A method to draw in exceptional talent is by crafting compelling job listings.However, numerous elements contribute to formulating a successful job listing. For example, you need to ensure the JD is gender neutral, devoid of exclusionary terminology, consistent, and easily comprehensible.This is where a text analysis tool becomes invaluable. These instruments assist in reducing bias in your job listing language, enhancing readability, expediting your JD crafting process, and generating uniform, compliant JD templates with minimal effort, among other features.
Therefore, in this piece, we’ll discuss reasons why you ought to utilize text analysis software for composing JDs, particularly if you’re hiring more than 50 individuals annually.
1) To Examine How Your Job Listings Stack Up Against Competitors
An effective text analysis tool evaluates your job listings against the industry regarding:
- Total Score (a rating composed of gender bias, readability, word count, etc.)
- Gender Bias
- Readability
You can observe that the company below holds a superior total score (61.88/100 compared to the industry average of 55.36) but still has potential for enhancement in Gender Bias and Readability.
2) To Identify Gender Bias in Your Job Listings
A reliable job listing text analysis tool assists you with gender bias in at least a few manners:
GENDER-NEUTRAL % AND SCORE IN DASHBOARD
A text analysis tool features a dashboard displaying the gender bias percentage of all your JDs. It illustrates gender bias by department/function, hiring manager, location, recruiter, and more.
This approach allows you to zoom out and recognize where the gender bias issues exist.
HIGHLIGHTS GENDER-BIASED TERMINOLOGY
For instance, Ongig Text Analyzer marks instances of feminine words (in yellow) and masculine words (in red).
In addition, you also find a “gender score” for each job listing.
SUGGESTS GENDER-NEUTRAL ALTERNATIVES
After highlighting the gender-biased terminology in your job listing, a text analysis tool goes further to provide synonyms so you have a replacement for the gender-biased terms with just a few clicks.
For example, in the JD below, the term “an expert” is flagged as masculine. Thus, 6 alternative terms are proposed for substitution:
GENDER-NEUTRAL LANGUAGE SCORE UPDATES
When you substitute gender-biased terminology with gender-neutral phrases, a text analysis software updates your gender neutrality score in real-time.
This way, you can monitor when you’ve achieved your target of eliminating gender bias.
For instance, in the JD below, the 100 “Gender Score” alongside the green icon of a figure indicates the JD is now gender-neutral.
3) To Evaluate How (Un)Readable Your Job Ads Are
A useful job listing text analysis tool informs you:
- An Average Reading Grade Level — As I mentioned several months ago, busy candidates are often the best fit and they tend to prefer reading at a very basic grade level (see “Why I Craft my Job Listings at the 8th Grade Level”). For example, the job listing below is articulated at the 14.4th grade level. The text analysis tool suggests reducing the number of words and sentences.
- An overall assessment of the readability of the job listing is also provided.
4) To Rectify Lengthy Sentences in Your Job Listings
Most job listings comprise sentences that exceed necessity.
A text analysis tool identifies these sentences so you can divide them and maintain the reader’s interest.
5) To Identify Superfluous Words in Your Job Listings
Most job listings include words that are unnecessary.
A few examples are “complicated words” and adverbs.
Complicated Words
For instance, this JD below employs the phrase “in order to”. Ongig’s Text Analyzer identifies “in order to” as a complicated term due to having a synonym (“to”) that saves you 3 syllables.
Did you know that many of the top candidates globally contend with a learning disability such as dyslexia? Furthermore, many of them get distracted after encountering a few multi-syllable words.
I often see job listings filled with numerous “complicated words.” Thus removing/reducing these “complicated words” can have a substantial impact!
Save candidates’ time and they’ll offer you their attention in return!
Adverbs
Many job listings also tend to contain an excess of adverbs, exemplified by the JD ad below for a Data Scientist filled with adverbs (the underlined words).
Ongig’s Text Analyzer shows that 6.8% of the words in the job listing below are adverbs. Consequently, it assigns a low adverb score to the job listing.
(7.2/100) since the adverbs fail to contribute any significance.
You can usually remove an adverb from a sentence, and the meaning stays unchanged. Being concise is always beneficial when composing job postings.
Thus, an effective job description text analysis tool emphasizes complex vocabulary and adverbs, allowing you to opt for their removal or modification. The most effective text analyzers also assist you in handling job postings and provide real-time, inline suggestions.
There exist several other superfluous words/phrases (such as passive voice) which I will examine in a future article.
For additional advice on crafting job descriptions, explore How to Craft a Job Description — Recommended Practices & Examples.
6) Composing Bias-Free JDs (Beyond Gender)
A reliable job description text analysis tool assists you in monitoring more than just gender-biased terminology in your JDs.
Biased terminology in a JD can disturb a candidate based on their ethnicity, age, ethnicity, disability, or other distinctions.
For example, some instances of non-gender-biased terminology we’ve frequently discovered in job postings include:
- “Master-slave”: Certain database engineer job postings utilize this expression to describe a database architecture. An inclusive alternative could be “primary/replica.”
- “Digital Native”: It’s preferable to focus on the skill instead of using this phrase as it introduces age bias. A better alternative might be “familiarity with Instagram.”
- “Crippled”: It’s more suitable to say “a person with a disability.”
And additional non-inclusive and derogatory terms we’ve identified in JDs.
For example, the job description below contains covert bias with the common term “brown bag sessions.”
This phrase has been employed for many years in job descriptions, but research reveals it’s associated with racism and colorism (historically, individuals used to assess the shade of a person’s skin by holding a brown paper bag to their face… If their face was darker than the bag, they faced rejection from some societal groups).
The image below illustrates how the Ongig Text Analyzer software highlights “brown bag” and proposes alternative phrases such as “learning session” or “sack lunch,” which promote inclusivity. This is particularly crucial when aiming to attract (and not alienate) individuals from underrepresented backgrounds:
Furthermore, Ongig’s Text Analyzer aids you in removing other forms of concealed bias beyond racial bias such as:
- Age bias
- LGBTQ+ (sexual orientation)
- Disability bias
- Neurodiversity bias
- Elitism bias
- Ethnic bias (multicultural bias)
- and more
7) Proposing SEO-Friendly Job Description Titles
Optimizing job descriptions for SEO assists job hunters in locating them effortlessly. Additionally, it clarifies to candidates precisely what the position entails and the kind of individuals you seek.
Most text analysis tools offer an “SEO Title Score” feature. This indicates that the text analyzer examines job titles and contrasts them with what potential candidates search for each month on Google.
Moreover, you will receive an integrated suggestion advising you to:
“Maintain your title to between 1 and 3 words, and 20 characters or fewer. This way, your job title will be more accessible for search engines (SEO) and enhance candidate application rates.”
8) Developing Custom Job Description Templates
Drafting job descriptions from the ground up requires time. However, with templates, you’ll save time on revisions and modifications.
Additionally, employing templates prevents you from overlooking crucial information and ensures consistency.
A job description template also accelerates your JD workflow. Particularly when hiring in high volumes (see image below).
Thus, a proficient job description text analysis tool utilizes AI and automation to assist in creating job description templates for scale, speed, and inclusivity.
The text analyzer also enables you to establish scoring targets like “readability” or “diversity” according to your hiring objectives while constructing the JD templates.
For instance, if you want to enhance the readability of your JDs, set your “readability” objective to an 8th-grade reading level (or lower).
Once
after you’ve constructed your job description templates, the text analyzer should provide you with additional suggestions on:
For more comprehensive guidance on crafting a JD template utilizing Ongig, click here.
9) To Edit and Refresh Job Descriptions
Job descriptions evolve over time due to new organizational practices, updated roles, technological advancements, and even shifts in industry trends.
Moreover, the manual method of editing and refreshing job descriptions is susceptible to mistakes and is laborious. Important details of your JD may also be overlooked.
Through manual editing and updating, you also cannot swiftly observe the alterations made.
This is where a text analyzer tool becomes essential, equipped with version control that allows you to monitor, adjust, edit, and assess all iterations of your JD.
With the text analyzer, you receive:
- Version comparisons: The text analyzer allows you to identify the distinctions between two iterations of your job descriptions. Thus, JD modifications can be thoroughly assessed, reducing miscommunications.
- Rollback capabilities: The version control feature permits you to revert to a prior job description version if unintended changes or mistakes occur. Therefore, you can effortlessly restore the correct version.
- Audit trails: Utilizing version control provides you with a detailed audit trail of your JDs. This allows you to observe any modifications in your job descriptions, such as the user, date, time, and specific alterations made.
By visualizing the entire process of updating and revising job descriptions, anyone on the recruitment team can grasp the rationale behind any modifications.
10) Offering Centralized Storage for JDs
If you continue utilizing the manual JD drafting process, your JDs are likely buried within your company’s Word documents and shared drives.
This also complicates the editing and collaboration efforts in writing job descriptions.
However, with an effective job description text analyzer tool, all your JDs are consolidated in one location. This can be a centralized cloud repository where the documents are organized in a file folder rather than being dispersed.
In this manner, it becomes effortless to verify that all your organization’s JDs conform to standardized formats, language, content criteria, and best practices.
11) To Generate Consistent Job Descriptions Swiftly
Drafting job descriptions manually is labor-intensive and takes considerable time. The likelihood of producing a job description that omits crucial JD sections is significant.
An effective job description is devoid of tedious industry jargon and convoluted language. Additionally, it should uphold consistency, comply with labor regulations, be racially inclusive, gender-neutral, and more.
Thus, a proficient text analyzer tool accelerates your JD writing process in the following ways:
- The text analyzer software utilizes AI automation to assist you throughout the JD creation, updating, editing, modification, approval, and publication stages.
- Provides pre-filled content, enabling you to avoid starting your job description from square one. The text analyzer employs content libraries and pre-existing templates to auto-fill specific JD sections and fields.
- Employs advanced intelligent suggestions to enhance the efficacy of your job descriptions. For instance, the text analyzer proposes appropriate job title lengths and highlights any essential JD sections you may have overlooked.
For example, Ongig’s Text Analyzer expedites your JD writing process by:
- AI-Assisted Job Description Creation: Ongig’s Text Analyzer simplifies the task of drafting your job descriptions from scratch. Just input your job title and the tool employs AI technology to handle the rest.
- Template Builder — Utilize straightforward 4-step templates to rapidly create your job descriptions.
- Streamlined User Management — The software accommodates as many users as needed with varying user permissions for crafting your job descriptions (such as Administrator, Editor, Auditor, and Editor+)
Content Optimization:
- Minimizing Bias: Mitigating bias is vital in today’s hiring environment. Ongig’s Text Analyzer’s “Optimize Content” function reduces gender bias to ensure the development of inclusive job descriptions.
- JD Score Enhancement: Witness your job description’s score improving as our Text Analyzer’s AI refines your JD draft.
- Exclusionary Word Elimination: The tool guarantees your JD is devoid of any exclusionary and discriminatory terminology by removing any identified “exclusionary words and phrases”.
By leveraging the features of text analyzer platforms, you expedite your JD creation process and attract qualified candidates.
12) To Streamline the Job Description Approval Workflow Process
The manual JD approval workflow is lengthy. Before you publish your job description, it needs to navigate through various personnel in the hiring team for approval before progressing.
For example, the hiring manager may initiate the job submission process. The talent acquisition lead could commence drafting the JD. Then, another individual in the diversity recruitment department might authorize the job posting. This manual approval workflow often leads to unnecessary delays.
A text analyzer tool simplifies this submission and approval flow by providing a “user controls” capability.
This ensures the job description is composed, edited, updated, modified, and approved promptly.
Thus, the text analyzer tool enables you to:
- Establish Access Control: With the text analyzer platform, every team member involved in writing the job description has
- Particular Authorizations to Carry Out the Procedure Promptly: For example, HR leaders may possess the capability to create the initial drafts. The talent acquisition heads may oversee templates and JD formatting guidelines. Meanwhile, the HR professionals might hold the ultimate decision-making power.
- Straightforward User Administration Process: Utilizing the text analyzer, you are able to establish an “Administrator” role to oversee the user profiles of those engaged in the JD drafting process. This way, no individual interferes with another’s responsibilities. Thus, everybody within the team can complete their tasks efficiently. Additionally, you can incorporate new members into the system seamlessly.
With this streamlined collaboration workflow, the job descriptions within your organization are published punctually.
Frequent Errors to Steer Clear of When Utilizing a Text Analyzer Tool
While employing text analyzer tools, it’s simple to stumble into a few recurring mistakes. Thus, here are some errors to be cautious about.
Excessive Dependence on Automated Recommendations
One of the most typical errors individuals commit is placing too much trust in automated recommendations. Instruments that offer sentiment analysis or keyword extraction, for instance, are incredibly beneficial. However, they should not substitute human discretion.
Text analysis applications can recognize central themes, but they may not fully grasp the intricacies of a given text. Machine learning and deep learning frameworks are potent, yet they occasionally miss crucial contextual elements or tone. This is particularly relevant with unstructured textual data, such as customer feedback or social media content.
Therefore, rather than merely accepting recommendations, dedicate the time to evaluate and modify them based on the specific requirements of your project. Whether handling customer satisfaction surveys, market analysis, or support inquiries, your own text must embody human insight, not solely the results of a text analysis tool.
Neglecting Context or Human Aspects in Writing
Another error is disregarding the context or human aspects in writing. Text mining and topic modeling can emphasize common words and their frequencies in extended texts, such as news articles or academic papers. Nonetheless, these tools may overlook subtle nuances or the deeper significance of the text.
For instance, word clouds or keyword prominence metrics can indicate which terms appear most often. However, they do not always encapsulate the principal ideas or interpretive approaches within the text. This is where human discernment becomes vital.
Context plays a crucial role across various domains, from document classification to regular expressions. Hence, consider text analysis software that evaluates a collection of terms from a specific era. Without acknowledging the historical or cultural backdrop, the analysis may not yield substantial insights. Similarly, in legal documents or business intelligence reports, comprehending the context can be the key distinction between achieving better results and falling short.
Whether you’re utilizing cloud-based APIs, open-source solutions like Voyant Tools, or robust platforms like IBM Watson Natural Language Understanding, always remember to merge machine-derived insights with human intuition. In this manner, you ensure that your text analysis yields meaningful, precise, and valuable results.
This harmonious approach aids in circumventing common missteps. It also guarantees that your engagement with text analytics tools produces real-time, data-informed decisions that genuinely elevate the customer experience, enhance readability ratings, and provide text analytics insights that are both actionable and pertinent.
WHY I COMPOSED THIS:
Ongig’s objective is to bolster your commitment to crafting the finest job descriptions. Composing an effective job description is essential for attracting and hiring exceptional talent. Schedule a demo today to discover how to create impactful job descriptions using our Text Analyzer tool.