Article: The Effects of Big Data and Technology on the Marijuana Industry

Let’s take a closer look at five key ways big data and technology are directly impacting the industry.


1. Big Data Streamlines the Marijuana Regulatory Process and Helps Close the Scientific Research Gap

One of the biggest challenges in the medical marijuana market is the inability to conduct clinical research on the efficacy of marijuana because it’s still a Schedule 1 drug at the federal level. Therefore, the growing marijuana market lacks the clinical data needed to help marijuana businesses create new and better products. Global Cannabis Applications Corp. (GCAC) is trying to change that.

GCAC’s Citizen Green technology uses artificial intelligence and blockchain to collect clinical data directly from consumers in an effort to streamline the regulatory process that impedes the manufacture of innovative marijuana products. In simplest terms, the technology rewards people who complete surveys with cryptocurrency – digital tokens – that they can use for products available through global medical cannabis programs.

The survey data is reconfigured into a clinical standard and combined with data from actual clinical studies as well as product information. GCAC says its Citizen Green technology provides better patient outcomes and helps researchers find qualified participants for clinical studies, which ultimately, speeds up the approval process for new medical marijuana products.

The reality is the cannabis industry needs access to clinical data to improve product development and further legitimize the industry overall, and they’re looking for innovative ways to access that data.

After being denied from receiving grant money, researchers from the University of New Mexico began using self-reported user data collected via the Releaf smartphone app to conduct research about medical cannabis consumption and symptom relief that led to studies published in two separate journals: Frontiers in Pharmacology and Medicines.

2. Big Data Improves Distribution in the Marijuana Industry

The distribution process for marijuana products is different from one state to another, but it’s always complicated due to security and regulatory compliance concerns. When it comes to getting products to the final distribution point – the customer or patient – big data and technology are having significant effects. Companies like Eaze and GreenRush offer web and mobile apps that enable people to choose their marijuana products and have those products delivered directly to them.

You might not instantly think that marijuana delivery and big data go together, but think again. Eaze captures data related to customers’ locations, products purchased, time spent considering each product, amount of time items were placed in the shopping cart before being removed, and much more. The company analyzes all of the data it collects and uses artificial intelligence, predictive analytics, and machine learning to put the information into usable formats for its clients.

Many companies use the data Eaze collects for marketing purposes – to target consumers with specific product messages, to create special offers, to develop new products, and more. The company helps businesses understand who their customers are and how those customers use their products. This data enables the businesses to develop better products and increase the return on their marketing investments.

3. Big Data Reduces Risk by Optimizing the Decision-Making Process

Today, big data is critical to decision-making in the marijuana industry. Having access to real-time intelligence can mean the difference between success and failure in this fast-moving marketplace. Technology platforms like Headsetand Zefyr track inventories, consumer data, and market trends from millions of data points. Using artificial intelligence and predictive analytics, the platforms turn the data into meaningful information that clients can quickly access.

Companies use the data available in these platforms to analyze inventory trends, reordering, items sold per transaction, number of items sold per budtender, transaction totals, grow cycles, production schedules, packaging needs, staffing requirements, product launches, market share, sales projections, wholesale prices, consumer trends, consumer behaviors, consumer spending, healthcare trends, and more. The data can also be used to analyze competitor brands, competitor product releases, and competitor prices.

Having access to this kind of data helps marijuana business communications, spending, and decision-making, but it does even more than that. It also helps these businesses stay ahead of the competition and gain measurable market advantages.

Big data also plays a role for investors who can use the artificial intelligence from VantagePoint to predict the cannabis stock market, identify patterns, and make less risky forecasts and investment decisions.

From a business risk perspective, cannabis companies use artificial intelligence, predictive data, and machine learning technology from companies like Adherence Compliance to analyze compliance data and predict where marijuana license holders are most likely to fail. This enables them to make critical decisions in advance in order to mitigate those risks.

4. Big Data Improves Efficiency and Revenue

A number of technology companies are developing solutions to improve operational efficiencies so cannabis businesses can streamline and automate processes and increase revenue. Several tech companies that offer solutions to cultivators have gotten a lot of attention over the past year, including Motorleaf, which tracks the growth rate of cannabis plants using artificial intelligence.

The GrowLife system uses data and artificial intelligence to automatically make changes based on growing conditions to reduce the cost of production and the risk of over-supply. At urban-gro, big data is processed at scale using its Soleil Technologies solution. Through predictive metrics, cultivators can make quick and better decisions that lead to improved crop outcomes.

Canada’s Wayland Group provides an integrated platform to cultivators that uses predictive data, artificial intelligence, and automation for environmental monitoring and building management. The result is improved asset utilization, fewer employees, shorter time-to-market, higher yield crops, and lower costs.

5. Big Data Improves the Customer Experience

In addition to its efforts related to product development discussed in #1, GCAC has taken steps to improve the customer experience in the cannabis industry using data and artificial intelligence. Last year, GCAC announced it would launch Sanna, which is an artificial intelligence chatbot that patients use to obtain information and recommendations related to medical marijuana. The artificial intelligence, machine learning, and natural language processing built into Sanna enable it to accurately analyze symptoms and treatment plans.

BudGenius is a different chatbot solution built with artificial technology and machine learning that uses its own cannabis testing results, scientific trial data, real user experiences, data about each marijuana strain, and artificial intelligence to help patients choose the best marijuana products.

Customer experiences can also be improved with the PotBot mobile app from Potbiotics, which uses artificial intelligence to sort through more than 30,000 cannabis strains, read peer-reviewed medical journals to analyze studies on cannabinoids, and match that information with up to 37 symptoms (such as cancer, asthma, and insomnia) to identify which strain is best to treat each specific condition.


Data and technology can predict the direction the industry is going in and what consumers will want next. Outside of the marijuana industry, small and large companies around the world already rely on data to make decisions in all aspects of company operations.

It’s not surprising that the importance of data has been recognized in the marijuana industry. As a result, new technology companies are opening in the cannabis space and traditionally non-cannabis companies are extending their brands to the marijuana industry.

However, all data is not created equal. The challenge is collecting, standardizing, and analyzing data that is highly reliable and relevant. In addition, the people using the data to make critical business decisions need to know what questions to ask in order to fully use the data available to them and leverage the power of artificial intelligence and machine learning. It all starts with quality data.

Bottom-line, companies that have access to real-time business intelligence and reliable predictive insights are better positioned to mitigate risks from all sources and increase revenue and profits. Data and technology – particularly data powered by predictive analytics, artificial intelligence, and machine learning – have changed the marijuana industry, and there’s no going back.

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