Using AI to help small business users write better job ads
I was responsible for introducing Seeks first AI feature on the employer side of the business. The experiment saw a 6% increase in conversion and had a 36% adoption, and has now been scaled to all of Seeks markets across Australia and Asia.
3 weeks (research & design)
Interaction & visual design
Lead Designer, Manager
The successful variant increased yield by 5.3%
problems
Many small business hirers don't know where to start when writing a job ad, let alone a effective one.
Adoption metrics for performance and premium products hadn't changed despite extensive experimentation to improve the inclusions and pricing.
Writers block
Over 50% of SME users interviewed in past research stated they didn't have clear performance expectations for any of Seeks products.
How can I stand out?
Metrics indicated that users were just defaulting to the cheapest product without considered higher-value, better fit alternatives for their hiring needs.
opportunity
How can we help hirers to create effective job ads & building confidence to complete their purchase?
Our teams ingoing hypothesis was that we could be doing a significant amount more to drive our users to consider higher-value products. We had the constraint of only utilising the existing data points and features available in the current experience, but with flexibility to re-structure their presentation altogether.
5% increase in performance ad adoption
Increase consideration of higher value products by 15%
Ad mix (percentage of different product types purchased)
Time on spend on selection page per user
process
Clearly communicating the problem we wanted to solve
Through cross-functional workshops as well as 8 qualitative research sessions run over 2 days, we landed on 3 key themes that were driving the observed behaviour.
Lack of structure
Lack of confidence
Existing ad selection design
Next I focused on a fast and structured exploration looking at numerous different approaches to design existing ad content in a way that clearly communicated value and resonated with users.
Existing ad selection design
Design explorations
Final designs
Showing restraint in order to ship fast and learn
A key part of preparing for on-platform experimentation was ensuring both variants were clearly differentiated. I emphasising different elements within the product hierarchy across both variants to ensure we could understand specifically what moved the metrics.
Unoptimised hierarchy of information
The current design emphasised price and the product name title, which was encouraging users to make a purchase desicion based on price and not the value received.
No laddering of value
It was unclear to users what they could expect from actually selecting a product. Feature information was positioned below CTA, leading to difficulty comparing product features and inclusions.
Unclear use case for selection
Current designs made it difficult for users to understand why they should pick a particular ad over another with similar terminology being used across products causing confusion.
Results
Relevance and simplicity best resonated with users
We had some exciting results with Variant 1 increasing performance ad adoption by 5.2% and time on page by 20% per visit. This outcome was a fantastic demonstration of the power of user-centred thinking, and has meant the team can isolate specific changes like hierarchy, composition and copy and directly point to their impact on business success.