a/b testing Archives

Upleveling A/B Testing with AI for Conversion Optimization

With artificial intelligence (AI) generated content sending traditional SEO into a tailspin, converting traffic that does make it to the website is more important than ever to marketers.

The challenge in our digital age is that traditional A/B testing methods are slow, resource-intensive, and miss hidden opportunities. Click To Tweet

Since the early days of digital marketing, one common way to improve on-page conversions has been A/B testing. The challenge in our digital age is that traditional A/B testing methods are slow, resource-intensive, and miss hidden opportunities.

Enter A/B testing with AI and machine learning, a game-changer that supercharges optimization efforts. Let’s look at ways to uplevel your A/B testing with AI to optimize conversions.

What is A/B Testing?

A/B testing, also known as split testing or bucket testing, is a randomized experiment that compares two versions of content to determine which one performs better. As this graphic shows, A/B testing is an effective tool to increase website and landing page performance.

Source: FinancesOnline

The testing process involves randomly showing users two or more page variants and then using statistical analysis to determine which version performs better.

Marketers can use the results to measure user behavior and make decisions based on statistics.

Marketers use these tests to optimize marketing campaigns, improve UI/UX, and increase conversions. For example, a marketer can test adding a payment method to an e-commerce store to see if it increases or decreases average revenue per user. Other assets testers can analyze include landing pages, display ads, buttons, and headlines.

Limitations of A/B Testing

Resources are the main limiting factors in traditional AB testing results. Anyone experienced with conventional testing knows that complexity quickly reaches an upper limit if testing relies on manual entries and calculations. Here are some examples:

Time and resource intensive. Setting up, running, and analyzing A/B tests can be time-consuming and require technical expertise. This limiting factor can be a hurdle for smaller companies or teams with limited resources.

Limited scope. Traditional A/B tests only offer insights into the variables you specifically test. They might miss broader behavior patterns or complex interactions between elements.

Difficulty achieving statistical significance. For low-traffic websites or tests of subtle changes, reaching statistical significance (where you can be confident the results are accurate and not due to chance) can be challenging, leaving you unsure of the winner.

Static and short-sighted. Traditional tests assume a stable environment, but visitor behavior and trends can shift over time. Traditional testing often struggles to optimize dynamic elements like product descriptions that constantly change based on user data or inventory. AI brings agility and personalization to this challenge.

Limited understanding of “why.” While this method shows what works, it often doesn’t reveal the underlying reasons why. This can limit your ability to apply learnings to future optimizations.

Not ideal for personalized experiences. Traditional A/B testing struggles to personalize experiences for individual users based on their unique behavior and needs.

AI-led Optimization of A/B testing

AI improves A/B testing in several ways. Machine learning algorithms analyze vast amounts of data, uncovering hidden patterns and predicting prospect behavior with remarkable accuracy.

This capability enables continuous, self-optimizing tests that adapt in real-time, identifying winning elements and delivering the best experience to each user. Gone are the days of static tests; AI unlocks a dynamic, data-driven approach to conversion rate optimization (CRO). Let’s look at some further benefits.

Benefits of A/B Testing With AI

Here are several ways AI changes the game with A/B testing:

Content Creation

No more writer’s block! Generative AI can help craft compelling A/B test variations for website copy, email campaigns, or social media posts. Consider it an intelligent collaborator who understands your brand voice and target audience, suggesting headlines, CTAs, and personalized greetings for different user segments.

Develop & Validate New Insights

Say goodbye to brainstorming in the dark. AI tools can analyze user data and past test results to suggest promising design tweaks, ad copy variations, or landing page layouts. Think of it as having a data-driven muse to spark your creativity and guide your testing roadmap.

Generate More Visuals

Ditch stock photos and generic visuals. AI algorithms can churn out unique, personalized images tailored to your target audience and specific test variables. Imagine dynamically generating product images that match a user’s search history or preferences, boosting engagement and click-through rates.

A/B Testing with AI Analyzing Results:

Go beyond basic conversion metrics. AI algorithms can delve deeper into user actions, uncovering hidden patterns and correlations that traditional analysis might miss. Imagine automatically identifying which user segments respond best to specific elements, allowing you to personalize your website and campaigns for maximum impact.

AI unlocks even deeper optimization through multivariate testing, analyzing the complex interplay of multiple variables simultaneously for truly data-driven decision-making.

By leveraging AI across these areas, A/B testing transforms from a manual, time-consuming process into a powerful engine for continuous optimization and data-driven decision-making.

How Can AI Improve Conversion Rates?

AI has the potential to significantly improve conversions by scaling the number of variables and increasing hyper-personalization.

A/B Testing on Steroids

AI can automate and optimize A/B testing, making it faster, more efficient, and more insightful. Among the benefits are:

Testing hundreds of variations. AI can simultaneously test multiple variations of website elements, ad copy, and landing pages, uncovering the optimal combination much faster than traditional methods.

Real-time conversion optimization. AI can analyze results in real-time and automatically adjust tests to optimize performance, ensuring you always show each user the best version.

Deeper insights. AI can analyze on-page actions beyond clicks and conversions, revealing hidden patterns and reasons behind user choices, leading to more informed optimization decisions.

Hyper-Personalization

AI can analyze vast amounts of user data, including demographics, browsing history, and past interactions, to tailor experiences to individual users, including:

Dynamic content. AI can personalize website content, product recommendations, and email campaigns based on individual preferences, increasing engagement and relevance.

Targeted ads. AI can analyze user actions to deliver highly relevant ads with higher click-through rates and conversions.

Personalized offers and discounts. AI can suggest customized discounts or promotions based on a user’s purchase history and interests.

With any new tool, the question is, “How do we get started?” Funnel Envy can help.

Below is a simple 5-step overview to give you a framework.

Implementing AI in the A/B Testing Process: A Five-Step Guide

Implementing an AI-powered A/B testing regime can be broken down into the following steps:

Define Your Objectives: Set clear goals – what metrics do you want to improve with AI-powered testing? Conversions, engagement, or something else?
Choose the Right AI Tool: Research your options based on budget, ease of use, and your specific needs (e.g., sample size, image generation, content creation).
Create Different Variants: Craft variations for your test elements, leveraging AI suggestions for personalization or generating multiple options simultaneously.
Analyze Your Results: Utilize the AI tool’s advanced analytics to uncover hidden patterns, go beyond basic conversion data, and understand on-page actions.
Apply Your Learnings: Adapt your website, personalize experiences, and inform future campaigns based on the insights and winning variations identified by AI.

Moving Ahead with A/B Testing with AI

Have you started implementing AI into your A/B testing, or are you planning to do so soon? It can feel complex and a bit intimidating to start on your own. At Funnel Envy, we have the experience and resources to help you set up and analyze your campaigns. Reach out today to learn more!

By Kala P|2024-02-22T19:49:19-08:00March 4th, 2024|A/B Testing|0 Comments

How AI Improves A/B Testing

Advertisers have been trying to divine what people will buy for decades. Marketers began taking a data-driven approach in the 1920s, testing the performance of different paper coupons. Today’s marketers rely on A/B testing of digital advertising assets. Trying different ad asset versions has been the cornerstone of data-driven decision-making for years.

A/B testing is powerful because it gives marketers unbiased data from real customers, not survey panels. As the online audience grew, digital marketers could run more tests faster while targeting audiences in unprecedented ways.

Artificial Intelligence (AI) is now emerging as another game-changer for marketers. For context, AI uses algorithms and machine learning to analyze data, recognize patterns, and make decisions.

Read on for an overview of how AI is revolutionizing A/B testing, making it faster, eliminating more guesswork, and ultimately improving results.

How AI is Changing Traditional A/B Testing

Today’s digital marketers are familiar with comparing two variations of an ad asset, such as a webpage, email campaign, app interface, or any other marketing asset. The goal is to determine which version performs better regarding a specific metric, such as click-through rates, conversion rates, or revenue.

A/B testing provides several of the following key benefits:

Data-Driven Decision Making: A/B testing provides empirical data, allowing businesses to make decisions based on real user interactions rather than assumptions or intuition.
Optimizing User Experience: By comparing different versions, businesses can identify elements that resonate better with users, improving user experience and customer satisfaction.

Increasing Conversion Rates: A/B testing helps identify the most effective strategies to increase conversion rates, such as optimizing call-to-action buttons, form layouts, or product descriptions.

The chart below shows the most commonly tested assets.

Source: Truelist and VWO

Overall, AI enhances A/B testing automation, personalization, instant optimization, and the ability to juggle dozens of variables simultaneously. Here are some more details about how AI and A/B testing work together:

Automated A/B Testing: AI algorithms can automate the process of A/B testing by continuously testing multiple variants in real time. Machine learning models can analyze vast amounts of data quickly, allowing businesses to adapt their strategies dynamically based on user responses.

Personalized A/B Testing: AI enables personalized A/B testing by analyzing individual user preferences and behavior patterns. It can customize website content, product recommendations, or email campaigns for different segments of users, ensuring a tailored user experience that leads to higher conversion rates.

Predictive Analytics: AI algorithms can predict which variations are likely to perform best based on historical data and user behavior patterns. This predictive capability helps businesses focus their A/B testing efforts on the most promising variations, saving time and resources.
Real-time Optimization: AI systems can analyze user interactions in real time and optimize the user experience on the fly. For example, AI can adjust website layouts, modify content, or change product recommendations based on user behavior, ensuring continuous optimization without manual intervention.
Advanced Multivariate Testing: AI can handle complex multivariate testing scenarios involving multiple variables and interactions. It can identify intricate patterns and correlations between elements, providing businesses with deep insights into user behavior and preferences.

By leveraging AI capabilities, businesses can optimize their marketing strategies and deliver highly personalized and engaging customer experiences, ultimately leading to improved conversion rates and overall business growth.

AI enhances A/B testing automation, personalization, instant optimization, and the ability to juggle dozens of variables simultaneously. Click To Tweet

AI shines in data analysis, personalization, and adaptive responses, so let’s look closer.

Faster and More Accurate Data Analysis

Before digital marketing, marketers struggled to get sufficient data for high-quality samples. Now, the problem is the opposite. A significant challenge in traditional A/B testing is the sheer volume of online user behavior data marketers need to analyze to make good decisions.

AI excels at processing large volumes of data quickly and accurately. Machine learning algorithms can sift through massive datasets, identifying meaningful patterns humans might miss.

AI can also speed up real-time campaign decisions by generating variations. Take headlines, for example. In traditional A/B testing, marketing teams have to brainstorm and develop all the different headlines to test.

Today, AI can generate a set of headlines based on massive amounts of historical data in less than a few seconds.

Not only that, but marketers can set up all the variations they want to test simultaneously. AI will run tests and keep track of feedback on several variations at once.

AI algorithms can analyze incoming data in real-time, enabling marketers to adjust their campaigns on the fly. This agility ensures that marketing efforts align more closely with variations such as current trends and customer preferences.

Personalization and Targeting

Personalization is the key to capturing customer attention and securing repeat business for a healthy Customer Lifetime Value (CLV). A Salesforce study found that 70% of consumers say that “how well a company understands their individual needs impacts their loyalty.”

It turns out all that granular data from social media data mining is a double-edged sword. Yes, it allows marketers to create refined target audiences, but it also means that consumers are now used to seeing relevant content. Brands that can’t deliver personalized content risk looking out of touch.

The good news is that AI takes possibilities for personalization to the next level. AI algorithms can identify individual preferences and tailor content by analyzing user behavior.

AI-enabled personalization goes beyond addressing the user by their first name or simple demographics. It extends to adapting in real-time to deliver content and experiences that resonate with specific interests and needs. AI results should improve over time in the best algorithms as they continuously learn from user feedback during A/B testing.

AI also improves segmentation, allowing marketers to categorize their audience based on various parameters such as demographics, behavior, and preferences. One example is Sentiment Analysis, where AI analyzes social media posts, reviews, and customer feedback to gauge public sentiment. Refined segmentation creates a more personalized experience, enabling marketers to create highly targeted A/B tests.

By tailoring experiments to specific segments, marketers can optimize their campaigns for maximum impact, increasing the likelihood of conversions.

Adaptive Testing and Continuous Learning

Traditional A/B testing follows a linear process: create variations, conduct the test, analyze the results, and implement changes. AI allows marketers to test many variations simultaneously while tracking test results in real time. This dramatically speeds up the testing process and introduces the concept of adaptive testing and continuous learning.

Instead of static experiments, AI-driven A/B testing involves a continuous learning approach. Machine learning algorithms analyze ongoing traffic to the website, identifying emerging trends and patterns. This iterative process allows marketers to adapt their strategies in real-time, ensuring their campaigns are optimized continuously for the best results.

Automation also plays a crucial role in adaptive testing. Based on tests, AI algorithms can automate traffic allocation, ensuring the right audience is exposed to suitable variants. Intelligent traffic allocation optimizes the testing process, maximizing the impact of each experiment. Marketers can focus on analyzing results and deriving insights, leaving the repetitive and time-consuming tasks to AI-powered automation.

Moving Ahead

By leveraging the power of AI, marketers can gain a competitive edge, reaching their audience with personalized, targeted campaigns that deliver results. As you embark on your A/B testing journey, focus on understanding your audience, harnessing the capabilities of AI, and embracing continuous learning.

At Funnel Envy, we know that even though the promise of AI is promising. We also know the actual implementation raises the bar for complexity in tracking and reporting. Our FunnelEnvy customer data platform enables you to create a personalized experience that responds to your website visitors within milliseconds. Reach out today to get the conversation started.

By Kala P|2023-10-19T09:42:08-07:00October 30th, 2023|A/B Testing|0 Comments

Softening the Ask – How to Improve Opt-in Form Conversions

The internet triggered a revolution in most fields, and marketing is no exception. The ability to track people’s online behavior gave marketers critical new data and insights into consumer behavior.

Capturing information via online forms added additional value—for example, email addresses. Unlike traditional mail, email was relatively free. While free can be great for a business, it also lowers the barrier to entry. Users’ email accounts soon became swamped with spam.

Eventually, the FTC regulated email standards, but people today still face crowded inboxes and are more concerned with privacy than in the past. Many are wary of filling out forms and sharing their information on websites.

The challenge for marketers is that forms are still essential to lead generation and sales. From landing pages to websites, Hubspot reported in 2020 that 83 (48%) of 173 study respondents say forms are their highest converting tool.

Source: HubSpot

Whether it’s a sign-up form for a newsletter or a contact form for inquiries, how you frame these forms can significantly impact conversion rates. In an era where people are increasingly cautious about sharing their personal information online, the art of “softening the ask” becomes crucial.

Let’s look at a few steps marketers can take to encourage web visitors to complete an online form.

Create a Form Audit

Before you dive into tweaking your forms, it can be helpful to know where to start. “Create a form” audit for your forms is a valuable tool. Here are some characteristics of high-performing forms to get you started.

Is the form context distraction-free?
Is there a compelling benefit to filling out the form?
Is the first step effortless?
Do the instructions offer clear guidance?
Do error messages do more than just point out errors? Do they help the user fix the error?
Does the password input field give an option to see the password?
Are you using drop-down menus for lengthy lists? (Hint – you want to avoid drop downs because they can introduce decision fatigue)
Does the form leverage microcopy to guide users?
Does the form validate responses in the field?
Do you have relevant social proof?
Do longer forms have multiple steps and progress indicators?
Is the submit/CTA button optimized?
If there are any next steps after filling out the form, are they clear?

You can also incorporate some of the following ideas into your audit to improve your opt-in form conversion rate.

Build Trust

“Softening the ask” boils down to building trust. Asking users to provide their information is a matter of timing. People are protective of their personal data, and their experience on the website needs to inspire trust.

Walk In Their Shoes – The Buyer’s Journey

Understand where your visitors are in their buyer’s journey. When they feel they are in the right place, they are more likely to see filling out a form as the natural next step.

Are they in the early research phase or signaling intent to purchase? Tailor your content and benefits accordingly. For those in the early stages, offer educational resources. Quizzes are a way to gamify forms and work well for some audiences. Prospects closer to a decision may appreciate a free trial or a personalized demo.

Gartner reports that B2B prospects’ behavior is changing. They prefer a digital-first approach and spend up to half their discovery phase in DIY research. 33% would rather not talk to a salesperson to complete a sale. That means forms leading to a direct sales contact or call back aren’t likely to convert as many as forms offering deeper dive information, like webinars or research studies.

Points for Professionalism

Make sure the form looks professional. You want to serve up something other than an equivalent of a used car salesman cliche experience. A poorly designed form doesn’t inspire trust. A visually noisy popup that keeps interrupting them feels intrusive and can cause prospects to click away.

Visual Cues – Logos and Badges

Visual cues such as trust badges, security logos, and affiliations with respected organizations can convey a sense of trustworthiness. Users who see these symbols on your website are likelier to believe you’ll handle their information responsibly.

Testimonials

Sharing testimonials from satisfied customers can have a profound impact on form conversion. Testimonials are the equivalent of online word-of-mouth recommendations. Real-life success stories and endorsements help potential leads see your value and encourage them to take the next step.

Be strategic about testimonials. Generalized kudos pack a weak punch. Tailor testimonials to highlight your USP and answer your buyers’ conscious and subconscious objections.

Privacy Transparency

Be transparent about how you intend to use the information collected. A clear privacy policy is a legal requirement and can also be a selling point. Your statement should outline how you use, store, and protect their data. Make sure users know that you respect their privacy and are committed to safeguarding their data. You can also reinforce this point in the confirmation email with a link to your privacy statement.

User Experience – Keep It Simple

Various studies have shown that the more fields there are to fill out, the higher the abandonment rate. So, one of the easiest ways to increase conversions is to decrease the number of required fields on the form to no more than three.

Some B2B companies get around this by offering a valuable lead magnet for free, like original research or detailed templates. They use multistep opt-in forms to segment and gain more information about leads, such as company size and occupation.

Placement and Pacing Matters

Try to position opt-in forms toward the top of the page, above the fold. Even for mobile phones and tablets, devices that don’t have a “fold” per se, presenting the form sooner rather than later is a best practice. The idea is to capture their attention so you don’t have to rely on them scrolling down to encounter the form.

That only gives you a little time to make a compelling case for why they should convert, so be clear about your unique value proposition (UVP), what benefit they will receive, and what will happen next.

Consider breaking the form into multiple steps for longer forms, like payment forms or intake questionnaires. Venture Harbour reported that breaking the form into multiple steps improved conversions by 300%. If it works for your audience, try quizzes, which are multiple-step forms in disguise.

Variety and Personalization

Bombarding users with the exact offers repeatedly feels like an annoying buzzing fly. If they’ve already received a whitepaper download offer, don’t present it to them again on the same page, especially if they opted in. Instead, track their progress and personalize the experience by showing them responsive content or offers that align with their behavior signals.

Moving Ahead

Fine-tuning website form performance can be challenging. Create forms that build trust and encourage user engagement by addressing emotional considerations, displaying trust signals, considering context, and tailoring content.

The good news is that form performance is easy to test. The more challenging part is the tech behind the analytics for form optimization. At Funnel Envy, we have the expertise and tools to help you dial in your website form performance and increase conversions. Give us a call today.

By Kala P|2023-09-21T07:10:26-07:00October 2nd, 2023|Analytics, A/B Testing|0 Comments

The best landing page design tests to boost conversions

With many elements of your marketing and funnels, there’s a degree of guesswork involved. Even companies who’ve been in their industry for many years and have deep knowledge of their audiences have to rely on their predictions based on the trends they’ve observed in the past.

But when it comes to designing your landing page, there’s a rare path to certainty: testing different options with real traffic to see which page visitors prefer. You might never be 100% accurate at giving every visitor what they’re looking for on your landing page, but with different tests on page elements, you can likely please most users.

The accuracy of your testing will determine how helpful your landing page data is for achieving business goals. Below are some of our favorite tests that will help you improve your landing page with quantifiable data. Our focus is on the specific elements of the page, and which style of test you want to use.

Headlines

By their nature, headlines are typically one of the first page elements that draw a visitor’s eye. That’s why ensuring your headlines are effective is essential for any industry-targeting audience. The famous advertising executive David Ogilvy said: “When you have written your headline, you have spent eighty cents out of your dollar.” He was talking about newspapers and flyers, but the principle still holds on modern landing pages decades later.

A good headline should always do the following:

Use action words related to the benefit of your product or service, not its features. For example, if you offer a software platform for manufacturing companies, your headline might use attention-grabbing verbs like “simplify,” “streamline,” and “organize.”
Incorporate jargon without overdoing it. Using the words and phrases that professionals in your audience understand is particularly important for B2B landing pages. These buyers are more discerning about the technical abilities of their vendors.
Address the visitor directly. Another key to good writing from the advertising world: the best copy speaks directly to the reader as an individual. This applies to your landing page headlines as well.

Form Field Labels

Most landing pages use at least one form for conversion, whether signing up for a newsletter or scheduling a demo with a sales representative. But to persuade people that it’s worth filling out the form and converting, they must first understand what the form means.

We recognize that form fields aren’t traditionally considered part of a page’s design – sometimes, they aren’t even part of the page, depending on the software stack you’re using. Many marketers simply fill out the form fields as an afterthought.

The problem with this approach is it neglects one of the most critical conversion elements on your landing page. Different people have different ways of recognizing the same things. No matter how well you know your audience, you’ll never be able to predict precisely what they think about a form title or a label. That’s why it’s critical to test as many of your form labels as possible, from the title of the broader form to the labels on each field.

No matter how well you know your audience, you’ll never be able to predict precisely what they think about a form title or a label. Click To Tweet

Calls-to-action (CTAs)

The CTAs on your page are the last element before a page visitor becomes a conversion. Although your landing page has many vital components, the CTA element is arguably the most crucial leverage point to improve conversions. Even if the rest of your page is well-optimized for conversions and technically sound, a poorly-designed CTA will throw people off and significantly restrict your results.

There’s a massive array of different types of CTA designs, but these are three of the most popular:

Colored shape. This is typically a diamond, rectangle, or oval in a color that stands out on the page – often a bright color like red, orange, or light blue. Within the shape, you’ll see a simple text-based CTA like “Book your meeting” or “Download the guide.”
Plain text. Plain text CTAs are simple calls to action embedded directly in the text. Some marketers will add a paragraph of text at the end of the page, while others will simply include it as a line at the end. A word or phrase in the text will sometimes be hyperlinked to allow the user to submit the form or convert in another way.
Image. An image-based CTA is excellent because it allows the most flexibility and customization, which means it has the best chance of standing out on the page and grabbing attention. Conversely, an image-based CTA also provides more technical risks than other kinds – not all platforms and browsing devices load images well, especially if they are large and complex.

Which kind of CTA design is best for your landing page? It’s impossible to offer a one-size-fits-all recommendation. Each landing page has its own layout and design theme that a CTA should fit into (while also standing apart). Also, remember to consider your audience. Are you trying to provide a product or service for a more buttoned-up industry like law or accounting? Or does your audience have a more laid-back vibe like the hospitality or travel industry? These factors should all weigh into your CTA decision – and the nice thing about them is they are all so distinct that it’s relatively easy to perform a test to decide which ones are most effective.

Our Final Thoughts on the Landing Page

As is the case with many of the suggestions we provide on different topics related to funnels and conversion rate optimization, the advice given in this article should be viewed only as a starting point. Everything we’ve discussed is based on what has worked best for companies we’ve worked with during our many years of experience – you may find that another idea you have for landing page design works better or that something suggested here doesn’t move the needle as you’d hoped.

And that’s completely fine! The key to success is backing up everything you do with testing and data. Without any empirical evidence to support your landing page design decisions, it’s impossible to know whether or not they are the right choices.

But if you’re relatively new on this journey or recently started using a much different landing page, you might be struggling to find answers for design optimization. This is where our expert team at FunnelEnvy can assist. We have experience working with companies in various industries – from consumer healthcare to industrial equipment. Our focus has been helping them build a better-converting landing page in each instance. We can meet you where you are and provide customized assistance with all elements of your landing page design, from technical aspects like page speed and caching to form fields and CTA design.

Are you interested in finding out more? Just click here to complete a short quiz that we’ve created to help us learn more about your needs and how we may be able to help.

By Raj C|2023-06-01T03:07:35-07:00June 12th, 2023|Analytics, A/B Testing|0 Comments

3 Examples of Helpful A/B Tests and Why They Work

A/B testing is a powerful tool for B2B marketers and considered a staple of the toolbox for improving a campaign. Marketing teams in every industry with every type of product and service can use A/B testing to figure out which option in a campaign works.

The fact that you must conduct A/B testing in a specific method to attain success doesn’t get discussed as regularly. A/B testing done the wrong way can cause a lot of wasted time and effort for your team. Even if you generate sufficient data from the tests, it won’t be as effective as with proper methodology.

To help you better handle your A/B testing, we provide three examples of some of the most crucial A/B tests you can perform in many different contexts. Remember: the advice here is general, so you’ll need to think about how to apply it to your specific funnel.

Landing Pages With a High Bounce Rate

Every experienced marketer knows the dreadful, pit-of-your-stomach feeling you get when you spend lots of time and resources building up what you think is a great landing page for your funnel, only to find that it flops with very little engagement and conversions.

You likely have a few landing pages already in mind that need to be tweaked and improved. If not, an excellent way to get started with this type of A/B test is to explore your analytics platform to identify which pages need the most improvement.

Here are a few other tips for landing page testing:

Have a predetermined length in mind. You don’t want to have one A/B test running for a week, another for a month, and another for just a few days – this distorts your data and dilutes the quality of the tests’ results.
Don’t make traffic splits equal. You should start by giving the existing landing page a larger share of site traffic, then slowly increase it. Do this to account for the potential negatives of incorporating any new idea onto a page.
Consider predictive traffic. In this blog, we’ve previously explored some of the relative benefits and drawbacks of using A/B tests compared to predictive bandits, which use machine learning models to determine the optimal version of your site to deliver to users. The most significant benefit of this approach is that it avoids the “one-size-fits-all” problem with A/B testing.

Important Form Page for your Funnel

You can apply form pages in several different ways within your funnel, for everything from a critical conversion step to a basic logistics element like booking a video call. With this in mind, it’s important to think carefully about which form you decide to A/B test.

A seemingly-minor form page setup improperly can have just as much of a negative impact as a final form directly tied to conversions. Click To Tweet

That doesn’t mean, however, that you should only test critical funnels directly linked to the main conversions you’re tracking. A seemingly-minor form page setup improperly can have just as much of a negative impact as a final form directly tied to conversions.

For example, imagine a well-designed form with dynamic fields, progress indicators, and other staples that should convert properly. However, when a user reaches the last step or segment – or even the confirmation page – there’s an element that causes users to lose confidence and fail to complete the subsequent steps to get them down the funnel.

That’s why we recommend considering A/B tests for even the smallest elements when it comes to forms. Form field length, field titles, progress bars, button text – even the form’s primary and secondary colors can impact how people view your forms.

It may not seem significant, but as is the case with many other types of A/B testing, a tiny change can significantly impact conversion rates.

Email Subject Lines

Almost every successful modern funnel will use some kind of email, especially for B2B marketers who need to provide their prospects with a significant amount of information along each step of their funnel.

Unlike some of the other elements discussed in this post, most people know the importance of email subject lines. They are frequently cited as determining whether people even open an email. According to Zippia, just under half of all email recipients will open an email based on the subject line alone. Similarly, about 7 in 10 email recipients will mark an email as spam based solely on the subject line.

Here are a few ways to A/B test email subject lines:

Experiment with length. Shorter is usually better here. Generally, it’s recommended that your email subjects be somewhere between 20 and 60 characters, but you should run some tests to find your own sweet spot.
Incorporate one or more emojis. Of course, it’s important to understand your audience and the email’s subject matter – with certain somber topics, it may not be smart to use emojis. On the other hand, an unexpected emoji can be a great way to stand out in someone’s inbox.
Sentence structure. Sometimes, a question is the most effective way to get a recipient’s attention. In other cases, using a short statement or fact is best. Remember that many marketers get in trouble by trying to make their subject lines too mysterious or clever. This mystery is often a direct route to the spam folder.

Regarding length and timing, the guidelines we mentioned apply here: start with a small percentage of your list receiving alternate subject lines. A 70/30 split is a great starting point; from there, you can slowly increase the number of subscribers who receive the alternate version.

Also, remember that you’ll need to get sufficient data to ensure that your test results have value. The specific amount of time it takes for your data to be significant varies depending on the size of your list, but you’ll generally want to give the test at least a week.

Final Thoughts on A/B testing

Anyone who says A/B testing isn’t valuable to their marketing funnel or overall business probably hasn’t been able to find an approach that works for them. Indeed, there are some situations where A/B testing isn’t the best option for tweaking your funnel.

But in many cases, all that’s standing between you and a successful A/B test is the right approach. If you’ve been struggling to find meaningful results from A/B testing, or you simply want to get an outside perspective on improving the process, our team at FunnelEnvy can help. We have many years of combined experience helping companies of all sizes in all industries ensure they get the most out of the resources they put into testing.

Just click here to fill out a quick quiz to learn more about us and our pricing and determine how best we can assist you with your funnel optimization requirements.

By Raj C|2023-03-13T11:34:09-07:00March 20th, 2023|Analytics, A/B Testing|0 Comments

3 Symptoms of Siloed Data and How to Fix It

Data siloing is like a poisonous, invisible gas: it’s hard to identify, you may not even know it’s affecting you, and it can cause significant health problems for your business.

Before we go any further, let’s back up and establish the term’s meaning. “Data siloing” is when you store important information in your business in a single, isolated place that is not easily accessible for people in the company outside of those who originally put it there. The term comes from the traditional silo used in agriculture to store grain or other supplies in bulk.

But unlike traditional silos, which are easily visible to most people, data siloing is challenging to identify. In fact, in our experience, companies suffering the most from data siloing don’t even know it’s an issue.

In this article, we’re going to correct that problem. Below are three of the most significant symptoms of data siloing. After we outline each problem, we’ll include a general fix for the problem that you can apply to these and other symptoms.

Redundancy and Repetition Across Departments

Most companies organize their teams into groups ranging from a handful of people to dozens of employees, depending on the size of the company and the nature of its work. Given this inherent separation between teams, it’s normal for there to be some repeated information across groups.

Suppose you see a huge percentage of information repeated in meetings, presentations, or other kinds of department-level communication, though. In that case, it’s a good sign that each group may have its data siloed. One classic example is a separation between an organization’s sales and marketing teams, which happens to companies of almost every size. Marketing teams often collect data related to a prospect’s initial demographic info: the size of the company they work at, their job title, etc. Once the sales team gets involved, they typically learn new information related to more specific details about the prospect. If the two teams don’t share data sufficiently, it can lead to repetition of the same tasks and frustration on the part of the prospect, ultimately causing them to drop out of the sales funnel.

Teammates Ask Several Questions About Other Departments

One of the most obvious signs that your company has a siloing problem is when individuals in separate departments have very few details about how different parts of the organization work. This disconnect often leads to questions about how the other part of the company completes tasks, inquiries they wouldn’t ask if data wasn’t so siloed.

Remember that there will always be some degree of separation between departments – that’s their nature. You wouldn’t expect someone in marketing to understand how to put together a quarterly accounting statement, just as you wouldn’t expect someone on the support desk to work on developing your company website. But when different departments in a company don’t have a basic understanding of how other groups work – where their files are stored, how they communicate internally, etc. – it’s a sign that you may store their data too far apart.

Changing Access Levels Takes Longer Than Expected

From small shops with just a few people to the largest global enterprises, companies of all sizes have some sort of permission structure. These systems typically govern things like access to software platforms, the ability to read and write data in a certain folder, or access to a certain email inbox.

During a normal month or quarter, it’s common to change these permission levels for several reasons. Old employees leave, new employees start, and some may even change positions in the team, bringing up a need for different permissions. It’s okay if permissions don’t change instantly, but if it’s regularly taking your team several days or weeks to change permission levels, it’s a sign that your data and processes may have a problem with siloing.

Solving the Siloed Data Problem

As we mentioned, these indicators are just symptoms of an issue with siloed data in your organization. You may come across other signs in your organization, but it’s arguably most important to note that you may not come across any signs at all. Data siloing can happen even within a growing organization that seems successful otherwise. It might not be a mission-critical issue, but if you don’t nip it in the bud right away, it can grow into something much more serious. Even if it never becomes the issue that threatens your business’s existence, there’s still a chance it can prevent you from operating at maximum efficiency.

Data siloing can happen even within a growing organization that seems successful otherwise. Click To Tweet

In our experience, the best way to prevent siloed data from becoming a problem that threatens your business to any degree is to implement a shared data platform that all the different teams in your business can access to share relevant information. Regarding sales and marketing alignment, we suggest our clients implement a tool known as a customer data platform or CDP.

The benefit of using a CDP is that, unlike traditional data-storing methods, this platform allows information to be put in and taken out by all the appropriate parties and applications. We refer to this as bidirectional integration. In other words, a CDP can integrate with all the tools you’re already using in your stack: a CRM, website analytics tool, email automation platform, etc.

In ideal cases, not only will implementing a CDP help you better manage the data your business uses on a day-to-day basis, it will help you get more out of that information to serve organizational goals better. For example, suppose you can input information about visitors to your website and the specific pages they visit. In that case, you might then be able to integrate it with data from your sales department about which particular parts of your solution prospects were most interested. The conclusions you can gain from these two types of data combined will be much more effective than the information you gain from analyzing the data alone, which often happens when siloed.

Final Word on Siloed Data

Although it’s not the most obvious problem or glamorous challenge to solve in your business, siloed data is still a profound issue worth trying to prevent. If you let it fester and expand within your business, it can eventually become such a severe problem that it impacts conversion rates and customer satisfaction.

Are you concerned that your organization may be suffering from siloing, or simply want to take preventive measures to prevent this situation from happening in the future? Our team is available to help. We have years of experience ensuring our clients can leverage the data they gather across the entire organization instead of watching their productivity suffer from inefficient communication and unnecessary re-work.

To get started, just click here and fill out a short questionnaire that will help you learn more about FunnelEnvy pricing and give us the info we need to determine how best we can assist.

By Raj C|2023-02-08T18:35:48-08:00February 20th, 2023|Analytics, A/B Testing|0 Comments

4 Key Metrics for Your B2B Sales Pipeline

There’s a lot for marketers today to consider when it comes to tactics for bringing in new business, but your sales pipeline is what ultimately defines the success of all your funnels, marketing campaigns, and other efforts to add new clients and revenue consistently. But considering the huge array of software tools and data available to modern B2B marketers, it can feel overwhelming to measure all the metrics in a pipeline.

We’ve identified four of the most important metrics for B2B marketers looking to understand their pipeline better. Every company is different, but in our experience, an organization can get a great sense of the overall health of its pipeline by paying attention to the four metrics below.

Velocity

Sales velocity is defined by HubSpot as the measurement of how quickly a deal moves through a pipeline and turns into actual revenue. Velocity is an important metric because it helps you understand and identify obstacles or bottlenecks in your sales process. It doesn’t matter how great your landing pages or nurture sequences are – if there’s an issue with your pipeline velocity, it’ll constrain your sales.

It doesn’t matter how great your landing pages or nurture sequences are – if there’s an issue with your pipeline velocity, it’ll constrain your sales. Click To Tweet

The widely-accepted formula for calculating pipeline velocity is to multiply the number of opportunities by the average deal value, then times your team’s average close rate, and divide that number by the length of your sales cycle. This formula is a great starting place to closely analyze each part of your pipeline to determine any obstacles.

For example, perhaps when evaluating the sales cycle length, you realize that your sales team is taking too long to follow up after the initial appointment with a prospect. Armed with this knowledge, you can adjust your sales process and inform your reps to follow up immediately after an appointment to keep the prospect moving through the sales journey.

Deal Size

The size of your deals doesn’t require any kind of complex formula to calculate, but it can still be difficult to identify issues in this area without some intentional analysis. For example, if your company has the same number of opportunities with the same sales cycle length as last year, but your revenue is down, it’s a sign that you may not be pursuing large enough deals.

Addressing a deal size issue is solely a matter of prospecting. Here are a few tips for finding higher-value prospects:

Use account-based marketing (or ABM). ABM defines a process by which you identify a handful of high-value accounts and create customized sales and marketing collateral explicitly designed for those accounts. According to Gartner, by the end of 2020, over 70% of marketers at midsize and large B2B organizations will be using or testing ABM.
Invest in thought leadership or content that brands give for free to gain trust and credibility by helping its intended audience. In a study published by LinkedIn and Edelman last year, 60% of B2B buyers said thought leadership builds credibility when a brand enters a new category, and 54% said they purchased a new product or service they had not previously considered. Thought leadership can help attract a more discerning type of buyer.
Get social. Participate in events, post on social media, and engage with your prospects in their communities. Remember to be genuine – it’s easy for people to identify someone who’s only interacting with them for the sake of a sale. Let your natural sense of curiosity and desire to help people guide your interactions.

Close Rate

Another straightforward yet critical metric for your sales funnel, a close rate identifies the number of prospects that become paying clients relative to the overall number of leads generated by your marketing efforts. Every company will have a slightly different close rate depending on the nature of their business. A more specialized company with a niche audience might be fine with a close rate between 5% and 7%, while others might be aiming closer to double digits or beyond.

While it’s possible to find general data online about close rates, a better approach is to track your own company’s close rate and assess where it needs to be for sufficient revenue growth. If there are problems with your close rate, it’s generally a sign to evaluate your sales team, the specifics of your client offer, or both. Solicit feedback from prospects whenever possible to better understand which elements are slowing down your close rate.

Sales to Support Ratio

This ratio may not be specifically related to the performance of your sales or marketing, but it’s still vital to understand how your sales pipeline affects the rest of your operations. It’s sometimes expressed as “sales staff to support staff,” but it isn’t necessarily just the number of people working at the organization in each department. For smaller companies with employees or contractors who handle multiple organizational tasks, it isn’t a simple “this to that” ratio.

However you quantify it, this metric is vital to understanding how much of your capacity the company uses for each client. You can also track this number based on deal size, client longevity, and other measures to get a sense of which types of clients require the most attention from your support team. You can use this data in your sales and marketing efforts going forward, helping you focus on the best types of buyers for your offering.

In a well-balanced organization, sales and support can handle a sufficient volume of responsibility that allows the company to stay on track with its goals. In assessing this metric at your own company, you may need to either increase your sales activity or add additional capacity for support, depending on how much your company’s product requires.

Final Word on Key Metrics for Your Pipeline

It’s essential to customize your pipeline metrics like any sales or marketing data. Every company has its own needs, meaning it might not make sense to track the same metrics as an organization in a different industry.

For best results with these pipeline metrics, track them for as long as possible and establish a performance baseline in each area. Note where the numbers are when things at the company are going well and vice versa when you hit a slow period. Doing this allows you to gain insight into where each of your metrics should be, giving you better context when you analyze your pipeline going forward.

If you’re unsure about what steps you need to take or which metrics to track to help improve the performance of your organization’s sales and marketing performance, our team is ready to help. FunnelEnvy has several years of combined experience working with B2B clients to identify gaps in their funnels, tweak critical elements like forms and landing pages, and optimize other aspects of the lead nurturing process to maximize your conversion rate.

Click here to take a short quiz and learn more about our pricing structure.

By Raj C|2022-10-20T04:37:11-07:00October 31st, 2022|Analytics, A/B Testing|0 Comments

How to Find A/B Test Ideas that Work

What should you test next?

Do you start with your CTA placement and button color or would you be better served to optimize your headlines? It’s a difficult decision to make and one that marketing managers often struggle with. Unfortunately, it’s a confusion that frequently leads to one result. Copying the methodology of a well known CRO or case study.

Sure this can sometimes bring a good lift in conversions, but more often than not copying another business’s test isn’t going to win you many new customers even when following their instructions to the letter.

So what’s the deal? Why would a test that’s worked so well for one person utterly fail when implemented on another site?

Well, it’s all down to one reason.

That test – the one you’re copying – was intended for an audience different to your own. Your audience is unique and will interact with your site in completely different ways. (more…)

By Peter Boyle|2015-11-09T16:15:03-08:00November 10th, 2015|Conversion Rate Optimization|0 Comments

Optimization and Testing Takeaways from OptiCon 2014

Last week leading A/B testing company Optimizely held their first conference in San Francisco, OptiCon 2014. In addition to several exciting announcements from the company, OptiCon brought together leading Conversion Rate Optimization and digital marketing professionals to share their experiences and learn from one other. As tools like Optimizely make the tactics of testing easier and more accessible, the challenge shifts to the process and organizational challenges that need to be overcome to build successful optimization programs. These seemed to be the dominant themes from the sessions that I attended, which I’ve summarized along with some key takeaways here.

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By Arun Sivashankaran|2014-04-24T15:15:32-07:00April 25th, 2014|Conversion Rate Optimization|0 Comments

The Top 20 A/B Testing Case Studies that Every Marketer Should Read

There are numerous ways in which testing, especially A/B testing or the more complex multivariate approach, can be used to help your business. From improving your copy to streamlining your design for the best possible user experience to removing friction from your checkout process, conversion rate optimization can help you improve the bottom line and reach your business growth and revenue goals.

One of the most common requests that I get is for case studies. Entrepreneurs and business owners are looking for examples of “how it’s been done.” These inside looks at testing can be helpful at every step of the process, from identifying what needs to be tested to creating hypotheses, from designing your tests to implementing the results in your business. Below is a selection of case studies from around the web that I’ve curated to help my readers and clients understand some specific aspects of the A/B testing process. What follows is a list of the tests, along with a quick description and what I think you can learn from them.