Why Cannabis Rivals Share Data

The value exchange is real.

Retail sales. Wholesale orders. Inventory levels. Product pricing. Consumer purchasing behavior. Loyalty activity. Marketing response rates. Banking transactions. Compliance records (and those pesky (led based?) tags). Product movements. Testing results.

Every day, brands, retailers, cultivators, manufacturers, and distributors allow software providers and other intermediaries to access some portion of their operating data.

Why?

Because in many cases, that data is useful beyond the company that created it but also for the company that provided it.

It can be anonymized, aggregated, normalized, analyzed, and transformed by independent and neutral organizations into products that benefit other participants across the industry.

And, for the most part, every industry, including cannabis, is comfortable with this arrangement.

Why?

Because when the value exchange is clear, sharing data just makes sense.

The Cannabis Industry Already Runs on Contributed Data

Consider how much of what we believe we know about the legal cannabis market comes from aggregated operator data.

How do we know which product categories are gaining or losing market share?

How do we know whether flower prices are falling?

How do we compare vape sales v pre-roll sales v flower sales v gummie sales?

How do brands measure their market penetration?

How do brands find retail accounts?

How can a company determine whether its products are underdistributed in a particular market?

How do we know which package sizes, strains, price points, or product formats are gaining traction and which are slowing down?

Much of the industry’s most valuable commercial data based intelligence does not originate from government agencies.

It comes from the industry players themselves. Competitors sharing data, again, to a neutral third party who is also non-conflicted.

Individual operators generate data through their ordinary business activities.

Instead of keeping that data in individualized silos, they allow software platforms to collect portions of that data (subject to contractual arrangements and permissions.) The information can then be aggregated, anonymized, normalized, modeled, and converted into intelligence that has value far beyond the individual company that originally generated it.

Again, every industry has been doing this for years.

Retailers Share Sales Data

The most obvious example is point-of-sale data.

Retail analytics companies such as @Headset and @BDSA and @lid alerts have built valuable market intelligence products using retail sales data, related market inputs and proprietary analytic techniques.

A single dispensary knows what happened inside its own four walls.

It knows that it sold 100 units of a particular vape cartridge last month. It knows that a certain pre-roll is selling faster than another. It knows its average basket size and which days of the week are busiest.

But that retailer cannot independently know what is happening across an entire state or market.

Once information from many retailers is aggregated and normalized, an entirely different picture becomes possible. The resulting intelligence can help answer questions such as:

Is the category growing?

Is the brand gaining share?

Is the average selling price falling?

Is the product performing better or worse than comparable products?

Are consumers moving from one form factor to another?

Which price tiers are gaining traction?

The individual retailer contributes a small piece of information. In return, the industry gets a much larger picture for a fair price.

Everyone wins.

That is the basic bargain underlying many data businesses.

None of this is unique to cannabis. Outside the industry, this is precisely what Circana, the company formed from the merger of IRI and NPD, and NielsenIQ have done for decades. Thousands of grocery, drug, and mass retailers feed their checkout data into a shared system. Individually, a single store’s scan data is a private record. Aggregated and normalized, it becomes the category share, pricing, and velocity intelligence that consumer brands rely on to run their businesses.

Competitors feed individualized data into the system and buy back important trends that their silo’d data would not show on it’s own.

The cannabis version is younger. The mechanism is exactly the same.

Retailers Share Inventory and Menu Data

Sales are only one source of industry intelligence.

Dispensary menus and inventory systems generate another enormous stream of information.

Companies including Hoodie Analytics, Pistil Data, and Happy Cabbage have developed products that help brands and other operators understand product availability, distribution, pricing, inventory movement, menu placement, and potential reorder opportunities.

The data collection methods differ.

Some information comes through authorized software integrations and data partnerships. Some comes from publicly observable online menus. Some analytical products combine multiple data sources. Some comes from proprietary software developments.

But the underlying economic principle is similar.

One store’s inventory position is not especially valuable to the broader market or that individual retailers itself.

Thousands of inventory observations, organized over time, can become extremely valuable.

A brand can potentially identify where it is underdistributed.

A sales representative can focus on accounts that appear to be running low on product.

A company can compare pricing across retailers.

A manufacturer can see whether products appear to be sitting on shelves or moving through the market.

A sales manager can direct a team toward opportunities rather than asking representatives to call every account indiscriminately.

A buyer beomes smarter!

Raw data becomes intelligence.

The same pattern has a long history in mainstream retail. Consumer brands have paid for years to understand where their products are stocked, at what price, and how quickly shelves turn, through distribution measures such as ACV and through e-commerce shelf trackers like Profitero. One shelf tells you almost nothing. But…thousands or millions of shelf observations from multiple competitors, tracked over time, tell you where a brand is winning and where it is losing.

E-Commerce Platforms See How Consumers Shop

The industry’s e-commerce infrastructure creates another valuable category of information.

A platform such as Jane Technologies sits at an important intersection between retailers, products, and consumers.

An e-commerce platform can potentially observe far more than a completed transaction.

Depending on the platform and data permissions, the ecosystem may generate information about product availability, search behavior, shopping activity, cart behavior, conversion, pricing, promotions, and purchases.

Again, the value of the information changes when viewed at scale across the silo’d states or even nationally and brands slowly roll out and gain traction across the country.

A retailer sees its own customers.

A larger platform can identify broader patterns.

What are consumers searching for?

Which products convert?

What happens when prices change?

Which products are frequently viewed but not purchased?

What categories are gaining attention?

The individual interaction is mundane.

The aggregate pattern can be commercially powerful.

Will your competitors benefit from the same access you are paying for? Yes. But you also benefit from access to their data to make intelligence based decisions.

This is the same advantage that platforms like Amazon hold in the broader economy, and that firms such as Stackline turn into products. A single seller sees its own listing. A platform sitting across millions of sessions sees what an entire market searches for, compares, abandons, and ultimately buys. The behavior of one shopper is noise. The behavior of millions is a demand map.

Loyalty and CRM Platforms See Consumer Behavior

Cannabis operators also share information through customer relationship management and loyalty systems.

Companies such as AIQ (formerly Alpine IQ) and Springbig, Distru and Sprout from Weedmaps help operators segment customers, analyze purchasing behavior, measure campaign performance, and improve marketing.

This creates another category of industry data: the relationship between marketing activity and consumer behavior.

A point-of-sale system can tell a retailer that a purchase occurred.

A CRM and loyalty platform can help connect purchases to customer segments, communications, offers, loyalty behavior, and repeat visits.

That information can be used to answer a different set of questions.

Which customers are becoming inactive?

Which offers drive purchases?

Which customer segments prefer certain products?

How frequently do different groups return?

Which marketing campaigns actually produce measurable results so your’re not discounting just for the sake of discounting?

Once again, the operator allows data to move into a specialized software system because the operator expects to receive something more valuable in return.

Better segmentation.

Better attribution.

Better retention.

Better marketing.

The mainstream version of this is one of the most valuable data businesses ever built. When a shopper swipes a loyalty card at Tesco or Kroger, the individual purchase is ordinary. Analyzed at scale, by dunnhumby in Tesco’s case and by Kroger’s 84.51 analytics arm, that loyalty data becomes the segmentation, targeting, and measurement that the retailer uses itself and sells back to the brands on its shelves. The customer/shopper trades data for discounts and relevance. The retailer builds an intelligence business on top of the exchange.

Wholesale Platforms See How the Industry Buys

The same phenomenon exists at the wholesale level.

LeafLink and Apex Trading have been operating large wholesale commerce ecosystems connecting licensed buyers and sellers.

The data generated by a wholesale marketplace is fundamentally different from retail POS data.

Retail data tells us what consumers bought.

Wholesale marketplace data can reveal patterns in what businesses order.

Which categories are retailers buying?

How frequently are they reordering?

How are wholesale prices changing?

Which markets are expanding?

What is happening to order sizes?

Where is purchasing activity accelerating or slowing?

Aggregated wholesale transaction information can become a market intelligence product because no individual brand, distributor, or retailer can see the entire market.

Each participant sees its own orders.

The platform can see broader patterns.

That difference in visibility is the foundation of the value.

Wholesale data businesses exist well beyond cannabis. Faire, the marketplace that connects independent retailers with the brands that supply them, uses aggregated order data across its network to forecast demand and recommend products no single store could anticipate on its own. Broadline distributors in food and other sectors have monetized their order data in similar ways for years. Each buyer sees its own purchase orders. The network sees the direction of the whole market.

Financial Platforms See Money Moving Through the Industry

The cannabis industry’s financial infrastructure creates yet another data pool.

Green Check Verified connects cannabis businesses and financial institutions through compliance and financial infrastructure.

The value exchange here is particularly easy to understand.

Cannabis operators want access to banking and financial services.

Financial institutions need information to manage Federal compliance and risk.

A specialized intermediary helps organize, verify, and monitor the necessary information.

At sufficient scale, the information flowing through these systems could, in aggregate, provide insight into broader industry trends.

Outside cannabis, the same logic runs through much of financial technology. Services like Plaid and Yodlee sit between consumers, businesses, and their banks, organizing financial data so that other tools can function. Payment platforms go a step further. Square and Stripe use a merchant’s own transaction history, data the merchant generates simply by operating, to extend working capital that a traditional lender would be slower to offer. The merchant contributes nothing extra. The platform reads the data already flowing through it and returns something the business could not easily get on its own.

This illustrates an important point:

Operators do not necessarily share data because they are interested in creating an industry data pool.

They share it because they want something valuable in return.

Banking.

Analytics.

Compliance.

Marketing.

Benchmarking.

Inventory management.

E-commerce.

Operational efficiency.

Ideally, they want total situational awareness at a fair price.

The aggregated dataset is often a byproduct of thousands of individual companies each making a rational decision to receive a specific benefit.

State Regulators Collectively Hold Massive Operational Datasets

Track-and-trace systems create perhaps the industry’s most comprehensive operational datasets, even if it sits behind a locked gate.

Through systems operated by companies such as Metrc (the Ticketmaster of Cannabis), regulated operators report enormous amounts of information related to plants, harvests, packages, transfers, testing, inventory, and sales activity, depending on the jurisdiction and license type.

Other regulated industries run comparable systems. Pharmaceuticals are moving through the phased rollout of the Drug Supply Chain Security Act, a federal mandate to trace prescription drugs electronically at the package level as they pass from manufacturer to pharmacy. Alcohol producers report to the federal government through the Tax and Trade Bureau utilizing software such as Eros, Encompass and StillTrack. When a product is regulated, mandatory data reporting tends to follow. Cannabis is walking a path that pharmaceuticals and alcohol walked before it.

This is different from voluntarily contributing data to a private market intelligence company.

Participation is generally tied to regulatory compliance and is typically locked up by the state.

But it reinforces the larger point.

The cannabis industry is not an industry in which data remains locked inside individual businesses.

It moves through an interconnected network of POS systems, track-and-trace platforms, accounting systems, wholesale marketplaces, e-commerce platforms, CRM systems, loyalty programs, financial compliance systems, inventory tools, and analytics providers.

Data sharing to neutral third parties by competitors is already part of the industry’s infrastructure.

Why Do Operators Allow It?

The answer is surprisingly simple.

Because the operator receives value in return.

Sometimes the value is direct.

Give a software provider access to sales data and receive dashboards and analytics.

Connect an inventory system and receive automated replenishment tools.

Connect customer data and receive segmentation and marketing automation.

Share financial information and gain access to banking services.

Provide compliance data and satisfy regulatory requirements.

Sometimes the value is collective.

A single operator’s information has limited analytical value.

A sufficiently large, properly governed, anonymized, and aggregated dataset can allow every participant to understand a market that none of them could see individually.

No, this is not unique to cannabis.

Industries throughout the economy operate on versions of this model.

The important question is whether the exchange is fair, transparent, neutral, secure, properly permissioned, and valuable to the contributor.

The Industry Shares Almost Everything, But in Silos

What is most interesting about cannabis data is not that the industry lacks it.

The industry is drowning in data.

The problem is that the information exists in separate silos.

One system sees what consumers buy.

Another sees what retailers order.

Another sees inventory.

Another sees consumer loyalty behavior.

Another sees marketing response.

Another sees product movement.

Another sees compliance activity.

Another sees banking transactions.

Each dataset answers a different question.

And each became valuable only when someone recognized that isolated operating records could be transformed into broader intelligence.

That may be the most important lesson.

Data does not need to identify the contributing operator to create value.

In many analytical models, the value comes from aggregation.

One company’s experience is an anecdote.

One thousand companies’ experiences can become a benchmark.

One transaction tells us almost nothing.

Millions of transactions can reveal a market.

One inventory position is a snapshot.

Thousands of inventory positions observed over time can reveal velocity, distribution, pricing pressure, and demand.

Cannabis Operators Are Already Data Contributors

There is sometimes an instinctive reaction in cannabis when a company asks an operator to contribute data:

Why should I give anyone my information?

It is a very reasonable question.

But it ignores how the modern cannabis industry already operates.

The better questions are:

What data is being requested?

How will it be protected?

Will the contributing company be identifiable?

Will the information be aggregated or anonymized?

Who can access it?

What products will be created from it?

And, most importantly:

What happens if you’re a curmudgeon and decide to sit by yourself?

Those are the questions that should determine whether a data exchange makes sense.

The mere concept of contributing data is no longer unusual.

Cannabis operators are already doing it every day.

They contribute sales data and receive market intelligence.

They contribute inventory data and receive analytics and automation.

They contribute customer data and receive marketing tools.

They contribute wholesale activity and gain access to commerce infrastructure.

They contribute financial information and receive access to banking and compliance services.

They contribute track-and-trace information because participation in the regulated system requires it.

The cannabis industry already understands the value of shared data.

It simply may not think about all of these activities as part of the same phenomenon.

They are.

The regulated cannabis industry has quietly built an ecosystem in which individual companies contribute pieces of information, intermediaries organize and analyze those pieces, and aggregated intelligence helps the broader industry make better decisions.

The question is no longer whether cannabis companies should ever share data.

They already do.

The more useful question is:

What other problems could the industry solve if operators could contribute carefully selected data, protect their identities and confidential information, and receive something genuinely valuable in return?

Hmmmm

Reklaim Credit Solutions has a few ideas!

I’ll be writing about that shortly!

This is Third-Party content and does not reflect (or not not reflect) the views of Cannabis Confidential or CB1 Capital.

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