It’s a maxim we’ve all heard and one we’re likely just as sick of. A saying which, if you spend any time on LinkedIn or other self-promotional platforms, you’ll find adorning countless updates, “motivational” images, and influencing all kinds of statuses. A belief so ingrained in the modern business psyche that it’s become almost synonymous with success. What’s the belief I’m referring to? Malcolm Gladwell’s idea that with 10,000 hours of practice, you can become an expert at anything. It’s an approach almost every successful person recommends. Countless hours of hustle will have you mastering your craft and reaching some…
Hi, I’m Corey. Are you an idealistic marketer, like me?
That is—do you plan your marketing campaigns by pretending technical limitations aren’t a thing and just map out the ideal experience you want for your prospects from first impression to final conversion? Like this:
A photo of my actual campaign flow on the whiteboard.
If your whiteboard looks this optimistic, read on. We’ll nerd out together.
After us idealistic marketers are done dreaming about our perfect campaign structure from start to finish, the harsh reality sets in: technical limitations are definitely a thing. When the time comes to figure out how to actually do something a little crazy, like augment lead data or enrich it with extra data pulled from ‘the internet’, things get much trickier. But if you’re dedicated to the campaign you mapped out, you really want to make it happen.
Often, you’ll ask a developer for help and hear, “Sure it’s possible. I’ll just need two weeks to code it up. Log a request and we’ll prioritize it against all the other requests for my genius.”
We both know you’re not logging that request, because it’s not getting prioritized.
Eventually, you run a campaign that looks exactly like what you’ve done before, or what everyone else is doing, because it’s relatively easy for us—lowly marketers—to pull off by ourselves.
Can’t we Execute More Sophisticated Marketing?
Is it too much to ask that we can create whatever the hell we dream up, so we can push the industry forward? To deliver the experience we think could make a difference to our prospects—one they might even enjoy?
Not if we need to rely on devs to help build our lead management or the integrations component of our campaigns for us, unfortunately.
However, I’ve found that more and more often I don’t need to have these futile conversations with developers. Modern martech has brought us tools to help, and the tool that comes up most often for me is Zapier.
Your Marketing on Zapier
Have you ever punched above your weight at work and solved a problem that that you’re totally unqualified to solve? It. feels. so. satisfying. You feel way smarter than you actually are.
I got that feeling when I used Zapier with Unbounce for the first time. I still get that feeling today. If you dream big enough, and can connect the right tools together, you can pull off campaign workflows that feel almost impossible.
Exactly how I felt having used Zapier for the first time.
Most recently, I tried to execute the campaign in the whiteboard photo above (the one above the Dragonball Z meme). The campaign—called Conversion Quest—challenges PPC marketers working in agencies to double the conversion rate of one of their client’s landing pages in 30 days.
When planning this campaign, I wanted to have a prospect fill out the form on a landing page with the current date (when they were “starting their quest”), and their current conversion rate. From there, they’d receive an email confirming their personalized quest goal and deadline by which they’d ideally complete the challenge (The email was to automatically pull in someone’s target conversion rate and their custom due date a month out).
Of course, when I’d planned this flow, there was no technical way to magically include a doubled conversion rate and custom due date directly in each prospect’s followup message. That is until my colleague reminded me of Zapier Formatter, which allows you to manipulate your lead data before it goes into your marketing automation platform (or CRM, or Email Marketing Service, or wherever other tool you can think of). Just 30 minutes later (and without approaching our dev team), I had augmented data going into our marketing automation platform.
Now Conversion Quest runs with custom info in the followup, all thanks to a quick Zap (a preconfigured integration template connecting two or more apps).
Here’s an example of the message I send in that campaign:
Here’s a sample of the email I manipulated data with via Zapier to personalize.
Now, are you going to need to use Zapier so you can build Conversion Quest?
No (that’s my great idea)… But my bet is you’ve got amazing campaign ideas for which Zaps could help you create a consistent (better!) experience for your leads, and help you stop relying on developers. As a bonus, Unbounce now has Integrations Powered by Zapier available right in the builder, so you can do this super quickly, without ever leaving Unbounce.
Here’s just a sampling of the Zaps available right in Unbounce. There are 60+ right in app, and with a Premium Zapier account you can access over 900!
Let’s dig into the versatility for a second.
Leveling up your marketing (without a line of code)
1. You need to connect a client’s hodgepodge of tools
In this case, you’re a marketing agency that needs to build high-converting lead gen landing pages, overlays or sticky bars that connect to anything and everything your clients use, which could include:
Follow Up Boss
A few quick Zaps can connect your lead data to all of the above.
2. You want to use an existing CRM or marketing automation platform, with custom landing pages/Unbounce
If you’re using a tool that requires you to use rigid forms or landing pages, but you’d rather have custom landing pages that look great, convert like crazy and give you more control over the experience, you’d simply Zap together your landing page builder with tools/platforms like:
3. Your CMS or Marketing Automation tool doesn’t enrich your data for you
With Integrations Powered by Zapier, if you collect a lead in Unbounce, Zapier can enrich the lead’s profile with extra data (using, for example, the lead scoring Zap) en route to wherever you’re storing your leads.
4. Your sales team would like to be notified immediately when a super qualified lead comes in…but they never check their email
For this, you can try sending notifications via the following Zaps:
5. You’d like to route leads to specific salespeople in your CRM depending on the info a prospect submits in a form
Joe Savich from Altos gave this a try in Unbounce, and had high praise for this email parser Zap:
“It’s pretty nice. The integration powered by Zapier was super easy to setup…I was able to create a lead notification with a condition that, depending on which custom field was chosen, would send that lead to the appropriate sales team. My client thinks I am a magician! I could see this being used a lot going forward.”
Overall, of all the feature releases in my 4 ½ years at Unbounce, Integrations Powered by Zapier is my all time favourite. Zaps from right inside our builder empower marketers to do things you shouldn’t be able to do, without developers. And they make you feel really smart.
If you’re committed to driving our industry forward with some next-level marketing (that may look impossible at first glance), I’d urge you to try zapping some connections together and getting creative. You might surprise yourself, or better yet your boss or clients.
Editor’s Note: We’ve been closely working with Maya on this article, and we’re happy to see the final result now being published on 18F. We highly encourage more teams to share the lessons they learned when building design systems or pattern libraries, and we’re always happy to support them in writing, editing and shaping that article. This post is a re-post of Maya’s final article.
Today, there are nearly 30,000 U.
For many people, a map of a transportation network is a given, an expected part of the system, something that just is — like a fire-escape plan in a building. So, when I say that I design transportation maps, they don’t understand. What is there to design even?
Well, let’s take the London underground map as an example. Designed by Harry Beck, it was the world’s first transportation map to use the principles of electrical circuit drawings.
Paid Ads > Webinar > Email Nurture > Push for the Sale Traffic Generation > Lead Magnet > Nurture > Grab the Sale Exit Intent > Lead Capture > Reengagement Series > SELL Funnels. Everywhere I turn in the world of internet marketing all I see is advice on how to create the most basic yet aggressive sales funnel. We’re told to push users toward the end goal. An end goal which is collecting their email address or increasing sales. And often, there’s little or no talk about how to progress from the funnel’s end goal. And that presents a…
Modern customers scour websites and research products they’re thinking of buying before making their actual purchase. When customers are 60% to 80% of the way down the funnel before they talk to anyone at your business, you can’t rely on traditional methods to generate loyalty. At the same time, fewer and fewer clients remain loyal to one specific brand. Loyal customers are profitable customers: repeat customers are cheaper to market to, spend more, and make more frequent purchases. Yet, only 27% of initial sales go on to become repeat customers. Companies need to invest in building loyalty among their customers….
The past year has seen quite a rise in UI design tools. While existing applications, such as Affinity Designer, Gravit and Sketch, have improved drastically, some new players have entered the field, such as Adobe XD (short for Adobe Experience Design) and Figma.
For me, the latter is the most remarkable. Due to its similarity to Sketch, Figma was easy for me to grasp right from the start, but it also has some unique features to differentiate it from its competitor, such as easy file-sharing, vector networks, “constraints” (for responsive design) and real-time collaboration.
Typography is a primary element of composition. Being a designer, I pay a lot of attention to its quality. Operating Photoshop is easy for me; however, to level up my skills, I am always learning to work with letters, using my hands, without any computer programs.
The first time I took a calligraphy course was about a year ago, and the decision was quite hard. I was sure that it would be painstaking and that I would need excellent handwriting to learn this art.
The best user experience is the one the user doesn’t notice. It appears smooth and simple on the surface, but hundreds of crucial design decisions have been made to guide, entertain and prevent trouble.
If the user experience design does what it’s supposed to do, the user won’t notice any of the work that went into it. The less users have to think about the interface or design, the more they can focus on accomplishing their goal on your website.
There was a time when simply launching an A/B test was a big deal.
I remember my first test. It was a lead gen form. I completely redesigned it. I learned nothing. And it felt like I was on top of the world.
Today, things are different, especially if you’re a major e-commerce company doing high-volume conversion optimization in a team setting. The demands have shifted; the expectations are far greater. New tools are being created to solve new problems.
So what does it take to own enterprise e-commerce CRO in 2016 compared to before?
Make money during A/B tests
While “always be testing” is a great mantra, I have to ask, “is you ‘always be banking?’”
Most of us have been running tests that inform us first, and make money later. For example, you might run a test where you’ve got a clear winner, but it’s one of 5 other variations, so you’re only benefiting from it 20% of the time during the length of the experiment.
Furthermore, you may have 4 variations that are underperforming versus your Control, so you could even be losing money while you test. Imagine spending an entire year testing in that manner. You’d rarely be fully benefiting from your positive test results!
Of course, as part of a controlled experiment and in order to generate valid insights, it’s important to distribute traffic evenly and fairly between all variations (across multiple days of the week, etc).
But there also comes a time to be opportunistic.
Enter the multi-arm bandit (MAB) approach. MAB is an automated testing mechanism that diverts more traffic to better performing variations. Thresholds can be set to control how much better a variation has to perform before it is favored by the mechanism.
Hold your horses: MAB sounds amazing, but it is not the solution to all of your problems. It’s best reserved for times when the potential revenue gains outweigh the potential insights to be gained or the test has little long-term value.
Say, for example, you’re running a pre-Labor Day promotion and you’ve got a site-wide banner. This banner’s only going to be around for 5-10 days before you switch to the next holiday. So really, you just want to make the most of the opportunity and not think about it again until next year.
A bandit algorithm applied to an A/B test of your banner will help you find the best performer during the period of the experiment, and help generate the most revenue during the testing period.
While you may not be able to infer too many insights from the experiment, you should be able to generate more revenue than had you either not tested at all or gone with a traditional, even split test.
BEFORE: Test, analyze results, decide, implement, make money later.
TODAY: Test and make money while you’re at it.
When to do it: Best used in cases where what you learn is not that useful for the future.
When not to do it: Not necessarily the most useful for long-term testing programs.
Track long-term revenue gains
If you’ve been testing over the course of many months and years, accurately tracking and reporting your cumulative gains can become a serious challenge.
You’re most likely testing across different zones of your website – homepage, category page, product detail page, site-wide, checkout, etc. Multiply those zones by the number of viewport ranges you’re specifically testing on.
What do you do, sum up each individual increase and project out over the course of a year? Do you create an equation to calculate the combined effect of all of your tests? Do you avoid trying to report at all?
There isn’t one good solution, but rather a few options that all have their strengths and weaknesses:
The first, and easiest, is using a formula to determine combined results. You’ll want a strong mathematician to help you with this one. Personally, I always have a lingering doubt that none of what is being reported is accurate, even using conservative estimations. And as time goes on, things only get less accurate.
The second is to periodically re-test your original Control from the moment at which you started testing. Say, every 6 months, test your best performing variation against the Control you had 6 months prior. If you’ve been testing across the funnel, test the entire funnel in one experiment.
Yes, it will be difficult. Yes, your developers will hate you. And yes, you will be able to prove the value of your work in a very confident manner.
It’s best to run these sorts of tests with a duplicate of each variation (2 “old” Controls vs 2 best performers) just to add an extra layer of certainty when you look at your results. It goes without saying that you should run these experiments for as long as reasonably possible.
Another option is to always be testing your “original” Control vs your most recent best performer in a side experiment. Take 10% of your total traffic and segment it to a constantly running experiment that pits the original control version of your site against your latest best performer.
It’s an experiment running in the background, not affected by what you are currently testing. It should serve as a constant benchmark to calculate the total effect of all your tests, combined.
Technically, this will be a challenge. You’ll be asking a lot of your developers and your analytics people, and at one point, you may ask yourself if it’s all worth it. But in the end, you will have some awesome reports to show, demonstrating the ridiculous revenue you’ve generated through CRO.
BEFORE: Individual test gains, cumulated.
TODAY: Taking into consideration interaction effects, re-running Control vs combined new variations OR using a model to predict combined effect of tests.
When to do it: When you want to better estimate the combined effect of multiple testing wins.
When not to do it: When your tests are highly seasonal and can’t be combined OR when it becomes impossible from a technical perspective (hence the importance of doing so in a reasonable time frame—don’t wait 2 years to do it).
Track and distribute cumulative insights
If you do this right, you will learn a ton about your customers and how to increase your revenue in the future. Ideally, you should have a goody-bag of insights to look through whenever you’re in need of inspiration.
So, how do you track insights over time and revalidate them in subsequent experiments? Also, does Jenny in branding know about your latest insights into the importance of your product imagery? How do you get her on board and keep her up to date on a consistent basis?
Both of these challenges deserve attention.
The simplest “system” for tracking insights is via spreadsheet, with columns that codify insights by type, device, and any other useful criteria for browsing and grouping. This proves unscalable when you’re testing at high velocity. That’s where a custom platform comes into play that does the job of tracking and sharing insights.
For example, the team at The Next Web created in internal tool for tracking tests, insights, then easily sharing ideas via Slack. There are other publicly available options, most of which integrate with Optimizely or VWO.
BEFORE: Excel sheets, Powerpoint presentations, word of mouth, or nothing at all.
TODAY: A shared and tagged database of insights that link back to the experiments that generated them and is updated on the fly. Tools such as Experiment Engine, Effective Experiments, Iridion and Liftmap are all solving some part of this puzzle.
When to do it: When you’re learning a lot of valuable things, but having trouble tracking or sharing what you learn. (BTW, if you’re not having this problem, you might be doing something wrong.)
When not to do it: When the future is of little importance.
Code implementation-ready variations
High velocity testing doesn’t just mean quickly getting tests out the door; it means being able to implement winners immediately and move on. To make this possible, your test code has to be ready to implement, meaning:
Code should be modularized. Your scripts should be modularized into sections functionality and design changes.
BEFORE: Messy jQuery.
TODAY: Modularized experiment code, separated css that aligns with classnames.
When to do it: When you wish to make the implementation process as painless as possible.
When not to do it: When you just don’t care.
Create FOOC-free variations
If your test variations “flicker” or “flash” as they load, you’re experiencing Flash of Original Content or FOOC. It will affect your results if it goes untreated. Some of the best ways to prevent it are as follows:
Place your code snippets as high as possible on the page.
Improve site load time in general (regardless of your testing tool).
Briefly hide the body or div element being tested.
Some people think of A/B testing as a way to improve the look of their website, while others use it to test the fundamentals of their business. Take advantage of the tools at your disposal to get to the heart of what makes your business tick.
For example, we tested reducing the product range of one of our clients and discovered that they could save millions on manufacturing and marketing without losing revenue. What are the big lingering questions you could answer through A/B testing?
BEFORE: Most of us tested button colors at one point or another.
TODAY: Business decisions are being validated through A/B tests.
When to do it: When business decisions can be tested online, in a controlled manner.
When not to do it: When most factors cannot be controlled for online, during the length of an A/B test.
Use data science to test predictions, not ideas
It is highly likely that you are underutilizing the customer analytics that are available to you. Most of us don’t have the team in place or the time to dig through the data constantly. But this could be costing you dearly in missed opportunities.
If you have access to a data scientist, even on a project-basis, you can uncover insights that will vastly improve the quality of your A/B test hypotheses.
TODAY: Predictive analytics can uncover data-driven test hypotheses.
When to do it: When you’ve got lots of well-organized analytics data.
When not to do it: When you prefer the spaghetti method.
Optimize for volume of tests
There was a time when “always be testing” was enough. These days, it’s about “always be testing in 100 different places at once.” This creates new challenges:
How do you test in multiple parts of the same funnel synchronously without concern for cross pollination?
How do you organize your human resources in a way to get all the work done?
This is the art of being a conversion optimization project manager: knowing how to juggle speed vs value of insights and considering resource availability. At WiderFunnel, we do a few things that help make sure we go as fast as possible without sacrificing insights:
We stagger “difficult” experiments with “easy” ones so that production can be completed on “difficult” ones while “easy” ones are running.
We integrate with testing tool APIs to quickly generate coding templates, meaning our development doesn’t need to do any manual work before starting to code variations.
We use detailed briefs to keep everyone on the same page and reduce gaps in communication.
We schedule experiments based on “insight flow” so that earlier experiments help inform subsequent ones.
We use algorithms to control for cross-pollination so that multiple tests within the same funnel can be run while being able to segment any cross-pollinated visitors.
BEFORE: Running one experiment at a time.
TODAY: Running experiments across devices, segments, and funnels.
When to do it: When you’ve got the traffic, conversions and the team to make it happen.
When not to do it: When there aren’t enough conversions to go around for all of your tests.
Don’t get stuck in the optimization ways of the past. The industry is moving quickly, and the only way to stay ahead of your competitors (who are also testing) is to always be improving your conversion optimization program.
Bring your testing strategies into the modern era by mastering the 8 tactics outlined above. You’re an optimizer, after all―it’s only fitting that you optimize your optimization.
Do you agree with this list? Are there other aspects of modern-era CRO not listed here? Share your thoughts in the comments!