Datapeople Reviews & Product Details

- Good formatting - Good recommendations - Simple and nice layout that helps structure a JD

- I find the 'scores' you have to hit, and the kind of words/phrases which are highlighted as being 'not recommended' are too limiting for what most companies need to write

I think Job Description management is what i find most useful about DataPeople. The Diversity recruitment aspect can be a little limiting due to the bar required to hit the score - which can end up causing the JD to be too vague.

Intelligent application that helps you to optmize your jobavertisements regarding differents variables like understaning, diversity, title ect.. Due that its based on AI, it makes it relly easy and understandable to optimize.

I work in Germany and most of our jobposts we still post in German language. However, the tool is designed and optimized for the English language, which makes it a bit cumbersome to optimize the ads in other languages accordingly.

- perfect length of jobposts - diversity optimized language - better titles - better, more targeted expression - useful hastags --> good starting point to optimize the ads with the hiring managers, because the tool shows you very clearly and well-founded what there is to optimize.

-Inclusive language -Similar UI to Textio

-Some suggestions for hard skills don't make sense (i.e. Microsoft Excel) -Needs more vocabulary or phrase suggestions (Textio had more features) -GH integration was clunky (messed up formatting) so it's easier to just copy and paste and not use the sync feature -When collaborating with Hiring Managers, it's not syncing properly so we have been moving off of DataPeople and making edits to JD on a Google Doc instead -Some Hiring Managers don't like that it shows who the role reports to because they can get a lot of outreach from external agencies

Using inclusive language in JDs

The ease of creating specifications with premade templates makes it easier to focus on the content of the advert. Once defined, datapeople compliant templates are in place it can really smooth out the process.

Sometimes Datapeople will flag some terminology which is specific to roles as not compliant. This then brings down your score so a function to ignore the suggestions would be a useful addition.

Datapeople allows for easy removal of phrases/words that would put people off applying for positions. Often this is useful as it would be difficult without these highlighted to locate them if looking at a block of text.

Datapeople provides some great suggestions on how to improve the quality of writing in our job descriptions, and use more inclusive language that will appeal to a wider audience and improve the diversity of our recruitment pipelines. I work in a large team with multiple recruiters, and having some uniformity in our job posts goes a long way in improving employer brand perception. We now have standardised templates that share information on key topics such as our commitment to diversity and inclusion, and company policies and benefits.

The suggested omission of soft skills from the role description (e.g. verbal communication, ability to prioritise, attention to detail) can cause frustration with hiring managers, particularly for project-focused roles for which there aren't many measurable role requirements. Managers often like to include these soft skills to provide a better flavour for what the role will entail.

Improving quality of writing: provides suggestions on how to improve the quality of writing in our job descriptions, and use more inclusive language that will appeal to a wider audience and improve the diversity of our recruitment pipelines. Enabling us to save compliant job descriptions that are standardised across the recruitment function: I work in a large team with multiple recruiters, and having some uniformity in our job posts goes a long way in improving employer brand perception. We now have standardised templates that share information on key topics such as our commitment to diversity and inclusion, and company policies and benefits.

I think the overall core functions of the product work well. Knowing our postings are more inclusive is reassuring. It's intuitive on how to improve the score of postings, and it doesn't take long to get your posting your target score.

The most common suggestion is that our job postings are too long. However, that is largely due to our diversity statement and including compensation information on the job post. My more recent postings have earned scores in the ~70 range (we require a min. score of 85) but if I delete the two mentioned sections, the score jumps to 90+. Personally, I don't think those sections should count. They're not describing the job per se. It also is frustrating that our score is dinged for not including them.

It tells us how inclusive or to what quality our job postings currently are. Inbound applications usually hold the lowest signal-to-noise ratio so anything we can do to increase their quality is meaningful.

This helps when writing content with multiple contributors.

The functionality could be expanded, and the rationale is questionable at times.It would be awesome if this was integrated into our ATS and maybe even our outlook.

Standardizing and templating job descriptions and messaging.

language recognition + automated suggestion of wording and phrases that fit better to the candidate pool adressed

not 100% clear when and where the created job ad is posted after finalising it

seamlessly creating new job ads while addressing the right candidate audience using the right language to get their attention

I think Datapeople has a good mission and purpose, I like the idea of using AI to help my teams write better and more equitable job descriptions. The UX /UI is solid and very easy to use

I think Datapeople needs some work on the corrections and suggestions for what to take out. When there is a line in a JD about "analytical skills" or "communication skills," Datapeople tells us that it's too ambiguous and we should remove it. However, there are obviously jobs that truly do require these skills. I understand that the goal is to remove vagueness, but I think there needs to be more clear suggestions of what can be used instead rather than ust saying that we shouldn't use "analytical skills." A positive example of this would be the suggestions for "Excel skills," I like that there are 3 separate suggestions listed of specific Excel skills. That is the kind of suggestion that is truly helpful rather than the ones that just tell us to remove an important skill for the role.

Making job descriptions more clear and more appealing to candidates, especially including underrepresented minority groups. This is really important to me and my company.

User friendly, "dummy proof, and clean interface

Often times making a lot of different suggested tweaks make minimal or no difference the score when it states that the description is "too long" is not helpful if it is indeed hard requirements - not clear if this means that reducing the content will make a higher score? this is not clear It would be ideal to default to your postings, not everyone else on the recruiting team's, it is more noise to funnel through

D&I in having more inclusive language

feedback on inclusive language and see how others have written in the past

it takes a while to write a job description

inclusivity

Usability - easy to read and format. Only takes a few minutes to begin working through it. I also like the way it explains the suggestions and rationalizes the benefit of being more inclusive.

There is no way to inform the tool that its suggestions are "wrong." Some language cannot be changed without innately changing the description of the role. This is particularly true for very technical roles where some of the languages refers to coding languages, tools, or industry-known acronyms. I wish we could click a button to add certain phrases as a stored database.

I don't personally have enough data to answer this. Its intent is to increase our diversity pipeline by making our language more inclusive. I would need more time to assess the tool to see against previous tools/processes, are we seeing a growth in diversity representation in inbound apps and throughout the hiring process.

That it gives clear suggestions on things to do to improve a job posting's language and length. It also has helpful suggestions along the way as you're editing. It also is publicly shared so other people have access to the job postings as well.

It takes a bit of time to get a handle on the application and how it works. But once you do, it's pretty straightforward. Some of the editing options are a bit clunky but they work.

Making sure that job postings have neutral language that is attractive to as many candidates as possible and doesn't disqualify someone before they even apply which gets us more applicants at the end of the day.

It provides good guardrails for HMs and helps us make more concise job posts.

The formatting is too restrictive and doesn't port over to Lever very well. The whole lever integration is pretty clunky in general. It flags terms as "bad" that are actually important to the job posting. The scoring system can seem arbitrary at times, for example changing one word took my posting from a score in the 70s to the 80s, but that word was part of the team name, so not really something I want to change.

It helps us write more concise job postings.

Checks for general biases and allows an understandable CTA.

UX is not as intuitive as other tools (e.g. Textio).

See above - helpful to avoid unconscious biases.