Conversion Research and Optimization — A review
The past week, arguably, has been one of the most enlightening thus far on my growth marketing Minidegree journey with CXL.
I have to mention that the program is one of the best you can find on the internet. They did not pay for this ad by the way. LOL
But seriously, I am rethinking my interest in Udacity’s Nanodegree program. The quality of lessons and resources on CXL is just too sturdy. Every digital marketer out there should be thinking of enrolling for one or more of their programs.
The past week’s lessons were in conversion research and optimization. There’s so much to unpack about the subject.
First, you need to be data-driven.
As a digital marketer, when you see a new brand’s website for the first time, there is entirely no way you can tell from the get-go if the website is performing optimally or sub-optimally.
Except you have spiritual powers, which I doubt, you need to diagnose first.
Yes, some problems might be crystal clear. But you might be wrong. You need to initiate research and collect some data.
What kind of data do you really need?
There’s so much data you can collect but collecting overwhelming data isn’t what matters, what matters really is the quality of data that you need to make an important decision. Analysis Paralysis results when you are collecting so much data that you don’t even know what to do with them.
Essentially, for every data you collect, you should be able to answer the questions: what will I do differently based on this data? What could I possibly be doing differently based on this data?
If the answer is nothing, then you don’t need that data.
For an optimization project, it is called conversion research. This is where you dig into all that may be wrong with the website and figure out where and how it is losing money. Once you can get a list of that, you can then design experiments and tests that can help with optimization.
The conversion research process for an established brand differs from that of a new business or a start-up.
If yours is a new business or startup with no customers to survey or data to analyze yet, you may want to leave conversion research and optimization out for now. You should be focusing on customer development — figuring out which product to build and for whom.
For established brands, Peep introduced us to the ResearchXL framework. The model uses 6 data inputs to help marketers collect relevant data, which when mined can yield insights that will help optimize websites.
- Heuristic analysis
- Technical analysis
- Digital analytics
- Qualitative research
- User testing
- Mouse tracking analysis
Step 1: Heuristic Analysis — experience-based assessment of your website
When starting to optimize for conversions, it’s best to begin by understanding the user’s experience on your website. Go through the website page by page in the shoes of a target user.
There are 4 features to consider when auditing a website for experience:
- Clarity — is the design and content on each webpage clear?
- Friction — what may be slowing your users down or refraining them from taking the desired action?
- Anxiety — what makes the users cringe? (e.g., are you asking for sensitive data, etc?)
- Distraction — does each page have multiple goals?
Step 2: Technical Analysis — find the small bugs that are losing you money.
After doing a comprehensive heuristic analysis, it is time to make sure everything is running smoothly from a technical standpoint.
First, the website needs to be running perfectly on the device and browser type that your users are on. This is called cross-device and cross-browser testing, respectively.
Then you need to do a speed analysis — does your webpage take longer to load? The attention span of your audience is short, you don’t want to keep them waiting for long.
Questions you should be trying to answer here include:
- Does the site work with every major browser?
- Does the site work with every device?
- What’s the user experience like with every device?
- Technical issues and poor user experience kills conversions.
Step 3: Digital Analytics — It tells you where the money leak is coming from
Digital analytics tools are invaluable when it comes to identifying where the money is leaking from your website. Insights that you extract from your digital analytics can instruct which areas you should be spending the most time optimizing.
Google Analytics is an invaluable tool for this.
Things to check on your dashboard include;
- Where are they dropping off (the drop-off point)?
- What kind of users or segments are dropping off?
- What type of behavior correlates with more purchases?
- Are you measuring all the right things? Is the data you’re getting authentic?
Step 4: Qualitative Research — what surveys do you need to run?
Qualitative research helps you extract more valuable data from your users about what they want to see and how. It also helps you understand your users’ experience and pinpoint areas of friction you need to work on.
Two surveys you should run:
Onsite polls — survey people who are on our website who may or may not be buying from you. A simple question like “what’s stopping you from making a purchase now?” can make a big difference. Test the survey in different pages to see how users respond.
Follow-up surveys — Survey people who just bought something from your website with a bid to understand what bottlenecks they faced in the process. According to Peep, emailing your customers 8–10 opened ended questions can do the trick. I believe this is subjective and a mix of open-ended and closed-ended questions may perform better.
Copy testing is a key part of qualitative testing.
Step 5: User Testing
Recruit people who represent your target audience. Specify specific tasks you want them complete and watch how they complete these tasks. What people say and do may not overlap. More important than what people say is what they do.
Step 6: Mouse Tracking Analysis
Mouse tracking can provide valuable insights into viewing and information processing patterns. Peep cites scroll maps (how far down they scroll on any given page) and click maps (where people click and where they don’t) as important notes from mouse tracking analysis.
If you’ve integrated tools that record and store user sessions, you should take a look at the recordings for hidden gems as well.
Now that you’ve completed the research, what next?
You’ve collected your data What next? What approach should you employ for sorting it?
After your analysis, you’ll have a list of problems that are losing you a lot of money and screaming for solutions and others that are just mild. Rank these issues in order of priority on a 5-point scale. You should also split the issues into relevant categories.
2 criteria are important when giving a score:
Ease of implementation (time/complexity/risk): If the data tells you to build a feature that may take months and change a copy that may take minutes. The former may not be something you’d prioritize for a start.
Opportunity score: This depends on how many users are exposed to the issue, and how close to the money the issue is. For an e-commerce website, for example, if you deduce that a big issue is coming from the checkout page. That’s a clear indicator that you should be prioritizing the solution to that issue.
Essentially: Follow the money. You want to start with things that will make a positive impact on your bottom line right away.
For prioritizing specific test hypotheses that address issues that you allocated into “test” and “hypothesize” you should use the PXL test prioritization framework.
Measuring the Effectiveness of a Testing Program
In order to avoid wasting time by repeating the same testing mistakes, it’s crucial to continually self-assess the efficacy of your testing programs.
Three key metrics Peep reveals as very insightful include:
- Testing velocity — how many tests are you running per month. The faster the test, the more test you run, the more you learn and grow.
- Percentage of tests that provide a win
- Impact per successful experiment — most tests globally are between -15% and +15% relative increase or decrease. Yours can be better.
One last thing — The Invesp Conversion Framework
The Invesp conversion framework is made of 8 comprehensive principles.
- Build buyer personas and focus on a few select personas when designing your layout, writing copy, and so on.
- Build user confidence, make them trust you by using all kinds of trust elements.
- Engagement. Entice visitors to spend a longer time, come back to visit, bookmark it, and/or refer others to it.
- Understand the impact of buying stages. Not everybody will buy something on their first visit, so build appropriate sales funnels and capture leads instead, and sell them later.
- Deal with fears, uncertainties, and doubts (FUDs). Address users' concerns, hesitations, doubts.
- Calm their concerns. Incentives are a great way to counter FUDs and relieve friction.
- Test, Test, Test.
- Implement in an iterative manner. Build smaller blocks, make smaller changes, and test them and improve their performance.
Phew! There’s really so much I can’t even begin to unpack about Conversion research and optimization in this article but I hope this helps you optimize your websites better.