SEOs. Stop ranking, think search behaviour

SEO isn’t just about ranking

What we click depends upon the search engine because interfaces, algorithms, precision and recall differ from search engine to search engine. Why do we click on SERPs?

Most of us are satisfied search engine users because we feel, for example, in control and are able to find relevant information. Search evokes emotions which is why there are 8.63 billion web searches carried out on Google daily, making search a repetitive task: There are more web searches carried out everyday than their are people on the planet. Repeating the same search, however, leads to even more personalised results but search engines’ algorithms also include diversity to ensure the best user experience. We click on SERPs because search is, for the most part, an enjoyable task.

Photo of retro Google UX

Classic Google user interface

Our behaviour changes:

  1. if the quality of results is affected;
  2. because of SERP presentation. This explains why Google, for example, updates their PPC presentation because by changing the interface we interact differently with the same element. In the case of Adwords more clicks are likely to have occurred earning Google more money;
  3. in accordance with the type of search task. In fact long snippets lead to better search performance for informational tasks but reduce performance for navigational tasks;
  4. due to individual differences.

Don’t make me click

The choice of keywords in the URL, description and title tag affect what we click because we subconsciously make a relevance judgement. Search engines highlight our keywords and place them in bold to help us to make a quick relevancy judgement. For SEO it is vital your important keywords are placed in the right places. Term location therefore affects click-through rates (CTRs) and as impressions increase so too will clicks if you create great meta data.

Whilst user effort includes CTRs and user experience researchers have broken user effort down more specifically and discovered that a search quality includes the following metrics: number of clicks; number of queries; number of query reformulations; and the rank and position of results. SEO cannot directly impact the number of queries and the number of query reformulations, however, we can increase the number of clicks, rank and position of results.

A case study increasing CTRs.
If you cannot change your rankings quickly then review CTRs to gain more clicks, for example, by including the keyword [every]. Would you click on [every men’s red jumpers] or [men’s red jumpers]? The former sounds far more interesting, let’s click on that instead.

Organic rankings do not, yet, include social media within their algorithms. You should include social within your SEO campaign today. Not only will your total clicks improve but you can influence keyword awareness through social media and therefore increase impressions for keywords. This is particularly useful if you are trying to rank an unusual or new keyword.

Do you think SEO is all about ranking or click-through rates? Tweet Gerald.

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  1. Al-Maskari, A. and Sanderson, M. (2009) A Review of Factors Influencing User Satisfaction in Information Retrieval. Journal of the American Society for Information Science and Technology. 61(5) pp. 859–868

3 ways search engines can track your behaviour

Search engines are keyword-led utility tools used to locate information on the web. Most search engines commonly record your behaviour. Some behaviours are commonly known, for example your search history, and some are less known, for instance, tagging your search engine queries. Either way most search engines record user actions to predict user intent within search sessions and, therefore, calculating what information you are going to search for in the near future.

A photo of a mouse cursor

Questionable click? No copyright permission required.

3 levels of search engine user tracking

  1. User actions can be tracked by search engines, for example, query logs, clicks and scoring. By analysing keywords with each of these user actions, search engines can further add value to this data. Query logs can also include subject categories, time spent on individual webpages and calculating what a searcher’s most favourite category is. This is likely to be constructed on a 3D cube with 3 dimensions: length, breath, and depth.
  2. Hidden user actions are tracked in a technical manner, such as, using AJAX or javascript. Hidden search engine actions include mouse movements or, for example, scrolling. Such tracking requires third party techniques because search engine instruments cannot record such data in their own right.
  3. Popular search engines now carry out regular user testing whereby Google, Bing and Yahoo, for example, get participants to sit in front of their search engine and complete eye tracking (the third way search engines track behaviour). These observed actions are much more sophisticated and are often incorporated with wider IT diciplines, such as, usability testing, for instance.

Tracking your behaviour, your rights

There is no international law that covers search engine tracking, however, the laws in your home country will help to protect you against legal concerns, for instance, privacy, data protection and breach of confidence. The biggest issue with search engine tracking is that we do not, as of yet, know precisely what search engines use to track our behaviour. In their response search engines are likely to argue that their tracking helps to increase personalisation and by withholding such methods they are giving away less information to their competitors. Although from a search perspective personalisation is positive, since relevancy of results is increased, public awareness is likely to challenge such behaviour tactics which is why search engines should consider opening up to transparency more and more as time progresses.

What are your opinions? Were you aware of the 3 layers of search engine tracking? Tweet Gerald.

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3 influential affects branding has on your marketing campaign

Branding and marketing

A brand is how we can relate to an entity. For marketing purposes branding facilitates with the following 3 elements:

Brand communication
As humans communication is key to link people together and create relationships. For marketing purposes brand communication helps us make meaning of a product or service. A brand’s communication can influence satisfaction and trust.
Brand satisfaction
Brand satisfaction is a transactional experience allowing us to reflect on past experiences. If this reflection evokes positive emotional responses then brand trust is automatically increased.
Brand trust
If we rely on a seller to deliver goods or services then we trust that brand. Brand trust can also be regarded as a consumer’s perception of the benefits enjoyed versus the cost incurred in the maintenance of an ongoing exchange relationship. In other words trust takes time to build and, therefore, cannot be automatically created.

B2B branding

The 3 points above, brand communication, satisfaction and trust, are written within a B2C context. B2B however will view brands differently and are likely to view 3 advantages to branding: manufacturer support; brand equity; and customer expectations.

A photo of a content marketing process

Content marketing cycle. No copyright restrictions (Wikimedia)

What influences price premium?

A brand’s image influences price premium because it is comprised of 3 elements: familiarity; attention to service; relationship management. Collectively these 3 elements influence price premiums.

On the other hand your brand, through player transgression, can terminate relationships by 4 elements: cooperation; trust; mutual understanding; and brand benefits. Communication is key to maintaining consumer relationships.

It was reported in the 1990s that if price and quality were met then a firm’s reputation and brand play a role in the purchasing decision. Your brand’s image can determine your success and help you develop as you progress into the future.

Brand personality

A brand’s personality is a set of human characteristics associated with a brand. Brand personality is affected by a brand’s perception: attitude; perspective; and consumer view. The 3 traits of a brand’s perception influence the development of a consumer’s positive brand personality.

Every marketer, in summary, wants a strong brand to gain trust through communication and customer satisfaction. B2B consumers are more likely to hardness long-term relationships whereas B2C often embrace in short-term relationships. Branding can influence these long- and short-term relationships by building familiarity, relationships and, more importantly, trust.

What does a brand mean to you? Tweet Gerald.

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  1. Azize, S. Cemal, Z. and Hakan, K. (2012) Does Brand Communication Increase Brand Trust? The Empirical Research on Global Mobile Phone Brands. Social and Behavioural Sciences. 58(2012) pp. 1361–1369
  2. Lindgreen, A. Beverland, M.B. and Farrelly, F. (2010) From strategy to tactics: Building, implementing, and managing brand equity in business markets. Industrial Marketing Management. 39(2010) pp. 1223–1235

3 localised SEO tips

Local SEO tips

Location-based searching contains 4 main technologies: georeferencing; geotags; GPS; and an internet connection. Today other signals are also used to enhance this data, for example, Yelp or other localised web application services, least not forgetting, social media profile information, such as, Google Plus location data, for instance.

To begin a localised campaign a blended approach is required. Google Places, for instance, are key to helping you rank locally yet Google Places are, strictly speaking, not going to help your traditional SEO ranking because social media is not used, so far, for search algorithm rankings.

Search engine optimisation

What elements are involved in SEO? Copyright free image.

Localised SEO became stronger with Google’s Venice update. Together with Hummingbird, Google now has the capacity to regularly construct a universal SERP and, in particular, localised SEO results.

A thorough 2003 case study analysed localised search engines with global search engines and found that global search engines were more effective and sophisticated than specialist, localised search engines. Search engine market share is much higher on global search engines than it is on localised search engines, therefore, focusing your localised SEO campaign on large search engines is key to gaining the largest audience.

Local analysis

In 2000 half of the UK population had a mobile phone now that stands at 94%. Mobile search is different to desktop search because we generally search for broader keywords and we use 2 types of keywords: explicit and implicit. So a mobile search for [restaurant] is an implicit search because it does not state a location. Therefore local SEO is mostly based on implicit keyword intent. With the increase of devices also comes an increase in mobile web search: 16% to 25% of all Google searches are now on mobile meaning that more and more people are carrying out implicit searches. Local SEO is also more important than ever before.

Name, address and telephone (NAP) numbers are key to local SEO. These should be reflected, rather like your digital brand, on, for example, social media accounts. On your site you should include your NAP details on the footer of each webpage too. This is now noted on search engine’s 3D indexes.

Another localised SEO tip is to review your structured data rather than simply focus on your NAP details, above. Think about your UX as you do this. Maps, text, photographs all help to shape up your contact page and structured data.

Reviews, trust and authority also help localised ranking. Reviews are an effective tactic to increase the click-through rate of your site, as well as, boost your trust and authority. Search engines particularly favour popular, voted, sites because it shows a reliable source of information.

Localised information is not, however, anything new. 50 years’ ago for instance businesses used local information to determine the location of their new store or relocation. Local services are always valuable and, arguably, help you to obtain an added layer of research to your target audience data: Market research is key to localised SEO campaigns.

Ranking locally using SEO

  1. Review your Google Analytic data and use this data to make a localised SEO conclusion. This will narrow down your locations and make a local SEO campaign realistic. Target larger cities, initially, and think of strategic ways to implement the information above.
  2. Take a blended approach. Use NAP, structured data, social media, hyperlinks and think devices for your localised SEO campaign.
  3. Target, primarily, global search engines because localised search engines are a very small percentage of the total market share and global search engines are better at ranking localised web sites.


Smith, A.G. (2003) Think local, search global? Comparing search engines for searching geographically specific information. Online Information Review. 27(2) pp. 102 — 109

Computer attacks: How to prevent cookie stealing, sniffing and redirection?

Common types of computer attacks

There are 4 main types of cookies (session, performance, functionality and targeting). In the EU web sites must, by law, display a cookie banner to ask for a person’s permission before cookies are used. Everyone has the right to allow or deny cookies. But if we accept and use computer cookies then is there a risk of cookie misuse?

Cookie stealing

A reflected XSS attack executes a script on the client that can be read by the client’s cookie. This cookies’ contents can send its value to the attacker (reflection) and the attacker can impersonate the client without obtaining the cookie by sending a XMLHTTPRequest. Such commands usually use “get” or “post” to obtain client data.

The best way to overcome a reflected XSS attack is to: utilise the browser’s security settings and policy by using permission zones and setting them accordingly, secondly, use a cross site request forgery, meaning cookies must be sent from the same origin policy from the client.

Web vulnerability

Today internet service providers literally provide you with an internet connection, however, surfing the web on the “naked” internet opens you up to even more vulnerability. You should therefore make use of virtual private networks (VPN) and proxy servers. Surfing safely allows your data to be more secure.

Lately Edward Snowden has revealed that NSA and GCHQ (UK) have been working on cracking a VPN’s secure setting. This is a complex task but it is possible because encryption is simply a bunch of complex numbers that, once cracked, can be analysed for any purposes. As technology progresses so too does misuse.

Hackers invented Firefox

“Hackers are not criminals”. Copyright of Jonathanmh Devintart. Reused, unmodified.

Main computer attacks

Sniffing refers to those who use their “naked” online connection sent by internet providers. To do this hackers sniff mentioned network devices if using URL based session IDs. Recently Google started encrypting their searches, and other search engines followed, which meant that HTTP became HTTPS (secure) and thus can reduce search engine sniffing.

Redirection occurs whenever information is sent back to a web server, as well as, redirecting it to the hacker. Redirection can occur from HTTP REFERER or CSS.

Would you like to add to the main types of computer attacks above? Tweet Gerald.

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  1. Gollmann, D. (2008) Securing web applications. Information Security Technical report. 13 [volume number missing] pp. 1–9
  2. Morgan, D. (2006) Maintaining state in web applications. Network Security. [volume and issue numbers missing] pp. 16–18

Web search engine user behaviour

Search engine behaviour

Age matters when searching. Young people, for example, have 7 types of browsing behaviour:

  1. Power users tend to make use of advanced search features.
  2. Developing users display unplanned search paths
  3. Social users share links with friends using social media accounts.
  4. Specific users focus on specified topics of interest.
  5. Rule-bound users are influenced by rules, for example, trust and are likely to revisit specified sites over and over again.
  6. Visual users love pictures and videos to find information.
  7. Nonmotivated users only search when necessary. Emotions are low, for example, excitement and contentness.

We generally read SERP results in an F shape. Each SERP result snippet’s title tag (top part of the F shape) is read first followed by the URL and the description tag. More broadly we also scan sites using an F shaped pattern so top left to top right, middle left to the middle of the screen, then top left right down to the bottom left. This F shaped pattern is a dominate behaviour across a lot of digital products. Put your navigation menu, for instance, on the left hand side or along the top of your screen to increase its visibility.


Hand drawing of Google’s homepage. Copyright of Robo7, resued, unedited from a creative commons licence.

User behaviour analysis

Young, or more specifically inexperienced, search engine users place more weight on SERP cues, for instance, keywords being highlighted in bold than their older counterparts. Age however does not determine how good of a search engine user you are (i.e. a 50 year old is not a better searcher than a 25 year old).

If the search engine user knows the topic they devote more time to analyse the document’s contents. This directly impacts keyword formulation, as such, topic knowledge means we are likely to search this topic more than others. So if someone is interested in fashion, for example, they are likely to search a lot of fashion-based web sites because they know a lot of keywords related to fashion (the topic).

Title pages alter SERP scanning and click-through rates. If an exact match has been returned then this search engine user is also likely to click on this document because it directly matches their query. It is, however, worth noting that most search engine users are not good at formulating keywords in the first instance. This is one of the main limitations of web search: Human beings are complex computer users.

When we examine search engine results we constantly try to make sense of the results. Although on most occassions we tend to make the correct relevant judgement at times our quick scanning can create a false positive. We do sometimes do not click on some results because our brain has literally processed that specific link as being irrelevant or, conversely, useful.

When we look at web search engine results we also integrate our own lives in to that search. As our “real life” changes dramatically so does our search behaviour this, therefore, explains why we sometimes carry out more in depth searches than others (i.e. our search behaviour changes with our environment).

Returning users practice “selective disregard” when it comes to toolbars, search and menus. This localised learning allows our brain to ignore specific regions of a site but we know they are there. This partly explains why organic traffic is higher than pay per click (PPC): Some people have selective disregard for PPC and therefore mostly look at organic traffic.

The number of tabs opened also influences user behaviour, in particular, initial scanning of web sites. The more tabs we have open the less concentrated we become. Tabs also influence user selection behaviour, for example, clicks which can cause us to jump around from site to site, or, as Peter Morville calls this, in web search, pogosticking between the SERP and individual results (back and forth).

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Google Hummingbird: Tail queries

Google’s Hummingbird update

If we use a search engine and get relevant results we are likely to use that search engine again and again. What causes people to switch search engines?

  • The most influential cause of search engine switch is due to long tail queries (so 6 or more keywords).
  • If a search engine processes a long tail query and returns low relevant results then this user is likely to switch search engine.
  • The processing of long tail queries equally distinguishes search engines and good search engines are those that can return relevant results for long tail queries

Popular search engines have recently adapted to this. Google in September 2013 announced a new engine known as Hummingbird. The new engine does not make Google a semantic search engine but it does improve the processing of long tail queries. In light of Google Glass and mobile devices conversational search is going to be the next big thing for web search. Hummingbird is essential to improve long tail queries.

Google and Microsoft’s Bing are not semantic search engines, however, they are getting better at returning relevant results. If you were to carry out a complex search, for example [picture of blue flower with 6 petals with sea front background], on Google you will soon find that the results will not be highly relevant. Search engines are beginning to see value in improving the relevance of long tail queries because irrelavant long tail queries causes search engine switch, often permanently.

There are several wider reasons that directly influence search engine switch. They include: localised learning of the system; advanced search features; culture; previous encounters; presentation of results; precision and recall (see below).

Photo of a hummingbird

Image of a hummingbird. Photo reused, unedited, copyright of Commons Wikipedia.

Why search engines give lots of results?

Search engines can be evaluated using 3 metrics: precision; recall; and speed. Precision is all about returning relevant results. Recall examines the number of results and matches them to the actual query. Speed, thirdly, is all about getting lots of relevant documents that match our query in a quick manner. Search engines incorporate these metrics into every search. This explains why we get pages and pages of relevant results for our search queries (precision and recall).

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  1. Zaragoza, H. Cambazoglu, B.B. and Baeza-Yates, R. (2010) Web search solved? In Proceedings of the 19th ACM international conference on Information and knowledge management — CIKM ’10. pp. 529
  2. Zhou, K. Li.X. and Zha, H. (2012) Collaborative ranking: Improving the relevance for tail queries. CIKM ’12. pp. 1900–1904