a very real chance that?your tests are going to perform about the same or worse (possibly much worse) than your current iteration. The more traffic you test, the more you put your bottom line at risk if something goes south.

The problem is, unless your website has a lot of traffic that’s already converting?at an acceptable rate, a conservative testing strategy will slow down your time to results. If your site isn’t working well (which is probably why you’re testing), your test probably isn’t going to make things that much worse.

The more traffic you push into your test, the faster you can figure out whether or not your new idea is working, learn from the test and press on to bigger and better things.

For this reason,?I typically recommend testing around 50% of your traffic so that you don’t put your bottom line at serious risk. Once your site is performing at an acceptable level, you can dial back to 10-20% to avoid rocking the boat too much.

As mentioned in the previous section, the more traffic you put towards a test, the faster you’ll get results. For example, if your online marketing isn’t profitable and you’ll have to shut things down in 6-months if you don’t boost your conversion?rate?by 200%, you might commit most or all of your traffic to your test to get things figured out as quickly as possible.

Marketers that want real results know that testing is an ongoing effort that will continue to pay big dividends. Fortunately, with a great strategy in place, you don’t have to test 7 times to produce a win. You’ll always have tests that don’t perform the way you expect them to, but the right strategy will allow you to use those tests as learning experiences that set your next test up for even greater success.

As you run your test, keep in mind that there’s a lot of emotion involved in site testing. If one arm of a test starts to perform better, it’s easy to start seeing dollar signs. If your variant starts to do worse, it’s hard not to turn off the poor performer. It’s losing you money, after all.

The problem is, you have to wait to get meaningful data. It’s a statistical fact that the more traffic you push through your test, the more accurate your results will be.?If you jump the gun and call a test early, you’ll be basing your decisions on emotion rather than data.

If that’s how you’re going to run your website, you might as well skip the whole testing thing.

Now, this is considered heresy amongst the statistical community, but you don’t always have to hit 95% confidence before accepting the results of a test. If you’ve got low traffic, 75-80% confidence may be all that you can get in a reasonable time frame. Sure, there’s a higher probability that your results might be off, but it’s the best you can do.

For marketing, it’s more important to decide what your acceptable confidence level is and then get enough data to reach that level of confidence. If you decide you’re okay with a 25% chance that your test data is wrong, then call the test at 75% confidence. Just don’t say you’re going to wait until you hit 75% confidence and then pull the plug at 50%.

If you want to improve your conversion rate in meaningful ways, you need to wait for meaningful data. As exciting or devastating as the initial results might look, you have to wait for the data to sort itself out.

Over the years, CRO seems to have become synonymous with A/B testing in the minds of many?marketers.

But here’s the thing, A/B testing isn’t the?only way to do CRO.

It might not roll off the tongue as nicely as “A/B testing”, but if you’ve got enough traffic, A/B/C/D/etc testing can allow you to produce?meaningful results much more quickly.

For example, Optimizely studied and reported on the factors that?defined the world’s best testing companies.

Guess what the 4 biggest factors were?

Does #4 surprise you? Apparently, the most effective CRO?doesn’t come from?A/B testing—it comes from testing multiple variants.

To put this in more concrete terms, according to Optimizely, just 14% of A/B tests?significantly improve conversion rates. On the other hand, tests with 4?variants improve conversion rates 27% of the time.

So, if you test 4?variants, you are 90% more likely to improve your conversion rate than if you just ran an A/B test.?However, 65% of CRO?tests are—you guessed it—A/B tests!

Basically, there are two reasons why multiple variant testing outperforms A/B testing: 1) it’s faster and 2) it allows you to test more?variants under the same testing conditions.

Sure, you can test the same things with a series of A/B tests as you can with a multiple variant test—it just takes?a lot?longer.

When you run an A/B test, you can really only learn one thing from your test. Your variant will either perform better, the same or worse than your original.

And that’s it, that’s all you can learn.

Now, if you’re smart about your A/B testing strategy, your results can teach you a lot about your audience and?make your future tests smarter, but you’re still only learning one thing from each?test.

On the other hand, with multiple variant testing, you can try out several?ideas?at the same time. That means you can simultaneously test multiple hypotheses.

So, instead of just learning that a hero shot with a smiling woman outperforms a shot of a grumpy man, you can also?see?if a grumpy woman image?drives more results than the?grumpy man pic or if a happy man outshines them all.

Or, you can try multiple combinations, like a new headline or CTA in combination with either the smiling woman or the grumpy man.

Running all of these tests simultaneously will allow you to optimize your page or site much more quickly than you could with a long series of A/B tests.

Plus, running a test with multiple variants will greatly improve the odds that a single test will deliver at least one positive result, allowing you to start getting more from your website?sooner.

Another problem with?successive A/B tests?stems from the fact that the world changes over time.

For example, if you are in ecommerce?and run your first A/B test during October and your second test during November, how do you know if your results aren’t being skewed by Black Friday?

Even if your business isn’t seasonal, things like differences in your competitors marketing strategies, political change or a variety of other variables can make it difficult to directly compare the results of A/B tests.

As a result, sometimes it can be hard to know if?a particular A/B testing variant succeeded (or failed) because of factors outside of your control or even knowledge. The more tests you run, the murkier your results may become.

However, with a multiple variant test, you are testing all of your variants under the same conditions. That makes it easy to compare apples-to-apples and draw valid, reliable conclusions from your tests.

To show you just how testing multiple variants can improve your marketing results, let me share an experience we had with one of our clients.

The client?wanted to get site traffic to their “Find Your Local Chapter” page, so?we decided to add a “Find Your Local Chapter” link to the client’s footer. That way, the link would be seen by as many people as possible.

Makes sense, right?

So, we put together something that looked like this:

At first, we figured we would just put the link in the footer and run a test to see if the link made a difference.

But then, we started wondering if there was a way to make the link even more noticeable. After all, getting traffic to this page was a big deal to the client, so it made sense to emphasize the link.

With that in mind, we added color to the link:

Now, this idea seemed logical, but at Disruptive, we believe in testing, not gut instinct, so we figured, “Hey, we’ve got enough traffic to test 3 variants, let’s take this even?further!”

The problem was, the client’s site was a designer’s dream—modern and seamlessly designed. To be honest, we had a bit of trouble selling them on the idea that creating a page element that interrupted their seamless flow was worth testing.

But, eventually, we convinced them to try the following:

It was very different from anything the client had tried?on the page before, but we decided to run with the idea and include it in our test.

A few weeks and 110,000 visitors later, we had our winner:

Not surprisingly, adding the?“Find Your Local Chapter” link?increased page visits by over?60% for every variant—that’s an awesome win, right?

But here’s the thing. With our original, strict A/B test, we would only have discovered that adding the link increased traffic by 63%.

On the other hand, by including a couple of extra variants, we were able with the same test to discover that—contrary to the client’s belief—the more our link “interrupted” the site experience, the more traffic it drove to the chapter page.

Sure, we might have reached the same conclusion with several more tests, but we achieved these results much more quickly and reliably than we would have with an A/B testing series.

As great as multiple variant?testing is, it does have one big limitation: if you don’t have enough traffic, a test could take months or years to complete.

In fact, in true multivariate testing—where you test to see how a large number of subtle changes interact to generate?your conversion rate—you want at least?100,000 unique visitors per month (for more information on multivariate testing, check out this great article).

On the other hand, you need far less traffic to simultaneously?test multiple page variants.

To see how long a multiple variant test will take on your site, try out this?VWO has a free sample size and test duration calculator from VWO. If the time frame makes sense for your business, go for it!

And that’s A/B testing. Or, at least, that’s enough about A/B testing to get you started.

A/B testing is a process, so you can expect to learn a lot as you begin testing your site. It will take time, ingenuity and patience, but you’ll soon be getting much better results from your marketing campaigns.

The best part about A/B testing is that it makes every aspect of your marketing better. You learn more about your audience, which helps your advertising. You discover what your customer really want, which makes it easier to create content that they’ll respond to. Most important of all, your site produces better results, which lifts every aspect of your marketing.

If you’re feeling a little overwhelmed, don’t worry, we’re here to help. You can either reach out to us here for a free consultation or you can check out the dozens of articles we’ve written about A/B testing and CRO here on the Disruptive blog.

Have you tried A/B testing? How did it go? What tips or tricks would you add to this article? Leave your thoughts in the comments below.

Author

Over his career, Aden has developed and marketed millions of dollars of successful products. He lays awake at nights figuring out new marketing tactics and is constantly upping Disruptive's internal marketing game. He loves to write, dance and destroy computer monitors in full medieval armor.

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