When Jobr got started in 2014, it was positioned as the “Tinder for jobs.” At a time when mobile job-search and recruiting was beginning to emerge, Jobr was poised to disrupt incumbent players with its mobile-first, consumer-friendly approach.

Monster was one of these incumbents. As a longtime leader in the jobs space in the desktop web era, Monster, like the other leading incumbents, struggled to make real headway on mobile.

Monster faced a problem with three possible solutions—invest in the existing mobile experience, build a new app from scratch, or acquire a strong up-and-comer in the field. That’s when Monster acquired Jobr and set out to create a more fluid mobile recruiting experience rooted in two-way conversations.

Jobr’s goal has always been to own the top of the funnel for both employers and job seekers. As a two-sided marketplace, getting the experience right for both sides was critical to achieving product-market fit, and in order to do that, job seekers and job posters needed to find value in the service soon after their on boarding to Jobr.

Jobr’s apps are focused on sparking that initial match between job seekers and recruiters and facilitating the conversation. On the employer side, that means either posting jobs and receiving applications or messaging candidates directly. On the candidate side, it means applying to jobs through the core Monster job search app, now powered by Jobr.

Building a Consumer-Grade, Cross-Platform Messaging Experience

Jobr started with a couple messaging systems built in-house and unapologetically clunky . After surviving a few months on a bare-bones MVP without push notifications, the company hired an engineer with experience building messaging systems in the XMPP days to build something more robust. That solution worked decently well in the early on, but it became clear that scaling the system beyond iOS to Android and desktop web and expanding their functionality would become unmanageable.

“Even though you have protocols like XMPP that are well defined, it still takes quite a lot to develop and maintain.” – Hari Anath, Jobr CTO

After deciding to move beyond build and towards buy, Jobr came across Layer. While it was still early days for Layer, the Jobr team took note of the ease of integration, usable APIs and open-source UI components. They found Layer’s integration team extremely helpful and responsive as they got messaging up and running, and were able to ship a smooth employer-seeker conversation experience across their different platforms relatively easily.

Iterating and Discovering New Valuable Conversations

After facing some challenges with liquidity in their two-sided marketplace – there were too many job seekers and not enough job posters – Jobr moved quickly on its feet to temporarily remove the job poster side of their experience and instead partner with other job boards such as Monster, Career Builder and Zip Recruiter for the supply side. In doing so, they temporarily put the two-way conversation experience between posters and job seekers on hold.

But Layer conversations wouldn’t be left out of the app for long. As Jobr began to scale their growth and customer success efforts, they started to think deeply about how to optimize the user experience to drive higher customer satisfaction and, ultimately, higher App Store ratings. As most app marketers are aware, strong App Store ratings heavily influence app store install conversion rates, and ultimately drive down the cost of customer acquisition – an incredibly important metric for a young company to manage.

As a means of listening to users’ issues and helping them resolve them, Jobr implemented a “Career Concierge” feature whereby app users could message a Jobr employee for support, feedback and troubleshooting. Leveraging Layer’s newly-minted Web SDK, Jobr quickly whipped up a messaging interface for their employees to talk to their users directly. They began using this channel as a way to gather customer feedback, address issues, and ask for positive App Store ratings from happy users.

After about a month of experimentation and a rapidly improving App Store rating, the team decided the project was both working and worth automating to an extent. After initially implementing some keyboard shortcuts based around common tasks, the team decided to task their in-house data scientist to build a bot to handle common interactions. Using standard python libraries for natural-language processing and their own training data, the Jobr team was able to stand up a proprietary bot delivered via a Layer conversation in about a week for version 1.

They identified a handful of positive messages like “thanks love the app” and then prompted users to rate the app 5 stars. They also found a few common questions that impacted the user experience and provided automated answers like “Have you tried using search?” and “Have you toggled your filters?” When the bot couldn’t confidently come up with a response, it would ping the Jobr customer feedback Slack channel with the dilemma, and a Jobr employee could either select the appropriate response from the bots list of most related options (training it in the process) or take over the conversation completely.

As a result of their concierge bot strategy, Jobr were quickly able to successfully automate responses to 40% of the inquiries that came through the concierge conversation. Today, the bot is able to take on the personality of 6 different Jobr employees, handle 10-15 different types of questions and automate nearly 80% of concierge inquiries. Their app is consistently rated over 4 stars in the App Store, indicating both a highly satisfied user base and driving down the cost of customer acquisition.

When, after the Monster acquisition, Jobr brought back the employer side of their service as “Jobr for Business,” the Career Concierge expanded to include a “Recruiter Concierge” to help employers navigate their side of the experience. By mixing automation with a human touch, Jobr was able to establish a powerful, direct relationship with both sides of their marketplace.

Back to the Basics: Two-Way Conversations

Since the beginning of Jobr, minimizing the time to value for both sides of the job search experience has been crucial. As a mobile-first innovator in the job search space, Jobr understood intuitively from day one the value of instant gratification, and in a job search context, that meant getting into a conversation with a qualified potential employee or employer as quickly as possible – and with as few taps. When Jobr reintroduced the employer product as Jobr for Business, they brought back employer-seeker messaging and put it at the core of the experience.

The magic moment here is referred to internally as “two-way conversations” or conversations where both participants have sent a message. Conversations are the natural next step after a match is made (something we learned long ago with Tinder) and represent real, tangible value to both sides of the marketplace in terms of moving closer to their goals – hiring a candidate or or finding a job.

On the employer side, Jobr tracks both the time it takes to enter into a qualified two-way conversation from the top of the funnel as well as the number of two-way conversations a user is engaging in. Conversations are even built directly into the monetization flow, as the Jobr for Business app is free to download and setup with a paywall when you try to send a message to a prospect.

Jobr is now a crucial part of Monster.com’s strategy on mobile, and as pioneers in the mobile job search space, they are investing in the conversations that make their service valuable.

If you’re hiring and want to try out Jobr’s employer solution you can sign up for a free trial here.

If you want to learn more about the Layer customer conversation platform and what it can do for your business, contact us today for a free demo.