As the Growth Lead for an online apparel store in Mumbai, you've noticed an unsettling increase in shopping cart abandonment rates.
A detailed EDA conducted by your data analyst reveals that users are frequently exiting at the product page, not at the landing or payment stages.
You need to guide the team in exploring plausible reasons for this trend to devise effective strategies for improvement.
Given the specific drop-off point, which of the following hypotheses sets should you consider to effectively understand and address the issue?
- Hypothesis Set A: Examine if the recent introduction of a new product filtering feature on the category collection pages is causing confusion, assess the impact of dynamic pricing strategies on customer perception, and analyze user feedback on product variety.
- Hypothesis Set B: Consider revamping the landing page to better highlight promotions and discounts, ensure product categories are clearly defined, and explore faster payment options to streamline the checkout process.
- Hypothesis Set C: Investigate the effectiveness of the newly implemented chatbot for customer assistance on product pages, review changes in product descriptions or images for clarity and appeal, and assess any recent adjustments in shipping policies or fees.
- Hypothesis Set D: Check for any technical glitches or increased loading times specifically affecting the product pages, evaluate the impact of recent changes in user account requirements for purchase, and consider the overall navigational flow of the site post recent updates.
Select the set of hypotheses that most logically aligns with the RCA approach considering the drop-off at the product selection page.