Client Services – December 2025 Report

1. At-a-glance

  • Tickets: 2,579 opened vs 2,690 closed – net reduction of 111 in the ticket backlog.
  • Phone activity: 177 inbound and 231 outbound calls, with ~15 hours of total call time.
  • Live chat: 38 chats handled, of which 25 were via the AI agent.
  • Training: 20 training sessions delivered, with very strong feedback.
  • Project / utilisation focus: Significant time invested in Agiito mapping, renewals follow-up, customer training, and data quality / configuration work.
  • CSAT (Venue Support): 97% positive (Very satisfied or Satisfied) from 78 survey responses, with 79% of respondents rating Very satisfied.

2. Ticket volumes

Overall

  • Tickets opened: 2,579
  • Tickets closed: 2,690
  • Net effect: Closed 111 more tickets than were opened, reducing overall queue size.

By team member

  • Leo: 138 opened / 140 closed
  • Mercedesz*: 52 opened / 65 closed
  • Jenine: 895 opened / 933 closed
  • Sarah*: 523 opened / 547 closed
  • Zac: 115 opened / 116 closed
  • India: 856 opened / 889 closed

Commentary:

  • The work is clearly concentrated around Jenine, India and Sarah, who together handle the bulk of ticket flow.
  • Every named team member closed at least as many tickets as they opened, which contributed to the overall reduction in backlog.
  • The balance of opened vs. closed across the team suggests good throughput and queue management through December.

3. Phone support

Call volumes

Inbound calls

  • Sarah*: 14
  • Mercedesz*: 46
  • Jenine: 33
  • Leo: 71
  • Zac: 13

Total inbound: 177

Outbound calls

  • Sarah*: 100
  • Mercedesz*: 23
  • Jenine: 65
  • Leo: 15
  • Zac: 28

Total outbound: 231

Call duration

  • Sarah*: 3:47:13
  • Mercedesz*: 2:34:24
  • Jenine: 2:24:09
  • Leo: 4:02:33
  • Zac: 2:03:52

Estimated total talk time: ~14 hours 52 minutes across the team.

Commentary:

  • Leo handled the highest total call duration, with just over 4 hours of talk time.
  • Sarah combined high outbound activity (100 calls) with nearly 4 hours of talk time, indicating a strong focus on proactive outreach (e.g. renewals and follow-ups).
  • Overall, phone remains an important but targeted channel compared to the heavy ticket volume.

4. Live chat

Chats handled in December

  • AI Agent: 25
  • Sree: 6
  • Vaishali: 0
  • Yashi: 5
  • Sargun: 2

Total chats: 38 (25 AI + 13 human)

Commentary:

  • The AI agent handled the majority of chats (25/38), taking a meaningful share of first-line interactions.
  • Human chat volumes are relatively low and spread across a small number of agents, which is consistent with chat being a supplementary channel at present.
  • The current balance suggests that AI is already absorbing a good portion of the simpler, high-frequency queries.

5. Training activity

Sessions completed

  • Sarah*: 8
  • Jenine: 6
  • Mercedesz*: 3
  • GRATIS / Leo: 3

Total training sessions: 20

Training feedback

Standard, London – 8 Dec 2025

  • Overall satisfaction: Very Satisfied
  • Expectations: Exceeded Expectations
  • Trainer knowledge & presentation: Excellent
  • Clarity of material: Very Clear
  • Coverage of topics: All expected topics covered
  • Post-training confidence: Very Confident
  • Duration: Just Right
  • Comment: “Sarah was super helpful. Look forward to speaking to my Account Manager about data.”

Hampton by Hilton Park Royal – 17 Dec 2025

  • Overall satisfaction: Satisfied
  • Expectations: Met Expectations
  • Trainer knowledge & presentation: Excellent
  • Clarity of material: Very Clear
  • Coverage of topics: All expected topics covered
  • Post-training confidence: Confident
  • Duration: Just Right
  • Comment: “Very informative.”

Commentary:

  • Training feedback in December was overwhelmingly positive, with both respondents rating trainer knowledge as Excellent and material as Very Clear.
  • Sarah is specifically called out for being “super helpful,” which reinforces the quality of delivery on customer-facing sessions.
  • Customers report being confident or very confident using the software post-training, indicating that sessions are effective in driving product adoption.

6. Utilisation and project work

Sarah – 141 hours logged

  • 3 hours chasing March renewals
  • 1 hour chasing February renewals
  • 9 hours on customer training
  • 96 hours on Agiito mapping

Total tracked to specific activities: 109 hours (~77% of logged time)

Summary: Sarah’s December was dominated by Agiito mapping, with additional time on renewals and training. This mix reflects a blend of project-heavy work and revenue-protection activity (renewals), alongside direct customer enablement through training.

Mercedesz – 131 hours logged

  • 3 hours on customer training
  • 2 hours on VDC enquiries
  • 83.5 hours on Agiito mapping

Total tracked to specific activities: 88.5 hours (~68% of logged time)

Summary: Like Sarah, Agiito mapping is the main focus for Mercedesz, with supporting time spent on customer training and venue directory (VDC) enquiries. This shows a strong contribution to the same strategic mapping project while still supporting operational demand.

Leo – 124 hours logged

  • 3 hours on customer training
  • 2.5 hours on the accessibility audit for Calder’s MEP
  • 2.2 hours on the GRATIS gap analysis
  • 2 hours on a commission rates issue for Calder

Total tracked to specific activities: 9.7 hours (~8% of logged time)

Summary: Leo’s tracked project time is spread across accessibility, GRATIS analysis, and commission-related work for Calder, with additional time in customer training. The relatively low proportion of time tagged to projects suggests that Leo’s remaining hours are predominantly BAU support (tickets / calls).

Jenine – 88 hours logged

  • 6 hours on customer training
  • 4 hours chasing March renewals
  • 15 hours adding users to venues that had no users

Total tracked to specific activities: 25 hours (~28% of logged time)

Summary: Jenine’s project and initiative time is focused on customer training, renewals, and data quality / configuration work (adding users to user-less venues). The remaining hours are largely frontline support (tickets and calls), which aligns with her very high ticket throughput.

7. Highlights & observations

  • Backlog reduction: The team successfully closed more tickets than were opened, reducing outstanding workload by 111 tickets over the month.
  • High individual throughput:
    • Jenine, India and Sarah are key contributors to ticket volume, each closing significantly more tickets than they opened.
    • All listed agents maintained at least a 1:1 open/close ratio, which is healthy from a queue management perspective.
  • Strong project focus:
    • Agiito mapping is a major time investment for Sarah and Mercedesz, together logging around 180 hours on this work alone.
    • Calder-related activities (accessibility audit and commission issues) and GRATIS gap analysis are being progressed primarily by Leo.
    • Renewals and user configuration clean-up (adding users to venues) are actively being driven by Sarah and Jenine, tying support activity to revenue and data quality.
  • Customer sentiment:
    • Training feedback is excellent, with customers describing sessions as very informative and trainers (particularly Sarah) as super helpful.
    • Post-session confidence is high, indicating that training is contributing directly to product adoption and self-sufficiency.
    • December CSAT for Venue Support was 97% positive (Very satisfied or Satisfied), based on 78 survey responses, with 79% of respondents selecting Very satisfied.
    • CSAT by agent remains very strong, with 100% positive feedback for Sreelakshmi Pradeep, Sargunkaur Sethi, Aanchal Kumari, Vaishali Adhikari and Sarah Green, 97% positive from the largest response volume for Yashi Jaiswal, and 83% positive for Jenine Gibbons from a smaller sample.

8. Suggested focus areas for January

  • Maintain backlog momentum: Continue to aim for closed > opened tickets to further reduce outstanding queues, particularly while Agiito and other projects remain in flight.
  • Balance project vs. BAU load:
    • Monitor capacity for team members heavily involved in Agiito mapping and other projects to ensure BAU SLAs remain stable.
    • Where possible, continue to use AI chat and self-service to absorb simpler queries.
  • Amplify training impact:
    • Use the positive training feedback in internal comms and, where appropriate, as social proof for more customers to book sessions.
    • Continue to track post-training confidence to ensure sessions are consistently enabling customers to be self-sufficient.
  • Data quality and renewals:
    • Sustain the effort on renewals chasing and venue user configuration, as both have a direct impact on revenue and platform usage quality.

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