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Last year there was a host of blog posts and thoughts on Semantic Search including this and this on the Koozai blog. A question to Matt Cutts in 2010 asking ‘What is the future of Semantic Search’ showed some early insight into what Google may be working towards. Let’s take a look at what we know.
When a web user searches for a particular query, the chances are that this query can be written in different ways and search engines would match it to results using plurals and synonyms of your query. This is the traditional way that search has worked and it has done a decent job of returning relevant results. Along with the recent algorithm updates that have cut down on the spam and manipulative ways to have a site show for a given search query, Semantic Search will make a bigger difference to answering a user’s search query with the most relevant results.
Traditional search algorithms match search queries with content and order the results by relevance and authority, loosely speaking. What semantic search is going to do is show you very detailed, relevant results through understanding your query in more depth.
Humans are very good at interpreting the use of language to associate words and topics with those mentioned or not mentioned. Computers are not great at this, but they are learning.
Google is always getting smarter and services such as Wolfram Alpha has been designed to only return informational results based on a search query.
You may have noticed the visual changes in the Google search results in recent months. Knowledge graph information, weather, sports scores, answers to maths questions, image result suggestions, keyword phrase suggestions. These are all part of the growth of Semantic Search and designed to help return a more relevant result to a query.
When you search for a brand such as Google in Google (yes the internet won’t explode if you do this) then you will get a nice company summary on the right hand side. Providing this information what is referred to as Knowledge Graph and is part of Semantic Search.
Search for ‘What is the weather in London this Monday’ and you’ll see the information right there. Google understands the key elements in your use of language.
Say I wanted to know the latest football score of my local team, a quick search using ‘Southampton FC latest score’ returns the following:
Inputting a calculation into Google such as ‘what is 25 times 4 divided by 2’ will bring up the calculator function with your calculation. This is just what I wanted to see, not a list of snippets of calculations from various websites.
When searching in Google Images, you are typically shown several sub options if your search is broad or has double meaning. For instance, if I search for ‘picture of a keyboard’, Google will show me the most popular type of keyword which is a typical computer keyboard. Along the top there are shortcuts to re-phrase your query with the next most popular ones: ‘picture of a music keyboard’, ‘picture of a piano keyboard’, ‘picture of a laptop keyboard’, etc.
It’s increasingly common to see Google suggest a completely different way of phrasing a search query. Google is almost trying to get users to ‘speak clearly’ in order to build up its understanding of what are the most common ways to ask things.
As you can see in the previous examples, some queries are understandable but some want you to refine your query to some more relevant results. Google has been unable to understand the context of your search and needs further help.
In the future we should see Google understand more of what you were thinking via your website browsing behaviour (when logged into your Google Account) and how you interact on social networks such as Google+.
Computers need to gain more of an understanding about who we are; much like our friends and family know us, Google will become smarter at learning our interests and personality.
Typically mobile users search for shorter keyword phrases and demand quicker, concise answers. What can Google do to help break down a user’s query and return a highly relevant result? Well location will play a large part in what is returned. The obvious one is if someone searches just the words ‘Italian restaurant’ Google is going to understand that you are probably looking for a local Italian restaurant to eat at now or in the near future. Other factors could include what device or mobile browser software is being used.
One way mobile search is looking to overcome the shorter search queries is through the use of voice. Google has voice search on android devices and iOS has Siri and dictation software built into its devices. This brings out longer more natural queries from users, however the search results need to interpret these well and return the right results. This is where Semantic Search will excel.
It’s not just Google that would help its users with Semantic Search results, ecommerce sites and Travel sites, for example, can help improve their conversion rates if they can better understand their visitor’s queries. Users may search for ‘somewhere hot at Christmas’ or ‘child friendly hotel in school summer holidays’. Traditionally these queries would struggle to return relevant results to a user. If an algorithm is smart enough to understand the Semantics then they would know that the user wants a holiday in the southern hemisphere for a number of days either side of December 25th, or the second user might want a hotel with a shallow swimming pool with availability anytime between the third week in July and the second week in September.
One example of a site getting ready to roll out Semantic Search on a huge scale is Facebook with its ‘Graph Search’. This will allow users to search for answers using a natural language such as ‘Which of my friends have been to Italy’ or simply ‘People who like Cycling’.
Webmasters can’t game the semantic search results as much as they might have been able to fool the search engines in the past with poor quality link building and keyword spam. As they become smarter at understanding what people are asking, more specific search results are going to be delivered.
Online marketers can capture traffic and business from the future Semantic Search results by considering these tips:
If you’ve got some good examples of existing implementations or have predictions on what else we might see changing, leave a comment below.
Word Cloud – Web 3.0 Via BigStock
In today’s multichannel world, there are mountains of data which provide insights into how users have interacted with your business and their path to conversion (or non-conversion). It is important to understand performance with multichannel marketing, which can be achieved through attribution modelling. Attribution refers to assigning credit to something (a channel, touchpoint, etc.) for the role it played in the final conversion. An attribution model is a rule, or set of rules, that assigns this credit correctly to the right channel or touchpoint.
For a long time, Bing, the UK’s second-largest search engine, has been underappreciated and, in some instances, even ignored. Often regarded as the inferior search engine to market leader Google, Bing has historically struggled to appeal to many in the digital world. Most PPC analysts would give justified reasons for neglecting Bing for so long; these include the volume of traffic and the user experience just not matching up to Google. However, the validity of these assessments is now diminishing. Bing has grown and improved rapidly in the last couple of years; if you are not integrating it into your comprehensive digital marketing plan, you run the risk of missing out on a large portion of your chosen market and significant revenue.