2 weeks of beta — What our users are saying
In the current scenario, a company’s success in meeting their business growth objectives is dependent on its ability to find, attract and hire talent. The Param.ai team has always been passionate about helping companies hire better and faster. With this mission in mind, we launched the stand-alone hiring platform two weeks ago, to a private beta. The product was received well, and here’s some of the great feedback we received from our users.
Finding top candidates within seconds:
With the number of incoming applications in response to job ads, it would sometimes be a few days before we could get to a good candidate. And as we all know, good candidates don’t stay on the job market for too long. Param helped find us great candidates immediately, so we could start engaging the candidate we might have lost out on.
Saving screening time:
Screening resumes takes me anywhere between 0.5–2 hours every day depending on what position I’m hiring for. Param has cut down the time spent on screening resumes by 70%. Param ranking is almost always accurate, helping me use the time I saved on screening on more important tasks like engaging with candidates, or working on strategic initiatives.
Screening is more objective and unbiased:
Recruiters tend to be influenced by the hiring managers’ biases/preferences while screening/hiring for open positions. This sometimes results in candidates getting screened out solely based on the college they went to (or didn’t) or the companies they worked for. With screening purely based on the skills required for the job, we saw a lot more candidates getting shortlisted for the next round. These candidates would have otherwise been screened out or rejected by either the recruiters or the hiring managers because of the biases.
Data wins over gut-instinct:
Param’s candidate relevance score and skill matching has helped me go to a hiring manager with objective data on why I think a candidate is a good fit. Param’s machine learning model matches the candidate’s skills to those listed in the job description, helping remove guess work while shortlisting candidates based on ‘instinct’ or the ‘candidate’s pedigree’ which was mostly the norm so far.
Job & candidate recommendations - the best feature:
The most favourite feature by far has been the recommendations feature. Param recommends suitable jobs for the candidate other than the one he/she has applied for or been tagged to. This helps recruiters engage the candidate for the most suitable job, helping the candidate find the best role for them, which also has a bearing on the offer to joining ratios.
The feature also recommends candidates to jobs. Which means that if Job A has 10 candidates tagged to it, another candidate tagged to Job B who might be suitable for Job A is also highlighted as a prospect to the recruiter. This helps the recruiter prevent losing out on ‘candidates applying to the wrong job’. This was one big limitation of the ATS that Param has helped solve.
We look forward to delighting more users during the beta. If you’d like to know more about the product, or would like to schedule a demo, please write to us at hello@param.ai
