FAQ

Here's what our process looks like:

• The recruiter provides us with a job description.
• Our AI then extracts the key hard and soft skills data, the education, employment, location information, as well as any other important criteria present in the JD.
• To ensure greater accuracy, it then expands on this list of keywords by generating synonyms.
• The AI then turns this list into requests that search multiple online sources for profiles that contain these keywords and synonyms.
• As a quality control measure, the AI simultaneously checks that the candidates in these profiles also have a LinkedIn presence.
• The ones that do are then ranked in order of relevance, based on the number of matching criteria.
• The top matches are then collated on a shortlist for the recruiter to screen.

We use a combination of public data sources, such as LinkedIn, job boards, professional websites, social media sites, and more.

The AI’s screening process is as accurate as the job description it uses as a basis for the requests that search multiple online sources for profiles that contain the same words and synonyms. Relevance is determined by the number of keywords and synonyms profiles and job descriptions have in common. The more matches, the more relevant a candidate is. Fewer matches obviously mean that a candidate is less relevant. You will find the most relevant candidates always at the top of your list for manual screening. Depending on the number of candidates you have requested, candidates might/will become less relevant as you go down the list.

The system removes any demographic identifiers from the job description at the same time as it extracts the key hard and soft skills data, the education, employment, and location information, as well as any other important criteria present in the JD. The AI uses only this information to generate a list of keyword and synonym-based requests that search the web for candidate profiles that contain the same keywords and synonyms. This is the only criteria by which candidates are matched, ranked for relevance and presented to you for manual screening.

When our AI finds new candidates, it simultaneously checks your database to see whether the new entry is indeed unique or if it matches an existing profile. It uses standard identifying data like name, contact details, etc. If there is a match, it won’t create a new profile. If the candidate is unique, it will. The same happens when our AI is updating profiles with new data. When the algorithm searches finds data on your candidates from sources across the web, it simultaneously checks it against the data you have. If there are any matches, it won’t add them to your profiles. If it’s unique, it will.

Every time you use our software you are fine-tuning and improving it. This is how it continually improves itself based on your needs. As a result, there is no requirement for you to adjust or alter it from an engineering perspective

No – our online web form is specifically designed to be as user-friendly as possible. You can also have two options in terms of how you might want to use the products – either through the PitchMe website or the ‘PitchMe’ tab in your Bullhorn ATS.

Yes. Check out our Case Studies page for more information.

On the rare occasion that the software can’t source the number of candidates you requested, we will email the CSV file that includes a list of the candidates that we did find. The email will also invite you to loosen the parameters and run the search again should you wish to generate a list of candidates that matches the number initially requested. We will only charge you for the number of candidates delivered.

On the very rare occasion that the software can’t source any suitable candidates for a specific role, we will email, notifying you of this and advising that you loosen the parameters and run the search again. We will only charge you for the number of candidates delivered.

The PitchMe tool identifies relevant keywords and synonyms associated with the job requirements. This involves understanding not just the literal meaning of words but also their context within the job description. It also utilises skill mapping, which goes beyond simply matching skills precisely to keywords. Skills mapping builds a proximity-based skills map, using the skills present on the CV to locate adjacent skills. For example, if software developers who are skilled in X also tend to have skill Y, our product will predict that during the process. This level of complexity ensures that a comprehensive profile of any candidate can be obtained, regardless of how common or niche the role might be. PitchMe’s tool has been incredibly effective in supplying high-value candidates for niche roles, as evidenced by this case study.