Welcome!
Learn more about the Textmetrics augmented writing tool:
- Smart Writing Assistant description & features
- Randstad HR Services case study
- BCR & ROI back-of-the-envelope calculations
- Technical information regarding the AI that powers the tool
To see how Textmetrics could work in your organization:
AI Smart Writing Assistant
- Writing tool analyzes text for reading complexity, DEI issues, formality, sophistication, style guide and preferences.
- Generates improvements and assists staff in writing high-quality content. It reads and assesses while the content is being written and offers suggestions to improve the text.
- AI-based algorithms recognize content characteristics such as readability for intended audience, how friendly, amicable, neutral, feminine, masculine, etc.
AI Smart Writing Assistant Features
- Readability – CEFR
- DEI module from Extanto
- Gender message balancing
- Accessibility WCAG standards
- Customizable to clients standards(corporate guidelines, publishers standards, learning objectives)
- Translates text across 12 languages in real time.
HR Job Description Case Study
Randstad
Job description must communicate core values clearly:
- Use language & important elements to attract right candidates
- Make descriptions simple
- Make job description easily found on internet
- Must match Randstad branding
This is a complex collection of language factors hard to apply correctly 100% of the time.
Textmetrics analyzes all elements that will increase conversion:
- Gives recruiter suggestions to maximize success of JD
- Uniform voice- AI uses corporate branding and marketing guidelines in suggestions
- Trains recruiters how to write effective job descriptions
- Attracts more diverse, higher quality field of candidates
Randstad recognized a 30% increase in efficiency using Textmetrics augmented writing tools.
Back-of-the-envelope calculations for BCR & ROI
Assumptions regarding our calculations:
- Size of company: 1000 employees
- # of HR employees (assuming 1.4 HR employees per 100 employees): 14 employees
- HR annual Costs: $1.3M (avg. salary of $85,000 each + benefits)
- Recruitment Costs (~15% of HR annual costs) = $196k
- Time Savings have been a range of 14-30 % for past clients. For our purposes we’ll use 22%.
- Time Savings(~22% of Recruitment Costs) = $43k
Benefit Cost Ratio/ Return On Investment
For a company with ~1k employees and estimated time savings of $43k, we calculate
BCR of 2.26:1 and ROI = 126%
Schedule a meeting to discuss how we came to these results.
How? The Technical Component
NLP: Natural Language Processing
- Natural Language Processing is the scientific study of language by a computer or AI.
- It is the method by which large amounts of text are consumed and analyzed for the purposes of identifying predictive patterns that facilitate the understanding and effect of the language.
- This NLP was developed by integrating university linguistic studies based on text learning analytics, text mining and AI.
AI: Machine Learning
- Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.
- Machine learning is then used to crawl big data sources (internet, Wikipedia, newspapers and other publications), ingesting sufficient data to enable the model to learn and evolve.
For an opportunity to see Textmetrics in action