Keywords are invariably the crux of any Adwords campaign. Keywords are the ultimate reflection of the users’ wants, needs and requirements and give you an essence of purpose behind the search which most marketers also like to call as ‘intent’.
In order to run a successful Adwords campaign, it is paramount to research, gather and group the keywords which will act as the bridge between the products and services offered on your business’s landing page and the search queries entered by the user into the search bar of search engine.
Regardless whether you have recently started running Adwords campaigns or you have extensive experience at managing multiple Adwords account, you should know how grouping the keyword impacts the cost incurred by your campaigns and how you can fine tune your Adwords strategy around it.
But before we dive into the topic, let me ask you: Is your keyword research process over?
In case you have not performed a thorough keyword research process, here is the guide To Do A “Proper” Keyword Research In Less Than 60 Minutes.
Once you are ready with the first exhaustive list of keywords relevant to your business and marketing objectives (Lead generation/online product sale, etc.), next step is compartmentalizing the keywords into the ad groups, in order to meet the pre-decided objectives of Adwords campaigns, and it may not be certainly easy but with some help it will be.
Fundamentally, regardless of the marketing channel employed, the buying process of a user remains more or less the same. Buying process starts with a user identifying the problem and ends up in finding the solution that the user seems as a best possible choice. This process however involves various stages where user searches for, identifies options and filters the best possible ones from the rest and finally completes the purchase.
Identifying the user requirement provides us an opportunity to develop ad content mentioning exactly what the user is searching for, at each of the buying stage. This also allows us to classify the keywords based on at what stage of the buying process the user belongs to.
A typical buying decision making process looks as follows:
Below are the examples of keywords for each of the buying stages. Note that, this is not the only basis to classify the keywords but one that may go hand in hand with the intent a buyer holds behind performing a search
At this stage, a customer is in the process of identifying the problem, finding answer to a question or simply facing a need, either basic or derived and wants to confirm the existence of the problem and possible solutions.
A user following a process to buy insurance will search for the definition of insurance, why one should buy insurance, what are advantages of the insurance and how it fits into his financial needs and planning. Many search queries will include generic word such as ‘insurance’, ‘what is insurance’, ‘benefit of insurance’, or specific questions like ‘which insurance is fit for 30 year old plumber’, ‘health insurance or life insurance’, ‘when should I buy insurance’, etc.
We can group keywords associated with intent to identifying the problem into categories such as definitions, benefits, information etc.
At the research stage a user has already identified the problem and is aware of possible solution. At this stage he starts a research to find out the choices available in the market which can provide that solution.
Carrying forward the example given above, the user looking for insurance will perform research with following queries : ‘ life insurance providers’ , ‘top 10 life insurance companies , ‘top rated insurance companies’ , ‘low cost insurance’ , ‘lowest premium highest returns life insurance’ , ‘ easy avail life insurance’ ‘best claim ratio insurance’, etc.
We can group keywords associated with intent to research the available choices into categories as top services, best reviewed services, low cost, best services, etc.
As the name implies, the user now is aware of multiple options available to him in order to make an ultimate choice to complete the purchase action. This is similar to a filtering out the
options by weighing them against each other by comparing different aspects.
The customer from the above example knows he has 10 options available to choose from, he may perform a comparison using search queries such as: ‘ABC life insurance vs. XYZ life insurance’, ‘which one is cheaper ABC or XYZ’, ’20 years vs 30 years life insurance’, ‘term insurance or life insurance which is better’, ‘go for mediclaim or medical insurance’, etc.
We can group keywords associated with intent to compare the choices into categories as comparison, cheaper, more returns, lower cost, etc.
The customer at this stage has performed complete research around the services/solution he is seeking to his problem and has finalized the same. He is seeking the best deal he can avail and the brand he thinks is the best among the available ones.
Finally the customer in our example will be looking for buying life insurance option with following search queries: ‘ buy life insurance’ , ‘buy ABC life insurance’ , ‘where to buy life insurance online’, ‘website to buy life insurance’ , ‘easy way to buy life insurance’ , ‘contact ABC life insurance company’ , ‘purchase life insurance in easy steps’ , etc.
We can group keywords associated with intent to complete final buying action into categories as buy, get, purchase, avail, contact, where to find, where to buy, number for, I want to buy, etc.
As I already clarified, there are other ways in which you can group your keywords and which can be another layer of classification over the one we discussed in this blog. The prime advantage of classifying the keywords based on their intent and position in the buying process is improved relevancy with what user is looking for, higher CTR and higher conversion rate.
A most important thing to remember is that our job doesn’t end after we have classified the keywords into the appropriate categories but only half done. The rest half is to create ads for each of them categories with relevant messages which will encourage the users to click on the ads.
Rest assured that the classification we discussed in this blog post will leave very narrow scope for irrelevant search queries, and hence improve the quality score and as a result performance of the campaign.