Zenjob Chooses ABsmartly Because They Bring the Culture and the Tool

Overview 

Zenjob, a leading jobs marketplace and personnel service provider for part-time employment, recognised that building an experimentation culture would empower their team to continuously test, learn, and refine their business and product strategies with intellectual honesty.  

Zenjob's short-term goals were focused on building traction and maximising the effectiveness of their operations. In the long term, Zenjob aims to foster a robust culture of experimentation across the entire organisation. This means scaling experimentation volume and increasing velocity, as well as creating a knowledge base that can be shared company-wide, ensuring that insights gained from experiments are accessible to everyone. By building this experimentation mindset, Zenjob aims to create a more agile, data-driven organisation where every decision is backed by evidence and every team member can contribute to driving the company’s success. Most of what they do is uncertain, so experimentation is not optional; experimentation is baked into their business strategy.

Challenge 

Finding the Right Partner for Personalised Support

Zenjob wanted to create a culture of experimentation company-wide, not just for a select few “experimenters” in the company. To make it a mindset for the entire team. They were searching for a solution that could provide a holistic approach to experimentation and make results accessible company-wide to democratise adoption. The unlimited platform users aspect of the ABsmartly offering “unlimited and unrestricted collaboration” is ultimately why they chose ABsmartly.

Zenjob had considered other experimentation platforms like Optimizely and LaunchDarkly, but they were looking for a partner to not only enable a experimentation culture but also a tool and team with a deep understanding of Zenjob's marketplace business model because marketplace experimentation is complicated; it’s different from retail or other B2C models. With marketplaces, bids or offers start and end sporadically, unlike retail offers that are mostly stocked goods that can be replenished. 

Zenjob appreciated ABsmartly’s uniquely personalised experience, including built-in coaching and support as they built and scaled the program, particularly because Zenjob had a relatively inexperienced experimentation team at the time. “What’s most interesting about ABsmartly is the personal touch element. ABsmartly’s built-in coaching and support were very, very important to our decision-making.” said Will Ellis, Zenjob CTO. This one-to-one, human connection and direct line of communication between ABsmartly and customers is hard to find in the industry. Zenjob said, “We enjoy working with ABsmartly on challenges and ideas, them sharing the roadmap and us making input, generally staying connected to us and our experimentation efforts.”

Solution

Building and Scaling the Experimentation Program

Zenjob ultimately chose ABSmartly because they loved the unlimited user access feature, which allows everyone in the organisation—from engineers and data scientists to company leaders—to engage with and understand the experiment results without the cumbersome workarounds or cost to add platform users that are required by other platforms. “Driving adoption means that everyone can look at experimentation results—we’re not interested in a seat licencing model, unlimited platform users what helped us chose ABsmartly and where it has to be for experimentation culture to thrive”

With ABsmartly, Zenjob began to run 1-2 tests per month, and they intend to scale the program and increase this to 20-30 monthly experiments. Zenjob has a diverse mix of people configuring experiments; a mix of engineers, data analysts, and data scientists, demonstrating that cross-team collaboration is key. 

Benefits

Driving Measurable Improvements in Key Metrics

Even in the early stages of the partnership, Zenjob has seen impressive results from its experimentation efforts. They increased the number of experiments they conducted each month, enabling them to double the number of applications per advertised shift, leading to faster and more efficient job placements.

Zenjob has seen a 5x improvement in the time it takes to receive applications for a newly advertised shift, allowing companies to fill positions more quickly, and their short-term cancellation rate has dropped from 11% to 7%, reducing last-minute disruptions for employers.

Using primarily Group Sequential Testing, allows Zenjob to move faster by requiring fewer visitors to reach statistically significant results. This is particularly important with their size of company and their traffic. Running only Fixed Horizon experiments would slow the program down. 

Zenjob also utilises our Segment.io integration to connect their Customer Data Platform (CDP) with the ABsmartly experimentation tool. Segment helps in unifying user profiles by resolving different identifiers into a single user profile. This is vital for experiments that require tracking user behaviour across different platforms or sessions. Using the Segment integration in their experimentation leads to efficient, accurate, and scalable experiments by streamlining data collection and management, reducing engineering overhead, and enhancing data governance. This ultimately results in faster and more reliable insights from their experiments.

Conclusion

“ABsmartly can generate real value for other companies because they bring the [experimentation] culture, not just the tool.” Zenjob’s successful experimentation program isn’t just about using the ABsmartly tool; it’s about continuous learning and open sharing. Together we host monthly experimentation support meetings to ensure that ABsmartly engineers are always on hand to answer questions and solve problems. “Never underestimate the difficulty of experimentation; the intellectual honesty part is probably the toughest. Many like to tout successes, but are we talking enough about failure? We rely on ABsmartly to bounce ideas off of and advise us in our efforts”.

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