Improving visibility on the Internet is vital for any e-commerce business. Proper SEO optimization is one effective way to enhance an e-commerce website’s visibility and attract more qualified traffic. Without a doubt, meticulous keyword optimization is an essential part of these SEO efforts. In particular, keyword optimization is crucial because it makes your website content more relevant to customers’ search intentions and aligns your offerings with their needs.
By incorporating targeted keywords naturally within your content, titles, meta descriptions, and product listings, you enhance your website’s relevance to user queries. This improves your search engine rankings and ensures that potential customers find exactly what they want when they land on your site.
However, e-commerce is highly competitive, and nearly everyone tries to find and use the best way to maximize SEO efforts. Numerous e-commerce websites have high authority, which casts a shadow on the new ones, making it hard for them to succeed.
How can you gain a competitive edge in this case? The answer is to approach keyword research in a data-driven way. Using the power of data analytics, thorough assessment of keyword metrics, sophisticated filtering, and systematizing can significantly improve your SEO efforts.
In this article, we explore data-driven keyword research and its benefits and provide a comprehensive checklist for doing it right.
Contents:
What is data-driven keyword research and why is it crucial?
1. Finding the seeds: how to identify your initial keyword pool
➤Tap into product or service categories
➤Analyze user’s search intent
➤Take advantage of your website analytics
2. Branching out: expanding your keyword list
➤Fetching keywords with modifiers
➤Getting keywords with an autocomplete feature
➤Getting keywords using a full-text search algorithm
3. Measuring keyword potential
➤Exploring the search volume
➤How do you get search volume for keywords?
➤Keyword difficulty and how to assess it
4. Filtering and prioritizing keywords in your list
➤How do you weed out irrelevant keywords using filters?
➤Prioritizing high-potential keywords
5. Continuous keyword optimization
Conclusion
What is data-driven keyword research and why is it crucial?
Organic search is the primary source of traffic for e-commerce websites. According to Reboot research, at least 43% of all e-commerce traffic comes from Google’s organic search. Keyword research allows you to tap into this significant traffic source, ensuring your website ranks well for relevant search terms.
Data-driven keyword research leverages an analytical approach to find and include the most relevant keywords in your keyword list. This method ensures decisions are based on actual data rather than assumptions, leading to higher conversion rates and improved ROI. The main features of data-driven keyword research include:
- Use of advanced keyword data sources, such as databases, API platforms, tools, and so on;
- Deep assessment of keyword metrics like search volume, keyword difficulty and refining them with additional data;
- Use of filters, algorithms, and sorting rules to filter and prioritize keywords in keyword lists;
- Analysis of search intent data, categorization of keywords based on SE product or service categories;
- Tracking keyword performance data from website analytics and monitoring keyword metrics changes for continuous performance assessment.
At first sight, data-driven keyword research may seem way more complicated than traditional research, but its benefits are worth investing in.
➤First, operating with actual data allows you to find the so-called “value keywords” with good traffic potential, low competition, and precise matching of user intent. By targeting such keywords, you can attract visitors who are more likely to convert into customers.
➤Secondly, proper assessment of keyword metrics and reliance on various data sources can ensure that your keyword strategy is well-informed and comprehensive. Analyzing metrics such as search volume and keyword difficulty from multiple data sources provides a more accurate picture of keyword viability. This multi-faceted approach helps you identify the best opportunities and avoid potential pitfalls,
➤Using specific approaches to filter and prioritize keywords allows you to focus on the most impactful terms that align with your business goals. Additionally, by applying filters and sorting rules, you can manage large volumes of keywords efficiently, saving time and resources.
➤Data-driven keyword research is necessary for large-scale projects, like keyword optimization of e-commerce websites, because it allows for precise targeting and scalability. E-commerce sites often deal with thousands of products and categories, making traditional keyword research methods insufficient.
➤Finally, approaching keyword research in a data-driven way can significantly improve the ROI of your SEO efforts. By making informed decisions based on concrete data, you can allocate your resources more effectively, focusing on strategies that yield the highest returns.
Now you understand that data-driven keyword research is a tactical necessity and a strategic advantage for e-commerce. Let’s discover how you can implement the data-driven approach to keyword research with our step-by-step checklist!
1Finding the seeds: how to identify your initial keyword pool
The most basic yet essential step is to build a pool of initial keywords, often called “seed keywords.” These define the foundation of your keyword strategy and are used to generate more specific keyword ideas.
Tap into product or service categories
Start by listing the product or service categories that your business provides. Accurately listing your product and service categories is vital for keyword research. Proper categorization ensures your seed keyword list is relevant and targeted.
Product and service categories are special groupings that organize your offerings into logical segments based on their characteristics, functions, or target markets. For instance, Google groups products into categories and subcategories with a category name and code.
For example, if you sell sports nutrition products, the category will be “Sports Nutrition Supplements”, with category code 10118. This category has a parent category, “Vitamins & Supplements”, with code 11772. Within the parent category, you can find other related product categories.
How do I get the list of relevant categories with codes? You can search manually for products and category lists from Google, but there is another option. In DataForSEO Labs API, we already have a complete list of Google product and service categories. You can get it by calling the DataForSEO Labs “Categories” endpoint or downloading the list in a CSV file.
To identify which keywords are relevant to a specific category, you can use DataForSEO Labs “Keywords For Categories” endpoint. This endpoint will provide you with a list of keywords relevant to the specified product categories. Let’s see how you can fetch seed keywords easily with this endpoint using the new DataForSEO Google Sheets Connector. Following our comprehensive guide, you can effortlessly connect DataForSEO endpoints to Google Sheets.
Once you have installed the Google Sheets Connector extension, navigate to Tools — Keyword Suggestions — Keyword Suggestions For Categories via the menu on the right. In the sheet, enter your product categories, specify a location, language, and number of suggestions you want to get. After that, hit the “Run” button to send a request.
Here’s the result. Click the “Save” button to save the result, and you can start again by specifying other categories.
Analyze user’s search intent
Understanding the intent behind user searches is crucial for starting effective keyword research. Search intent refers to the purpose behind a user’s search query and can be broadly categorized into four types:
- Informational – searching for information on a specific topic, like “what is whey protein?”;
- Navigational – finding a particular site or page, for instance, “musclefeast supplements shop”;
- Commercial – researching products or services before deciding, such as “best sporting nutrition shops”;
- Transactional – completing a specific action, such as a purchase, for example, “buy protein bars.”
Defining search intent makes targeting and prioritizing the right keywords easier during research. For instance, you can analyze potential customers’ search terms at different buying cycle stages to capture a comprehensive set of seed keywords.
What methods are used to determine the search intent of keywords? First, it can be identified manually by examining the query language, particularly its semantics and syntax. However, this approach does not provide accurate intent identification. Different queries can blend multiple search intents, making manual classification challenging and often subjective.
A more sophisticated technique involves determining search intent by analyzing the SERP layout and features. This technique involves examining how search engines interpret and respond to specific queries. By looking at the types of results displayed (e.g., product listings, knowledge panels, featured snippets), you can infer the search engine’s understanding of user intent. This approach is usually applied by various SEO tools.
How can you get precise search intent for multiple keywords? For example, you can do that with the help of the DataForSEO Labs Search Intent endpoint. Using this endpoint, you can easily retrieve search intent for up to 1000 keywords in one request. This endpoint employs a custom machine learning algorithm that detects search intent by analyzing both linguistic keyword properties and data from Google SERP.
The “Search Intent” endpoint is also available in the Google Sheets Connector. To access the endpoint, Navigate to Tools — Keyword Suggestions — Search Intent in the menu. In the sheet, enter your keywords, specify a location and language, and click the “Run” button to send a request.
After you get the result, click the “Save” button to save it and start with another list of keywords.
Take advantage of your website’s analytics
If you already have a website for your shop and connect it to Google Search Console, you can fetch some keyword data from there. This can provide insights into what terms people use to find your site. Moreover, you can find essential metrics for keywords your website ranks for that you won’t find anywhere else, like number of clicks by keywords.
You can navigate the Performance section in Google Search Console to find keywords for which your website ranks and their metrics. The “Queries” table shows which keywords have the most clicks, impressions, and average position in search results. This tool also shows organic click-through rates (CTR), helping you gauge the effectiveness of your keywords.
(Image source: SEOPress)
Additionally, Google Search Console has its own API that you can use to discover even more keywords that your website already ranks for. You can get up to 25,000 keywords in one request to Google Search Console API and sort the results by clicks, impressions, and position on SERP.
To access the Google Search API, follow a series of steps within the Google Cloud Platform Console. First, navigate to the console and either create a new project or select an existing one. Once you’re in the project, go to the “APIs & Services” section. There, you’ll need to search for the “Custom Search API” and enable it for your project. After enabling the API, you can create credentials and obtain an API key. This key will allow you to authenticate your requests to the Google Search API. With these steps completed, you’ll be ready to start making API calls.
The keyword data from Google Search Console API is also more precise, and you can fetch data for various time ranges. Using this data, you can outline which terms bring in the most clicks and impressions and include them in your seed list.
There, you’ll need to search for the “Custom Search API” and enable it for your project. After enabling the API, you can create credentials and obtain an API key. This key will allow you to authenticate your requests to the Google Search API. With these steps completed, you’ll be ready to start making API calls.
The keyword data from Google Search Console API is also more precise, and you can fetch data for various time ranges. Using this data, you can outline which terms bring in the most clicks and impressions and include them in your seed list.
2 Branching out: expanding your keyword list
Now that you have created your list of seed keywords, the next step is to expand it with more specific keywords to attract more traffic and leads. We will explore several methods for doing that.
Fetching keywords with modifiers
Start with using keyword modifiers to create variations of your seed keywords. Modifiers can include adjectives, locations, or purposes (e.g., “best plant-based protein,” “affordable vitamin complex,” “sports nutrition for runners”).
You can obtain new keywords with modifiers in different ways. First, you can use the paid or free keyword tools. For example, Google Keyword Planner is a free tool for finding keywords for ad campaigns, but you can also use data from here to expand your keyword list. You can access it by creating a Google Ads account, and you don’t need to start an advertising campaign to do preliminary keyword research. However, the problem is that detailed keyword metrics are unavailable unless you’ve launched advertising campaigns in your Google Ads account.
Here, you can insert your seed keywords and get some additional ideas with modifiers or completely different keywords you haven’t seen before. Additionally, you can review and filter the list to find more relevant keywords.
Another convenient way to pull keywords with modifiers is to use the DataForSEO Google Ads API “Keywords For Keywords” endpoint. This endpoint is based on the Google Ads API and retrieves data directly from it. You can specify up to 20 keywords and get as manyas 2000 keyword suggestions in one request. Besides relevant keywords, this endpoint retrieves keyword-related metrics like search volume and competition metrics. Using this endpoint, you can fetch many keywords to expand your keyword list.
Let’s see how you can fetch keywords with this endpoint. First, make a call to the “Keywords For Keywords” endpoint. You can learn more about how to use DataForSEO API endpoints in our dedicated article.
POST: https://api.dataforseo.com/v3/keywords_data/google_ads/keywords_for_keywords/live
In the response field, specify a language_name, location_code, or location_name and keywords. You can also set a date range using date_from and date_to, and specify sorting options in sort_by field.
The request should be structured like this:
[
{
"location_code": 2840,
"language_name": "English",
"keywords": [
"sports nutrition"
],
"date_from": "2024-03-01",
"date_to": "2024-06-01",
"sort_by": "search_volume"
}
]
The result will return as follows:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "6.3170 sec.",
"cost": 0.075,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07081901-1535-0368-0000-209b6cbae14f",
"status_code": 20000,
"status_message": "Ok.",
"time": "6.2546 sec.",
"cost": 0.075,
"result_count": 1344,
"path": [
"v3",
"keywords_data",
"google_ads",
"keywords_for_keywords",
"live"
],
"data": {
"api": "keywords_data",
"function": "keywords_for_keywords",
"se": "google_ads",
"location_code": 2840,
"language_name": "English",
"keywords": [
"sports nutrition"
],
"date_from": "2024-03-01",
"date_to": "2024-06-01",
"sort_by": "search_volume"
},
"result": [
{
"keyword": "vega protein",
"location_code": 2840,
"language_code": "en",
"search_partners": false,
"competition": "HIGH",
"competition_index": 100,
"search_volume": 22200,
"low_top_of_page_bid": 0.07,
"high_top_of_page_bid": 3.11,
"cpc": 1.52,
"monthly_searches": [
{
"year": 2024,
"month": 5,
"search_volume": 22200
},
{
"year": 2024,
"month": 4,
"search_volume": 22200
},
{
"year": 2024,
"month": 3,
"search_volume": 27100
}
],
"keyword_annotations": {
"concepts": [
{
"name": "vega",
"concept_group": {
"name": "Other Brands",
"type": "OTHER_BRANDS"
}
},
{
"name": "protein powder",
"concept_group": {
"name": "Supplement",
"type": null
}
},
{
"name": "protein",
"concept_group": {
"name": "Nutrient",
"type": null
}
},
{
"name": "powder",
"concept_group": {
"name": "Product",
"type": null
}
}
]
}
},
{
"keyword": "gatorade protein bars",
"location_code": 2840,
"language_code": "en",
"search_partners": false,
"competition": "HIGH",
"competition_index": 100,
"search_volume": 22200,
"low_top_of_page_bid": 0.3,
"high_top_of_page_bid": 2.09,
"cpc": 1,
"monthly_searches": [
{
"year": 2024,
"month": 5,
"search_volume": 18100
},
{
"year": 2024,
"month": 4,
"search_volume": 22200
},
{
"year": 2024,
"month": 3,
"search_volume": 22200
}
],
"keyword_annotations": {
"concepts": [
{
"name": "gatorade",
"concept_group": {
"name": "Other Brands",
"type": "OTHER_BRANDS"
}
},
{
"name": "protein",
"concept_group": {
"name": "Nutrient",
"type": null
}
}
]
}
},
{
"keyword": "zeus nutrition creatine",
"location_code": 2840,
"language_code": "en",
"search_partners": false,
"competition": null,
"competition_index": null,
"search_volume": 0,
"low_top_of_page_bid": null,
"high_top_of_page_bid": null,
"cpc": null,
"monthly_searches": [
{
"year": 2024,
"month": 5,
"search_volume": 0
},
{
"year": 2024,
"month": 4,
"search_volume": 0
},
{
"year": 2024,
"month": 3,
"search_volume": 0
}
],
"keyword_annotations": {
"concepts": [
{
"name": "Non-Brands",
"concept_group": {
"name": "Non-Brands",
"type": "NON_BRAND"
}
},
{
"name": "creatine",
"concept_group": {
"name": "Supplement",
"type": null
}
}
]
}
}
]
}
]
}
You can then copy the result and metrics for further elaboration or start with another list of seed keywords.
Getting keywords with an autocomplete feature
Using the autocomplete feature is also an effective way to enrich your list with additional keywords. It is present in different search engines and generates queries based on the user’s real-time input.
For example, you can insert keyword phrases in the Google search bar, use modifiers, or point the cursor in different parts of the keyword phrase to get various results. To get more relevant results for e-commerce, you can also use the autocomplete feature of major existing online retailers, like Amazon.
If you want to use autocomplete for large-scale keyword research, you will probably need immense amounts of data. Manual scraping is time-consuming, and you need technical expertise to avoid Google anti-scraping measures.
To avoid these difficulties, you can use DataForSEO’s Google Autocomplete API. With this API, you can access autocomplete data programmatically and nearly instantly obtain large amounts. Google Autocomplete API is also easy to use and cost-effective, especially for large-scale keyword research.
Getting keywords using a full-text search algorithm
Another popular method for extending a keyword list is a full-text search algorithm. It is a technique used to search for documents or records in a database by examining the words within each document or record. Unlike simple keyword searches, full-text search allows users to find relevant information based on the entire content of documents. Topics, phrasing, citation, or additional text attributes are considered in full-text search.
A full-text search requires gathering a large collection of texts related to your niche and reviewing them. Given the volume of text data involved, you should create a structured database and use specific algorithms to analyze it and extract relevant keyword ideas.
But in DataForSEO, we created a solution that frees you from all this complicated work. With the DataForSEO Labs “Keyword Suggestions” (Similar Keywords) endpoint, based on a full-text search algorithm, you can easily get a list of relevant keywords. The endpoint returns only those search terms that contain the keyword you set in the request with additional words before, after, or within the specified keyword.
You can also use this endpoint with our Google Sheets Connector to quickly get the results. First, navigate to Tools—Keyword Suggestions—Similar Keywords. Then, specify seed keywords, location, language, and the number of suggestions you want to get. Once you are done, click the “Run” button.
With the DataForSEO Labs Keyword Suggestions endpoint, you can get a structured list of search queries that include your seed keyword.
3Measuring keyword potential
After building your keyword list, measure each keyword’s potential to ensure you target the most effective terms. Measuring keyword potential is vital for assessing which of the keywords in your keyword list are most likely to drive valuable traffic and conversions to your website.
Acquiring data on keyword metrics is the primary step in evaluating a keyword’s potential. Let’s explore some of the significant keyword metrics, what they represent, and how they are estimated.
Exploring the search volume
First, the search volume of keywords is used to estimate how many searches for a certain keyword took place within a certain timeframe. The primary sources of the search volume data are Google and Bing. They provide search volume data for the past month, so it is usually measured monthly. For instance, search volume can be pulled from Google Ads via the Google Ads API. Search volume can be refined with other types of information, like keyword impressions, to provide more realistic numbers.
Another source for estimating search volume is clickstream data. It is information collected while a user navigates the Internet and captures terms that the user enters in the search engine, the sequence of pages visited, and interactions such as clicks. Clickstream data is retrieved from various plugins, extensions, and other applications.
Clickstream data is then refined and combined with special coefficients to estimate the search volume. Clickstream-based search volume can also be used to accurately calculate the keyword’s overall search volume.
How do you get search volume for keywords?
You can pull search volume using various approaches. Usually, search volume can be extracted directly from Google Ads API, but to do that, you need to obtain a developer token. Using SEO tools is also an option, but the quality of search volume values may vary from tool to tool, depending on the approach used to estimate them.
DataForSEO also offers a solution to retrieve search volume values with the “Search Volume” endpoint of the DataForSEO Keywords Data API. This solution is based on data from Google Ads, so you can effortlessly get keyword search volume without starting an advertising campaign and without the limitations of Google Ads.
To get search volume data quickly, you can connect this endpoint to Google Sheets, but in an even more convenient way, using our integration with the Make.com platform. With these tools, you can create custom data flows effortlessly. You just need to create a scenario for the Search Volume endpoint, connect it to the sheet with keywords, and then run the scenario to get the search volume.
Here is what the scenario looks like in Make.com:
Here is an example result in Google Sheets:
Following our integration guide, you can easily pull keyword search volume to Google Sheets.
Keyword difficulty and how to assess it
After evaluating the search volume of keywords, you also must consider that it may be hard for a website to rank for certain keywords, especially with a high search volume. The keyword difficulty metric helps to identify keywords with good traffic potential and low competition. It generally indicates how challenging it is to rank in the top 10 organic results for a specific keyword. In the DataForSEO Labs “Bulk Keyword Difficulty” endpoint, the keyword difficulty score is calculated by analyzing the ranking of the top 10 websites by certain keywords and assessing the Domain Rank and Page Rank for each result. This metric is typically expressed as a value from 0 to 100, where 0 means virtually no competition, and 100 indicates exceptionally high competition.
Let’s explain how to use the DataForSEO Labs “Bulk Keyword Difficulty” endpoint to assess keyword difficulty. This endpoint provides the keyword difficulty metric for up to 1,000 keywords in a single API request, making it highly convenient for large-scale keyword research.
First, call the Bulk Keyword Difficulty endpoint:
POST: https://api.dataforseo.com/v3/dataforseo_labs/google/bulk_keyword_difficulty/live
Specify the location_name, language_name, and up to 1000 keywords in the keywords array.
Request example:
[
{
"location_code": 2840,
"language_code": "en",
"keywords": [
"sports nutrition",
"vegan protein",
"food supplement shop",
"plant based protein"
]
}
]
After that, you will get the result in JSON:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.0891 sec.",
"cost": 0.0104,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07081905-1535-0392-0000-2d5b77992ada",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.0315 sec.",
"cost": 0.0104,
"result_count": 1,
"path": [
"v3",
"dataforseo_labs",
"google",
"bulk_keyword_difficulty",
"live"
],
"data": {
"api": "dataforseo_labs",
"function": "bulk_keyword_difficulty",
"se_type": "google",
"location_code": 2840,
"language_code": "en",
"keywords": [
"sports nutrition",
"vegan protein",
"food supplement shop",
"plant based protein"
]
},
"result": [
{
"se_type": "google",
"location_code": 2840,
"language_code": "en",
"total_count": 4,
"items_count": 4,
"items": [
{
"se_type": "google",
"keyword": "food supplement shop",
"keyword_difficulty": 100
},
{
"se_type": "google",
"keyword": "plant based protein",
"keyword_difficulty": 57
},
{
"se_type": "google",
"keyword": "sports nutrition",
"keyword_difficulty": 59
},
{
"se_type": "google",
"keyword": "vegan protein",
"keyword_difficulty": 52
}
]
}
]
}
]
}
In the items array, you can find the objects containing the keyword and its difficulty score.
Here, we can see that the keyword “food supplement shop” has a high difficulty score of 95, indicating that it will be tough to rank by this search term. On the other hand, the keyword “sports nutrition” has a significantly lower difficulty score of 58.
3Filtering and prioritizing keywords in your list
Subsequently, you need to filter out irrelevant keywords and find ones that can drive you traffic. Let’s see in detail which keywords should be excluded first.
➤Keywords with very low search volume should generally be avoided. These terms indicate that very few people, if any, are searching for them. While there might be exceptions for niche topics, investing time and resources into targeting keywords that only some people search for is inefficient.
➤Keywords that don’t match specific search intent. Even if a keyword has a high search volume, it may need to align with what users are looking for or what you’re offering. For instance, if you are selling sports nutrition, a keyword phrase with informational intent, “what is sports nutrition” might not directly lead to sales if you’re primarily focusing on e-commerce.
➤Keywords that don’t match certain product categories. Including keywords related to your industry that don’t directly correspond to what you sell or provide can lead to mismatched expectations. If your sports nutrition shop does not sell energy drinks or vitamin complexes, you should filter them out of your list.
➤Keywords with very high difficulty score. Keywords with extremely high difficulty scores, especially those dominated by major authoritative websites or brands, should be cautiously approached. These keywords are often highly competitive and may require significant time, effort, and resources to rank for, especially if your website is relatively new or has lower domain authority. While it’s unnecessary to avoid all high-difficulty keywords, it’s often more strategic to focus on a mix of medium-difficulty keywords and long-tail variations that are more attainable.
How do you weed out irrelevant keywords using filters?
How do you filter out your keyword list according to these recommendations? Using the endpoints of the DataForSEO API, you can apply filters and sorting rules to get a list of matching keywords in the result.
Let’s see how you can get a list of relevant keywords using filters in the “Keyword Ideas” endpoint of DataForSEO Labs API. For instance, you want to get keywords with a search volume above 200 and a difficulty score below 50, matching the transactional search intent and specific product category (in this case, “Sports Nutrition Supplements”).
To do that, specify the seed keywords, location, and language in the request field. You can also set the closely_variants parameter to true to get keywords based on the phrase-match search algorithm. If you want to specify the number of keywords you want to get in the response, use the limit parameter.
Then, in the filters array, apply the following filters:
["keyword_info.search_volume",">",200]
["keyword_properties.keyword_difficulty","
["search_intent_info.main_intent", "=", "transactional"]
["keyword_info.categories","in",[10118]
Finally, order the keywords by search volume in ascending order and difficulty score in descending order using "order_by":["keyword_info.search_volume,desc","keyword_properties.keyword_difficulty,asc"].
The request should be structured like this:
[
{
"keywords": [
"whey protein"
],
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"closely_variants": true,
"filters": [
[
"keyword_info.search_volume",
">",
200
],
"and",
[
"keyword_properties.keyword_difficulty",
"
After sending the request, you will get the following result:
{
"version": "0.1.20240626",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.1804 sec.",
"cost": 0.011,
"tasks_count": 1,
"tasks_error": 0,
"tasks": [
{
"id": "07081910-1535-0400-0000-58fb16586240",
"status_code": 20000,
"status_message": "Ok.",
"time": "0.1237 sec.",
"cost": 0.011,
"result_count": 1,
"path": [
"v3",
"dataforseo_labs",
"google",
"keyword_ideas",
"live"
],
"data": {
"api": "dataforseo_labs",
"function": "keyword_ideas",
"se_type": "google",
"keywords": [
"whey protein"
],
"location_code": 2840,
"language_code": "en",
"include_serp_info": true,
"closely_variants": true,
"filters": [
[
"keyword_info.search_volume",
">",
200
],
"and",
[
"keyword_properties.keyword_difficulty",
"
Prioritizing high-potential keywords
You can start picking high-potential keywords after getting a list of relevant keywords. But how do you figure out which keywords have the potential?
First, consider so-called “long-tail keywords”. These are longer and more specific keyword phrases that visitors are more likely to use when they are closer to the point of purchase or when they use voice search. Long-tail keywords might have lower search volumes than short-tail ones but often have higher conversion rates because they capture more specific intent.
For instance, instead of targeting the highly competitive keyword “whey protein," you might target a long-tail keyword like "post workout whey protein." This keyword is more specific and likely to attract visitors who know precisely what they want, thus increasing the chances of conversion. To get long-tail keywords first in the results list, you can, for example, order the results in the Keyword Ideas endpoint by ascending search volume or apply a search volume range using ["keyword_info.search_volume",">", value1], “and”, ["keyword_info.search_volume"," in filters.
Another effective strategy is to focus on question-based keywords. These often align well with user intent and can be excellent for capturing traffic from voice searches and featured snippets. For example, instead of just targeting "protein powder," you might target "what is the best protein powder for muscle gain?". To retrieve question-based keywords from the DataForSEO labs Keyword Ideas endpoint, you can apply filter ["keyword", "like", "%what%"] in the filters array.
Lastly, don't overlook the power of branded keywords combined with product categories or features. If you sell, for example, sports nutrition supplements of certain brands, you might target keywords that combine brand names with specific product types or benefits. For instance, "optimum nutrition whey protein for muscle gain" or "myprotein vegan protein powder" could be effective keywords. These combinations often have lower competition than generic terms while still attracting highly targeted traffic. To filter out branded keywords combination in the API response, apply a filter ["keyword", "like", "%name of the brand%"].
5Continuous keyword optimization
Finally, once you have a well-developed keyword pool and have optimized your website content, remember that keyword optimization is an ongoing, dynamic process. Continuously developing and refining your keyword strategy and website content is essential to staying ahead of the competition. Here are important tips to consider:
➤Regularly track the performance of keywords you already rank for. Use tools like Google Analytics and Google Search Console to monitor changes in impressions, click-through rates, and website visits to identify any issues or progress. You can set up custom reports in Google Analytics to track these key metrics.
➤Track changes in keyword metrics. Tracking changes in keyword rankings, search volume, and other metrics is also crucial. Various keyword tools are available for this purpose. By monitoring your keyword rankings, you can quickly identify any drops and take action accordingly.
➤Analyze user interaction metrics of your website. Understanding how users interact with your site once they arrive is crucial for optimizing your content and user experience. By analyzing metrics such as bounce rates and engagement levels, you can gain insights into how well your site meets user expectations. High bounce rates or low engagement indicate that visitors are not finding what they are looking for or that the content needs to be more compelling to keep them interested. This feedback suggests a need for content optimization.
➤Monitor competitors’ keyword performance. Regularly analyze your competitors' keywords to identify gaps and opportunities. This information can guide your keyword selection and content development to outperform your competition. For this purpose, you can use the DataForSEO Labs API Ranked Keywords endpoint to get broad data on competitors' keywords.
➤Don’t forget about content updates. Regularly update and refresh your existing content to keep it relevant and engaging. Search engines favor fresh content, and updating old posts with new information and keywords can improve your rankings. Conduct a content audit to identify outdated or underperforming content that could benefit from a refresh.
Conclusion
Effective keyword research in the e-commerce industry can be challenging but achievable. The key to success lies in adopting a data-driven approach, focusing on keyword potential, and avoiding random assumptions.
Leveraging deep assessment of keyword metrics, fetching data from various reliable sources, and refining it will yield the most precise results. A sophisticated approach to filtering keywords based on advanced filtering techniques and sorting algorithms enables you to identify high-potential keywords quickly. Grouping keywords by categories and assessing the search intent properly will ensure that your content aligns with what users are actively seeking. That is what data-driven keyword research is all about.
This checklist can be your roadmap to achieving top search results for your e-commerce website. However, to maximize its effectiveness, you need to leverage the power of data-driven SEO tools.
Luckily, in DataForSEO, we have a comprehensive set of APIs for in-depth keyword research and more:
- Keyword Data API for finding new keyword opportunities and search volume;
- DataForSEO Labs Bulk Keyword Difficulty to assess keyword difficulty;
- Ranked Keywords to get data on competitors' keywords;
- Search Intent endpoint for detailed assessment of keywords’ search intent.
Embrace the power of our APIs now and win the e-commerce competition!