AI, Machine Learning, and Consumer Preferences: The New Frontier of Cannabis Sales and Marketing

In today’s industry, if a cannabis dispensary has a robust patient and consumer base, gathering data about their preferences and shopping habits is far from easy. 

Retailers are often combining loyalty data, purchase history, purchase frequency, average amount spent, time in store, customer feedback, and other informational metrics all from different platforms–including their inventory management platform, point-of-sale (POS) system, or their customer relationship management (CRM) software.

On top of those logistical challenges, dispensaries must contend with strict regulations around the storage and use of that data, as well as simply having incomplete data because of false entries or opt-outs due to privacy concerns. 

The accumulation of these hurdles makes painting a complete picture of customers challenging–and ultimately prevents dispensaries from better serving their clientele because it could lead to inefficient operations as it relates to inventory, ineffective marketing strategies, 

However, the advent of artificial intelligence (AI) and machine learning (ML) could change all this–and lead dispensaries to more quicker and meaningful insights. 

Opportunities for Cannabis Dispensaries 

AI and ML have been hot topics for years now, but the recent release and accessibility of ChatGPT by OpenAI sent shockwaves throughout the world. 

ChatGPT was quickly lauded as the fastest adoption platform–accumulating more than 100 million users in the first two months. 

(In fact, ChatGPT was partially used in the creation of this post.) 

It’s inspired the world to wonder–for better or worse–what’s possible? 

While the future of AI and ML is far from certain, here are just 7 ways these concepts could improve cannabis dispensary operations in sales and marketing:

1. Data Unification and Cleansing 

As the name suggests, data unification involves bringing disparate systems of data together. Machine learning can help dispensaries help identify relevant attributes, resolve discrepancies, and create a unified database of customer information. It may do this by identifying common attributes and linking records based on those attributes. Machine learning can also help to remove duplicates and effectively “clean up” that data into a uniform format. It will also have the ability to do all this in real-time, as customer information is constantly changing and updating. 

2. Feature Engineering 

Featuring engineering with machine learning means extracting relevant attributes and building them into predictive models. For dispensaries, this could mean taking features such as demographics, past purchase history, visit frequency, preferred products, and other items–and highlighting relevant patterns and relationships to this data, which can help the dispensary to more fully understand preferences and shopping behaviors.

3. Customer Segmentation

Machine learning also has the ability to divide a customer base into distinct groups based on similarities in data. This can help dispensaries more specifically target customers for promotions, offers, and product recommendations whether that customer is new, loyal, or simply interested in a specific category.

4. Automation of Routine Tasks

Repetitive and time-consuming functions, such as inventory management, order processing, and data entry–will become much easier in the world of artificial intelligence. This will ultimately help dispensary operators save large chunks of time while also removing human errors–so they can focus on more effectively marketing to their customers.

5. Customer Support Chatbots

AI-powered chatbots can enhance customer satisfaction and reduce response times by offering support in real-time. Even outside of business hours, chatbots have the ability to handle inquiries such as product questions, operating hours, order status, and more.

6. Dynamic Pricing 

Dynamic pricing is the strategy of pricing products in real-time in response to market conditions such as supply levels, customer preferences, and competitor prices. AI algorithms can process large volumes of data to determine the optimal price for products at any given time. This can help dispensaries stay competitive and capture additional revenue during peak periods.

7. Predicting Sales and Marketing Trends

AI and ML can analyze historical data and identify patterns that can help better predict future sales, customer behavior, and marketing outcomes, which can help dispensaries better utilize their given resources to make an impact within the marketplace.
The concepts merely scratch the surface of what is possible in this new frontier in artificial intelligence and machine learning for cannabis dispensaries. The successful implementation of AI and ML will ultimately help dispensaries operate more efficiently and become better providers to their clientele. However, care and attention toward the adoption, monitoring, and evaluation of these concepts is critical to align with company goals, protect customers’ interests and also to operate compliantly and responsibly. 

The team at Mosaic is closely watching this space and utilizing these concepts to improve our all-in-one eCommerce and loyalty program. 

We seek to help cannabis retailers finally mirror their high-touch, in-person experience by bringing together fragmented technologies and providing seamless online ordering experiences. 

If you’re interested in learning more with a free demo, schedule time with our team here.