An Overview of Conversion Optimization
Conversion optimization applies to all companies, from startups to large corporations. Even if your digital experience — website, app, whatever — is converting fairly well, there’s almost always room for improvement, which just means if you’re not doing some type of conversion optimization you might be leaving money on the table. Or maybe you don’t know exactly what conversion optimization is, well have no fear, I’ve put together the following primer so dive in!
What is conversion optimization?
Let’s start by answering that million dollar question: what is conversion optimization? Conversion optimization, also commonly referred to as “conversion rate optimization” or CRO, refers to a systematic approach, employed by digital marketers, for increasing the percentage of visitors to a website or mobile app that take a desired action or set of actions. Generally speaking, those desired actions are of benefit to the business because they advance a person in a predefined marketing funnel. That definition might sound a bit abstract, so let’s break it down a little. In other words, conversion optimization is a methodology that digital marketers use to get more users of their websites or apps to do more of the things they want from them. Those “things” are actions that benefit the business — they’re business goals — like purchasing, subscribing or submitting a sales lead form. So in essence, the conversion optimization process involves understanding how users move through your site or app, the actions they take and what could be keeping them from completing the business goals. Conversion optimization is often compared to direct response marketing in that the primary objective is to generate more success at the bottom of the marketing funnel (i.e. more sales, more leads, etc.) without investing more money at the top of the funnel (e.g. paying to drive more site traffic, etc.) and so by way of doing that, increasing the return on investment (ROI) of related marketing expenditures and the overall profitability of the business.
What is a conversion?
To “convert” is a digital marketing term for when a visitor or user takes those desired actions — buying a product or service, giving the business something of non-monetary value like an email address in exchange for a whitepaper, or maybe completing a form to refer the business to a friend, the list can go on. In short, those desired actions, those business goals, are defined by the business model. The main goal of an ecommerce website is to sell products. For a SaaS platform, it’s to sell subscriptions. You get it. Basically a conversion is an action that advances the goals of the business. In this sense, a user converts from a state of being less valuable to the business to a state of being of more value to it. And those actions might occur pre-purchase in the acquisition or activation phases or post purchase in the loyalty and retention phases.
What is a conversion rate?
In essence, marketers will identify conversion actions throughout the customer journey they deem meaningful to the health, sustainability and growth of the businesses then measure how often users are taking them, and finally, based on what they’re seeing, formulate strategies to increase the frequency. This frequency, in digital marketing, is a percentage referred to as a “conversion rate”.
Along the way, marketers look for more and more of these conversion actions to track and influence. As explained, some of the first ones are quite obvious. Purchases for instance are something you’d watch from day one. They are what a digital marketer would refer to as a “macro-conversion”, those main goals we talked about. Whereas, others need to first be identified, observed and tested to prove whether they correlate with a macro-conversion like sales before becoming something the digital marketing team deems meaningful enough to look for a way to influence. These are what marketers would refer to as “micro-conversions”.
Macro-conversions are, as stated, those actions that lead directly to behaviors fundamental to the business model. For example, a sale creates revenue. Pretty straightforward.
Micro-conversions alternatively are preliminary steps that you believe may lead to a macro-conversion. They are “stepping stones” or if you will “baby steps” that lead to users taking bigger ones. For example, a user signs up for your monthly promotional email. This act of signing up is a micro-conversion that might lead to that user buying something after receiving one of the emails.
Tactical vs. Correlative Micro-conversions
However, spotting micro-conversions isn’t always that straightforward. Sometimes the relationship of a given action and its ultimate influence on a macro-conversion isn’t clear at first and only becomes clear after empirical observation. That is, you only realize that that action is in fact a micro-conversion after you observe a pattern. To explain, let me take a step back and further define different types of micro-conversions. There are two: “tactical’ and “correlative”.
- Tactical: Tactical micro-conversions are ones that are explicitly designed by a marketer. In other words, they’re marketing tactics, things like, offering a form to sign up for promotional email. These types are tactics that are pretty well known. They’re best practices that digital marketers routinely use as a method for moving people along during the consideration phase before ultimately leading to a sale.
- Correlative: Correlative micro-conversions are ones that empirical observation tells us are leading indicators highly correlated with a user ultimately going onto a macro-conversion. For example, Dropbox claims that when a new user uploads at least one file (micro-conversion), there’s a strong chance that he or she will go on to sign up for the paid service (macro-conversion). Hence, one of the marketing team’s jobs at Dropbox is to try to incentivize users to upload their first file.
Generally speaking, there are usually multiple of these conversion types within any one digital experience. And in conversion optimization, the baby steps are the “art” behind the science. Good digital marketers identify them, especially the “correlative” variety, through a strict process of observing, tracking, experimenting and analyzing user behaviors. At scale, digital marketers employ an entire system of these types of measurements to track myriad behaviors across the entire customer journey.
How does conversion optimization work?
The fundamental idea behind conversion optimization is:
- First gain an understanding of certain user behaviors (relating to your site or app) by observing and measuring them.
- When you feel you have enough of an understanding of those behaviors, hypothesizing what sort of changes or improvements you might employ to influence future behaviors in your favor.
- Testing the implementation of those changes or improvements to try to prove or disprove your hypothesis.
- Assessing the results of your tests, drawing conclusions and taking action based on your learnings.
In other words, conversion optimization is an empirical process, consisting of:
- Observing and measuring user actions at scale and throughout a site or app experience.
- Then analyzing and drawing insights from the data collected.
- And finally, designing and implementing improvements tied to those insights.
In summary, we are talking about an empirically-based, systematic approach to gathering insights and then using them to effect positive change to the benefit of your business. Again, the system might look something akin to:
- Data Analysis: The marketing team analyzes the data collected by employed tracking efforts (e.g. SEO tools, Google Analytics, heat mapping, NPS, etc.), from pre-acquisition all the way through retention, and draws insights on what it could be telling them about all the different ways people are interacting during the customer journey.
- Experimentation: From there the marketing team develops hypotheses for why something might be happening (or not happening) and based on these hypotheses, designs experiments to test them. An experiment might be something like A/B split-testing a call to action, headlines or button colors on a landing page.
- Results Analysis: Upon completion of an experiment, the marketing team analyzes and draws strategic insights from the results gathered, and formulates strategies and action plans for implementing any learnings.
- Iteration: The marketing team applies steps 1-3 iteratively and continuously. It goes without saying data-driven, continuous improvement is imperative to the success of any digital marketing initiative. For the system to have considerable impact, it must be applied iteratively, ad infinitum. The effect of which over time is that the system gets better and better at eliciting desired actions from users.
The system is often visually represented in the following way.
What’s an example of something conversion optimization might tell us?
Conversion optimization might identify and answer questions like:
- Why are users dropping off at certain points in the customer journey?
- Which actions might I take to stem that drop off?
Imagine you’re wondering why you’re seeing a big drop off in your ability to convert free trial customers into paying customers. In other words, a lot of people are coming to your website and a high percentage of them are getting intrigued enough by what you’re offering to sign up for a free trial, but not as many as you need are taking the next step after trial to become paying customers. In this case, your “visit to trial” conversion rate is probably looking pretty good — a lot of people are converting into trial customers. But the story goes south as you get further into the customer lifecycle. Only a small percentage of those trial customers go on to become paying customers, in which case your “trial to paid” conversion rate isn’t looking so good and you want to investigate.
- How do you explain the behavior?
- What went wrong?
- What part of the experience did they not like?
- Was it the product or something else?
- Was it the price?
- Was it the process?
- What actions could you take to improve the conversion rate?
These last questions are all important ones, answering them is the very essence of conversion optimization which you might employ in the following way:
- Conduct Analysis: Look at all user behaviors related to the issue.
- Draw Insights: Analyze the behavior to divine patterns that suggest adverse effects, like process friction keeping users from converting in higher percentages.
- Develop Hypotheses: Once you’ve identified these patterns, develop hypotheses for ways you might affect them, that is, in this case removing process friction.
- Design Experiments: With your hypotheses in hand, design experiments for testing them in order to prove the existence of a casual relationship. For example, regarding the friction you’ve identified, you will want to prove a cause and effect relationship between certain attributes of your digital experience and the resulting friction. In other words, are those attributes causing the friction you’re seeing?
Additionally, in designing an experiment it’s critical to:
– Design a measurement plan (i.e. ensure goals can be measured properly) and…
– Know what success looks like from the outset.
- Analyze Results + Prioritize Next Steps: After collecting data from your experiment, you review the results with a multidisciplinary team (e.g. designers, business analysts, strategists, engineers, customer service, etc.) and then prioritize recommended changes from the perspective of the broader list of optimizations you’re hoping to tackle. Doing this prioritization objectively is critical. One way to do that is to go down the list of proposed changes and have each person in the group score each item, then add up the numbers and prioritize by score. This method is simple and transparent, and importantly, ensures everyone’s opinions carry the same weight (which helps avoid situations where the highest paid person in the room is the de facto sole decision maker).
- Implement Changes + QA Test:
And finally, you..
– Implement changes to your digital experience based on your prioritization
– Thoroughly QA test those changes — Note: Do not skimp on the QA testing part, lest you break your website. Keep in mind, breaking a site is an excellent way to create unnecessary cross-company friction.
– Push them live.
So in summary, conversion optimization relates to:
- Defining the right questions
- Formulating a good hypothesis from your questions
- Designing experiments to prove your hypotheses true or false
- Figuring out how to measure the results of your experiments in a way that prove your hypotheses according to that binary criteria (true/false)
- Running experiments and divining insights from their results
- Prioritizing work and implementing changes
- Iterating. That is, implementing a system to keep doing steps 1-6 continuously.
Why is a good system important?
Conversion optimization can spawn a lot of follow on questions — where the more questions you answer, the more questions you have — which is why it’s imperative you employ a system and adhere to it methodically, lest you go down proverbial rabbit hole after rabbit hole with little to show for your efforts. Say, for example, you want to answer the following question: do more people click [a given] button on [a given page] when it’s orange rather than grey? So you run an experiment and it shows that a causal relationship does exist (i.e. more people DO click [that given] button on [that given page] if it’s orange rather than grey). Where might that lead? Well, of course, you’ll probably change the button color permanently to orange but it might also lead to new questions like: will this work across my website? In other words, do orange buttons versus grey ones, as a general rule, get clicked more often? The bottomline is, proving causality requires doing a lot of controlled experiments, testing variable by variable, in order to definitively say yes or no on the question of whether a causal relationship exists. And these follow on questions are why you keep testing, peeling back layer after layer, systematically and methodically, continuously.
Why do conversion optimization in the first place?
I’ll give you six good reasons…
- Operations will be more efficient: Before conversion optimization became standard practice, generally speaking, when you wanted to test something on your website you had to take a leap of faith — implement it at great time and expense, and if it didn’t work out well, you then had to change it back at great time and expense. These days mainstream testing tools allow you to quickly and easily set up split tests and gather clear results without permanently implementing anything, which means you’ll feel emboldened to try new things.
- Marketing will be more efficient: Acquisition costs are arguably the biggest marketing costs a business will incur over its lifetime and considering that it’s generally more cost-effective to convert a higher percentage of current visitors than to pay for more, it’s imperative to be optimizing your marketing funnel and site experience. A conversion optimization system allows you to be nimble in setting up, testing and implementing optimization efforts. And conversion optimization testing when done right is safe and controlled, without the concern of damage or any long-lasting impact to your site or business, affording you the ability to take risks and to discover improvements you may never have anticipated (or felt comfortable trying). Additionally, conversion optimization serves to plug leaky funnels and customer bases — invariably yours has holes, everyone’s does — so your overall marketing spend is efficient and importantly, retention continues to improve. Retention, in marketing terms, is the process of building high enough engagement with existing customers that they continue buying your products or services. Effective retention efforts enable you to build a lasting relationship with customers and when they stick around longer, the better their lifetime value (LTV) and the more likely they spread the word about you within their circles of influence. So it’s important to think about conversion optimization in that way:
– Endeavoring to reduce your customer acquisition costs (CAC) consistently, albeit in increments, over the long haul.
– Improving retention and thus LTV.
– And ultimately, supporting word of mouth (WOM) referrals, the best and cheapest form of acquisition.
Think of conversion optimization as a compound interest rate — a little bit each month will add up nicely.
- You will make smarter decisions driven by data not your gut: Conversion optimization eliminates “I think” and replaces it with “I know.” Of course, you will use your gut instincts to develop hypotheses but then you test them with experiments designed to collect data and validate a direction before taking a leap. If you follow this approach methodically and comprehensively, ultimately you’ll see better results from your decisions over time.
- You’ll know a lot more about your visitors than ever before: Truth be told, no two customer groups are the same which is why it’s vital to test and experiment to figure out what your group prefers. And learning these insights affords you the ability to better guide any future efforts around development, design and marketing as you’ll already know what your customers want and, critically, which directions boost conversions.
- Your SEO will improve: Yes, you read it correctly. Conversion optimization can improve your SEO by helping you identify what you need to fix in order to reduce the deleterious effect high bounce rates (aka “pogo-sticking”) might have on your ability to rank in organic search. “Pogo-sticking” is defined as a user bouncing back and forth between the search engine results page (SERP) and the sites listed there. In essence, a user conducts a search and clicks a site option listed on the SERP but quickly, upon arrival determines that the site they chose isn’t what they’re looking for so they quickly click the back button to go back to the SERP list. They then choose another site option from the list and on and on. This pattern is called “pogo-sticking” and it’s something that can hurt your rank in organic search. Why? Remember Google wants users to discover the right content quickly and easily, and pogo-sticking implies the opposite. By using conversion optimization to test and improve your landing pages with respect to bounce rates, you can avoid the adverse effects of pogo-sticking. This might look something like:
– Testing Copy: To avoid pogo sticking, landing pages shouldn’t be static, rather they should be regularly updated to reflect changes in the marketplace, recent statistics, etc. This is something you can and should test.
– Testing UX: Say the content a lot of users are seeking is stuck below the fold on your landing page, they may arrive, not see it and summarily pogo stick back. Testing can reveal these sorts of hard-to-identify UX issues.
- You’ll make more money: Conversion optimization won’t result in thousands of dollars in additional revenue right away but it will steadily add incremental revenue that you’ll notice over a period of time. Of course, any given test might identify that “golden” opportunity garnering immediate and significant impact, but generally speaking, the benefits of conversion optimization more often reveal themselves over the long haul. The sum total of lots of small improvements that together result in much higher conversions and revenue. Let’s look at an example. You change the location of a form on a page which earns you two extra leads per month. This may not seem like a lot but consider the following:
– Over the course of a year that’s 24 more leads.
– If you close those leads at a rate of 10%, that’s 2+ more new customers.
– If your average customer is worth $20K then that little change might amount to more than $40K in additional revenue.
Year over year, this accretive effect can really add up…
A Good Conversion Optimization Rule of Thumb
A general rule to consider when thinking about a conversion optimization program: if your digital experience — site, app, etc. — gets more than 200 conversions per month, you absolutely need to employ a conversion optimization program. And, if it gets more than 1,000 per month and you haven’t yet, you’re leaving something on the table. Alternatively, if it gets fewer than 200 conversions per month, stick with focusing on increasing visitors first. Why? With those traffic numbers, it’ll be hard to run an effective split testing program. Not that you won’t be able to split test — in fact, I recommend you do, to optimize around micro-conversion steps — but understand that it won’t be at sufficient scale to iterate rapidly.
In a series of posts, including this one, I’ll attempt to give you a basic framework for implementing a conversion optimization program, including: