Seasonal lifecycle
of apparel

Apparel retailers face significant challenges managing issues like seasonal changes in fashion, and ranging the perfect mix of clothing sizes.
These magnify two retail curses; namely large-scale markdowns and deadstock; that negatively impacts both gross margin & environmental sustainability.
These issues are so prevalent that this vertical promises our highest expected return: around 4% of an apparel retailer’s gross margin, straight to the bottom line.
Tymestack is here to help.
Our journey begins in-season: optimizing price and stock allocations to deliver sell-through targets, minimizing end-of-season issues. Over time, we gather insights to guide teams and reduce CapEx in subsequent pre-seasons.
Accuracy and precision accumulate across seasonal stages, and year-on-year, to deliver significant gain.

Operational priorities

Pre-season

Manufacturing
Design and production planning
Ranging
Creating a balanced and profitable product range
Buying
Design, sourcing, and procurement negotiation

In-season

Base price estimation
Distributing inventory across geography & channels
Marketing & promotions
Driving sales through advertising, PR, and in-store activities
Pricing & discounting
Dynamically optimizing pricing strategies to maximize revenue
Replenishment
Managing stock levels to meet demand

End-of-season

Markdown & clearance
Reducing prices to sell excess inventory
End-of-season sales
Final clearance events to liquidate remaining stock
Deadstock management
Handling unsold inventory
Learning & optimization
Analyzing performance to inform future seasons

Financial risks

Pre-season

CapEx at risk
Significant investment in product development, sourcing, and buying

In-season

OpEx at risk
Ongoing operational costs, including marketing, sales, and inventory management
Full-price sales, successful promotions, and efficient inventory management
Shelf-clogging, losses on discounts, losses on store allocations

End-of-season

CapEx and OpEx at risk
Costs associated with markdowns, clearance sales, and potential write-offs
Discounts, markdowns, and write-offs on unsold inventory

Analytical considerations

Pre-season

Forecasting
Predicting customer demand and trends

In-season

Pricing optimization
Dynamically adjusting prices to maximize revenue
Promotion optimization
Evaluating the effectiveness of promotions and targeting the right customers
Allocation optimization
Distributing inventory effectively across channels and stores

End-of-season

Pricing optimization
Dynamically adjusting prices to maximize revenue

Why current forecasting and optimization fails

  • Inaccurate, outdated and imprecise modeling and technology
  • Inadequate data and incorrect assumptions: Limited visibility into customer behavior and market trends
  • Static models: Inability to adapt to changing conditions and unexpected events
  • Lack of real-time insights: Delayed decision-making and suboptimal outcomes

Common and widely accepted costs of failure

  • Excessive CapEx deployed
  • Lost sales opportunities
  • Lost margin
  • Excess inventory costs
  • CapEx write-offs
  • Reduced customer satisfaction
  • Diminished brand reputation