1. Executive summary

• Team utilisation for March (after holiday adjustment) was ~84%, with individual utilisation between 77% and 91% once Leo’s 40h, Jenine’s 24h and Mercedesz’s 8h holidays are excluded from working time. 
• Ticket volume was 2,699 opened and 2,772 closed, with India and Sarah carrying the heaviest ticket loads. 
• CSAT remained excellent at 4.80 / 5 from 118 March responses, with ~90% “Very satisfied” and no negative ratings in the March subset. 
• Telephony: the CS team handled 1,525 calls (958 inbound, 567 outbound) totalling ~30 hours of talk time; average call duration was ~71 seconds.
• Chats & AI: there were 149 chats in March, with 96 (64%) routed to the AI agent and 36 handled by human agents, mainly Sargun, Vaishali, Yashi and Aanchal. 
• Training: the team delivered 58 sessions (Leo 21, Jenine 16, Mercedesz 14, Sarah 7) with all March training-survey respondents rating their session “Very Satisfied”. 

2. Utilisation overview

2.1 Adjusted utilisation (including holiday impact)

• Sarah: 100 of 120 working hours
• Jenine: 135 of 173 working hours
• Mercedesz: 127 of 173 working hours
• Leo: 114 of 173 working hours :llmCitationRef[8]

Holiday adjustments (reducing the working-hours denominator):

• Leo: 40h holiday → 173 − 40 = 133 working hours
• Jenine: 24h holiday → 173 − 24 = 149 working hours
• Mercedesz: 8h holiday → 173 − 8 = 165 working hours
• Sarah: no holiday adjustment provided; remains at 120 working hours

Team overall: 476 logged hours over 567 adjusted working hours → ~84.0% utilisation. 

2.2 Holiday overview

• Leo: 40 hours of holiday; utilisation rises from ~65.8% (using 173h) to ~85.7% when holiday is excluded.
• Jenine: 24 hours of holiday; utilisation rises from ~78.1% to ~90.6%.
• Mercedesz: 8 hours of holiday; utilisation rises from ~73.5% to ~77.0%.
• Sarah: no holiday adjustment mentioned; utilisation remains 83.3% (100 / 120h).

2.3 Activity mix (qualitative)

• Sarah: 24h IHG mapping, 6h contacting July renewals, 4h chasing June renewals, 7h on client training, 6h on the 3- and 6-month engagement plan; remainder on support tickets. 
• Jenine: 21h IHG mapping, 16h TVD reports, 16h customer training; remainder on tickets and other tasks. 
• Mercedesz: 15h IHG mapping, 6h postcode/town correction project, 12.5h chasing aged debt for Finance, 14h customer training; remainder on tickets. 
• Leo: 21h on customer-training calls; remaining logged hours on support tickets. 

2.4 Tickets and channels as utilisation context

• Calls (Client Services, Zoom): 1,525 total calls; 958 inbound, 567 outbound; ~29h 58m total call time; ~70.7s average call duration. 
• Chats: 149 chats in March overall; AI handled 96 and human agents handled 36 (Sree 0, Vaishali 7, Yashi 7, Sargun 18, Aanchal 4). 

3. Customer training activity & feedback

• Sessions delivered (March): GRATIS/Leo 21, Jenine 16, Mercedesz 14, Sarah 7 → 58 sessions (workbook explicitly states this is for the whole of March).
• Surveyed attendees: 11 completed March training surveys (each one attendee). 
• Average satisfaction: 5.0 / 5 (all responses “Very Satisfied”). 

Top positive themes (trainer not captured in the survey):

• Clarity & understanding – e.g. “During the second session, we went through an example enquiry which enabled me to really understand how the system operates.”; “Clear explanation.” 
• Practical, real-time examples – “visual learning, seeing things actually happen in real time.” :llmCitationRef[21]
• Thoroughness & opportunity focus – “Complete analysis of the profile and business opportunities.” 
• Helpfulness & attitude – “Very good nature and happy to answer all questions and provide solutions.” 

Improvement themes:

• Pace slightly fast – “Maybe explaining things a little slower so I could note it all down.”; “slow down a little.” 
• Few other asks – several comments explicitly state they are not sure there is anything to improve. :

Per-person training completion (delivery):

4. Overall satisfaction survey results

• Total responses (March): 118. 
• Average CSAT: 4.80 / 5 (Very satisfied=5, Satisfied=4, Neither=3, Dissatisfied=2, Very dissatisfied=1).
• Distribution: Very satisfied 106 (89.8%); Satisfied 12 (10.2%); 0 responses in other categories in the March subset. 

CSAT by agent (Venue Support and others named in March CSV):

Top positive drivers (with quotes and agents):

• Speed & responsiveness
  • “very efficient and quick” – for Aanchal Kumari. 
  • “Super quick - thanks Team x” – for Aanchal Kumari. 
• Proactive resolution & system support
  • “The team were straight in on contact when they detected a potential issue (I wasn’t even aware!) and then within thirty minutes, Aanchal had come back and the issue was all resolved! Amazing!” – for Aanchal Kumari. 
  • “Vaishali was very helpful and patient in helping me resolve my issue :)” – for Vaishali Adhikari. :llmCitationRef[31]
• Helpfulness & communication quality
  • “A big thank you to Vaishali Adhikari for responding to my issue so promptly.” :llmCitationRef[32]
  • “Really good meeting and the notes were excellent. Very helpful.” – for Jenine Gibbons. :llmCitationRef[33]

Top negative drivers (with quotes and agents):

• Enquiry-closure / opening-hours clarity – “We had an enquiry that came in when the venue was closed for the next day… by the time I looked at the enquiry from home the agent had closed it… it should not be possible to close the enquiry before we are given the opportunity to respond.” – for Sargunkaur Sethi. 
• Third-party IT delays (Waterstons) – “The issue wasn’t resolved quickly by the Waterstons help desk… another member of Waterston’s… resolved the issues quickly & efficiently.” – survey lists Vaishali Adhikari as agent, but the delay sits with external IT. 

5. Weekly & monthly trends

Channel totals (Monthly Data – February vs March). :llmCitationRef[36]

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• Tickets: 2,699 opened vs 2,772 closed; India and Sarah are the main volume carriers. 
• First-response & resolution times: not available numerically for March in the workbook; cannot be reported.
• Calls (Zoom): concentrated across Sarah, Jenine, Leo, Mercedesz and Zachary, with short average durations (27–83s for most agents; ~180s for Zachary, reflecting likely escalations).
• Chats & AI: AI handled 96 of 149 chats; human workload concentrated with Sargun, Vaishali, Yashi and Aanchal. :llmCitationRef[39]
• Training: 58 sessions spread through the month, with significant clusters mid- to late March across the H10 group and several UK venues.