Live outbound voice AI campaign for one of Australia's largest registered training organisations, targeting lapsed student leads across multiple course categories and all Australian states.
A genuine conversation means the student spoke substantively — real engagement, not a brief hello before hanging up. That definition matters for understanding where the real conversion opportunity sits.
| Stage | Rate |
|---|---|
| Total database called | 100% |
| Did not connect (voicemail or no answer) | 83% — the gap SMS and WhatsApp closes |
| Phone answered | 17% answer rate |
| Genuine two-way conversation | 6.7% of answered calls |
| Conversation without booking | 74% of conversations |
| Confirmed advisor appointment booked | 26.1% of genuine conversations |
Conversion quality is strong. When Claire gets a student into a genuine conversation, she books one in four. The challenge to solve is reach. That is exactly what the SMS and WhatsApp pipeline addresses.
Morning calls (9am to 12pm) and afternoon calls (3pm to 6pm) both showed the strongest genuine conversation rates. Evening calls produced higher answer rates but lower engagement — students picked up but were less ready to talk.
NT and TAS both showed standout genuine conversation rates from answered calls. NSW and VIC led on volume with solid engagement. State-level performance informs how we weight call scheduling each week.
Students who answered but could not talk were offered a callback at a time of their choosing. Student-initiated callbacks sit outside standard telemarketing hour restrictions, so Claire can follow up evenings and weekends.
| Day | Answer rate | Conversation rate | Bookings |
|---|---|---|---|
| Monday | 15.0% | 18.3% | Strong |
| Tuesday | 15.1% | 15.4% | Low |
| Wednesday | 23.4% | 5.8% | Moderate |
| Thursday | 16.6% | 8.9% | Low |
| Friday | 15.3% | 14.6% | Strong |
| Saturday | 13.6% | 8.2% | Low |
| Time slot | Answer rate | Conversation rate | Bookings |
|---|---|---|---|
| 9am to 12pm | 15.3% | 11.6% | Highest |
| 12pm to 3pm | 13.8% | 9.1% | Low |
| 3pm to 6pm | 15.6% | 11.6% | High |
| 6pm to 8pm | 25.9% | 3.6% | Very low |
Every week we review call timing, lead age cohorts, course category performance, and state-level engagement. The campaign parameters update accordingly so each successive week performs better than the last.
The biggest lever we identified early: lead age matters. Students whose original enquiry is over two years old respond differently to the opening conversation than students who enquired recently. We now run separate script variants by lead age cohort, which has improved genuine conversation rates meaningfully.
The second lever is channel coverage. Voice alone only reaches the students who happen to answer. SMS warm-up sequences before a call and WhatsApp follow-ups after significantly increase the proportion of the database that ever enters a real conversation with Claire.
| Optimisation | Why |
|---|---|
| Reduce evening calls by 50% | High answer rate but very low genuine conversation rate after hours |
| Prioritise high-performing lead sources | Some lead sources show nearly triple the conversation rate of others |
| Script variants by lead age | Two-year-old leads need a different opening than recent enquiries |
| Weight morning and early afternoon slots | Consistently outperform evening calls on conversation rate |
| Focus on highest-converting course categories | Mental Health and Education leads show standout engagement rates |
Book a 30-minute call. We'll walk through this data, map out a campaign for your leads, and show you what a pilot looks like in practice.