Conversion optimisation is a dark science that deserves more light.
At the forefront of digital marketing is the aptly named Digital Marketer, found via digitalmarketer.com.au and started by Ryan Deiss. If you want cutting edge information and best digital practice for your business, Digital Marketer is an excellent resource.
There is so much conversation around building content and generating traffic. But what happens with traffic once your customers arrive? Do they convert? Questions abound. And most marketers don’t have the answers:
- How can I improve my website’s user experience to achieve more leads and sales?
- Why are customers exiting my website, not going through my CTA pathway?
- What’s working and why? What’s NOT working and why?
It’s in the shadows because it’s undervalued and deserves greater focus.
To help shine the spotlight on this technical art, I interviewed Justin Rondeau, whom I met at Digital Marketer’s Traffic & Conversion Summit in Sydney. With a depth of experience that includes over 2,500 CRO tests, Mr Rondeau shares optimisation insights as well as key conversion principles that underpin digital marketing strategy.
You will learn:
- Why inaccurate customer data is like building on sand
- Why case studies shouldn’t be treated as blueprints to success
- The latest trends in conversion optimisation
- How to correctly set up an A/B test
- How to avoid 3 conversion optimisation mistakes
Edward Crossin: What's your background and how did you land the Conversion Optimisation Manager position at Digital Marketer?
Justin Rondeau: In late 2010, I found a back door into marketing when I accepted a job out of University at a small software company in Cambridge, MA. When you work for a small company you take on a lot of different roles, and marketing became one of my roles. When I took the Director of Marketing position I generated the most revenue in my first month than any other month they had seen in the last two years. I did this using different email optimisation tips.
From there I was hooked on optimisation and with my success record was given the chance to optimise the site and develop better funnel flows and user interfaces. Though the term ‘Conversion Rate Optimisation’ wasn’t used as often back then, that’s exactly what I was doing and what I continued to do for the rest of my career.
Unfortunately the benefit of working for a small company, the multiple roles, turned into a major problem. I only wanted to do optimisation work, so it was time to move on. I started with WhichTestWon shortly thereafter.
WhichTestWon provided me with a unique experience, I got to optimise our own site, train companies, and get the test data from companies spanning virtually every industry. This gig got my face on everyone’s radar and helped make connections with people all over the marketing world. One person I met during this time was Ryan Deiss. Specifically I had the pleasure of speaking at a few of his events.
After nearly 3 years with WhichTestWon I left to start my own consultancy, which was short lived. Owning your own company is HARD and you don’t get to do the stuff you love as much as you thought you would. Ryan offered me a position at Digital Marketer.
EC (Edward Crossin): Describe your day-to-day focus and priorities?
JR (Justin Rondeau): My day consists of analysing our funnels and finding opportunity areas. I’m really more or less a data plumber. My entire focus is coming up with innovative ways to boost conversions on the site. This involves digging through Google Analytics, watching thousands of session recordings, analysing heatmaps, digging through user surveys, and so on…
When I’m not doing that stuff I am either writing for our content team, developing presentations for different conferences, or spearheading a new project.
EC: What's changed in the conversion optimisation over the last 12 months and where do you see changes in the future?
JR: There is a big trend toward clean data and being anti case study. I am a major advocate of the former. When you take the helm at a new company or get a new client, you need to verify if the data is actually accurate! If you don’t you are just improving upon a foundation built on sand.
The anti case study movement also makes sense, but I think people need to slow their roll. If we contextualise case studies as content that should be used to inspire new ideas and are not to be taken as gospel, then I think we are OK. If people are to read into case studies in any way more than this then it should be for examples that actually provide the raw data and methodology.
Personalisation and segmentation have also been huge over the last 12 months. Personalisation techs have become cheaper and easier to implement (reminds me of testing techs over the last five years) and are a great way to boost conversions. Advanced segmentation has been a great way to pull out more data because averages tend to lie! What looks like a loser to the general public may be a huge winner for new visitors on mobile.
Optimizely just released a personalisation tool that looks promising (I just had a demo by their product development team). Optimonk is a powerful on-site retargeting tool that can do engagement based personalisation with pop ups. Evergage is an enterprise level personalisation tool. Monetate is another personalisation/testing suite.
EC: What's changing across the digital marketing landscape and what should smart marketers be ready for?
JR: Smart marketers need to pay attention to what is going on with Google. They are launching new Gmail ads as well as implementing custom audiences.
I’d also recommend implementing (when it’s available) the call to action buttons on Pinterest and Facebook.
EC: Which social media tool is exciting you right now and why?
JR: I think Facebook still has the goods. Facebook advertising has changed digital advertising as we know it. Case and point Google is launching a custom audience tool.
EC: What are the main Digital Marketer metrics that you use for conversion optimisation?
JR: This depends on the campaign really, but I’ll stick to our acquisition funnels:
- Leads Generated
- Immediate upsell add to cart
- Immediate upsell sales
- Digital Marketer Lab Sales
If I’m optimising a page for our certifications or some of our higher ticket products, obviously the main converting action is that cert or that product.
EC: What are the most important elements in setting up an A/B test?
JR: Digging through the data and developing a hypothesis for your test are the most important elements for setting up a test. If you don’t have a reason to test, it will be a flop. If you don’t have a goal and a way of identifying the winner (or loser), the test will flop.
The split test itself, the part where you change up the elements, is the fruit of all of the rigorous labour and as the fruit it gets the most attention. What should get the attention is the process of developing these tests!
EC: Not all businesses have the resources for a marketing or conversion optimisation specialist. What would be some simple advice for those businesses?
JR: If they don’t have the cash I’m going to make an assumption that they might not have the traffic either to run traditional split tests. What I’d tell these people to do is use Google Analytics (it’s free) to identify the holes in their funnel. Then I’d invest in a tool like HotJar to give me qualitative insights into what is broken on the pages I identify with Google Analytics.
EC: What are 3 typical conversion optimisation mistakes, and how to avoid them?
- Not having a clear stopping point for their test. You can fix this easily by using a test duration tool, rounding up to complete the week, and sticking to it.
- Testing for the sake of testing. The mantra ‘Always be testing’ gets reduced to ‘Test Everything’ which is wrong. Not everything can or should be tested, it is up to the marketer to be able to identify something that is functionally broken and needs to just be fixed.
- Confirmation Bias. A lot of optimisers only look for the positive trend and then are happy with results. They are just confirming their own assumptions and in most cases our assumptions are dead wrong.
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