SEO
Study · 2026-08-20

Technical E-commerce SEO study of Georgian online shops

We checked 1,468 pages across 38 websites against 13 criteria. The market's median technical health score was 74.1.

The results show what a client should check on their own website. Product information markup and the management of category pages often need to be reviewed.

What Georgian online shops are missing

We checked 1,468 pages across 38 Georgian online shops. Below are the elements that Google uses to understand product and catalog pages and that most websites have not yet set up in full.

  • Product Schema

    Product schema is special structured data that helps Google better understand information about a product. Through it we can supply the search engine with details such as the product's name, price, availability, brand, rating, photo and other information. Correctly added Product schema increases the chance that the product will appear more informatively in Google's search results, for example with a price, stock status or rating.

  • Canonical Tag

    The canonical tag is an HTML tag that tells Google which URL should be considered the main, primary version of a page. It is used in particular when identical or very similar content is available at several different URLs. The canonical tag helps Google process duplicate pages correctly and shows which URL it should consolidate the SEO signals onto.

  • Title

    The title is the page heading that Google shows in search results. Out of 37 websites only 13 have a unique title on every page, while in the rest repeated titles make it harder for Google to tell the pages apart.

  • Breadcrumb

    A breadcrumb is a path shown at the top of a page that indicates how the customer gets from the main category to a specific product. Out of 38 websites only 17 have a breadcrumb, while in the rest it is harder for Google to understand the hierarchy of the site's categories and pages.

  • Alt text

    Alt text is a short description of an image that helps Google understand what is shown in the photo. Out of 33 websites only 12 have alt text filled in on product images, while the rest make less use of the opportunity to get additional traffic from Google Images.

  • The catalog's second page

    The second and subsequent pages of a catalog should point with a canonical tag to their own URL and not to the first page. Out of 22 websites only 1 has this set up correctly, while in the rest it can become harder for Google to discover and index the pages and products deeper in the catalog.

The market in figures

38
websites checked
1 468
pages checked
13
technical criteria
74.1
median technical health score, out of 100
66.7%
websites without Product schema
42.1%
websites with a canonical defect
59 689
modelled lost visits per month
₾1 309 836
modelled loss per year

What we checked and how many had it right

27 core SEO elements were checked across 38 websites. A rating of "had it right" means that the website met the relevant criterion. The threshold for each criterion is given in the table next to the element checked.

CheckHad it rightThreshold
Out-of-stock product in the index
Do pages of out-of-stock products stay in the index or are they controlled
0.0%
Small sample
≤ 30%
The pagination canonical is correct
The canonical of page 2 points to itself (and not to the first page)
4.5%
Yes
Price in the schema
Is the price marked up in the structured data
24.2%
≥ 80%
Product schema on the product page
Do product pages have Product schema (the markup needed to show price and stock in search)
27.3%
≥ 80%
Stock status in the schema
Is stock availability marked up in the structured data
27.3%
≥ 80%
Breadcrumb schema
Is the page hierarchy marked up (home → category → product)
28.9%
≥ 80%
Duplicate titles
How many websites have no repeated titles (the page title shown in the search result)
35.1%
≤ 5%
Image alt text
Do product images have a text description (alt)
36.4%
≤ 20%
The canonical points to itself
Does the canonical point to its own page or to another one
44.7%
≥ 90%
Breadcrumb navigation
Do the pages have visible hierarchical navigation
44.7%
≥ 80%
Title length on the product
Does the title fit in the search result without being cut off
45.5%
≥ 80%
Unique H1 on the category page
Is the main heading of the categories unique or repeated
46.9%
≥ 95%
meta description on the product
Do product pages have a description displayed in the search result
51.5%
≥ 90%
Canonical on every page
Do the pages have a canonical - an indication of which version of the URL is the main one
52.6%
≥ 95%
The sitemap is declared in robots.txt
Can the search engine find the page map from robots.txt
57.9%
Yes
Open Graph image
Do the pages have an image for sharing on social networks
60.5%
≥ 80%
meta description on the category
Do category pages have a description displayed in the search result
68.8%
≥ 90%
Broken links
How many websites keep their share of broken links within the norm
76.3%
≤ 2%
Open Graph title
Do the pages have a title for sharing on social networks
76.3%
≥ 80%
sitemap.xml exists
Does the website have a map of its pages for the search engine
78.9%
Yes
Core Web Vitals on mobile
Loading speed and stability on a mobile phone
86.5%
≥ 75%
Page 2 of the catalogue works
Does page 2 of the category open with a 200 status
89.5%
Yes
lang attribute
Is the page language declared in the HTML
89.5%
≥ 95%
Category text
Do category pages have searchable text beyond the product list
90.6%
≥ 50%
Filters do not create excess URLs
When a shopper selects colour, size and price, the website often creates a new URL. Such URLs run into the thousands and Google crawls them instead of the real pages. This check looks at whether the website controls these URLs
97.4%
Low risk
viewport for mobile
Is the mobile screen parameter declared
97.4%
≥ 95%
charset is declared
Is the character encoding declared (so that Georgian letters display correctly)
100.0%
≥ 95%

13 criteria

Category pages

89.3
Market median score

A category page brings together related products under a single topic or product group. An accurate and informative description helps Google better understand the page's topic and supports higher visibility for the relevant search queries. 68.8% of websites had the category description right.

Product pages

71.1
Market median score

A product page combines detailed information about a specific product with the option to buy it. A complete description helps the customer make a choice and increases the page's visibility for more specific search queries. 51.5% of websites had the product description right.

Duplicate titles

84.7
Market median score

The title is the page heading that Google often shows in search results. Identical titles can turn several pages into competitors with one another for the same search query. 35.1% of websites stayed within the acceptable threshold for duplicate titles.

Filters and their URLs

100
Market median score

Product filtering helps the customer sort a product list by various parameters. Managing it correctly spares Google from processing excessive and near-identical URLs. 97.4% of websites had filter control right.

Canonical

90.8
Market median score

The canonical is an indication that helps Google determine which URL is the main version of a page. Using it correctly reduces the risk of SEO signals being split between duplicate pages. 52.6% of websites had the canonical right on every page.

Structured data

18.3
Market median score

Product schema is structured data that supplies Google with information about a product, including price and availability. This data can appear as extra detail in search results and attract the customer's attention. 27.3% of websites had Product schema right.

Out-of-stock products

65
Market median score

An out-of-stock product page shows a product that is temporarily or permanently no longer available. Managing such pages incorrectly can lead the customer to an unavailable product and force Google to process unnecessary URLs. We checked only 3 websites against this criterion and none of them met the requirement.

Pagination

50
Market median score

Pagination means distributing the products in a catalog across several pages. Setting it up correctly helps Google treat the second and subsequent pages as independent pages. 4.5% of websites had the canonical on the second page right.

Page discovery by Google

92
Market median score

Page discovery means whether Google finds all of a website's important pages. sitemap.xml and robots.txt help it do so, while broken links get in the way. 78.9% of websites had sitemap.xml right.

Core Web Vitals

100
Market median score

Core Web Vitals assess a page's loading speed, interactivity and visual stability on mobile devices. Good metrics improve the user experience and reduce the risk of the page being abandoned early. 86.5% of websites met the defined threshold.

Category content

66.8
Market median score

Category text is a description that, alongside the product list, explains the topic on the category page. It helps Google understand the page's content and increases visibility for broad search queries. 90.6% of websites had the category text right.

Internal links

69.6
Market median score

Internal links connect a website's various pages with one another. A correct structure makes it easier for the customer to move around the catalog, and it helps Google discover pages and understand the site's hierarchy. 44.7% of websites had hierarchical navigation right.

Language and the page's technical foundations

86.8
Market median score

The HTML language attribute tells Google what language a page's content is written in. Specifying it correctly helps the search engine identify the page's language accurately. 89.5% of websites had the language attribute right.

Where the money is lost

At the first stage, the model calculates the potential loss of organic traffic. To do this, organic traffic is multiplied by a loss factor that shows what share of traffic may be lost because of a particular SEO defect. A maximum loss threshold is defined for each defect.

At the second stage, the lost visits are converted into orders using the segment's average conversion rate. Conversion shows what share of visits ends in an order. At the third stage, the resulting number of orders is multiplied by the segment's average order value, that is, the average value of a single order.

The result is a modelled estimate and not an actual financial loss. The real impact may differ and depends on price, stock, competition, customer behaviour and other factors.

1. Lost visits

The potential loss of organic traffic is calculated by multiplying traffic by the loss factor. The factor is the sum of the values defined for the various SEO defects, although each defect has its own maximum threshold. For example, the impact of Core Web Vitals is assessed at a maximum of 12%, while for Product schema the maximum threshold is 5%.

2. Lost orders

The number of lost visits is multiplied by the relevant segment's conversion rate, which yields the number of orders likely lost. The model uses a conversion rate of 1.5% for supermarkets and 0.8% for the electronics segment.

3. Financial loss

The number of lost orders is multiplied by the relevant segment's average order value, which yields the estimated financial loss. The model uses an average order value of ₾70 for supermarkets and ₾450 for the electronics segment.

Where the loss factor comes from

The loss factor is not a single number; it is calculated separately for each website from that website's own assessment scores. Each criterion has two predefined parameters: a threshold above which the loss counts as zero, and a maximum share that this defect cannot exceed. If a website's score is above the threshold, no loss is charged for that criterion. If the score is below the threshold, the loss grows proportionally: the further the score is from the threshold, the closer it moves to the maximum share. The shares of all criteria are then summed, and the total has an overall upper limit - for a single website the model never counts a loss of more than 35% of organic traffic. The thresholds and maximum shares are expert assumptions and not a measured quantity, which is why they are stated openly below.

DefectScore thresholdMaximum upper limit
Core Web Vitals4512%
Page discovery by Google559%
Duplicate titles608%
Category content407%
Canonical556%
Product pages556%
Structured data505%
Pagination505%
Filters and their URLs455%
Internal links504%
Language and the page's technical foundations503%
Total upper limit for a single website35%
Example: a mid-sized electronics shop

If a mid-sized electronics shop has 55,383 organic visits per month and the model applies a 2.9% loss factor, the estimated loss is roughly 1,606 visits per month. At a conversion rate of 0.8%, that amounts to about 13 lost orders. With an average order value of ₾450, the estimated financial loss comes to ₾5,850 per month and ₾70,200 per year.

  • Organic traffic: 55 383 visits per month
  • Loss factor: 2,9%
  • Lost visits: 1 628 per month
  • Conversion 0,8% → 13 orders
  • Average order value ₾450 → ₾5 850 per month, ₾70 200 per year
DefectWebsites affectedVisits per month₾ per month
Structured data
Without structured data the price/rating is not visible in search - CTR drops
2729 808₾56 022
Canonical
Without a canonical the signal is scattered among duplicates
129 906₾17 581
Pagination
A pagination problem - the depth of the catalogue does not make it into the index
135 229₾11 528
Internal links
Weak internal links - link weight does not reach the deep pages
124 491₾8 857
Product pages
Weak product pages - long-tail traffic is lost
64 429₾7 273
Duplicate titles
Duplicate title/H1 - the pages compete with each other for the same query
73 465₾4 253
Category content
Without category text the page cannot rank for broad queries
41 766₾2 654
Indexation
A sitemap and indexation problem - some of the pages do not make it into search
1506₾668
Core Web Vitals
A slow mobile experience - the user leaves before the page loads
186₾310

These figures reflect a modelled estimate and not an actual financial loss. The organic traffic data is taken from Ahrefs, while the conversion and average order value figures are assumptions applied at segment level. The metrics used and their values are given above.

Segments

The data for 7 segments shows each segment's median technical health score, conversion rate and average order value. This comparison lets the client assess their own metrics in the context of the relevant segment. The segment's conversion and average order value data is also used in the financial loss model.

Online platform
66.3
Median score
Conversion assumption 1,0% · average order value ₾120
Electronics and appliances
78.9
Median score
Conversion assumption 0,8% · average order value ₾450
Supermarket and FMCG
57
Median score
Conversion assumption 1,5% · average order value ₾70
Fashion and clothing
80
Median score
Conversion assumption 1,0% · average order value ₾160
Beauty and health
75.1
Median score
Conversion assumption 1,4% · average order value ₾90
Home, furniture, construction
77.2
Median score
Conversion assumption 0,7% · average order value ₾380
Specialized
61.7
Median score
Conversion assumption 1,2% · average order value ₾110

Shops checked

The logo grid shows only those websites on which the automated check was completed in full. The remaining websites were excluded because of restrictions on automated access, technical unavailability or the absence of an operating online shop.

  • Agrohub - logo
    Agrohub
    agrohub.ge
  • AutoPapa
    autopapa.ge
  • Biblusi
    biblusi.ge
  • Breezy - logo
    Breezy
    breezy.ge
  • Citrus - logo
    Citrus
    citrus.ge
  • Domino
    domino.com.ge
  • DressUp - logo
    DressUp
    dressup.ge
  • Elit Electronics - logo
    Elit Electronics
    ee.ge
  • Europroduct - logo
    Europroduct
    europroduct.ge
  • Extra.ge - logo
    Extra.ge
    extra.ge
  • Goodwill - logo
    Goodwill
    goodwill.ge
  • Gorgia - logo
    Gorgia
    gorgia.ge
  • GPC - logo
    GPC
    gpc.ge
  • Grandel - logo
    Grandel
    grandel.ge
  • Holst - logo
    Holst
    holst.ge
  • Hotsale - logo
    Hotsale
    hotsale.ge
  • INGCO - logo
    INGCO
    ingco.ge
  • iSpace - logo
    iSpace
    ispace.ge
  • JYSK - logo
    JYSK
    jysk.ge
  • Ketogen - logo
    Ketogen
    ketogen.ge
  • Kontakt Home - logo
    Kontakt Home
    kontakt.ge
  • LC Waikiki
    lcwaikiki.ge
  • Mi House - logo
    Mi House
    mihouse.ge
  • Modus - logo
    Modus
    modus.ge
  • Moli - logo
    Moli
    moli.ge
  • Nikora Supermarket - logo
    Nikora Supermarket
    nikorasupermarket.ge
  • Nova - logo
    Nova
    nova.ge
  • Pharmadeals - logo
    Pharmadeals
    pharmadeals.ge
  • Pharmadepot - logo
    Pharmadepot
    pharmadepot.ge
  • Sulakauri - logo
    Sulakauri
    sulakauri.ge
  • Superstore - logo
    Superstore
    superstore.ge
  • Swoop - logo
    Swoop
    swoop.ge
  • Tegeta Motors - logo
    Tegeta Motors
    tegeta.ge
  • Tsamali.ge
    tsamali.ge
  • Veli.store - logo
    Veli.store
    veli.store
  • Vitamini.ge - logo
    Vitamini.ge
    vitamini.ge
  • Wishlist - logo
    Wishlist
    wishlist.ge
  • Zoommer - logo
    Zoommer
    zoommer.ge

Methodology in brief

01

The study included 38 websites on which the automated check was completed in full.

02

A crawler is an automated system that checks a website's pages and analyses their technical SEO elements. Within this study it checked 1,468 URLs.

03

The study is based solely on publicly available web pages and their technical data. The analysis does not include internal data on orders, advertising campaigns or customer behaviour.

04

The loss model is based on traffic, conversion and average order value metrics. The resulting figure is a modelled estimate and not a confirmation of actual revenue or financial loss.

FAQ

Frequently asked questions

At the first stage it is recommended to check the price, stock status and Product schema on product pages. Next, the canonical on every page and the canonical specified on the catalog's second page should be reviewed. A developer can carry out the technical check of these items within a short time.

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