In traditional consumer packaged goods markets, the balance between retailers and manufacturers is dynamic and competitive. When it comes to consumer data and shopping behavior data, retailers have a huge advantage over their manufacturer providers. Why? Because they have access to SKU level shopping data, and with the advent of loyalty/frequent shopper card programs, retailers now have an extra powerful layer of consumer demographic behavior included in their tool kit of shopper related data to analyze and make future business decisions. Additionally, they can then provide this data to a third party analytics firm such as Nielsen or IRI who themselves resell it back to the manufacturer for the brand’s own analysis.

How does this relate to the emerging cannabis industry for retailers and brands? Depending on the state in which a retailer is operating, the parallels are there, but so are the differences from a traditional CPG market setup. In some cases, the brand has much greater visibility into their products performance at the retail shelf. This is because the brand is either a vertically integrated producer and retailer and can see the path it’s products take from the farm and factory all the way to the consumer, or the market runs on direct wholesale relationships between maker and seller and market performance data is easily shared. Elsewhere, the market, as it is in California, is segmented into a more traditional “three tier” supply chain model including producers, distributors and retailers, which presents a more “CPG”-like market with the same disruptions to data that are found in traditional grocery channels.

Because the cannabis market is structured in a variety of ways and remains immature, the opportunity for retailers and brands to track the performance of products across both store locations and customer types and the opportunities for applying consumer data-led business intelligence are many and varied. Let’s consider just a few.

Demographic Segments

With tools available to retailers, including POSs that collect and store customer profiles (where allowed or permissioned), that are customer-specific or customer-segment specific, retailers and the brands they share data with can gain valuable knowledge about who is buying, qnaswering questions such as what products, where and when purchased, allowing operators to begin to see the “Why” in how consumers decide to purchase particular product segments, brands, formats, price levels, etc. Answering questions such as below are enabled when you are effectively capturing and segmenting your customer shopping data:

• Age, gender, zip code of each shopper 
• Name, email and phone number when allowed by state regulations and given written permission by the shopper (most loyalty programs are set up for this specifically)

Behavioral Segments

While demographic customer data is important to understand and compare against broad industry trends, HOW shoppers behave, at retail and by product type and brand, is the key to creating insights that will lead to brand and retail decisions on product mix, product format and ingredients, and how much of each product and segment to invest in either making or stocking.

• SKU level purchase behavior over a given time period by consumer and group
• Product and Shopping Preferences (stated or implicit) by consumer or by demographic group
• Product performance at retail in terms of velocity of turn-over vs competing SKUs and formats.

NOTE: What is product velocity? It’s a measure of how quickly your stock is depleted for a given product or segment over a fixed period of time. 

• For retailers, it’s a store-by-store measure to determine the efficiency of it’s wholesale buying decisions – if product A sells faster than product B over the same time period, you might want to stock more of A in the future all other thighs being equal.
• For brands, velocity of one’s products at retail is going to give you visibility into which markets, which stores and which merchandising decisions (menu placement, price promotion, pop-up store investment, etc) are driving positive sales volume at pace with the market.

So with all of this data, what sorts of decisions can be made by the manufacturer and the retailer in determining how to improve their individual market presence?

• • A retailer can determine what to order next or more of

• “Gummies are outperforming Chocolates among reorders”

• • A retailer can offer discounts to underperforming segments of their customer list

• “Haven’t shopped in 90 days? We want you back! Here’s an offer”

• A retailer can determine what time of day is the most busy shopping time and deploy additional budtenders during those times
• A manufacturer can see that new flavors are catching on more quickly than legacy flavors and adjust production accordingly
• A manufacturer can determine which geographical areas to focus wholesale sales efforts
• A Manufacturer or retailer can determine pricing adjustments based on SKU velocity vs segment, etc.

Conclusion

All players in the cannabis supply chain, from growers and manufacturers to distributors to retailers have something to gain by carefully capturing, tracking and analyzing data that they gather from shopper behavior segmented by customer demographics and individual shopping behaviors. The tools for managing this data are still immature, but with the right strategy and approach, using customer shopping data can and should become second nature to any operator in the cannabis value chain, from grower to retail location.