Conversion Rate Optimization Checklist

Awesome! You've decided to begin a CRO strategy to improve your website's performance. Below you'll find a checklist of the key activities and tasks we'll be performing. 

Expect this entire process to take anywhere from 4-12 weeks.

1) Setup


Setup Data Analytics

If it's not already setup, we set your website up with Google Analytics and let the data come in for a few weeks to a month before we move forward.

Setup Visual Analytics

We'll setup appropriate software to track what your visitors are doing and what they are clicking on. The type of software we use depends on the budget for this project. There are premium tools and free options we can review with you.

Define Business Goals & Success Metrics

First we'll work together to define the key business goals for your website. Specifically, what success looks like and how to measure it via Key Performance Indicators (KPIs).


Next, we'll move to the digital realm of metrics & goals to define which specific metrics we can capture and the goals to measure performance.

Examples:

Metrics
- Time on site
- Bounce rates
- Add to cart
- New Visitors

Goals:
- Time spent on site > 5 minutes
- Added item to cart

- Contact form submitted



Wait for Data

We need to give these tools time to start tracking. Ideally we have a few weeks to a month of data analytics before we start review it. Visual analytics can be analyzed immediately once we have a key strategy in place.


2) Customer & Traffic Analysis


Review the Funnel 

A conversion funnel defines the path a visitor takes from becoming aware of your website to becoming a customer. We will review your funnel and document where they are coming from, and the paths they go through to becoming customers.

Review the Data

We look at how much traffic you have (the top of the funnel) and if it's strong enough to begin CRO or if more traffic is required before CRO can be effective.


To run CRO a specific page and goal needs to have daily traffic. 

Refine and Tweak the Funnel 

We sit down and discuss what would an ideal funnel looks like and what gaps currently exist. Here we get to dream about the goals we defined and how a funnel can support this.

Define Conversion Goals using Funnel Stages

Using the funnel design as a guide, we will list out the specific conversion goals for each stage. While the bottom of the funnel is typically the focus for customers, it is best practice to create intermediate goals higher up to cater to all types of visitors. For example, newsletter opt ins, or contact form submissions, or ebook samples are great ways to warm leads up and move them to the bottom.

photo from hubspot.com


3) Usability Analysis & Planning


Review Industry Averages

We'll look at your industry and find comparable data for your competitors and other businesses. This will guide the targets for measuring success.

Defining Baseline Conversion Rates

By now there should be enough data to understand what your baseline metrics should be. For example, 10 out of every 1000th visitor inquires about a product for sale, 1 out of every 1000th visitor makes a purchase. Once we know what's "normal" we can start to set targets.

Define Conversion Goals

We need to define what metrics will be used as a basis for goals and defining what success looks like to your business.

For example, time on site, lower bounce rates, number of purchases, adding to cart, unique visits etc... 

Identify Simple Fixes

Diving a bit more into details we will identify any simple updates that could be made to the site which could improve the flow for customers and are obvious issues. These are simple fixes to reduce friction and improve clarity with your visitors. From changing copy or fixing actual bugs, these tasks can be performed with confidence that they will improve the customer experience.

Review the Customer Journey

We'll look at the customer journey through the funnels or however they are browsing your site. See where your visitor are coming from, where they drop off and how many actually make it through. Combined with visual data we can hypothesize what leaves room for improvement.  

photo from hubspot.com


4) Experimentation


Build & Prioritize the Hypothesis with P.I.E.

Based on the the previous phase, we'll build a list of hypotheses to experiment with.

A hypothesis looks like the following "I believe reducing the number of forms on the order form will result in increased leads because visitors keep skipping the name field and quitting".


To prioritize, we use the "P.I.E" framework which ranks the value of a hypothesis by "Potential", "Importance", and "Ease" on a scale of 1 to 5 where 5 is the best.


For example, a high potential means the specific page or section has a lot of potential to be improved. It may have a very low conversion rate.


High Importance would be a page that is visited by a lot of traffic already. This is typically where most people focus on when short listing areas to focus on.


Ease is how simple it is to do the specific update. This is what your web development team would prefer working on :)


Taking the score we divide by 3 and then have our final score out of 5. Although a bit qualitative in nature, this method allows us to rely on the data backed system of making decisions instead of letting recency bias affect our judgement on which task to .

Implement It

We implement a hypothesis, or more and create alternate versions for experimentation. The type of test can either be a straightforward A/B test which tests 2 distinct versions of a page, or a multivariate test which tests multiple variations on a single page together.


For example, a multivariate test could have a different header image and button copy. This would result in 4 possible combinations that would be split among your traffic.


Multivariate testing is more complex and can be more difficult to interpret, so we recommend keeping changes small when possible.

Approve & Run It

We'll review the changes with you and if it's approved we'll schedule the experiment to run as soon as possible.

Wait and See

While the tests run we'll monitor the results periodically to see how it's going. The length of the test depends on the volume of traffic and amount of conversions that exist. The higher the numbers the faster it can run. Unless your site has a large amount of traffic, expect at least 2 weeks before a result can be finalized. 


5) Review & Repeat

We've reached the end! There are three potential results from the experiment.

Hypothesis Worked:

  • Do we need to do more work to implement this change?
  • Can we do more optimization from this point?
  • What did we learn about our customers?
  • Repeat this for the next experiment

Hypothesis Failed or was Inconclusive:

  • Is our hypothesis flawed in someway?
  • Was our data flawed or skewed?
  • What does our visual analytics tell us?
  • Should we tweak the hypothesis or move on to something else?

Conclusion:

From here we repeat back to phase 2 and continue the process of continual improvement.