Client Account Manager

Client Account Manager Interview Questions and Answers

Updated 1 Oct 2024

Q1. Do you have any queries in compensation & leaves policy ?

Ans.

Yes, I have queries regarding compensation & leaves policy.

  • I would like to know about the company's vacation policy and how it accrues.

  • Can you provide information on the company's sick leave policy and how it is managed?

  • I am interested in understanding the process for requesting time off and how it impacts compensation.

  • Could you clarify the company's policy on maternity/paternity leave and any benefits provided?

  • I would like to know if there are any additional perks or benefit...read more

Q2. Do you think client management is B2C is easier than B2B ? Why ?

Ans.

Client management in B2B is typically more complex than in B2C due to longer sales cycles, multiple decision-makers, and higher stakes.

  • B2B client management involves longer sales cycles and more complex decision-making processes.

  • B2B clients often have multiple decision-makers involved in the purchasing process, making it more challenging to manage relationships.

  • B2B transactions usually involve higher stakes and larger contracts, requiring more strategic and personalized accou...read more

Client Account Manager Interview Questions and Answers for Freshers

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Q3. How will you manage work from home by creating a proper office space?

Ans.

I will designate a quiet, well-lit area in my home for work, with a comfortable chair and desk setup.

  • Designate a specific area in your home for work to create a separation between work and personal life.

  • Ensure the area is well-lit and free from distractions to maintain focus.

  • Invest in a comfortable chair and desk setup to promote good posture and reduce physical strain.

  • Organize the space with necessary office supplies and equipment for efficiency.

  • Establish a routine and bound...read more

Q4. What is trending in AI now?

Ans.

Trending topics in AI include natural language processing, computer vision, and ethical AI.

  • Natural language processing advancements for improved chatbots and virtual assistants

  • Computer vision technologies for object recognition and autonomous vehicles

  • Ethical AI discussions around bias, transparency, and accountability

  • AI applications in healthcare for diagnosis and personalized treatment

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