A Beginner’s Guide to Google Suggest For Marketers and SEO

Google Suggest is the name of Google’s auto-complete function. If a user enters a letter or a word in Google’s search field, they are automatically shown associated terms in a dropdown menu. These suggestions are generated based on the most frequently searched terms. If a user enters the word “car”, for example, associated terms like “carmax,” “cartoon network”, “cars” and “car credit” are suggested.

This function helps users save time and may also provide them with additional information about the topic they are researching. Google Suggest is not only a useful function from a usability perspective, but it’s also essential for businesses and figures of public interest.

There are several potential risks and opportunities associated with Google Suggest, both from a marketer and a user standpoint.

How Did Google Suggest Emerge?

Pretty much everyone who searches online comes into contact with Google’s autocomplete algorithm. The feature has been around for 5 years and is mostly taken for granted nowadays. Most people, among them – unbelievably – search engine optimizers, neglect the following questions:

• How can I use Google suggest to my advantage?
• How could it potentially be harmful to my client?

Before we answer these questions, first lets explore how the Google Suggest function works.

Basically Google’s auto suggest function aims to improve the usability of its search engine. Suggestions help the searcher save time entering long phrases like “Samsung Galaxy S4”. Thanks to Google Suggest, that term can be chosen after “Sams” is entered.

Another helpful aspect of the auto complete function is the checking of search terms for spelling mistakes. If the user enters “hairdesser” in the search mask, the search engine giant offers the term “hairdresser”.

Search Rate, Search Manner, & Search Frequency of Google Users

Here Google tends to be transparent. Official statements by the search engine giant stated that previously entered search phrases do influence the auto completion. For example, if “holiday mallorca” is often entered in the search mask chances increase that “holiday mallorca” will be suggested to another user when he or she enters just “holiday”.

There are a couple of other elements which are also considered. Although these “objective” factors haven’t been made public by Google, other aspects like the search frequency can easily be identified. When the interest for media events like Prince William’s and Kate’s wedding gradually fades, these search suggestions – e.g. when “wedding” is entered – are displayed less and less often. Constant terms like “plan wedding” on the other hand rise in popularity again after the furor of a big event has died down.

What Else Plays an Important Role for the Google Suggest Function?

Although it should be self-evident, for the sake of completion, the language used and the place where the search query is entered also play a role. In earlier iterations of the algorithm only the country was used, but now Google has been successfully differentiating between individual cities of a country. This has to be taken into consideration for SEO, since different search results are displayed depending on the place, and these are even dealt with preferably. The following example makes this aspect clear:

Although the term “shopping basket” has a higher search volume than “shopping center london” the local search term is preferred if just “shopping” is entered in the Google search mask. Figure 3 makes clear that Google even differentiates between single districts in Berlin.

However, these suggestions only seem to emerge if the user has entered his or her location in the settings and already did multiple search queries. Otherwise, the suggested terms are broader with the actual location being the first suggestion, no matter if it was determined in the settings or not.

It is important to note that when changing the settings one can only choose locations that do exist in the respective country. In order to get search results from other countries one needs to change the settings on the country-specific Google cover page. In order to verify our thesis, changing the location should lead to other suggestions in local searches.

Figure 5: Changing the location in Google’s search settings

And in fact, if we search for “shopping center” in google.co.uk, no districts are suggested, even if “London” was chosen as the location. The suggestions are identical to those that appear if no location was entered at all. Consequently, at google.com, the same terms are suggested no matter if with or without location (e.g. New York). Depending on the different Google cover pages (co.uk / com), however, we get different suggestions.

Figure 6: No districts are suggested in google.co.uk …

Figure 7: … and neither in google.com

One can therefore assume that it is the multitude of local search queries responsible for the search suggestions. After all, in the previous examples no city-specific districts were suggested but rather a thematically larger bandwidth of terms, even if those consisted mainly of different cities.

When it comes to mobile search, another phenomenon can be seen: Even though we searched with google.co.uk and chose London as our location, the first suggestion is “shopping center berlin” (our actual location).

Figure 8: Mobile devices know our actual location

Since smartphones always know where we really are, getting local search results from other locations seems to be impossible – contrary to stationary devices. Instead, local search suggestions always display a person’s present location – no matter what the settings are. It is very likely that this will be the case on stationary devices in the near future, too, and local search results will noticeably enhance Google’s suggestions.

Why then, for some search queries are no suggestions are displayed at all? This is due to the fact that Google follows strict guidelines when it comes to pornography, copyright violations, violence, and similar negatively charged terms. So the search engine provider automatically filters out terms that can be classified into the above-mentioned problem areas. On the other hand, it can take some time until breaking new is validated by Google and implemented as suggestions.

Chances and Risks for Reputation Management

Nowadays, how an enterprise is perceived online and in public strongly depends not only on a professional position, but also on internet users. Thanks to Twitter and Co., information and reviews spread like a virtual wildfire. Today companies are dependent on the opinion of a huge and partly anonymous crowd. This has effects on the auto completion of Google Suggest, for example as a result of usage of certain search terms over the course of time.

The problem example is this: Sometimes, Google associates a brand with fraud or other negative terms. Since search behavior and search frequency affect Google Suggest, this phenomenon can be explained by short-run trends. For example, if a well know blogger writes a scathing (not necessarily true) blog. When this happens, potential clients can be turned off of the brand.

On the other hand, these same mechanisms can have positive consequences for a company. If terms like “experiences” and “opinions” are suggested after a brand name, this can lead a potential customer to read positive reviews and signal that others are interested in the brand.

Chances and Risks in Affiliate Marketing

An interesting train of thought how Google Suggest can have positive influences on the business model of an affiliate shop owner is the following:

Let’s assume a Google user searches for an online shop to get information on the latest events, etc. If this online shop offers vouchers and other users have searched for these vouchers before, the user will be suggested a combination of the chosen shop and the word “voucher”. This gives the user a whole new idea since he could even save money during the purchase! Affiliates who rank high for a voucher term in connection with a brand can be happy about this suggestion by Google. On the other hand, another shop owner may lose important traffic because of the suggestion.

Risk: Distracting the Searcher

The next example goes one step further. If a Google user searches for “credit card” , he has already made the decision to get one. However, while searching he stumbles upon the term “credit card free”, his intention might change. Therefore, the searcher ends up searching for free credit cards instead of a particular company he was initially interested in.

Unjustified Brand Advantages?

The following figure illustrates another risk, respectively, or an advantage for some companies:

Figure 9: When searching for “car”, the first suggestion is “carmax”.

Here the question emerges: To what extent is this suggestion justified? On the one hand, these brands’ websites are a good suggestion because they are often searched for. On the other hand, these suggestions influence the user and could cause distortion of competition. Consequently, one could question whether this was Google’s initial intention.

Furthermore, even if just the letter “e” is entered in the search mask, certain brand names appear. Although the searcher might be looking for something completely different, the fact alone that a brand is mentioned amplifies its level of awareness and potentially makes the user resort to these brands in the future.

Figure 10: Brand names are displayed after only one letter was entered

Conclusion

One of the most important results is the fact that Google Suggest influences the user. This happens consciously – “I’ll just take a look at what Google is suggesting to me” – as well as unconsciously. One reason is that the completion function has become a normal and even integral part of the Google search for most people. The above mentioned examples gave situations in which the auto completion function clearly influences our search behavior. It has become clear that this can be an advantage for some companies and a disadvantage for others.