Boost Your Average Sports Basket with Targeted Bundles & Upsells

You are a B2B e-commerce expert specializing in the sports sector. Analyze the following data to propose a strategy for optimizing the average basket through bundles and upsells, tailored to [TYPE_OF_SPORT] and [SEASON].

Context:

• Product categories: [CATEGORY_LIST] (e.g., running shoes, road bikes, dumbbells, etc.)
• Current average basket: [CURRENT_AVERAGE_BASKET] €
• Objective: increase of [PERCENTAGE_OBJECTIVE]% in 3 months
• Customer behavior: [CLIENT_BEHAVIOR] (e.g., 60% buy a single item, 30% two items, 10% three or more)
• Seasonality: [SEASON] (e.g., pre-summer, back-to-school sports season, winter)

Specific constraints for the sports sector:

• Bundles must respect technical compatibilities (e.g., ski bindings-boots, bicycle frame sizes)
• Upsells must take season into account (e.g., offer a breathable jersey with running shorts in summer)
• Cross-sell suggestions must be based on recurring purchases (e.g., buyers of treadmills -> interested in cardio accessories)

Rules:

1. Propose 3 distinct bundles: one for beginners, one for intermediate, one for expert, with bundle price (discount 10-20% depending on [PRODUCT_MARGIN]).
2. For each bundle, define 2 relevant upsells (one higher-end product and one accessory) with a hook text.
3. Justify each choice with industry data (retention rate, seasonality, buying behavior).
4. Include tracking KPIs: bundle adoption rate, average basket increase, ROAS of upsell campaigns.

Provide a structured answer in a table: Bundle name, Products, Discount, Upsell1, Upsell2, Justification, KPIs.

Variables: [TYPE_OF_SPORT], [SEASON], [CATEGORY_LIST], [CURRENT_AVERAGE_BASKET], [PERCENTAGE_OBJECTIVE], [CLIENT_BEHAVIOR], [PRODUCT_MARGIN]