For those of you who are not as familiar with our Market Intelligence and Content Strategy Automation platform or just need a re-cap of the potential it has, here it is.
Our new product offering reinvents the way to do market and competitive analysis, keyword research and content strategy for SEO and content marketing purposes. This process can now be automated, saving SEO and content marketing teams hundreds of hours of work and creating unparalleled opportunities to achieve rapid SEO success.
Using Big Data, data science algorithms and graph databases we can automatically analyse the Web Graph for a brand and provide optimisation and content creation insights across millions of pages and keywords while solving the following use cases:
- Provide a definitive picture of Google’s algorithm at work in a market
- Perform a SWOT analysis of the market and benchmark a brand’s organic visibility against its top 100 competing sites
- Visualise Google’s clustering of topics and discover ‘000s of high traffic/revenue content optimisation and content creation opportunities
- Set winning short-term and long-term SEO and content marketing strategies that play to a brand’s competitive strengths
To put this into perspective, let’s look at a practical example scenario:
Let’s say an SEO team is pitching to a major brand like DIY.com (or maybe the in-house SEO team is reviewing its 2018 SEO and Content Marketing Strategy).
One of the first steps will be to evaluate and benchmark the brand’s current position against the competition before delving into where the best opportunities are for driving a large amount of the right kind of quality converting organic traffic to the site.
An initial analysis reveals that DIY.com has 6.4m pages on their website and ranks for at least 95,000 keywords on the first 3 pages of Google.co.uk. Not bad! But how big is the market potential and who are they competing against?
The problem with current SEO tools and traditional methods of competitive analysis is that they are overwhelmingly manual, painful and limited by what can be achieved by one or more humans in the time available. They are good for finding your current ranking keywords and what you have in common with your competitors, but they are not good in four main areas:
- Defining your entire market and relevant competing sites, and
- Discovering and prioritising the best content marketing opportunities
- Showing you who you compete with in each topical niche across the whole market
- Assessing competitive market concentration so you can see topical niches by ‘Authority’, e.g. ‘Monopoly Clusters’ where one brand is a clear authority and is winning; ‘Duopoly Clusters’ where two brands are head-to-head and ‘Fragmented Clusters’ where no single brand is an established authority and there’s a golden opportunity for you to become the authority brand.
A traditional SEO might use some of the better-known tools (i.e. Searchmetrics, SEMRush) to find some of DIY.com’s competitors, visibility data and download several spreadsheets full of keywords to sort.
Figure 1: SEMRush data for DIY.com
Figure 2: Searchmetrics data for DIY.com
Both of these tools have large keywords databases and are good at telling you how many keywords you have in common with your competitors and how many keywords your competitors rank for. What they fail to tell you is, which of your competitors’ ranking keywords are relevant to you. i.e. where your opportunity is!
We call this the “Venn Diagram Problem” – illustrated below.
Figure 3: The Venn Diagram Problem
So, what about the rest of DIY.com’s competitors (eBay, Homebase etc.?) – this is exactly where the Venn Diagram fails us, it is very difficult to compare 3 or more competitors.
As mentioned previously, even highly skilled SEO teams can often only scratch the surface of a market in the time they have available to do their research.
This is where big data and machine learning can dig much, much deeper and much more quickly.
We have solved this problem for not just your top 5 or 6 competitors but for your top 100 competing sites. It can define your market using only relevant keywords, making comparing search visibility more meaningful. Our platform can now automatically weigh and measure the keyword opportunities and find the best opportunities based on a combination of traffic potential and competitive strength for every niche in any market.
For DIY.com (Fig 4. & Fig 5.) we’ve found 92,996 ranking keywords (less than current tools with bigger databases) but we discovered a market of 808,676 keywords – that’s 715,680 opportunity keywords (267,680 more than the largest list from SEMrush)!
Figure 4: Authoritas data for DIY.com – Market Overview
Figure 5: Authoritas data – DIY.com’s Top 100 Competing Sites by Organic Traffic and Domain Strength
For Amazon.co.uk we find there are 70,130 keywords in common with DIY.com and 229,582 of its 2mn+ ranking keywords are relevant and competing in DIY.com’ market (Fig 6.)
Figure 6: Authoritas data – DIY.com’s Competing Keywords with Amazon
The market of 808,676 keywords is clustered and classified algorithmically into closely related niches of pages and keywords that occur in the SERPs. The below chart shows that clusters such as clothing, mattress, bathroom, and kids represent the biggest opportunities for traffic growth and DIY.com is relatively strong against the competitors in each niche.
Figure 7: Authoritas data – DIY.com’s Content Opportunity Analysis
Figure 8 and 9 below show the mattress cluster URLs and the top keywords to create content around.
Figure 8: Mattress Cluster
Figure 9: Top Keywords within the /beds URL
Every cluster is assessed and prioritised based on the potential traffic for all URLs and keywords in that cluster and the relative domain strength of the leading competitors in that niche.
It’s simple then to pick battles you can win with sites that are weaker than you whilst you build long-term authority. e.g. The table above shows the market is fairly fragmented (there is no single dominant player for the related keywords that this page ranks for and could rank for), Argos are performing well for some of the keywords with larger search volumes but they have competition from a number of other brands.
So hopefully you can see it’s automated. It’s very visual and easy to use and it produces clear recommendations in two areas:
- Optimise Existing Content – these are the pages that you are already ranking for with the greatest potential ROI
- New Content Suggestions – these are ‘virtual pages’ with related keywords that could be worth creating
Why would you do manual keyword or market research anymore when a machine can accomplish in hours what a team of well-trained expert SEOs using the best of current industry tools would take months to achieve?
Seems like a no-brainer…
If you want to see a real example of this data in action, have a look at our Priceminister.com case study. They managed to increase their organic visibility by 41% in 5 short weeks…
For eCommerce sites – there’s an added bonus. By integrating your Google Analytics or Adobe Analytics (Omniture) data we can help automate a revenue-focused SEO & content marketing strategy.
If this looks like something you could benefit from – don’t hesitate to get in touch. or fill in the form below for your free market snapshot. We’d be happy to run your site and take you through the data we find otherwise, just leave us a comment in the section below.
Lauren plans, manages and executes key marketing campaigns and initiatives that fuel the success of our company. She has a background in PPC campaign management but is focusing more on the technical side of SEO these days.