Thanks for attending our webinar on Basket Analysis + our brief dive into recent coronavirus data as it relates to the cannabis industry! We’ve answered the questions you all dropped in the chat and compiled them for you below.
Find the recording here and a link to the slide deck here.
Want to stay informed on how coronavirus is impacting the industry? Make sure you check our blog for daily updates.
1) What markets does Headset data cover?
The data in the webinar today was for Adult-Use (or recreational) sales in each market listed. Sales figures are post-discount and pre-consumer paid taxes. Consumer paid taxes are sales tax and cannabis sales tax in all markets and excise tax in the state of WA. Canadian data is reported in CAD. Sales totals include all Adult Use sales (this includes delivery and online ordering where it is allow). We do not break data down into delivery/online vs brick-and-mortar but just show the aggregate total.
2) What time frame was used for the data?
The data in the presentation (unless otherwise noted) were for sales in 2019 (whole year). Though many slides compare 2020 sales in Jan/Feb to dates in March, specifically referring to the slides that addressed market changes after the COVID-19 outbreak - these slides are noted.
3) What dates were states “locked-down”?
It varies by state. Please visit the Headset blog post for up-to-date information.
4) Can you explain the measure on slide 14 (Index of Daily Sales Compared to Same Weekdays in Feb)?
This graph compares the average daily sales for each weekday in Jan/Feb 2020 to daily sales in March. For example, we see that on March 3rd, CO had an index of 1.1. This means that sales on Monday, March 2 were 10% higher than sales on the average Monday in Jan/Feb 2020 in Colorado.
5) Does a beverage count as an edible?
At Headset, we consider Edibles and Beverages as two discrete categories that are mutually exclusive.
6) For attachment rate, how do I know which item was the primary item in the cart?
It would depend on your definition of primary. For attachment rate we generally think of products as attaching to other products and look at it both ways.
For example, let’s say there are 100 baskets broken down as follows:
30 Shampoo Only
60 Shampoo + Conditioner
10 Conditioner Only
The attachment rate of Conditioner onto Shampoo baskets is 60/(60+30) = 66%
The attachment rate of Shampoo onto Conditioner baskets is 60/(60+10) = 86%
Here, since we see that 86% of the time when a person buys conditioner they also buy shampoo, BUT only 66% of shampoo purchases come with conditioner, we can assume that shampoo is the driver product and conditioner is the passenger.
7) What is the attachment rate of Edibles to Flower?
Looking at slide 31 we see that of all the Flower baskets 11.5% of them contain an Edible product. So Edibles attach themselves to Flower baskets 11.5% of the time.
8) What time period are you using for attachment rates and do they change over time/by season?
This presentation looked at the entire year of 2019. However, attachment rates do exhibit seasonal and even daily/hourly trends.
9) Can the Headset retailer app help me do basket penetration and attachment rate analysis for my store?
Not just yet, but keep an eye out for an announcement from us soon!
10) How robust is your attachment rate data in Canada seeing as 2.0 products are still new to market?
As new products become available we anticipate attachment rates to change. This is especially true when products are limited in supply to start. While we did not show any attachment rate data in Canada on today’s webinar the data would still be “robust”, but it will likely quickly change as products become more available.
11) Can you be more specific with California and the trends there? For example, what are the top five items being sold and has that changing with COVID 19?
We have highlighted a few products on our blog post. However, if you log into your Headset Insights App and go to the “Holiday Bump Analysis” dashboard you can input any given day or time period and review sales trend changes by brand, segment, category or any combination of the three to see which products are most effected by micro-level sales shifts such as Covid-19 announcements.
12) Can we use customer historical purchase data to make recommendations at the right time?
On average they buy $x edibles every x weeks. This is something we can currently do with our customer data at Headset. If you are interested in learning more please reach out to our sales team at email@example.com