Optimizing your website to ensure high conversion rates is one of the most important aspects of any marketing strategy. The thing is, it is also one of the toughest areas to deal with. That is why I have decided to share some of our insights about the process while suggesting a simple, yet effective, 4-step model for building a successful conversion optimization strategy.
Here at Dynamic Yield, we provide real-time personalization and conversion optimization tools for enterprises and medium-size businesses. Our clients range from major enterprises and industry leaders with an international presence to medium-size businesses from a various spectrum of sectors and verticals (such as retail, travel, insurance, gaming, media, etc.). We are very proud of our client relationships and are passionate in ensuring effective outcomes. Our customer success team, which consists of experienced web analytics professionals and conversion optimization experts, strive to nurture relationships with our customers and understand their business models, challenges and marketing optimization requirements.
Through our managed services, we oversee the conversion optimization process, making sure our tool delivers great results. While at times it all may look like magic, the truth is that crafting a successful conversion optimization methodology is a tough and complex process. The only type of “magic” involved would be following a well-defined systematic process using strategic and methodical steps.
Build a powerful conversion rate optimization process. Learn how to integrate advanced segmentation, A/B testing and personalization in a single framework.
The 4-step Systematic Conversion Optimization Methodology Chart
This chart provides a bird’s eye view of the process, which suggests a systematic conversion optimization methodology. Each step in the process is represented with a unique color. The X-axis represents the elapsed time between the steps of the process; each circle represents the estimated capacity of the specific process in terms of work involved. Of course, in reality, the amount of work may vary from one case to another. Relatively speaking, the bigger the circle is, the more time consuming the task involved is for marketers.
Step 1: Investigation
This step has a clear and straightforward objective: to gain a high trust level with your web analytics data. Generally speaking, it is a two-part process:
- Data Collection – Auditing the technical implementation of your analytics tags is a crucial stage during which you are aiming at making sure the data is collected in a complete and effective way with minimum discrepancies and measurement gaps. In this step, you should be looking for implementation errors, missing data, untagged pages, etc.
- Data Filtering – Once you have completed the initial technical QA step, it is time to clean up the data, making it more readable and valuable for deep, upcoming analysis. There are many different ways of filtering out noise from your Google Analytics data. I would recommend you to start by consolidating duplications (such as duplicate URLs in the reports), filtering internal IP addresses, excluding bots and known spiders, implementing custom campaign parameters to your URLs, etc.
Suggested reading list:
– 10 Ways To Improve Google Analytics Data Accuracy, by Dave Fimek.
– Don’t Trust Your Google Analytics Data Just yet, Perform a Tag Audit, by Yaniv Navot (myself).
– Get Rid of Noise With These Fundamental 9 Google Analytics Filters, by Yaniv Navot (myself).
Step 2: Research
Now, when you trust the data and feel comfortable with its level of accuracy and organization, it is time to move forward and learn as much as possible about the business and its online activities:
- Business Objectives – The main questions you should be asking are why does the website exist and what are its objectives?
- Website Goals – The next part is to figure out what are the goals of the website are, which can help you achieve the desired business objectives. In other words: explore what the desirable outcomes of the business objectives are. For example: the objective of a retail site is to sell products, and, as a result, grow the business and increase revenue. So the goal of the website is to increase online sales.
- Website KPIs – Once goals are defined, it is time to figure out the specific metrics that are involved in the process of measuring the success or failure of the defined website goals. For example: if the website is a news publisher with goals to increase reader loyalty, possible KPIs would be: (1) Reducing bounce rate. (2) Increasing average pages per visit. (3) Increasing engagement within article pages. (4) Increasing the average time on site. (5) Increasing the percentage of returning visitors to the site.
- Data Analysis and Opportunity Discovery – At this point, you are already familiar with the business objective, goals and KPIs. In addition, you trust the data and are familiar with its structure and applied filtering. Now, it is time to dive deep and crunch the numbers, develop audience segments and look for pain points and opportunities to improve KPIs. Here are some basic examples of segmentation: (1) Device type: Set up audiences by device types – desktop and mobile. (2) Page category: Set up site variables on category pages to measure how well each individual category performs. (3) Traffic sources: Set up audiences by traffic source to measure how well the different marketing campaigns perform. (4) Customer type: Set up audiences by customer type to understand how different customers interact and impact the business.
Suggested reading list:
– Web Analytics 101 Definitions – Goals, Metrics, KPIs, Dimensions, Targets, by Avinash Kaushink.
– How to (Finally) Make Web Analytics Work for You, by Neil Patel.
– 10 Optimization Experts Share Their Favorite Google Analytics Reports, by Peep Laja.
Step 3: Optimization
Now, it would be a good time to take the opportunities you have discovered and put them into practice:
- Hypothesis Consolidation – The optimization process begins with consolidation of claims, or hypotheses, about potential changes to the site that may (hopefully) cause positive, desired outcomes. Do not confuse these statements with facts. These are not facts, but argued ideas that are based on data analysis and knowledge that you have gathered. They act as a starting point for the optimization process.
- Developing Optimization Plan – Based on your hypothesis, start building the optimization plan. In particular, explore what the specific changes are that you would like to implement and test by preparing the new copy, designing materials, and such.
- Implementation – Now, put all of the ideas into action and go live on the site. The time and effort that will be required from you in this step will vary depending on the accessibility and usability of your marketing optimization software. When implementing, remember to configure different content variations, as well as targeting conditions, and, if using website personalization software, content personalization triggers as well.
Suggested reading list:
– Unlocking Your Company’s Growth Engine with Conversion Rate Optimization, by Sean Ellis.
– “You are better off assuming that your visitors are lazy”, by Tim Ash.
– Conversion Optimization Prioritization, by Jim Sterne.
Step 4: Evaluation
Once enough data is gathered, it is time to analyze results and arrive at conclusions:
- Report Analysis – Explore the optimization reports, look for noticeable changes. Identify new audience segments, methodological pitfalls and find out where you succeeded. Do not be afraid of finding failed initiatives, they would only help you gain valuable insights about what is working better for your target audience.
- Optimization Adjustments – If necessary, modify your optimization initiatives with different targeting conditions and segments. Always double check yourself and preview the results to avoid any errors. Adjust and be patient. Depending on traffic, it may take a while before getting high-confidence, sustainable results.
Suggested reading list:
– Why Reaching and Protecting Statistical Significance is So Important in A/B Tests, by Idan Michaeli.
– How to Run a Successful Conversion Rate Optimisation Programme, by Dan Croxen-John.
Conversion optimization is not a linear process, but a circular one. It includes researching, A/B testing and analyzing. Once you are done with the final evaluation step, it is a good idea to go back to Step 3 and formulate new hypothesis and optimization ideas.
This post was an overview of our internal conversion optimization strategy. I hope that you will find the suggested key stages of the process useful and valuable to your own optimization efforts.