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One of the accepted truths within SEO is that an image-intensive website can be a challenge to get indexed in search engines. This post looks at ways to optimise images and considers the future for image optimisation.
Alt descriptions are one way of optimizing images on a page. This is giving an image a description which matches the image, using an alt tag within the page code. This example was found on the BBC website home page:
The alt tag in the code looked like:
Alt tags are used when a browser or software is unable to display the image, for example if the image file is lost or if the software does not support images. It is important to remember that alt tags are often also used by screen readers to read a web page to blind people, so they must be descriptive of what the image is showing.
From an SEO perspective, these descriptions can also be used to include the keyword which the page is being targeted for. The key is to make sure this should not look false or forced in where it does not read naturally. As with all SEO, the user should be the primary concern when creating alt descriptions. Alt descriptions should ideally be no longer than around 140 characters.
The file name is also known to influence the search engines perception of what an image is. The file name may be the next best way to optimise images, especially if the site uses a CMS which makes it difficult to apply alt attributes. This should not be as along as an alt description, but still needs to include a descriptive name for the image which includes the keyword targeted for the page.
Because search engines put the user at the centre of their ranking decisions, it makes sense that having large image file sizes which take an excessive amount of time to download may work against getting your page to rank. This is a factor which can affect page speed, which is acknowledged SEO factor, and so naturally supports the idea that large file sizes which take time to download are more likely to be challenging to get indexed.
A good tip is to simply resize the image before uploading it, rather than compressing it using the CMS. This will ensure that it isn’t unnecessarily large and help reduce the loading time.
The content around an image on a web page is also crucial, with elements such as image captions playing a specific role. Again, image captions should be descriptive but also include the keyword which the page is targeting. Even the content on the rest of the page in general is giving clues to the search engine about what the image is likely to be of, so it is important to pay attention to the text on the page and specifically the text immediately surrounding the image.
Link building can also help strengthen an image intensive page, in the same way as a regular page. This is one technique which can still be used on pages which are entirely image based. It is recommended that image intensive sites try to keep to one image per page, so that the link building into that page can be particularly focused with the term it targets using anchor text. If a page has many different unrelated images on, such as a gallery, it can be much more difficult to rank as the link building into the page may need to target several terms. It is also important to remember that the link should preferably to the regular page, rather than the image location (Image URL).
What Does the Future Hold for Search Engines Reading Images?
It has been speculated that search engines do have the technology to read images. One of the reasons behind this is the fact that this kind of technology is already being used by Google within other applications, such as Google Goggles, so may be just a matter of time before search engines integrate the reading of images in this way into other algorithms.
Similar technology is seen within some software programs where a scan of a document (which is technically an image) can be read for the text that is within it. This is known as Optical Character Recognition or OCR. In addition to this, Google Images also already lets you choose image results containing specific colours, as well as image types, such as face images, clip art, line drawings or photographs. This illustrates that the technology for reading images is already part of their algorithms to some extent.
Vector screens via BigStock