Conditioned price dynamics... Brain: How did $15.50 become $5.50 overnight? Mind: Do you wanna bu...Conditioned price dynamics... Brain: How did $15.50 become $5.50 overnight? Mind: Do you wanna bu...
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Conditioned price dynamics...
Brain: How did $15.50 become $5.50 overnight?
Mind: Do you wanna buy or not?
You: It’s Black Sunday–let me buy 2.
–
Salesman: People buy based on their emotions.
Everlune 🤍 - The page every wedding vendor overthinks: Pricing.
Three-tier package comparison, add-ons list, FAQ built right in, no more "message us for pricing."
Putting the three tiers, add-ons, and FAQ on one page is exactly what wedding vendors keep avoiding. The quiet type treatment makes the pricing feel considered instead of salesy.
How do you make a beauty Shopify store feel premium without sacrificing conversion?
That was one of the questions behind my work on BLOME Beauty.
I focused on creating a shopping experience where brand storytelling, product education, trust signals, and conversion paths work together not compete with each other.
From product discovery and visual hierarchy to CTAs, social proof, mobile responsiveness, and the path toward checkout, every section was designed with the customer journey in mind.
The goal wasn't just to make BLOME look beautiful. It was to make the experience easier to understand, navigate, and buy from.
A Python-based data analysis project focused on identifying customer churn patterns and understanding the factors associated with customer attrition.
Key areas covered:
• Data cleaning and preprocessing using Pandas
• Exploratory Data Analysis (EDA)
• Churn distribution and customer segmentation
• Analysis of customer behavior and key patterns
• Data visualization using Matplotlib and Seaborn
• Identification of factors associated with higher churn risk
• Business-focused insights from customer data
The project demonstrates how Python and data analysis techniques can be used to explore customer behavior and generate actionable insights for retention-focused decision-making.