Online business owners face an increasingly aggressive online marketplace, with increasingly competitive keywords to rank for.   

E-Commerce SEO's have the daunting task of identifying and analyzing every single possible keyword, but more importantly needing to understand the user intent and persona behind the search query, and at what stage that search fits into the user journey.  Only then can they begin to optimise their content accordingly.

Location Based Targeting Thailand

Category Keyword Research

User Intent Research

Classify the Data

Identify User Persona's


Phase 1

Category based Keyword Research

First we need to find out the top organic competitors for your prodcuts, either globally if you're selling worldwide, or your local market such as, .de, etc. For the purposes of this article, we will be using, Thai e-commerce competitors and branded websites, and we will be looking at the home appliance market as an example.

We begin by looking at the key products in the home appliance niche such as Fridges, Freezers, Cookers, and small kitchen appliances in, and what type of Thai language search queries are being used to find these products online.

Very quickly we see that the SERP's are not just filled with manufacturing and brand websites, but leading e-commerce sites here like Lazada, Shoppee, Robinsons, BigC and Tesco Lotus are the sites that tend to perform best in the SERP’s.

Phase 1b

After determining competitors, we needed to extract the keywords from each website for desired categories and combine them in different Excel sheets for segmentation

Product Keywords

Desired categories are the main and sub-categories of the leading and top ranking e-commerce sites.

BigC Categories and Subcategories

For keyword extraction, we always recommend using Ahrefs because they have the most comprehensive keyword pool and we don't want to miss any important keywords.


Phase 1c

Now we need to do some data wrangling. Once we have all this data, how do we sort it and make use of it? As you can imagine there are hundreds, if not thousands of unnecessary keywords after the extraction process. You'll want to remove all branded keywords except your own or your clients as these are of no use for organic SEO, however they can still come in useful if you plan on running PPC and target branded search queries so keep these to one side.

Phase 2

User Intent Research

As a result of Phase 1, we now have an excel file that covers all Category and Sub-category sased Keyword Research.

We then needed to find all review, rating and comparing web sites which are performing best in SERP's, so we can begin to segment users in the Discovery stage from users who are looking to buy a Fridge or Washing Machine but don't know what brand to users who know exactly what they want and which brand.

Product Review Segmentation

Phase 3

Classifying the Data

Here is the toughest and most important step of the whole research. Every phase in this step requires deep focus, manual work and intelligent reasoning in order to differentiate each search query and match them to their corresponding User Journey stage

Firstly we need to begin by understanding the filters we're applying.

Below you can see our Customer Journey segmentation which contains the “Filters” sheet. These are the filters we use for classifying the entire data, user and persona. For example, if a keyword contains “cheap” it should be classified as 2:

Customer Journey Filter


We had to examine the data and truly understand the user intention behind every single search query, and then segment these into 10 persona’s before starting to next step


Phase 3b

Because of the nature of the journey, filtering should follow an order and we use:

 6 – 5 – 4 – 3 – 2 – 1 – 7 – 8 – 9 – 10

We started with the filters belonging to group 6 first because these are users who know what they want, which brand and are looking to buy. We continue with group 5 and go on with the order above. So, if any keyword has a filter word both from group 6 and 5, that keyword will belong to group 6 because group 6 comes before group 5. If we encountered a keyword that could not be categorized, we marked it as group 0

Customer Journey Filters

Phase 3c

Category name vs. Feature KW's


All of the filters imply a word in a keyword. For example, the “what is” filter in group 3 will filter all the keywords contains “what is”. But this rule is not valid for two filters: Category name in group 1 and feature KWs in group 3.

Category name filter implies keywords with category name on it. For example, “washing machine”. But don’t forget “buy washing machine” is not a category name filtered keyword because it has “buy” in it and group 6 comes before group 1.

Feature KWs implies a product feature like color, size etc. For example, “cordless vacuum cleaner” is a feature keyword and belongs to group 1.

Classifying the keywords between group 1 (category name) and group 3 (feature KWs) was one of the biggest challenges through the whole research. Because of this, we finished all other filters first and then started with category name and feature filters. We have also created a rule to make things easier. According to this rule if a keyword takes part as a category or sub-category on, it should be classified as group 1. If it is not, then it belongs to group 3. As an example, let’s try to classify “integrated washing machine”. Here is the screenshot of Curry’s laundry category:

Category Keywords

We see that “integrated washing machine” is a sub-category. So, this keyword should belong to group 1.



Phase 4



As you will see in the image below, there are also some personas inside the groups. So, keywords should be classified by personas, too. For example, if a keyword contains “review” it should be classified as 3a not just as 3.

Persona Segmentation

Phase 5


As a result, you should have 5 separate pieces of segmented data. It should contain:

  •      Keyword & Search Volumes
  •      Main category & Sub-Category
  •      User Journey/Personas
  •      All filters/intent 
  •      Category vs Features

Next Steps...


Now that you have this awesome array of data, the next steps should be looking at Technical SEO for your existing pages, and creating news ones if they don't yet exist, in order to rank for the different search queries and stages of a user's journey. For example, a highly detailed, in-depth FAQ pages for every category in order to target Stage 8 and 9 Users.

An FAQ is always a great idea, Google loves Q&A's, and it's a great way of bringing additional traffic and assisting users with tips, guides and problems. Another good idea would be to create a large, in-depth Product Glossary with unique definitions and descriptions for every possible feature and mechanism of the product you sell, E.g Definition of Ergonomic Fridge, all internally linking back to the relevant category or product page.

Building on the FAQ/Q&A idea, another great strategy is implementing Schema markup and creating Rich Snippets for each of the questions which have the potential to rank Position 0 as a Featured Snippet for Group 7, 8 and 9 user search queries.

We also recommend implementing Aggregate Rating/Reviews on all product pages so the sub-pages that rank in SERPS stand out more with those lovely shiny 5 Gold Stars!

To leverage the Group 5 user who is looking for deals/promotions and the search queries that include this, a separate dedicated page could be built specifically for promotions and offers in your industry niche. For price search queries we also recommend implementing schema markup for product, description, price, review etc again giving you the opportunity to rank Position 0 as a Snippet.

And last but not least, Content Marketing and Digital PR as a means of acquiring authoritative links from High Domain Authority publications and media sources is essential if you're is going to rank at the top of SERP's to capture the Group 6 user.


By Nick Dudley-Jones

Co-Founder of GO PR