Building the System from the Ground up
Net Solutions’ team of designers and engineers combed through the details of Sandeep’s wireframes, rolled up their sleeves, and got to work. The User Interface (UI) team created a compelling, modern design for the marketing website that helped VOYlegal stand out in an established field to gain a foothold in the industry.
Simultaneously, they developed the backend system, equipping it with capabilities that impressed experienced recruiters and encouraged them to join the fledgling startup. At the center of those backend features was a core CRM, and the team began by focusing on recruitment workflow solutions that imported job listings and job requirements from existing sources.
In order for the CRM to create true value for Sandeep and his team, it needed to parse profile data from a wide range of sources in a variety of formats—a test the new system passed with flying colors. This helped VOYlegal’s recruiters hit the ground running, since the new system was able to:
- Access data from many different sources (e.g., resumes, job descriptions, the existing CRM)
- Identify key bits of information
- De-duplicate records and specific data
- Integrate all relevant information on the back-end
Once the core features of the Minimum Viable Product (MVP) were in place that empowered recruiters to do their jobs, Net Solutions worked diligently to implement the following features—those that would give the new startup a powerful advantage in their industry.
Conversation Tracking: Effectively tracking conversations between recruiters and candidates was a key component of the new system. Net Solutions updated the system to log all forms of communication with candidates and tie those notes to relevant records. This allowed anyone in the system to get a clear picture of a candidate’s strengths and drives, picking up where the previous recruiter left off and delivering seamless service.
Advanced Search: The search feature in the MVP was very basic, and it took time to search through the vast database. To improve the system, Net Solutions created a Phoenix-based search tool that was quick and powerful.
Beyond that, they improved and expanded the search capabilities, allowing recruiters to conduct:
- Broad-based searches
- Narrow searches
- Everything in between
This meant that a recruiter could search for a candidate based on highly specific criteria. If there were no matches, the recruiter could expand the criteria bit-by-bit, viewing a larger pool of profiles until they found the right mix of candidates.
Powerful Templating System: Net Solutions designed and built a versatile email templating system that would trigger custom emails, targeted to different recipients, based on specific events. This allowed VOYlegal to communicate efficiently and effectively with its customers and candidates while adhering to its branding guidelines.
Market Research: The system tapped into a massive database of job openings, candidates, and related data to create a market research tool that analyzed and presented key metrics in an intuitive manner. VOYlegal now offers market research reports, built from this tool, as a service to their clients.
Candidate Job Search: Net Solutions updated the website to allow candidates to directly search for job listings available through VOYlegal. Not only did this help existing candidates find job opportunities—it attracted new legal professionals to join VOYlegal’s database, increasing their pool of exceptional candidates.
System Maintenance and Upgrades: VOYlegal relied on Net Solutions to perform PHP updates and security fixes. Over time, however, maintaining and building further on the legacy CakePHP implementation began to impact the system’s speed and increase the cost of running it. Based on Net Solutions’ advice, Sandeep decided to update the Laravel & PHP 7 combo with a corresponding update to the MySQL database.
The tech stack update improved the site’s performance, provided additional capabilities thanks to Laravel, and provided the opportunity to update the search from Phoenix to Elastic search as well. This greatly improved the search capabilities and response times of backend searches.
The elastic search tool also allowed for fuzzy matching (i.e., matching based on keywords that are similar to a search criteria, the way Google includes search results for similar words or words with slightly different spellings).