How search works and tips on how to improve your rankings

We’ve had a few queries recently about how search works and in particular how Folksy is indexed by Google and how Folksy on-site search works and what improvements are planned. Whilst both are about items being found by potential buyers, they are two separate questions which I’ll tackle in turn and suggest ways you can help to improve your chances of being found in search results both externally and through Folksy.
Google Main Search

(image by moneyblognewz)

External Search

How does Google index items for sale on Folksy?


Google constantly crawls the web, revisiting pages already in its index, and crawling new pages if finds along the way.

In terms of a Folksy item page, that means Google will usually first find the existence of the item through a link on another page. Some of those links may be from other Folksy pages, for example:

  • Category pages
  • Shops pages
  • The homepage
  • Other item pages
  • Blog posts
  • etc.
Google may also find new item pages when places elsewhere on the web link to them, for example:
  • Other websites
  • Blog posts on other sites
  • Twitter
  • Some parts of Facebook
  • Google +
  • Pinterest
  • etc.
By and large, older content will perform better than newer content because:
  1. Google have had more time to find the content
  2. The older content has had more time to build up more links and mentions elsewhere, thus letting Google know that it is worth ranking highly
Usually this means new listings on Folksy will not appear as high up the search rankings, all things being equal, as older listings. This is one of the reasons that we designed in the “sold out” banner to an item page pointing to other items in that person’s shop, so you still get the search value of older items back to your shop on Folksy.

Improving your item’s chances of doing well in Google search

Bearing all of this in mind, how can you maximise your chances of your items being seen in search?


At Folksy we do a lot of work on search engine optimisation to make sure items perform well, for example by making sure fields that the search robots index are well described.Individual item performance will be down to how competitive that search term is, but 2 things you can do as a seller to improve your chances are:

  1. Make sure your items are described well.
  2. Make sure your items are linked to, so that Google can find them easily, and so that Google can understand where to rank them (based on the number and quality of links).
For example, post items on Twitter and Facebook and blogs if you can. In general the more links to an item from trusted sources, the more search ‘capital’ your item page has. Google has ways to manage link spammers, so don’t be over zealous, but do try and link to your work in relevant content.
Google now use Google + to help rank content on the web. This is effectively a way to build in “social” value to their rankings. So if you haven’t got a Google + account, we’d recommend you start one and then click the +1 button next to your shop or items in Google search.

There’s more info about that on Google’s “Search, plus Your World” info site.

Two notes about discrepancies and changes

We’ve had a couple of questions about discrepancies and changes recently too, so we thought we’d try to clear those up.

Question 1: Are view counts artificially enabled by Google spiders?

The discrepancy some people have noted between the view counts we used to provide on the admin screens and the metrics Google provide through Google Analytics which many people have integrated, is probably explained by the fact that the count we used to provide was probably influenced by ‘spiders’ or robots used by the search engines when indexing the web. Each time a spider / robot indexes a page it is generally counted as a page impression.

Whereas Google Analytics only measures views in a browser where javascript is enabled so is a more accurate measure of actual people looking at a web page.

Question 2: Has the re-design affected results from Google Image Search?

On researching this we found that it is explained by Google changing the way Google image search worked. They did this in mid-July last year in the UK, and this meant almost all image search traffic was re-categorised from being ‘referral’ traffic to being treated as search traffic. Here’s the graph showing where the ‘referral’ traffic appears to drop:


The search traffic wasn’t lost, it seems most of it was re-classified as organic search traffic.

Changes to the naming convention of images on Folksy (we append image file names with the type of image they are e.g. main etc) have had no bearing on how they are indexed or returned in results. Interestingly, people coming to Folksy via image search convert into sales far less than ‘normal’ web search (which is explained by most people looking for an image to use rather than looking to ‘shop’).

There’s more info on the Google Images change over on Search Engine Roundtable


Internal Search

How does internal search work on Folksy?

For items, the current search technology we use creates a searchable string by joining together a number of different fields such as title, item description, category name. We then have an algorithm that gives these fields different “weights” which equates to a higher score when the search string is queried. If someone searches using multiple words then only those items that match all of those words are returned, so if you search for “pink floral skirt“, only items matching all of those words will be returned (33 as of now). These words could appear separately anywhere in the listing.

If you use speech marks to define a term, for example “pink cushion” you will return all items that have that exact term (in this instance 8). If you search for “pink” and “cushion” without the speech marks it returns many more (799 items as of now) as search is returning all mentions of cushion and pink. Ideally we would like the results to return all those results with the term “pink cushion” first, this is called n-grams for approximate matching and is something we will be working on in the next phase of development on search (see below).

Shop search works in a similar way to item search, using the fields shop title and also shop description and username where we append an appropriate weight to the different fields in the string we create.

The advice on how to maximise the likelihood of your items being seen in search is to describe your item really well, both in the title and description and inspiration fields but also using facets such as colour. The fuller and more accurate the description, the better.

Next stage developments

Search is quite a complex area and one which is constantly being looked at by any service with a large amount of content.  There are three areas of search we are enhancing:

  1. Relevancy – creating a more advanced algorithm to return more relevant results (including n-gramming – basically term matching – and stemming – a process for reducing words to their root form e.g. plural to singular etc.)
  2. Filtering – providing functionality to allow people to filter search results by price and also by category
  3. UI – improving the search field to incorporate auto-suggest based on popular search terms, best suggestions in the search results as well as grid view and list view

This work falls into our workstack after Guest Login and Checkout improvements have been delivered. The estimated start date for the search work is March 1st.



  • January 22, 2012


    Very useful info…..thanks :-)

  • January 22, 2012


    There appears to be a contradiction in your explanation of how the internal search works –

    “If someone searches using multiple words then only those items that match all of those words are returned, so if you search for “pink floral skirt“, only items matching all of those words will be returned (33 as of now). These words could appear separately anywhere in the listing.”

    But “If you search for “pink” and “cushion” without the speech marks it returns many more (799 items as of now) as search is returning all mentions of cushion and pink.”

    I don’t understand what the difference is between ‘pink floral skirt’ and ‘pink cushion’ in these examples. Why does the first example only bring back listings where all 3 words are mentioned, and the second bring back listings where either ‘pink’ or ‘cushion’ is mentioned?

    • January 22, 2012


      Apologies for not being clearer. The distinction is between words and terms. If you search using words without speech marks they are searched for as singular entities, whereas if you use speech marks to define a term, for example “pink cushions” then the term (i.e the words exactly as they appear, in that order, together) will be searched for. n-gramming, which we will be working on in due course, searches for terms when you don’t use speech marks and will construct an algorithm for relevancy based on some the words being searched in the order you write them in the search field, so the search technology will, in future, look for the singular words ‘pink’, ‘floral’ and ‘skirt’ when you use these terms but will also look for the bigram and trigram “pink floral” and “floral skirt” and “pink floral skirt” too. It’s not too simple to explain in lay terms. Wikipedia has a page on n-grams if you care to dig a bit deeper: