How Sparks Sports Academy Cut New-Agent Onboarding Time by Up to 50%
Bringing new customer-service agents up to speed took long, inconsistent manual coaching, and conversations still varied batch to batch.
Interview with
Bagas Hidayat
Customer Service Training Lead
20–30%
agent conversion rate with AI-assisted guidance
30–50%
faster new-agent onboarding time
80–90%
training completion quality score
Standardized
training quality across every batch
About Sparks Sports Academy
Sparks Sports Academy relies on customer service agents to guide families from an initial chat toward a suitable sports-program booking. As new agents join, the quality of those conversations depends on how quickly they can learn and apply the right guidance.
The case is about the agent learning process as much as the customer conversation. The academy needed a way to prepare new staff while maintaining a consistent standard for answering course and booking inquiries.
The Challenge
Before Cekat.AI, Sparks Sports Academy relied on conventional onboarding and manual coaching to prepare customer service agents. As training demand grew, the team struggled to improve chat-to-booking conversion, shorten the learning curve for new agents, and keep training quality consistent across every onboarding batch.
Conventional onboarding and manual coaching took time from experienced team members. Training could also vary between batches, while newer agents still had to answer real customer questions and help convert inquiries into bookings.
“Every new batch needed coaching, but we also had to keep the quality of live customer chats consistent.”
Cekat.AI Solutions for Sparks Sports Academy
The approach for Sparks Sports Academy combines several connected workflows, from the first conversation through team follow-up.
“Guidance during the chat gives a newer agent a clearer way to answer without waiting for a coach to review every message.”
Guide agents while they handle a real booking inquiry
Agents receive assistance while handling inquiries, helping them respond with a more relevant next step toward booking. The agent can use the suggested next step in the moment, while still owning the final response to the family.
Give new staff a repeatable route through onboarding
New agents can practice and learn from a more structured process instead of depending entirely on one-to-one manual coaching. A shared learning flow reduces dependence on the availability and habits of one experienced coach.
Keep response standards consistent between training batches
Shared guidance establishes a common baseline for handling customer questions across onboarding batches. The same guidance helps the team compare readiness between batches instead of relying only on informal impressions.
Results
The following outcomes reflect the figures recorded in the client's case-study material. Their scope follows the available data.
20–30% agent conversion rate with AI-assisted guidance. The reported conversion range applies to agents working with AI-assisted guidance in the chat-to-booking flow. The recorded range applies to agents using the guidance in the chat-to-booking flow, not to every academy conversation.
“The value is in both parts: agents become ready sooner, and customers still receive a more consistent conversation.”
30–50% faster new-agent onboarding time. A more structured learning path shortened the time required to bring new agents into the workflow. Shorter onboarding means new team members reach the working conversation flow earlier while keeping guidance available.
80–90% training completion quality score. The recorded quality score reflects how well agents completed the supported training process. The quality score reflects the training process described in the case material, rather than a customer satisfaction score.
Standardized training quality across every batch. Using the same guidance across batches reduced variation in training quality; no separate percentage is given for this outcome. Consistency across batches is the qualitative outcome; the source does not supply a separate numeric standardization rate.
