As the dust settles on the post-4/20 cannabis event, it’s time for businesses in the industry to reflect on what they can learn from the data generated during this important time. The post-4/20 data analysis is essential for understanding customer behavior, identifying trends, and making informed business decisions. In this post, we’ll preview 11 things to analyze in your data to gain insights and improve future events and operations.

Retail Sales Data

Retail sales data is essential for understanding customer behavior and preferences. Data points to analyze include new vs. returning customers, customer demographics, customer location, and customer preferences. By examining these data points, businesses can better understand their customer base, identify areas for improvement, and optimize their marketing strategies.

Retail Sales Data To track

New vs. returning customers:

• What it is: Measuring the percentage of new versus returning customers after 420 season.
• How it’s collected: The data is collected by tracking the number of customers who made a purchase during this period and analyzing whether they were new or returning customers. Typically your POS or rewards system will have a “sign up date” that can be used to identify customers who signed up either on or right before 4/20
• Why it matters: This KPI can help companies fine-tune their marketing strategies to attract new customers and retain existing ones, ultimately increasing revenue and brand loyalty.

Customer demographics:

• What it is: Measuring the characteristics of customers such as age, gender, and other demographic factors.
• How it’s collected: The data is collected by your POS or rewards system when they sign up.
• Why it matters: Understanding customer demographics can help companies tailor their offerings and marketing strategies to appeal to their target market. By identifying which age groups, genders, and other demographic factors are most likely to make purchases, companies can modify their marketing strategies to improve customer engagement and increase revenue.

Customer location:

• What it is: Measuring the geographical location of customers who made a purchase after 420 season.
• How it’s collected: The data is collected either by your POS / rewards systems and / or shipping addresses provided by customers who place delivery orders
• Why it matters: Analyzing customer location can reveal if a business is attracting mainly local customers, who are more likely to be reliable, or if it is relying on customers from out of town. This information can be used to update marketing and sales strategies to attract more local customers or target specific regions to expand the customer base. Additionally, customer location can highlight areas where a business may be underserving, prompting them to make necessary adjustments to their marketing and sales strategies.

Customer preferences:

• What it is: Measuring the popularity of different products and strains among customers after 420 season.
• How it’s collected: The data is collected by tracking customer purchase behavior and analyzing the receipts of sales of different products and strains.
• Why it matters: By tracking customer preferences, businesses can identify which products and strains are most popular within their operations and amend their inventory and sales strategies. This data can also help businesses identify any trends in product popularity and change their offerings as needed. This KPI can help companies optimize their inventory and increase revenue by stocking the products and strains that are most in-demand among customers. Understanding customer preferences is also critical for ensuring customer satisfaction and loyalty.

Customer Data

Understanding customer behavior is essential for building a loyal customer base. Analyzing customer data, such as purchase history and preferences, can help businesses tailor their offerings to meet customer needs and increase customer satisfaction.

Customer Data To Track

Purchase history:

• What it is: Measuring the purchase history of customers, including the frequency and value of their purchases, the products they have purchased, and the time between purchases.
• How it’s collected: The data is collected by tracking customer purchase behavior, analyzing sales data, and using customer relationship management (CRM) software to store customer purchase history.
• Why it matters: By delving into the purchase history of customers, businesses can gain valuable insights into the broader purchasing trends that are associated with the customer demographics mentioned earlier. This data can help businesses better understand their customers, identify opportunities to upsell and cross-sell products, and adjust their inventory and sales strategies to increase revenue.

Sentiment:

• What it is: Measuring customer sentiment for products and strains. Sentiment analysis involves tracking the attitudes and emotions of customers towards a brand or product.
• How it’s collected: The data is collected through surveys, social media monitoring, online reviews, and customer feedback.
• Why it matters: By tracking customer sentiment, businesses can get a sense of which products and strains are most attractive/in-demand and modify their inventory and sales strategies. This data can also help businesses identify any trends in product popularity and adjust their offerings in response.

Feedback:

• What it is: Measuring customer feedback, including reviews, ratings, and comments.
• How it’s collected: The data is collected through online platforms such as Google, Yelp, and social media, as well as through customer surveys and feedback forms.
• Why it matters: By tracking customer feedback, businesses can identify areas for improvement in customer experience and address issues to improve customer satisfaction. This data can also help businesses identify which areas they excel in and promote those areas to increase customer loyalty. By responding to customer feedback, businesses can show their customers that they value their opinions and are committed to providing exceptional customer service, ultimately increasing customer loyalty and revenue.

Inventory Data

Analyzing inventory data is critical for optimizing stock levels and reducing waste. Key inventory data points to analyze include inventory turnover rates, popular products and strains, inventory levels before and after the event, and stockouts or overstocked products. By examining these data points, businesses can optimize inventory levels, reduce waste, and increase profitability.

Inventory Data To Track

Inventory turnover rates:

• What it is: Measuring the rate at which a business’s inventory is sold and replaced over a given period of time. A high inventory turnover rate indicates that a business is selling its inventory quickly, while a low rate may indicate slow sales or overstocked inventory.
• How it’s collected: The data is collected by tracking the number of units of each product or strain sold during a specific period of time and calculating the ratio of inventory turnover.
• Why it matters: Inventory turnover rates help businesses identify which products and strains are most popular and are selling quickly, which can help optimize inventory levels and prevent stockouts while also reducing waste.

Highest sales volume/revenue generated by product/strain:

• What it is: Measuring the sales volume and revenue generated by each product or strain.
• How it’s collected: The data is collected by tracking the number of units sold and the revenue generated for each product or strain.
• Why it matters: This KPI provides businesses with valuable insights into which products and strains are generating the most revenue, allowing them to tailor their inventory and sales strategies to meet customer preferences and optimize profitability.

Inventory levels before and after the event:

• What it is: Measuring the inventory levels of products and strains before and after a specific event, such as the 420 season.
• How it’s collected: The data is collected by tracking the inventory levels of products and strains before and after the event.
• Why it matters: By tracking inventory levels before and after the event, businesses can optimize their inventory levels and reduce waste. This data can help businesses determine which products and strains are most in demand and adjust their inventory levels accordingly.

Stockouts or overstocked products:

• What it is: Measuring the occurrence of stockouts or overstocked products for each product or strain.
• How it’s collected: The data is collected by tracking the number of stockouts or overstocked products for each product or strain.
• Why it matters: By tracking stockouts or overstocked products, businesses can fine-tune their inventory levels and reduce waste. Stockouts can help build exclusivity and hype around products and brands, driving demand and prices. Overstocked products should be evaluated for discounting or other strategies to reduce inventory and prevent waste.

The Bottom Line

Post-4/20 data analysis is essential for cannabis industry businesses to gain insights into customer behavior, identify trends, and make informed business decisions. By analyzing wholesale and retail sales data, customer data, inventory data, and cultivation data, businesses can optimize their operations, reduce costs, and increase profitability. We encourage all businesses in the industry to use this information to improve future events and operations.