Melt Site Icons - Final Wide and deep SEO strategy through keyword research at scale

Keyword research at scale, SEO strategy, consultancy

  • Multilingual SEO strategy through our proprietary process for keyword research at scale
  • Dataset of 300,000 keywords
  • Unlocking the search potential of a huge product catalogue

Since its launch in 2010 has become one of the world’s best-known furniture and homeware retailers, and a leader in ecommerce. It operates internationally, with a huge range of furniture and homeware products available in eight territories, with annual revenue of more than £170 million. Unlocking the SEO potential of a huge catalogue

The team at knew their product catalogue had huge search potential, but they didn’t have the data to properly assess it, or the means to get the data on the scale needed.

As a leader in enterprise-scale ecommerce, the site was already ranking well for a lot of terms, but not as well for interchangeable product names or synonyms. The team came to us wanting help to inform their future content strategy to grow the site’s search presence.

Because of the sheer size of the site and the topics it could cover, the team needed us to provide keyword research at scale that covered their entire search footprint so that they could fully understand the ranking potential of the site, get a full view of their query spaces, and prioritise content based on both opportunity and seasonal peak.

The solution: Keyword research at scale

The team were on a tight deadline and needed a quick solution. The scale and variety of keywords and query spaces was huge – sells everything from sofas and desks to glassware, kitchen accessories and wall art. This makes for a huge variance in keywords, from directly product-related terms (2-seater sofas, leather sofas) to informational ones (how to reupholster a sofa).

Using our unique process for carrying out keyword research at scale, we combined various data sources (product lists, category pages, product filters) and combined informational modifiers (how, where), along with other inputs to define a seed keyword list that would provide keyword research for the full product set, as well as keyword research suitable for a blog at scale.

We also mined search volume over a 12-month period, which allowed us to find when search volume would peak, and recommended producing content at least a month prior to make sure it would be indexed and visible. This could also be timed with a paid campaign to maximise the peak of interest.

We stored all this data in a database and added a front-end application so the team at could take it away and arm their content team internally without needing expert knowledge of SQL and Python.

The outputs: A complete keyword universe

In two months we delivered a project of 300,000 keywords. This not only gave the team the basis for a complete content strategy and on-page optimisations; it also allowed us to analyse in both huge breadth and depth what queries the site has strong rankings for, and pointed us to where they could earn further rankings for existing products.

We have since moved onto a second phase in English, French and German.


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