Since joining HubSpot I've been shifting some of my focus more heavily towards conversion optimization. I've had a wealth of data to play with and have been able to work with some seriously intelligent people.
One of the challenges with any kind of website optimization project, be it search engine optimization, conversion optimization or UX optimization, is being able to identify areas in which you have an opportunity to make a big impact.
If you're going to be spending valuable time on optimization projects, you'll want to ensure that you're getting the best possible return on your time. I'm going to walk you through my process for identifying a range of different opportunities, introduce you to the framework that we use within the Optimization team at HubSpot for prioritizing projects, and then show how you can go about setting goals for these projects.
First thing's first...
Before you even begin trying to identify optimization opportunities within your website you'll need to have some necessary tools in place. The first tool you'll need is an analytics package, for example, Google Analytics, Adobe Analytics, Mixpanel, etc. Along with this, you'll want to have some kind of testing tool in place, for example, Optimizely, Unbounce, KISSmetrics, etc.
Other tools that you may want to consider would be behavioral testing tools like Hotjar, UserTesting.com or Crazy Egg (I use all three of these tools). There may be other tools that you want to invest in once you've developed some initial test hypotheses, but these should be good enough for now.
Website Optimization Opportunities
All of your optimization projects should be goal-driven.
If you haven't already, start by outlining your major business goals. For example:
- Increase top-of-the-funnel leads by x.
- Increase marketing/sales qualified leads by x.
- Increase online sales by x.
- Grow brand awareness.
- Increase organic search traffic to your website by x.
- Increase app installs by x.
- Reduce customer churn by x.
The above are just a few examples of business goals, but these will vary largely depending on your type of business and individual priorities. These goals are always my starting point when looking at identifying new optimization opportunities.
A good starting point is to list all of the pages within your website that have an impact on achieving each goal, ranked in order of performance.
Let's take 'increasing marketing/sales qualified leads' as an example. In order to assign someone as a marketing qualified lead they'll need to have performed a specific action or set of actions on your website. For example:
- Asked for further details/specifications on your product(s)/service(s).
- Got in touch directly with your sales team via a web form.
- Requested a free trial or sample of your product(s)/service(s).
- Added products to cart but abandoned the checkout process.
If I were looking at the "requested a free trial of your product(s)/service(s)" action, then I'd break down each page that a user would be engaging with before they performed this action. This is likely to be the 'free trial' information page (or set of pages), the main pages that users enter the website via when they convert, and the page(s) with the web form to request a trial.
To get this information you'll need to do some analysis within your analytics tool, which brings me to the first stage of the opportunity identification process...
Going through the analytics of a website can sometimes be a bit of a minefield, especially if you're not that familiar with analytics software.
Before you just start mindlessly browsing through Google Analytics, you'll want to go back to your list of business goals, as the best thing to do is hone in your analysis to something specific. If you don't do this you risk wasting a hell of a lot of time going through data where you're unlikely to find anything useful.
When I'm looking for an opportunity to achieve a specific goal, I'll take the following steps:
- Identify the goal that you're trying to achieve.
- Outline all of the pages within your website that can influence that goal.
- Rank the pages based on their importance within the process.
- Gather data for each of the pages.
- Highlight underperforming pages within the process.
- Uncover the major contributing reasons as to why these pages are underperforming.
- Outline some potential changes that could be made.
- PIE score the recommended changes (I'll get to this soon).
- Prioritize and execute all projects that meet your specific PIE criteria.
Before I go into giving some examples, let me just explain the PIE framework that we use in the Optimization team at HubSpot to prioritize our optimization projects:
The PIE Framework
Don't underestimate the importance of having a solid framework to work within when you're planning out optimization projects. The PIE framework is used specifically to prioritize the projects that you're suggesting and it's broken down into three ranking criteria, scored on a 10-point scale:
Potential: this part is all about the potential improvement towards achieving your goal. If a specific project is highly likely to make a big impact towards your goal then it's likely to rank closer to 10, whereas projects with very little potential to see improvements will sit at the other end of the scale.
Importance: this score focuses on how important the traffic to these pages is. An example of a high-importance page could be your homepage due to the fact that it probably brings through the majority of your high-conversion traffic. If you find an underperforming page but it doesn't really drive much traffic of value, it's likely to rank far lower.
Ease: the ease score is an important factor here because it looks specifically at how difficult it could be to make changes to a page (or set of pages). This could be due to technical reasons; for example, your CMS doesn't let you edit certain sections of a page that you want to edit. Another reason could be that a lot of stakeholders have to be consulted before changes are made to a certain page (product pages, for example), so it could end up taking a long time to get sign-off.
Each of these three factors should receive a score out of ten, and then you will take an average of the three scores to calculate the final PIE score. Here's an example of a PIE-scored project:
Goal: increase daily qualified email signups by 30% over 6 months.
Project: redesign the ebook landing page template to include unique summary content and align to specific keywords in order to rank better in the search engines.
PIE Score: 8.33 (P:7 / I:10 / E:8).
In the example above I ranked the project a 7 out of 10 for potential based on the possible increase in traffic from the search engines that can impact my goal.
The importance score of 10 was given because these pages are probably the most important for generating new email signups across the site. They're usually the place where all my signup forms are placed and have the highest conversion of any other page on the site.
Finally, the ease score of 8 was given because there is a relatively small amount of development involved, but a fair amount of extra content creation needed. It's not overly difficult but the content creation alone would prevent this from being a 10.
This framework doesn't have to be restricted to optimization projects; you could use this for prioritizing any kind of project or task that you're looking to work on. More than anything, it helps you prioritze much more efficiently.
Case Study: Historical Optimization Project
To help you understand the whole process of identifying a new optimization opportunity, I'll walk you through an example of a project that Pam Vaughan worked on last year that saw some incredible results.
The goal was to increase the number of monthly leads being generated by our blog content. The first step after selecting the goal was to identify the pages on the website that have an impact on achieving it. To do this, data was pulled on any page that could result in a new lead being generated after a blog article pageview as well as all of the blog content itself.
A simple way to look at the different pages that form part of the conversion funnel is to look through the User Flow report within Google Analytics.
Once the pages have been identified, it's time to grab data on them that can be used to both find opportunities for optimization and to prioritize using the PIE framework. Here are the data points that were pulled:
- Total traffic to each of the pages.
- Breakdown of traffic sources to the pages.
- Lead conversion rate for each page.
- The content upgrade that was being used to generate leads from each blog post.
Using this data, Pam was able to quickly identify which posts had both a low conversion rate and high traffic volume. These pages scored very high on the 'potential' metric. Alongside this, Pam pulled through blog posts with both a very high conversion rate and volume of traffic.
By analyzing the top performing content (high conversion rate/high traffic), Pam discovered something very interesting:
Blog posts that had a CTA that included the most searched-for keyword to get through to the blog post were seeing above-average conversions.
To explain this a bit better, let's take this scenario:
- A user comes through to an article on the HubSpot blog titled, "How to write a press release".
- The keyword that they searched for in the search engines to find the article was, "press release template".
- Within the first few paragraphs of the article there is a CTA with the words, "Download our free press release template".
- The CTA links through to a relevant ebook that can be downloaded in exchange for subscribing, and consequently becoming a lead.
This is an actual example from the project that resulted in the following conversion rate increase:
Pretty impressive, right?
To scale this project up, Pam prioritized the pages on the blog with the lowest conversions rate to traffic volume ratio and began a small test. The keyword data that was used to find what people were searching for to get to the blog posts was taken from within HubSpot, but this data can be sourced from with Search Console too - here's how:
- Log in to the Search Console profile for your website.
- Navigate to the Search Traffic>Search Analytics report.
- Click the radio button to filter by Pages instead of Queries.
- Click on one of the URLs in the list.
- Now select the radio button to filter by Queries instead of Pages.
Here's an example of the keywords driving traffic through to one of the articles on my blog:
This method will only let you do this on a URL by URL basis (i.e. you can't do it for a bulk list of URLs all at once). If you're only analysing a small number of pages then it will be fine, but if you need to scale this up then I'd recommend using URL Profiler (I also put together a full tutorial on using URL Profiler), an awesome tool that pulls this data directly from your Search Console account in bulk.
Once all the data is there, the pages can be PIE scored and the project can begin. This is actually a project that we continue to do on an on-going basis to boost conversion rates from our blog content, and it's having a huge impact. I'd highly recommend reading Pam's full case study here.
Website Optimization Ideas
Using the process that I've outlined above, you'll be able to identify, prioritize and execute optimization projects. To get you started, here are a few ideas for areas of your website to inspect as well as things you may be able to do to improve them.
1. Reoptimizing Existing Content for SEO
Goal: growing organic traffic to your website.
Overview: when most people look for ways to drive more traffic to their website from the search engines, they immediately start thinking about new content they can produce. But before you think about building anything new, start looking through what you've already got. Identify pages on your website that have low organic traffic but a good number of links pointing to them, then reoptimize the on-page content towards the keywords they're starting to rank for.
Process: start by gathering the following pieces of data on each of the URLs of your site:
- Monthly organic traffic volume.
- Number of linking root domains.
- Monthly impressions in the search engines.
- Top 3 keywords currently bringing through traffic currently (even if it's small numbers).
- Total word count of page content.
- The page title and H1 content.
You can gather all of this data by using a tool like URL Profiler and linking your Google Analytics, Search Console and Ahrefs/Majestic/Moz account to it.
Sort your dataset by pages with the highest number of linking root domains. From here, highlight any pages that have a below-average level of monthly organic traffic (you could do this with conditional formatting in Excel). You should immediately have some visible candidates for improvement at this point (as you can see in the screenshot above).
Once you've found some URLs that could be reoptimized, you'll want to do some quick keyword research for each of them to see which keywords could be focused on to grow traffic.
One of the first things I do is use Ahref's Position Explorer tool to show me any keywords that a URL is currently ranking for - I tend to look for keywords on page 2 or 3 that could be bumped up to page one with some on-page tweaks. You can also use SEMrush and Search Console data for this.
If I haven't found any low-hanging fruit within Ahrefs Position Explorer or Search Console then I'll do some extra keyword research to find some terms that are not only relevant to the content, but could also bring in some good traffic numbers.
Once I have my keywords ready, I'll do a quick audit to see if they currently appear in the page title, the H1 of the page and within the body content. I do this within Excel using a SEARCH function.
If it makes sense, I'll add the new keyword into the page title and the H1 (or H2), and then add some extra content to the page to build a little more relevance to the term. If there's the opportunity to create a few more internal links within the website that have keyword-focused anchor text, then I'll do that too.
Scaling this up is pretty easy and even someone with very basic SEO knowledge can follow this process.
2. Evaluate the Effectiveness of Your Lead Capture Funnel
Goal: increase the number of leads generated from your website.
Overview: when you're trying to grow leads to your website, don't start by saying, "let's try using a different color on our CTAs" or "let's try a new pop-up". Instead, you should be looking at your whole lead funnel to evaluate how effective it is for driving leads from your target buyer persona instead of just going down the path of trial and error with a bunch of different tactics.
Process: map out the individual conversion paths that each of your target buyer personas can take to become a lead via your website. This can be very basic or very complex depending on both how complicated your product/service is and how your process for generating leads has been set up.
I'll use the example of my blog to show my most common lead conversion path:
- The visitor lands on one of my blog posts via organic search.
- The visitor clicks on one of the CTAs within the blog content and is sent to a targeted landing page.
- The visitor enters their contact details and subscribes to my mailing list in exchange for the download of an offer.
- The lead is added to an email workflow where they are periodically sent information of interest to them.
The main pages involved here are the entry pages (the blog content) and the landing pages. The email workflows are more focused on nurturing, so that would be examined after the lead capture stage and a project that would have to be looked at in isolation.
From here I'd pull the following data:
- Organic traffic stats across all blog posts.
- First-touch conversion data for each blog post (if you have this).
- Click-through rate (CTR) to offers landing pages within each blog post.
- Conversion rate for each of my offers landing pages after a user has visited them from a blog post.
- Conversion rate for each of my offers landing pages from a direct visit.
Using the above data I'd be able to find out which types of content on the blog are generating the most leads, which blog posts have a low CTR to landing pages and which landing pages have a poor conversion rate.
By splitting the conversion rate data for the landing pages based on visitors that have gone straight to that page (perhaps via organic or paid search) vs visitors that have come from a blog post, I can determine whether the landing page is the issue or whether it's more of a contextual issue, i.e. the offer being promoted within the blog post isn't well suited.
This information will help you understand the following:
- Whether specific offers are well suited to each blog post.
- Whether you need to reconsider the design of your landing pages.
- Whether you need to address your CTA strategy within blog posts.
- If you have holes within your lead funnel that are causing inefficiencies.
- If there are some high-value pages that could have a stronger CTA to drive more leads.
To go even deeper you could run user testing analysis to monitor the behavior that your website visitors are displaying within your landing pages or within your blog content to help shape the user journey across your site.
From here you can then make educated decisions around the tactics you will implement to improve performance.
3. Identifying Page Speed Issue
Goal: increase engagement on website content.
Overview: page load times have to be one of the most overlooked aspects of optimization across any websites. In e-commerce in particular, the difference of a couple of seconds can be the difference in making a sale or not. Just ask Amazon - they found that a page load slowdown of just 1 second could cost them as much as $1.6 billion in yearly revenue.
Process: a pretty incredible and fairly difficult to find metric within Google Analytics is the Document Interactive Time report. This metric shows the amount of time, in seconds, that it takes for a web page to load enough that a user can start interacting with it. This is very different to Page Load Time, which looks at the total time it takes to load all the elements on a page.
A lot of people misinterpret the page load time metric, thinking that this is how long it takes before a user can see any content at all.
Open up Google Analytics and then go to Behavior > Site Speed > Page Timings. Once you're there, click on the link that says DOM Timings, just above the graph.
Now, in the far-right column in the table you'll be able to select Avg. Document Interactive Time (sec). Simply by comparing this to Page Views will enable you to see high traffic pages on your site that are loading really slowly and may be having a negative impact on engagement, conversion and even SEO.
I'd mark these pages for speed optimization and then PIE score out each URL to determine which are of the biggest priority to fix.
Hopefully this has helped to structure your thinking towards ways in which you can squeeze more out of what you've currently got on your website. The one piece of advice that I'd like you to take away is to remain data driven within all of your tests, but to drill down and focus your analysis around specific goals. If you don't, you'll spend all your time analyzing and none of your time actually getting things done (trust me, I speak from experience!).