SayonE Technologies

SayonE Technologies

Sayone Technologies is a company based in India that uses web crawling technology to provide its services. The company mainly deals with the provision of services, such as the development of primary software applications. Clients are assisted in designing, developing, and implementing software models at significantly lower costs and timely delivery of their models. To find these clients, Sayone Technologies uses visualization and web crawling techniques. The organization has an efficient team of experts in crawling. The team has specialized in crawling, searching for information from the Internet, and integrating it into applications. Besides, the company also provides mobile software and web development services. Of the various types of search technologies, which ones are they utilizing? Sayone uses crawler-based search technology. Primarily, this technology uses a crawler, also referred to as a spider or a bot, to crawl and index new content in a database that is being searched. There are always four initial steps that this search technology follows before finally displaying the search results from different websites:

Crawling- This search technology crawls through the entire web to find the appropriate content, if available, with the help of software known as a spider, bot, or a crawler. With a team of experts, Sayone designs its crawlers (Ellison, Glenn, and Sara Fisher 2009). The frequency of crawling will depend on how the software has been coded. In most cases, it happens after three or four days. Search results will always show new content, depending on how the crawler has been instructed to update content.

Indexing-This happens after crawling. Indexing is the identification of expressions or words that are relevant to what is being searched. The phrases identified are known as keywords. The crawler is designed such that when it does not comprehend the meaning of the content, it ranks it lower when displaying results. This is always solved by optimizing content to ensure that it is understandable. Once the crawler understands the material, it is ranked the highest in the search results.

Calculation of relevancy- The search string is compared with the indexed content from the database. There is always a high probability that more than one piece of content contains the search string. Whenever this happens, the most relevant content is calculated using various algorithms. Every algorithm focuses on different aspects, for example, links, keyword density, Meta-tags, among other elements.

Retrieval of results- This is the final step in web crawling technology. It involves displaying results in a browser, for example, in a specific order. Correctly, the results are shown in the order of their relevancy. The most relevant comes first, while the least pertinent is always displayed last.

Sayone uses crawling technology primarily because it saves on time. With the use of a crawler, this technology automates tasks associated with web page content and code scanning. These tasks would have otherwise consumed a lot of time. Besides, the implementation of this online search technology has the following benefits as indicated by Henzinger (2007):

It archives old copies of sites in HTML files, which are static-This, therefore, means that old and relevant information can be displayed even after many years.

Identifies typos, lousy content, and text-Therefore, users could still find what they were searching for, even after mistyping the content.

Extracts content from different sites and enables users to view them in spreadsheets. With this, users can quickly analyze the results.

They are locating links that are broken. With these links located, technology makes it easier to fix these links.

Performs sanity checks for quality assurance- This ensures that nothing unusual happens whenever a version of a site is released.

Old versions and new versions of sites are compared. Besides, the soon-to-be-live site versions are also compared with already live versions. This ensures the quality of results. A variety of information is extracted, for example, information relating to page Meta tag, headlines, body texts, and tags that describe images.

Pages are tested. Besides, debugging is automated. This makes it possible to identify any errors that may lead to improper functioning of the website.

Any task that a person would have done in a given amount of time, for example, finding relevant information to display after a search, the crawler does it in an automated way. It extensively finds relevant results and presents them within seconds.

Sayone should consider looking into the media and find out what is being said about the organization. It should also reviews industry forums. Besides, the organization could find comments that are posted by its customers on external sites, for example, on social media. Consequently, the organization can reply to them. The team of crawling experts can closely monitor social media sites, for example, Twitter and Facebook, news sites, and industry forums to obtain information on what competitors are saying about them. Such kind of data will be vital to the marketing team of the organization and help in keeping a pulse on the image of the company. Besides, it makes it easier to understand the perceptions of customers regarding the services of the organization.

Target lists- Sayone Technologies could use the crawling technology to conduct an extraction of entities from the website. For instance, the organization needs to reach out to all companies that require their services. A crawler is useful in setting up crawl target websites that offer listings of relevant companies. This pulls information such as contact names, addresses, and phone numbers if they are available. Besides, such kinds of data can be provided in one repository. Upon acquiring this information, the organization could use it as a metric to gauge the position of the organization concerning its objectives.

Avoid duplicate content-Sayone technologies that ought to avoid duplicate content. Repeated content decreases the rate of crawling. Crawlers identify duplicate content very quickly. Consequently, less of their content is recognized, and eventually, the results being lowly ranked when they are displayed. This means that only a few people access them. By avoiding duplicate content, then the rate of crawling is improved. Duplicate content could be between websites and pages (Clay & Esparza, 2011). Sayone Technologies could use resources for content duplication that are available online to check the authenticity of their content.

Providing new and relevant content-Sayone Technologies should regularly update their content. Besides, the content should be appropriate. Content includes anything from videos to images (Clay & Esparza, 2011). Fresh content and relevant content will always be ranked first. Therefore when any search is conducted, then their content can be easily accessed because it appears first in the list.

Optimizing images- Crawlers are not in a position to comprehend pictures directly. Sayone Technologies uses a lot of images in their content. Therefore, they ought to adopt mechanisms such as using alt tags to give a description that crawlers can index. Images become part of search results when they are optimized appropriately. There exist various optimization tools that could be used to realize proper optimization; for example, the Google image sitemap (Clay & Esparza, 2011). With this, crawlers can quickly locate images and consequently, a reasonable amount of traffic from the crawlers. More people can easily access their content.

References

Bughin, J., Corb, L., Manyika, J., Nottebohm, O., Chui, M., de Muller Barbat, B., & Said, R. (2011). The impact of Internet technologies: Search. High Tech Practice. McKinsey&Company.

Clay, B., & Esparza, S. (2011). Search engine optimization all-in-one for dummies. John Wiley & Sons.

Ellison, Glenn, and Sara Fisher Ellison (2009). “Search, obfuscation, and price elasticities on the internet.” Econometrica 77.2, 427-452.

Henzinger, M. (2007). Search technologies for the Internet. Science, 317(5837), 468-471.