The company, which was founded back in 2016, has built a cross-platform chatbot to automate candidate support and increase efficiency around hiring by applying machine learning and natural language processing for what it dubs “talent interaction”.
The target customers are large enterprises with Jobpal offering the product as a managed service.
For these employers the pitch is increased efficiency by being able to rapidly respond to and engage potential job applicants whenever they’re reaching out for more info via an always-on channel (i.e. the chatbot) which is primed to respond to common questions.
Candidates can also apply for vacancies via the Jobpal chatbot by answering a series of questions in the familiar messaging thread format. Jobpal says its chatbot can also be used to screen applicants’ CVs and recommend the most promising candidates.
It takes care of the logistical legwork of scheduling interview appointments — leaving HR departments with more time to spend on more meaningful portions of the recruitment process.
Co-founder and CEO Luc Dudler tells TechCrunch it has more than 30 enterprise clients at this stage, generating “thousands of conversations” per day. Customers he name checks include the likes of Airbus, Deutsche Telekom and McDonald’s.
The software works on popular messaging platforms including WhatsApp, Facebook Messenger, WeChat and SMS, and is available in 15+ languages — though Jobpal confirms the German market remains its largest so far.
“The sheer volume of interest and number of questions enterprises receive from prospective talent is often difficult to deal with, which results in a suboptimal experience and frustrated candidates. Conversational interfaces and Natural Language Processing enable us to deliver a candidate-centric experience and increase the efficiency of the recruiting function,” says Dudler, arguing that the recruitment landscape has become “candidate first” — putting the onus on enterprises to get the “candidate experience” right.
“This technology allows employers to engage with candidates when they want and on the platforms they use, such as WhatsApp. This gives control to the candidates, meaning they can get answers in a matter of seconds, instead of days or weeks. For Internal HR teams, they can spend time more time finding the best talent, as jobpal automates tedious and time-consuming tasks, allowing recruitment teams to focus on more value-add tasks.”
“We focus mainly on communication and engagement, and our customers only do in-house recruitment. We don’t work with agencies,” he adds.
Jobpal points to increased engagement from use of its chatbot — claiming companies are seeing more queries from jobseekers than they used to receive emails, as well as arguing the “low-friction” approach is accessible and convenient and leads to increased conversion rates.
With any automated process there could be a risk of biased and unequitable outcomes — depending on the criteria the chatbot is using to sift candidates. Although Jobpal says it’s not using algorithms to take recruitment decisions, so the biggest bias risk looks to be in the hands of the employers setting the criteria.
Misinterpretation of candidates’ queries based on the technology failing to understand what’s being asked could potentially lead to responses that disproportionately disadvantage certain applicants. Though Jobpal says queries that are too complex are routed to a human to deal with.
“We get a lot of queries about the application process/deadline/evaluation, qualifications needed, supporting documents, working hours, growth options and salary that Jobpal is designed to deal with,” says Dudler, of Jobpal candidate users. “Our chatbots don’t answer questions that are too personal, too obscure or anything non-recruitment related such as customer service queries.”
“Jobpal stores the query data but it’s de-associated from the candidate data. This data is used to train AI models which supports general communication as well as company-specific chatbots. We don’t mine or sell candidate profiles, and we don’t do algorithmic decision making in the recruitment process,” he adds.
The software integrates with a number of enterprise Human Capital Management suites at this point, including SAP SuccessFactors, Workday, Oracle (formerly Taleo), Avature and Smartrecruiters.
The seed round follows what Dudler couches as “a huge increase in demand” — with the team spying an opportunity for further growth.
“We’ll be investing in product development and tripling our headcount in the next 12 months. Specifically, we are looking to recruit a VP of marketing,” he tells us.
Chatbots still strike many consumers as robotic — and even irritating — but the technology has nonetheless been flourishing in the customer support and recruitment space for several years now. Business areas where there’s no shortage of repetitive tasks for automating. And where being able to offer some level of service 24/7 is a major plus.
On the hiring front, the power imbalance between employer and job applicant might even make interfacing with a bot more appealing for a candidate than the pressure of talking to an actual human who already works at the target employer.
For certain types of jobs employee churn can also be incredibly high — making hiring essentially a neverending task. Again, chatbots are a natural fit in such a scenario; being scalable, they take the strain out of repeat and formulaic conversations — with the promise of a smooth pipeline of candidate conversions.
Given all that there’s now no shortage of recruitment chatbots touting automated support for HR departments. At the same time there’s unlikely to ever be a one-size fits all approach to the hiring problem. It’s a multifaceted, multi-dimensional challenge on account of the spectrum of work that exists and jobs to be filled, and indeed the human variety of jobseekers.
This is why there are so many different ‘flavors’ and ‘styles’ of chatbots offering to assist, some with algorithmic matching, and/or targeting different types of employers and/or jobs/industry (or indeed jobseekers; passive vs active) — others just super basic tools (such as the Jobo bot which alerts jobseekers to vacancies matching criteria they’ve specified).
Some more sophisticated chatbot examples include MeetFrank (passive job matching); Mya (for recruiting agencies and massive enterprises, including for shift filling); Vahan (low skilled, blue-collar job-matching for high attrition delivery jobs); and AllyO (conversational AI for “end-to-end HR management”).
With so much chatbot competition pledging to ‘streamline recruitment’ by applying automation to the hiring task, employers might be forgiven for thinking they have a fresh choice headache on their hands.
But for startups applying AI technology to ‘fix recruitment’ by making talk cheap (and structured), the patchwork of players and approaches still in play suggests there’s ongoing opportunity to grab a slice of a truly massive market.