Peak season
Customer service
E-commerce
Nearshoring
Outsourcing
Peak season puts every part of an e-commerce customer service operation under pressure at the same time.
Contact volumes increase. New agents join the team. Experienced employees spend more time supporting them. Back-office queues grow. Customers expect faster answers precisely when operations have less room for error.
After more than 16 years of managing customer service operations, including peak seasons for e-commerce and retail clients, we have seen the same pattern repeatedly: peak season rarely creates operational weaknesses. It exposes the ones that were already there.
Long queues, declining FCR or missed SLAs are usually symptoms. The actual problem often started weeks or months earlier — in forecasting, recruitment, training, workforce planning, knowledge management or process design.
Organizations often respond by hiring more advisors. While additional capacity is important, people alone cannot compensate for gaps in planning, knowledge, technology or operational coordination.
The question is therefore not whether your contact center can handle more interactions.
It is whether your operating model can continue performing when customer demand, operational complexity and time pressure all increase simultaneously.
What does peak season pressure look like in practice?
Peak season does not mean that every part of a customer service operation grows at the same rate.
In one e-commerce and retail operation managed by Axendi, contact volumes increased significantly across channels during the 2023 peak season:
- email enquiries increased by 352%, from 8,727 in July to 39,460 in December
- chat interactions increased by 2,099%, from 289 in April to 6,356 in December
- inbound calls increased by 324%, from 24,165 in May to 102,453 in December
At the same time, the customer service team grew to meet this demand.
This is why peak-season readiness cannot be reduced to one question: How many additional agents do we need?
Different channels, processes and customer needs scale differently. The operation has to absorb all of them at the same time.
From our experience, eight operational gaps appear particularly often when organisations prepare for peak demand.
Recruitment starts too late
One of the most common operational gaps during peak season is not recruitment itself—it is when recruitment begins.
Many organizations start hiring only after they see customer demand increasing. By then, the peak is already approaching, leaving little time to recruit, onboard and prepare new advisors before contact volumes reach their highest level.
Recruitment is only the first step. New employees still need to complete onboarding, training, system access, supervised practice and competency validation before they can handle customer interactions independently. Until then, they increase workload rather than operational capacity, relying on experienced advisors, team leaders and trainers for support.
Seasonal recruitment is particularly challenging in e-commerce, where businesses compete for the same pool of candidates ahead of Black Friday and the holiday season. Delaying recruitment by even a few weeks can significantly reduce the time available to build a stable, productive team before demand peaks.
What goes wrong
Recruitment begins in response to rising demand instead of being planned months in advance. Organizations measure success by the number of people hired rather than the number of advisors who will be fully operational when peak season begins.
Operational impact
The business enters its busiest period with a larger workforce but insufficient productive capacity. Experienced employees spend more time coaching and supporting new hires, reducing the availability of the very people needed to maintain service quality. As a result, queues grow, response times increase and customer experience deteriorates despite higher headcount.
Productivity doesn’t scale at the same pace as the team
Adding advisors is only one part of scaling customer service. The surrounding operational structure must grow as well.
Larger teams require additional team leaders, quality specialists, trainers, workforce planners and knowledge support. Without these functions, operational complexity increases faster than the organization’s ability to manage it.
This imbalance often explains why service levels fail to improve even after significant recruitment efforts.
As more advisors join the operation, consultation requests increase, quality monitoring requires more resources, and supervisors spend more time solving operational issues instead of proactively managing performance.
The organization has more people—but not necessarily more capacity.
What goes wrong
Frontline recruitment expands while leadership, quality assurance and operational support remain largely unchanged.
Operational impact
Average handling times remain high, escalations increase and experienced employees become the operational bottleneck instead of the customer demand itself.
Training is limited when it matters most
When recruitment starts later than planned, training is often the first activity to be compressed.
This may seem like a practical solution because advisors become available sooner. In reality, the operational cost appears only after they begin serving customers.
Peak season creates different customer enquiries than those handled during normal operations. Delivery delays, promotion rules, payment issues, returns, stock shortages and system incidents require advisors to make fast, confident decisions under pressure. Without sufficient preparation, they spend longer searching for information, escalate more cases and provide inconsistent answers.
What goes wrong
Training focuses on getting advisors into production quickly rather than preparing them for the situations they are most likely to face during peak season.
Operational impact
Consultation volumes increase, handling times grow, First Contact Resolution declines and customers receive inconsistent experiences across channels.
The operation optimizes speed instead of resolution
As queues grow, the natural reaction is to reduce Average Handling Time (AHT).
While shorter interactions may appear to improve productivity, they do not necessarily solve more customer problems.
When advisors rush conversations, transfer cases unnecessarily or provide incomplete answers, customers often need to contact the company again. The operation becomes busier without becoming more effective.
What goes wrong
Operational decisions prioritise interaction speed instead of customer outcomes, with too much focus on AHT and too little attention to First Contact Resolution, repeat contacts and customer effort.
Operational impact
Queues continue growing even though advisors are handling more interactions. Customer satisfaction declines while operational costs increase.
Back-office processes become the hidden bottleneck
Customer service can only resolve issues that the wider organisation is able to complete.
Refunds, complaints, payment verification, order corrections and warehouse requests often depend on teams outside the contact centre. If those processes fail to scale during peak season, advisors continue accepting contacts but cannot deliver outcomes.
Customers then make additional enquiries simply to check the status of their existing case.
What goes wrong
The organisation expands customer-facing capacity without increasing the capacity of back-office processes that complete customer requests.
Operational impact
Open cases accumulate, resolution times increase and customers generate additional demand through repeat contacts, even when the contact centre is performing well.
Automation is expected to fix poorly designed processes
Automation can significantly reduce repetitive work during peak season. AI chatbots, voicebots, agent-assist solutions and workflow automation help organisations improve efficiency and absorb higher contact volumes.
However, technology only performs as well as the processes behind it.
If policies are unclear, knowledge is outdated or escalation paths are poorly designed, automation simply reproduces those weaknesses at greater scale.
What goes wrong
Technology is implemented without sufficient attention to process design, knowledge quality, customer journeys or human escalation paths.
Operational impact
Customers abandon self-service, repeat information across multiple channels and eventually require advisor support, increasing rather than reducing operational demand.
Staffing plans assume perfect attendance
Even the best workforce plan can quickly become ineffective when sickness, unexpected absences or employee turnover reduce available capacity.
During peak season, organisations have very little operational flexibility. Losing even a small number of experienced advisors can have a disproportionate impact, particularly when specialist knowledge is concentrated within a few individuals.
Operational resilience requires more than filling every planned shift. It requires contingency planning, cross-trained employees and the ability to quickly reallocate experienced advisors where they create the greatest business value.
What goes wrong
Workforce planning assumes full attendance and provides little contingency for unexpected absences or operational disruption.
Operational impact
A manageable increase in customer demand quickly develops into an operational crisis because there is insufficient resilience built into the workforce plan.
Outsourcing begins after the crisis has already started
Many organisations consider outsourcing only after internal operations have become overwhelmed.
By that stage, service levels have already deteriorated and customers are experiencing longer waiting times.
However, outsourcing is not an emergency solution. A partner still requires time to understand processes, integrate systems, recruit advisors, transfer knowledge and establish governance.
The organisations that benefit most from outsourcing treat it as part of their peak-season strategy rather than a last-minute rescue plan.
What goes wrong
External support is sought only after performance has already declined, leaving insufficient time for implementation and operational readiness.
Operational impact
Knowledge transfer becomes rushed, responsibilities are unclear and both organisations spend peak season reacting to problems instead of preventing them.
Peak season exposes the operating model
Long queues and missed service levels are rarely the real problem during peak season. They are the visible symptoms of operational gaps that existed long before demand increased.
Late recruitment, compressed training, fragmented planning, overloaded back-office processes, poorly implemented automation and limited operational resilience may appear manageable during normal operations. Under peak conditions, they quickly combine into a much larger operational challenge.
Organisations that consistently deliver excellent customer experience during peak season prepare more than additional capacity. They build an operating model that remains resilient when demand, complexity and customer expectations all increase at the same time.
