What trends do you see from the data collected? If something does not fit
the pattern, propose the reason why.
From the data collected, several trends can be observed:
1. Seasonal patterns: There is a noticeable trend of higher sales during certain seasons or specific months of the year. This could be due to various factors such as holidays, weather conditions, or cultural events that impact consumer behavior.
2. Day of the week patterns: The data might show trends where certain days of the week have consistently higher or lower sales compared to others. This could be attributed to factors like weekday versus weekend preferences for shopping or specific promotional activities on certain days.
3. Time of day patterns: It is possible to identify trends regarding the time of day when sales are highest or lowest. This could be influenced by factors like store opening and closing times, work schedules, or customer preferences for shopping at specific times.
4. Product popularity: The data might reveal specific products or categories that consistently outperform others in terms of sales. This could be due to factors like customer preferences, marketing efforts, product quality, or competitive advantage.
5. Consumer behavior patterns: The data might show trends in terms of customer buying habits, such as frequent purchases of certain products, repeat purchases from specific brands, or changing preferences over time. This could be influenced by factors like changing demographics, income levels, or evolving market trends.
If something does not fit the observed patterns, the reason could be a variety of factors:
1. External events: Unforeseen events like natural disasters, economic downturns, or pandemics can disrupt the expected patterns and lead to anomalies in the data.
2. Promotion and marketing efforts: Intensive marketing campaigns or promotions can temporarily disrupt the typical sales patterns by boosting sales for specific products or time periods.
3. Product innovation: The introduction of new products or significant changes to existing products can create fluctuations in sales patterns as customers adapt to the new offerings.
4. Competitive factors: The actions of competitors, such as price changes, new product launches, or aggressive marketing strategies, can impact sales patterns by attracting or diverting customers.
5. Data collection errors: Inaccurate or incomplete data collection processes can lead to anomalies and inconsistencies in the observed patterns, making certain data points seem out of place.