Keyword research - part 3: keyword strategy

In the first part of our three part series, we covered the basic terms and concepts behind keyword research and sketched out a plan for creating keyword lists. Part two laid out which keyword research tools should be used for this task. But simply finding good keywords isn’t enough if you plan on using them as part of an SEO strategy for various onpage op­tim­isa­tion tech­niques. In order for a keyword strategy to truly work, it’s important to also evaluate the iden­ti­fied keywords and co­ordin­ate them with the structure of the online project you’re aiming to optimise. Part three of our series deals with keyword analysis, keyword pri­or­it­isa­tion, and keyword mapping.

When completed, a thorough keyword research results in an extensive list of search terms that you can use for the online project that you plan to optimise. In order to develop a solid keyword strategy you need to run both qual­it­at­ive as well as quant­it­at­ive analyses on the search terms you’ve iden­ti­fied and pri­or­it­ise these according to their relevance for search engine op­tim­isa­tion (SEO). Factors like the re­spect­ive search volume levels of in­di­vidu­al keywords, proximity to con­ver­sion as well as the level of com­pet­i­tion for these terms in the search engine results pages (SERPs), are all relevant criteria for a keyword analysis. Words with multiple meanings also have an effect on how they can be used for SEO.

Search volume

A term or phrase’s search volume indicates whether and how often a keyword is used within a web search. Tools like Google’s Keyword Planner show the average monthly search rates of in­di­vidu­al words. These values are of con­sid­er­able im­port­ance for website operators, as they reveal insights on user behavior. Remember, the goal of search engine op­tim­isa­tion is to achieve a high ranking in the SERPs through relevant keywords and generate as many visitors as possible. That’s why words that feature high search volumes are pri­or­it­ised when de­vel­op­ing a keyword strategy. Following this, keywords that don’t have any search volume what­so­ever should be struck off your list.

Proximity to con­ver­sion

In contrast to search volume, con­ver­sion proximity cannot auto­mat­ic­ally be de­term­ined. Instead, values for each in­di­vidu­al keyword need to be de­term­ined while col­lect­ing data. One standard that’s proved quite useful for this task is the AIDA model. According to this, customers go through four phases until they finally make a purchase decision: Attention, Interest, Desire, and Action.

The trick of this part of the analysis is to find out where (i.e. which stage of the pur­chas­ing process) a user was when they used the keyword in a search. While in­form­a­tion­al search queries may reveal a more modest con­ver­sion proximity, terms that indicate a wider interest in a specific product or service show a middle con­ver­sa­tion proximity (e.g. red shoes). High prox­im­it­ies to con­ver­sions are assigned to search terms featuring trans­ac­tion­al in­dic­at­ors (buy, rent, etc.)

Com­pet­i­tion

Research tools, such as Google’s Keyword Planner, can also help give insights on the com­pet­i­tion (i.e. their status within the SERPs). Just how in­flu­en­tial these results are to your keyword strategy is a question that depends on your budget. With enough resources available to also reach highly sought-after keywords, the com­pet­i­tion becomes less of an important factor to consider. Without deep pockets for a more robust campaign, however, tough com­pet­i­tion may mean needing to adjust your keyword strategy; often focusing on promising long-tail or niche keywords may be your best bet. In addition to finding other com­pet­it­ors, Google itself is also a force that you’ll have to reckon with when drafting a strategy. With AdWords ads, shopping sug­ges­tions, image bars, and answer formats, like the Knowledge Graph, the search engine giant reserves valuable space in the SERPs for its own content or services that may be relevant to the searched keywords.

Ambiguity

If you’ve got any ambiguous search terms (homonyms, polysemy) within your keyword list, you should carefully consider just how useful these are for gen­er­at­ing potential customers. The following example shows why carefully con­sid­er­ing whether or not to include such terms is important: a Google AdWords search reveals that the term, watch, has an average monthly search volume of 1,220,000 hits. Jewelers and small retailers need to therefore evaluate for them­selves how many of these searches were actually intended for a Casio or Rolex—and how many were searching for the verb, to watch.

A simple Google search will show you whether ambiguous keywords are relevant for the project you intend to optimise. Search engines interpret ambiguous search items according to how the majority of searches have been carried out using this term. If a Google search of the term in question yields results showing that the com­pet­i­tion has an offer that matches the web project you intend to optimise, then it would make sense to include this term in your keyword set. If, on the other hand, Google displays results that reflect an al­tern­at­ive meaning of the word, then it can be assumed that the majority of searches are being made with this variant in mind. Putting in the effort of im­ple­ment­ing an onpage op­tim­isa­tion of the term doesn’t offer as much potential. When the majority of users associate different content with a specific keyword, then it’s less probable that a higher ranking will be achieved through al­tern­at­ive in­ter­pret­a­tions of that same keyword. In such situ­ations, it’s often best to eliminate such vocab­u­lary from your keyword lists.

Threshold keywords

If it’s your goal to optimise an existing project, then carrying out a status quo analysis will generally help you discover which keywords your website ranks for. You should take this po­s­i­tion­ing into account during the pri­or­it­ising phase. Current rankings can also be iden­ti­fied via the Keyword­Mon­it­or. Here, threshold keywords are of par­tic­u­lar interest, as they show how much potential there is for a sig­ni­fic­ant rise in visitor numbers. Such potential is exhibited within the example positions of 11, 6, 4, and 2.

When weighting keywords according to the criteria above, the following approach has proven itself useful: during the first step, the search volume priority and the con­ver­sion priority of all keywords are de­term­ined according to scales ranging from 1 to 3. These are then tallied up according to the cor­res­pond­ing weighting. The result is a keyword priority, which is then further adjusted through an ad­di­tion­al filter in the second step: despite the proximity to con­ver­sion and high search volume, keyword ambiguity as well as how the com­pet­i­tion ranks with the desired words can result in the de­valu­ation or elim­in­a­tion of search terms. Threshold keywords, on the other hand, should be more strongly un­der­scored in the keyword strategy.

Search volume pri­or­it­isa­tion

Depending on the industry and range of products on offer, the search volume of a project’s keywords may vary. That’s why no generally accepted threshold can be defined when pri­or­it­ising keywords according to search volume. The criteria that de­term­ines whether a keyword is preferred isn’t its in­di­vidu­al value; it’s the search volume of a given term in relation to the cluster or entire keyword list. So when referring to a search volume as being ‘high’ or ‘low’ all depends on context.

One reliable approach when pri­or­it­ising search volume is the ABC analysis, which sorts keywords in des­cend­ing order according to their search volume and separates them into the three segments A, B, and C. How the segments are weighted depends on the project. Typically, however, a dis­tri­bu­tion of 10, 30, and 60 percent is im­ple­men­ted. In this case, segment A en­com­passes 10 percent of the search terms for which the highest search volumes were iden­ti­fied. These are then given priority 1. Logically, this is followed by segment B, priority 2, and segment C, priority 3.

In addition to quant­it­at­ive keyword analysis, which is based on search volume, qual­it­at­ive aspects together with con­ver­sion proximity also influence keyword pri­or­it­isa­tion. Website operators should always take their own offers into account when eval­u­at­ing keywords. A keyword like last minute flight may have a high con­ver­sion proximity, but it can only be ef­fect­ively used if the website also offers such cor­res­pond­ing products or services. Pri­or­it­ising according to con­ver­sion proximity is carried out manually and at the dis­cre­tion of the site operator or the SEO expert who’s con­duct­ing the keyword analysis. And given that the con­ver­sion pri­or­it­isa­tion is accounted for in the next step with the search volume pri­or­it­isa­tion, it’s wise to scale the values according to the same scheme (e.g. priority 1, 2, and 3).

If the website you’re op­tim­ising contains terms that are already being used for search engine ad­vert­ising purposes (SEA), then it’s possible to create a pri­or­it­isa­tion of these keywords with the help of auto­mat­ic­ally obtained con­ver­sion rates. Al­tern­at­ively, you can combine the benefits of both SEO and SEA by running ads on promising search terms. This allows you to test your as­sess­ments before SEO measures, like content creation and op­tim­isa­tion, are employed.

If the results from both the quant­it­at­ive and qual­it­at­ive pri­or­it­isa­tion are to evenly influence keyword priority, then a term’s search priority (SP) and con­ver­sion priority (CP) are added together and then divided by two:

     KP = (SP + CP)/2

Depending on the project, it makes sense to weight the keyword pri­or­it­isa­tion’s eval­u­ation criteria dif­fer­ently. For example, a website operator in charge of a site that ex­clus­ively offers in­form­a­tion­al content would be able to ascribe less value to the con­ver­sion proximity of a term and take this into account when pri­or­it­ising keywords. In this case, a weighting coef­fi­cient would be used:

SP weighting = 70%
CP weighting = 30%

KP = 0.7*SP + 0.3*CP

If the keyword priority has been cal­cu­lated according to search volume and proximity to con­ver­sion, then it’ll be worth your while to do some manual fine-tuning of the keyword set. This is done by taking optional filters into account. Some examples include: the situation of the com­pet­i­tion, possible ambiguity of keywords, or current search engine rankings.

If you’ve used keyword research and keyword analysis to identify and evaluate all of your relevant keywords, then the last step on your way to de­vel­op­ing your keyword strategy is to match the search terms with the structure of the site you’re op­tim­ising. This is known as keyword mapping, a process which takes into account both existing subpages as well as new landing pages for central keywords. The keywords are allocated in clusters. For this process, related search terms are grouped together. Depending on the scope of the text, it’s re­com­men­ded to optimise websites for 5 to 7 keywords—focus on the search term for which you were able to identify the highest search priority. Of course, clusters that are too large can also be reduced by removing less-relevant keywords. If you think it’s worth the effort to create a new landing page, then make sure your decision to do this is based on the iden­ti­fied keyword priority as well as your available budget.

The keyword strategy is the starting point for a website’s onpage op­tim­isa­tion. It’s important to know which search terms your target group is using in order to search for products and services that are related to your product. You can use this knowledge to create cor­res­pond­ing content. What’s more, keyword strategies can be used to implement internal links and construct backlink profiles. If you want to create new landing pages based on keyword strategies, then make sure that you strengthen these internal links with high-quality backlinks. And in the context of internal linking, use the keywords gained from this process for anchor texts.