How an AI Chatbot Automatically Registers Prospects for Open Days

The AI chatbot triples open day registration rates compared to forms

The open day registration rate via chatbot reaches 18.4%, compared with 6.2% via a website form and 4.8% via email campaign. The chatbot does not outperform by accident: it detects intent in real time, collects data without friction and sends personalised reminders before the event.

This article walks through the mechanism step by step: how the chatbot identifies a prospect interested in an open day, how it captures the information needed for registration, and how it cuts no-show rates from 52% to 14% through automated follow-up.

If you are new to the topic, our complete AI chatbot guide for schools covers the fundamentals.

Step 1 — Detect open day intent during the conversation

The signals that trigger the registration flow

An AI chatbot does not suggest the open day at random. It detects intent signals in the prospect's questions:

• Direct questions: "When is the next open day?", "Can I visit the campus?"
• Indirect questions: "What are the tuition fees?" followed by "What are the career prospects after graduation?" — a prospect who asks two high-frequency questions (89% and 84% of conversations respectively, based on analysis of 12,000 Skolbot conversations) signals serious interest
• Behavioural signals: programme page visit + admissions page visit + return to the homepage — the prospect is comparing and deliberating

When the chatbot detects one or more of these signals, it naturally proposes the open day as the next step: "The best way to experience the campus and meet the faculty is our next open day on [date]. I can register you in 30 seconds — what is your first name?"

The advantage of conversational timing

A static registration form waits passively for the prospect to find it, fill it in and submit it. The chatbot intervenes at the exact moment when interest is highest — while the prospect is asking questions, while they are engaged. The conversion rate gap (18.4% vs 6.2%) is largely explained by this timing.

Step 2 — Collect registration data without friction

The conversational form

The chatbot transforms a form into a conversation. Instead of presenting six fields at once, it asks questions one at a time, in a logical sequence:

1. First and last name — already started naturally ("What is your first name?")
2. Email — "Where should I send the confirmation?"
3. Phone — "A number so I can send you a reminder the day before?"
4. Programme of interest — often already identified during the conversation
5. Current level of study — to prepare a personalised welcome
6. Plus-one — "Will you be coming alone or with someone?"

The completion rate of a conversational form exceeds that of a standard web form because each question arrives in context. The prospect does not see a wall of fields: they are responding to an interlocutor that takes an interest in their situation.

Handling objections in real time

During data collection, the prospect may hesitate: "I'm not sure I'm free that day." The chatbot responds immediately with alternatives: "We also have a session on [alternative date]. And if neither date works, I can arrange an individual virtual tour." A static form has no capacity to adapt to objections.

Step 3 — Reduce no-shows with automated follow-up

The open day no-show problem

Without reminders, 52% of registered prospects do not attend the open day. This rate drops sharply with an appropriate follow-up strategy:

| Reminder method | No-show rate | |----------------|-------------| | No reminder | 52% | | Email only (D-1) | 38% | | SMS only (D-1) | 31% | | Chatbot personalised follow-up | 19% | | Chatbot + SMS combined | 14% | | With personalised programme reminder | 11% |

(Source: tracking of 4,200 open day registrations across 12 institutions, Oct 2025 – Feb 2026.)

The chatbot's follow-up sequence

The chatbot deploys a three-stage reminder sequence:

D-7: preparation

The chatbot sends a personalised message: "Hi [first name], your open day at [institution] is in one week. You showed interest in the [programme name] programme. Do you have any questions before your visit?" This message reopens the conversation and lets the prospect ask follow-up questions.

D-1: actionable reminder

"Your open day is tomorrow at [time]. Here is the address and directions: [link]. You will meet [programme head name]. Any last-minute questions?" The reminder includes concrete practical information — not a generic message.

D+1: post-event follow-up

For attendees: "How was your visit? Would you like to move forward with your application?" For no-shows: "We missed you yesterday. Would you like an individual visit or a video call?" The chatbot does not lose the connection.

Step 4 — Qualify and hand over to the admissions team

The enriched dossier

After registration and (ideally) attendance, the chatbot passes the admissions team an enriched file containing:

• The registration data collected
• The complete conversation history (questions asked, concerns raised)
• The programme of interest identified
• A prospect maturity score (based on number of interactions, nature of questions, time spent)
• Open day status (registered, attended, absent, rescheduled)

The admissions team does not start from scratch. They resume the conversation where the chatbot left off, with full context. The 7% of cases requiring human support (Source: automatic classification of 12,000 Skolbot conversations, 2025) arrive already qualified and documented.

The measurable impact on the enrolment funnel

From traffic to open day attendance

The chatbot improves every step from website visit to actual attendance:

| Metric | Without chatbot | With chatbot | Improvement | |--------|----------------|-------------|-------------| | Open day registration rate | 6.2% | 18.4% | ×3.0 | | No-show rate | 52% | 14% | −73% | | Website bounce rate | 68% | 41% | −40% | | Prospect return within 7 days | 12% | 34% | ×2.8 |

(Sources: UTM tracking 2025-2026 season, 35 institutions; open day registration tracking, 12 institutions; A/B test, 22 websites; cohort analysis, 8,000 sessions.)

Calculating the net gain

For an institution that runs 4 open days per year with a target of 200 registrations per event:

• Without chatbot: 200 registrations × 6.2% form rate = 12 web registrations × 48% attendance = 6 attendees per event × 4 events = 24 attendees/year via web
• With chatbot: 200 page visitors × 18.4% = 37 registrations × 86% attendance = 32 attendees per event × 4 events = 128 attendees/year via chatbot

The chatbot delivers a 5× increase in qualified open day attendees through the web channel.

For the detailed financial return, see our student chatbot ROI analysis. To understand how reminders reduce open day no-shows, read our article on open day optimisation for schools.

FAQ

Can a chatbot really register a prospect for an open day without human intervention?

Yes. The chatbot detects interest, collects data (first name, email, phone, programme), confirms the registration by email and schedules automated reminders. Human intervention only occurs after the open day, for personalised follow-up with the most advanced candidates.

What no-show rate can be achieved with a chatbot?

The best measured results reach 11% no-show when the chatbot combines personalised follow-up with a programme-specific reminder. The average with chatbot plus SMS is 14%, compared with 52% without any reminder. The key is personalisation: the prospect receives a message that mentions their name, their programme of interest and the name of the person they will meet.

How long does it take to set up the open day scenario on a chatbot?

With Skolbot, the open day scenario is pre-configured and can be activated within a few hours. You need to input the dates, locations, available programmes and admissions team contacts. Customising the reminder messages takes an additional half day to match the institution's tone.

Does the chatbot handle registrations for both virtual and in-person open days?

Yes. The chatbot adapts the flow depending on the format: for an in-person event, it collects the address and provides directions; for a virtual event, it sends the connection link and schedules a technical check the day before. Conversion rates are similar for both formats when the chatbot handles registration.

The AI chatbot does not just answer questions — it turns every conversation into a concrete registration opportunity. From intent detection to post-event follow-up, it automates the entire journey while maintaining a personalised experience for every prospect.