Note: This is a guest article written by Tyler Hakes, the strategy director at Optimist, a full-service content marketing agency. He’s spent nearly 10 years helping agencies, startups, and corporate clients achieve sustainable growth through strategic content marketing and SEO. Any and all opinions expressed in the post are Tyler’s.
Almost 10 years ago, I got my first job in marketing.
I was right out of college, and I was eager to prove myself and light the world on fire.
Like most people in their early 20s, I was convinced that I knew everything. I thought I had all of the solutions to every problem. I was a marketing mastermind, of course, because I had managed to get a few hundred people to follow me on Twitter.
It didn’t take me long to learn that I didn’t quite have all of the answers. In fact, I had a lot to learn. And it became more important for me to understand what I don’t know and to learn rather than to feel like I already had the answers.
Since then, I’ve worked for agencies, corporations, and startups. As a freelancer and agency owner, I’ve done marketing for every kind of company imaginable—from custom hats to apartment rentals. I’ve put together dozens of content marketing strategies and written/published thousands of articles, ebooks, and landing pages.
In all that time, I’ve come to realize something really, really important.
I don’t know anything.
Sure, I have accumulated a lot of knowledge and skills in the digital marketing space. I understand, at a high level, how things work. And I know, directionally, what the best practices are for achieving results.
But when it comes to executing any particular tactic, writing a particular type of content, or advertising to a particular market, each scenario is a little different. What I think will work best is usually wrong.
With this realization in mind, I’ve developed a kind of manifesto. It’s a way to remind myself that it’s okay to not have all the answers. It’s okay to be wrong, as long as you commit to finding the right answer eventually. Embrace a testing mentality.
Assume You’re Wrong
The biggest challenge with having a testing mentality is accepting that you are almost always wrong.
Let me say this again: You’re wrong.
It can be difficult to swallow. But don’t take it personally. Don’t link your personal worth to your ability to guess which messaging will get the most clicks or which blog post will drive the most social engagement. That’s just silly.
This isn’t Mad Men. You’re not Don Draper. So, don’t spend a million bucks trying to come up with the best idea. We live in a digital age of data. We’re able to track, measure, and test anything and everything that we do in business. There should be no more guesswork.
And what we generally consider to be “conventional wisdom” about best practices when it comes to optimization is also generally wrong. (That’s why it’s called “conventional wisdom,” after all.)
It’s become a driving force for my work and my business. I assume that I know nothing and that everything—anything—is open for testing. Test, fail and learn. In that order.
And instead of taking it personally, I just accept that it’s impossible for someone to know the right answer 100% of the time.
As such, it makes way more sense to defer to the data whenever possible.
Unfortunately, you can’t possibly test every single variable to determine the single best approach, messaging, targeting, or design.
But you can get a head start.
Begin any testing cycle by looking at companies that test and optimize regularly. Then, steal their findings. Rather than starting from square one, begin your own testing with their current best case—the design, ad, or content that they’ve found to be most successful.
You can do this in a number of ways.
Look at crowd-sourced A/B or multivariate test communities like Behave.org.
Visit competitors websites and emulate what they’ve done.
Use social media to uncover specific messaging/positioning/CTAs used by competitors.
For our work on content marketing, we begin any client engagement with an extensive research and competitive analysis process. It’s the foundation of our content marketing strategy—is what we already know working for competitors and other companies in the space?
We’re able to gain years (or decades) or knowledge in a matter of weeks. We avoid expensive, time-consuming, and frustrating trial and error by just stealing what works and iterating on it from there.
Prove Yourself Right (Or Wrong)
Once you have learned to not internalize the results and found a base to start with, it’s time to test.
Depending on what it is you’re testing, you’ll want to generate dozens—or hundreds—of variations. Try different colors, placements, layouts, or strategies.
Of course, a tool like VWO will help you execute these tests quickly and measure the results.
Create an experiment sheet that allows you to track each experiment and the outcome of that experiment. Remember to constantly challenge your own assumptions.assume you’re wrong and that you can come up with a variation that works better.
This kind of data-driven testing mentality applies not only to tactical tweaks or changes. You can assume a similar mentality for your entire strategy.
When we work with a new client on content marketing, we make a whole bunch of new assumptions.
Each piece of content that we create serves a strategic purpose within our larger framework. Because of this, we have a specific goal for that piece—to generate search traffic, to earn links, to generate social shares, and so on. And this is the benchmark that we use to measure our effectiveness.
So, we may begin with an idea about which kinds of content will best accomplish those goals.
But, in most cases, we have never created content in this particular market. We have never tried to build relationships within this particular community. We’re just guessing (per our past experience with other clients and other industries).
This means that what we really want to do is try what we think we will work, get the results, and then incorporate that data to help us improve in the future. A lot of times, we’re wrong. If we didn’t adopt a testing mentality, then we would just carry on being wrong.
Obviously, this is not ideal. It’s better to be wrong and to learn from that mistake than to be blind to your mistakes. This is why we apply a testing model to everything from our overall strategy to specific, tactical implementation—content flow, calls to action, outreach emails, and so on.
We want to achieve the best results we can, even if it means that we admit we were wrong.
Do It All Over Again
Think you’ve found the right answer? You’re probably wrong—again.
Any test is only as good as the variations that you’re considering. So, while you may have identified a clear winner of those that you’re considering, that doesn’t mean that you’ve objectively identified the best possible solution.
Whatever is working best now could only work half as well as the true best case. And it’s just a matter of time until you hit that particular variation.
It’s the pursuit of continuous improvement. It’s relentless.
This is the foundational idea behind “growth hacking,” which is really just a data-driven, experimental approach to growth. It takes trial and error—over and over again—ad infinitum.
It’s why many software teams have embraced agile development because it allows for iterative progress and improvement rather than investing all of your time and resources into a single window or opportunity.
Testing isn’t just about making small tweaks. It’s about embracing a culture of continuous learning and improvement. It’s about the pursuit of truth, even when it makes you feel stupid.
And it all starts by admitting that you don’t have all the answers.
We’re all aware that our time on this planet is limited. It’s an undeniable, yet liberating fact about human life.
This is one of the reasons that as humans, we aspire to:
achieve greatness in everything we do,
take the world forward,
be our best possible selves, and so on.
To achieve success and improve our lives, we’re trying to optimize the limited time we have.
At the start of 2018, many of us would have made New Year resolutions for the year in the hope to change an undesired behavior, achieve a personal goal, or otherwise improve any other aspect of our lives.
We make them to serve as a personal roadmap in meeting the goals for the next 12 months.
In this blog post, we’ll focus on how you can achieve your new year resolutions by following and applying conversion rate optimization principles.
New Year Resolutions and CRO
At VWO, we champion the idea of following conversion rate optimization as a structured, methodical process.
Over time, CRO experts and practitioners have realized that being methodical and data-driven in your approach can increase the propensity of success manifold.
Without it, you’re just shooting in the dark, hoping for something to stick.
Similarly, if you follow a framework for optimizing your life (read: achieving your new year resolutions), the chances of your success will increase.
Step 1: Research: Identify Key Areas of Improvement
The first step of the Conversion Rate Optimization process is to identify key areas of improvement by tracking your visitors’ behavior.
You begin with analyzing the quantitative data you have available from tracking goals and funnels. And use this to pinpoint what parts of the conversion funnel needs fixing. This data tells you wherecustomers are dropping off in your conversion funnel.
Next, you look at the qualitative data available from your visitors’ visual behavior analysis, website surveys and form analytics, to figure out the reason why your they are dropping off.
Only when you know what needs fixing, can you go ahead and plan to fix it. Which is why research is the most crucial step of your conversion rate optimization process.
The more thorough and comprehensive your research, the better your chances of success.
Takeaway for Your New Year Resolutions
The first step in the CRO process is finding what to improve. Similarly, the first step in setting new year resolutions for yourself should be to identify what habits, behaviors, or aspects of your life you wish to change.
For this, you’ll have to rely on the corresponding empirical information about yourself you already know.
Consider this example: for the previous year, you have been running low on money at the end of every month. You now know the where of the problem.
The reason being, the exorbitant shopping and regular cafe-hopping, among many others. This gives you the probable why of the problem.
With this information available, you are now aware of one aspect of your life that you can improve. Apply the same to figure out more in a similar manner.
Step 2: Hypothesis Phase – Construct an Educated Hypothesis
After the research is complete, you’re able to identify the pages that have the highest drop-off. And hence, the highest scope of improvement.
Per this information, you should be able to construct a hypothesis about what changes to your pages or funnel can bring about a desired change.
At its core, a hypothesis consists of 3 parts:
Here’s an example of a good hypothesis: I believe moving trust signals closer to the billing form will result in 5% more checkouts because it instills confidence in the payment gateway.
Takeaway for Your New Year Resolutions
From the research phase, you can glean enough information to make an educated guess about the changes you can make to your life and their possible impact.
Building on the example shared in the previous step, consider the following hypothesis:
I believe freezing 20% of my monthly salary in advance will result in having adequate money at the end of the month because I won’t be making unnecessary expenses.
Similarly, you can create more hypotheses for your new year resolutions, based on the areas of improvements identified from your research.
After you have a number of hypotheses available, prioritize these as the next step.
Step 3: Prioritization Phase – Prioritize Test Ideas
After you uncover areas of improvement for your funnel and create hypotheses for testing, you need to plan out your testing schedule. What do you test first?
Several frameworks exist to help us out here. One of the most popular is the P.I.E. framework formulated by Chris Goward at WiderFunnel:
Takeaway for Your New Year Resolutions
Depending on what you’re aiming to improve and the many ways possible for you to achieve it, you’d have created a number of new year resolutions, which you can go ahead and follow.
However, not all new year resolutions would be created equally. Perhaps, you’d want to focus more on being physically fit than cutting down on your spending habits. Which is why you should prioritize.
Just as it would make more sense to reduce drop-off on your eCommerce store checkout page first compared to the home page. You need to determine what new year resolutions you should focus on more. And then, aim to follow the plan through the end.
Step 4: Testing Phase — Choose the Right Test and Set It Up
After the hypotheses are created and prioritized, it is time to test these per the complexity of the change. By using A/B Test, Multivariate Test, or Split URL Test.
Testing helps validate or invalidate your hypothesis, else it can give you learning to implement in future optimization efforts.
Thankfully, the operational aspect of your tests can be taken care of by an A/B testing software. Something which also comes built-in within VWO’s conversion optimization platform.
Takeaway for Your New Year Resolutions
By now, you would have prioritized the actions you need to take to achieve your new year resolutions. You should go ahead and implement these.
You can track the progress of the results you achieved for fixed durations (say, two months), and see if these are close to the expectations.
For the example we had been considering in the steps above, you can do the following:
Save an amount that you would need by the end of the month, in a bank account other than your primary one. See if you are able to manage without having to spend it before the d-days arrive.
In case the plan for improvement you have created is not helping, you should go back and create a new one, based on fresh research and analysis.
Step 5: Learning Phase — How To Analyze Test Results
Learning from your test results is the last but an equally important task as any other in your conversion optimization journey.
If your hypothesis is validated, that is, your test is successful. You can now go ahead and implement the winning version on your live website. Also, share your learning with team members and other departments.
If your hypothesis is invalidated, that is, your test has been unsuccessful. In such a case, jot down all the key learning points for future optimization experiments. Make sure you don’t repeat the mistakes, if any.
Takeaway for Your New Year Resolutions
Based on the success, or the failure, of the improvement plan you’ve set yourself on, you should decide whether to follow it till the end, or to change things altogether while including learning from your efforts.
Are You Ready to Optimize Your Life?
Let’s face it. Following up on your new year resolutions, acquiring good habits, and so on is… tough, to say the least. It requires a whole lot of determination, will power, and focus to bring a drastic change in your life.
As optimization and experimentation are our bread and butter, with this post, we aim to contribute our perspective on how you can achieve your new year resolutions, keeping in mind the concepts of conversion rate optimization.
We believe you can follow the CRO framework to optimize your new year resolutions, and hence, your life. At the very least, you’d have experimented with something new and practical.
We spoke with Patxi Gadanon, who works as a Senior Web Manager for one of the leading fine arts brands in the world, called Colart. In his role, Gadanon ensures that all websites within his purview provide excellent user experience and display up-to-date content. Colart has been a VWO customer since early 2017, after Gadanon evaluated several A/B testing tools including Optimizely. He explained how he arrived at the conclusion that VWO is the right web testing and conversion optimization solution for the Colart brand.
When Gadanon started working at Colart in January 2017, he quickly realized that its website would engage visitors more if optimized with the help of web testing and conversion rate optimization (CRO) practices. As he started looking for the ideal web testing solution for Colart, Gadanon evaluated his options on the following parameters:
Quality of customer support Does the tool have a dedicated support team? What is their availability like? Do they respond in time? Can they answer technical questions regarding test implementation? To implement a scalable testing process, Gadanon needed to set up and run tests with minimal IT help.
Ease of use Is the tool easy to use? How much effort and resources would it take to train the team on it? A tool that is easy to use would help his team resolve subjective debates with visitor data.
Tool features Does the solution meet all requirements? Does it integrate with other tools and analytics platforms easily? “The primary objective of the website,” Gadanon said, “is to build credibility in the Colart brand. Although we sell our products through the website, we do not identify as an ecommerce company. We measure success in terms of visitor engagement.” Therefore, in-depth visitor behavior analysis was a critical requirement.
Pricing How flexible are the pricing options? Is the tool within the budget? Will the Digital Director approve the quotation?
The team used several tools for different requirements and managed to get some quick wins, but it soon became obvious that they should look for a solution that would help them bring everything under their testing program at one place. It was important to select an all-features-in-one tool that allowed testing on multiple domains from a single platform.
Based on these factors, Gadanon shortlisted two options—VWO and Optimizely—and proposed these to Louise, his manager and the Digital Director at Colart. Even though Gadanon had used Optimizely for his previous employer and was comfortable using it, he drew up a quick price and feature comparison and got demos for both tools before making a decision.
What Didn’t Work with Optimizely
When asked why he did not choose Optimizely for Colart, Gadanon cited its poor technical support during the presales period. The team at Optimizely did not share the code with him and preferred to speak with developers instead. This was a problem because development for the Colart website is not done in-house. Gadanon also sensed a reluctance to provide a solution even after the problem had been identified. “I had to keep following up for help. It felt like I was begging to get more support, even after I had mentioned that we were in a rush to decide on an A/B testing solution. By the time the Optimizely demo was scheduled, we had already made up our minds to go with VWO instead,” Gadanon said.
He was also aware that Optimizely slowed down websites, and that didn’t help either. Gadanon’s team had received poor feedback about the flicker that visitors noticed on websites running tests by using Optimizely. It is now a widely acknowledged issue across digital media.
More importantly, Optimizely charges users separately for each domain it runs tests on. The digital team at Colart manages several sub-brands and approximately 20 web domains that they concurrently wanted to run tests on from a single account. The inflexible per-domain pricing model was, therefore, a deal-breaker for Gadanon and his team.
Why VWO Emerged as the Tool of Choice for Colart
VWO emerged as the preferred solution for Colart for a variety of reasons.
VWO Support (Presales and Post-Purchase)
Gadanon was impressed with both the presales and post-sales support that he received from VWO. “I can trust the VWO Support team to respond quickly and give me a clear, straightforward response, even when it’s something I would not like to hear,” he explains.
VWO provides 24×7 hands-on support across phone, email, and chat. VWO also has in-app guided onboarding and an up-to-date knowledge base containing all the information users would ever need. Even better, enterprise customers get dedicated customer success managers to help them set up their accounts and get testing immediately.
VWO also has a flexible pricing model that worked for Colart and its sub-brands. If a team like Gadanon’s wants to run tests on multiple domains from a single account, it can simply pay by the average number of unique monthly visitors on its website, no matter how many domains it runs tests on within that visitor quota—and this is precisely what they chose to do.
More information about VWO pricing plans is available here.
No impact on the page load time VWO uses asynchronous code to serve campaign data, compared to synchronous code used by Optimizely. Asynchronous means that the code contacts VWO servers in the background, downloads, and processes the test package while the rest of the page continues to load and render in the browser as usual.
Optimizely’s synchronous code makes the browser wait until Optimizely can deliver the test package, long enough for visitors to notice. And in the improbable case of VWO servers being unavailable, the original page gets loaded, ensuring that visitors’ experiences remain unaffected. This is why Gadanon’s team has never received complaints about a flickering issue with VWO.
FriendlyUI Gadanon also found the VWO user interface to be intuitive and easy to browse. While commenting that the dashboard is organized well, he described it as a “wizard” that holds a lot of information and options and allows for a steeper learning curve for nontechnical people like him.
VWO Heatmaps While Gadanon admits that his team hasn’t used the platform to its full potential, he notes that the Colart brand has benefited from VWO in multiple ways.
Optimizely lets its customers manage and run A/B tests and personalize their website for visitors. On the other hand, VWO provides a data-driven testing solution that connects every step in the visitor journey to impact conversion rates. Customers can bring their entire conversion optimization program on a single, connected platform—track business goals, analyze visitor behavior, build data-driven hypotheses, run tests, and personalize content. Using the Analyze capability of VWO, Gadanon and his team have been able to analyze visitors’ behaviors on the Colart website. “We use heatmaps and scrollmaps to ensure that the design elements of every new page are working for our website visitors,” he stated.
On-page Surveys The digital team at Colart has also used VWO Surveys to settle internal, subjective debates. When they noticed that in some instances, pages hit per session and time on site were high, they wanted to find out if people were lost or if the content was not engaging enough. Some team members attributed it to poor site navigation and user experience. To verify this hypothesis, Gadanon setup on-page surveys which revealed that 90% of visitors who took the survey were satisfied with the site and approximately 50% were happy with the site experience, leaving no room for further debate.
Minimal IT Dependency Gadanon notes that with VWO, his team has been able to set up and run tests with little IT help. The team usually tests changes to website content to see what visitors prefer and then plans to increase the testing frequency in the future.
It helps that the team does not need to integrate VWO with many third-party tools apart from its analytics platform. Therefore, it requires less support from a developer than it would have needed if it had chosen Optimizely.
Considering the experience of Gadanon and his team with both Optimizely and VWO, it becomes clear that VWO is the ideal A/B testing and conversion optimization platform for Colart and its many sub-brands. As a connected conversion optimization platform, VWO has helped the team deliver an improved user experience to its digital audience. It comes as no surprise then that Gadanon describes VWO as the “Swiss knife of web testing—an A/B testing tool as well as a research and monitoring tool for websites.”
Looking for a detailed feature comparison between VWO and Optimizely? Find it here.
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