E-commerce has evolved in many ways and now makes online shopping easier for modern-day customers. In 2019, an estimated 1.92 billion people purchased goods or services online. The number is predicted to grow between 2019 and 2021, from 1.92 billion to 2.14 billion. Online shopping became even more popular in 2020 because of store closures and shoppers’ fear of contracting the COVID-19 in public. Statistics show that the e-commerce field is on the rise, meaning that more and more businesses are selling their products and services online.
However, becoming more visible for customers in the top e-commerce marketplaces requires in-depth research and knowledge. Developing and maintaining an e-commerce SEO strategy may help sellers do a better marketing job. Web scraping is an essential part of keyword research for e-commerce. It helps to collect large amounts of public data for keyword analysis. However, gathering and maintaining data comes with challenges.
What is e-commerce keyword research?
Keyword research for top e-commerce marketplaces is part of an SEO strategy. The process helps to find the search terms sellers use to rank higher and get more traffic to their product or service pages. When sellers choose keywords for top e-commerce marketplaces, they explore how customers discover things they want to buy. Usually, sellers make a business keyword list that is relevant to their products and categories.
Importance of keyword research
Thoughtful research can provide sellers with information about:
- competitors and their actions;
- ideas for content marketing;
- understanding of consumer trends;
- insights into their customers needs.
However, the research includes more than constantly discovering new product keywords. It is also essential for sellers to track keywords’ performance and analyze the history of multiple keywords that would allow making data driven decisions. Understanding how search algorithms work in e-commerce platforms can be a tremendous driving force for business growth.
Types of e-commerce keywords
By now, you should have a decent idea why keyword research is important. It is essential to note a few most common types of e-commerce keywords: product and service details, competitors keywords, and audience terms. We will dig deeper into each of these types to understand what public data can be collected for keyword analysis.
Product and service keywords
Product or service description is essential for several reasons. First of all, it is an opportunity for sellers to interest the customer in buying the product or service. Second, it is a place to use keywords sellers could not fit in the product title. Without optimizing titles and descriptions with relevant keywords, the product page will have fewer chances to appear in the search results.
Sellers use keywords that make their product (or services) relevant to the queries potential clients are searching. Collecting public data on how specific search results change with different queries help sellers understand which keywords to use in descriptions.
Keywords and terms that competitors use can also provide valuable insights. Sellers have to constantly monitor their competition to be aware of what is happening in their market.
Knowing what keywords and terms helped competitors make it to the top of the search results can help build a successful keyword strategy.
Sellers collect public data about their competitors from top e-commerce websites. However, it is important to note that this data has to be used only for analysis, not for copying their content or other malicious intents.
Audience terms reveal a variety of additional interests that sellers might never have guessed to convert well for their products or services. Audience terms can add additional value to descriptions and bring more traffic to product pages. For example, if a seller is providing cake decorating products, keywords about presents or parties may be relevant to their customers as well.
Of course, it is not possible to include all the keywords in the description. This is why top e-commerce platforms have additional fields in seller accounts, where sellers can enter their “hidden keywords.”
The magic behind finding what keywords can be used is simple: collecting public data and analyzing it. Analyzing how specific search results change with different queries is the most common way to do it.
Search engine vs. e-commerce keywords research
Top e-commerce marketplaces index information and use various factors to determine what pages show in the product search results. Even if search engines are based on different technologies, they work similarly. Basically, leading e-commerce websites can be described as search engines as well. In fact, a consumer survey has shown that more US digital shoppers start their product searches on Amazon rather than Google.
The most common way to find relevant keywords for web search and e-commerce platforms is by entering different search terms, and gathering found public data. Therefore, sellers usually combine results from search engines and top e-commerce websites for more in-depth analysis.
Web scraping for e-commerce keyword research
Simply put, web scraping is a widely used method to gather public information from e-commerce websites. Data gathering bots automatically request and extract data from target websites. Web scraping unlocks an ability to collect data on a large scale in a short period of time.
For sellers who want to ensure their products are ranking high, gathering public data from relevant categories is enough because analyzing their competitors in rankings may increase their revenue. In this case, it is more than enough to use in-house web scrapers powered up by the right proxy type to ensure a smooth data collection process.
However, sellers usually outsource e-commerce scraping services that gather and provide relevant e-commerce data because they lack knowledge and resources or want to save time. Service providers are constantly collecting data for their customers, and they face various challenges due to the amount of data required.
E-commerce scraping challenges
Collecting data on a large scale from leading e-commerce marketplaces is a complicated task. Gathering and maintaining vast amounts of data requires a lot of resources and knowledge. We outlined the most common challenges service providers may face.
- Overcoming bot detection measures. Top e-commerce websites usually implement security measures that block malicious bots. These measures typically cannot distinguish good bots from malicious ones because bots can share similar characteristics. Therefore, good web scraping bots that collect information about e-commerce keywords are often mistakenly flagged as bad, making blocks inevitable.
- Accessing geo-restricted data. When service providers collect data on a large scale for their clients, they need to access e-commerce keywords data regardless of its geo-location. Otherwise, their keyword research loses its value. However, specific keyword information may not be accessible from different regions.
- Processing gathered information. To provide structured and relevant information about e-commerce keywords for their clients, service providers have to process collected data. This process is called data parsing. However, data parsing is complicated when it comes to large-scale web scraping because of the constant layout changes of leading e-commerce marketplaces.
Solutions to deal with e-commerce scraping challenges
Dealing with data gathering challenges may be difficult. However, there are a few ways how service providers choose to approach web scraping.
Suppose service providers choose to use their in-house web scrapers. In that case, it is essential to note that almost all web scraping projects are impossible without proxies, especially when dealing with large-scale data operations. Proxies unlock content worldwide, meaning that all the data is accessible regardless of its geo-location. They are also used to avoid IP blocks. Residential proxies are less likely to get blocked due to their origin.
It is also important to remember that the more data collection process mimics an organic user, the lower are the chances of being blocked.
If service providers choose to outsource third-party web scraping services, they can dedicate more time to providing their clients with an in-depth e-commerce keyword and ranking analysis. Dealing with web scraping challenges will be on their third-party provider’s side. For example, web crawler tools like Real-Time Crawler can get accurate data effortlessly and keep web scraping costs low because clients are paying only for successful e-commerce data delivery.
However, sometimes outsourcing this kind of service may seem costly, and finding a reliable provider may take some time. Each company has to evaluate its resources, budget, and needs before deciding which approach suits them best.
Online shopping is becoming increasingly popular every year. Gathering data from leading e-commerce marketplaces and learning how to use keywords can help sellers make data-driven decisions, rank higher on search results, and improve content strategy. This leads to increased customer count and revenue.
The process of gathering public e-commerce data on a large scale is challenging. Dealing with anti-bot measures, processing vast amounts of data, and accessing geo-restricted data are just a few of many challenges. Reliable proxies or quality data extraction tools can help facilitate this process. However, companies have to decide which approach is best for them: using and maintaining in-house web scrapers or outsourcing third-party tools.