Cannabis Advertising 101: Understanding Contextual vs. Behavioral Ad Targeting

As a cannabis marketer, you’ve likely heard about the death of third-party cookies on many popular web browsers. Data privacy and new regulations are causing big changes in the digital marketing landscape, and it is important to understand how your programmatic ad targeting capabilities will be affected.

Cannabis Behavioral and Contextual Targeting

Programmatic Ad Targeting Options in A Cookieless World

The loss of third party cookies will make it more difficult to track in-browser user behaviors in some cases, and agile cannabis marketers need to shift gears from behavioral ad targeting and supplement ad placements with contextual ad targeting approaches.

Let’s differentiate between the 2 targeting options to help you better understand where your ads may appear on websites and apps. We’ll break down what each targeting option is, how it is used, and the benefits of each so you can target each ad campaign to the most applicable audiences. Here’s everything you need to know about contextual vs. behavioral targeting for your cannabis ads. 

What is behavioral targeting? 

Behavioral targeting ensures the ads served to a user are relevant to their interests. Ads are analyzed and placed on web pages based on the users historical web browsing behavior.

Cookies and pixels track and collect data based on consumer demographics and behaviors such as websites visits, content views, ad clicks, purchases, and keyword searches. Data is then stored in a programmatic advertising (DSP) demand-side platform and further segmented into audiences representing distinct search and shopping behaviors.

For example, one audience segment may be “purchased cannabis flower in past 3 months” or “clicked on dispensary ad for concentrates”. Analyzing buying patterns and targeting audience segments by user behaviors you can get a sense of their product and buying preferences and serve highly engaging ads. 

How Does Behavioral Targeting Work? 

Behavioral targeting relies on past behaviors and actions to predict future buying behaviors. But how? 

The process consists of three steps: data collection, segmentation, and application. 

  1. Data is collected through pixels, MAIDS, or cookies to create user profiles. 
  • Two types of data to collect: user information and consumer behavior. User information is the essentials: demographics, location, mobile data. Consumer behavior is tracking online behaviors to learn more about habits and behaviors. 
  1. Market segmentation is sorting your audience into groups based on the products or service preferences. Data management platforms (DMPs) and (DSPs) help to store segmented data into different consumer groups, so they are standing by and ready to target when your ad wins an auction. 
  2. Create ad, launch, and optimize campaigns based on results.

Understanding behavioral targeting will allow cannabis businesses to identify:

  • Where to cross-sell or upsell products 
  • Reasons customers have stopped doing business with your company so you can reduce future churn rate 
  • The best time to reach out to target audiences – time of day, day of week, or what stage of the buyer’s journey they are in
  • Customer expectations and/or pain points – identify where your business can support consumers and how to get them back through the door.
  • High-value customers – how to keep them and create more loyal customers
  • Spending your marketing dollars on those that are ready to buy – more loyal buyers, or potential heavy users of your products/services 

Pros and Cons of Behavioral Targeting

Using personalization in your marketing is preferred and expected by 90% of consumers, as it shows your customers you understand their needs and wants. When your cannabis business understands the different customer audiences, you can personalize marketing messages to nurture leads, improve brand perception, increase engagement online, or provide recommendations for products or services. 

Analyzing past behaviors of your cannabis retail customers can help predict future purchases. This can also help decrease churn rate by anticipating when a customer is likely to stop using your products. This signals a good time to target the customer with retention campaigns to reengage them. 

Another benefit is being able to optimize ad performance and monitor behavioral changes in your target audience. This can help your business stay ahead of the competition by knowing your audience inside and out. 

Some of the downsides to behavioral targeting have to do with updated privacy regulations and the loss of third party cookie data. It also relies on past behavioral data, which may not match up with the customer’s current mindset or buying habits. 

What is Contextual Targeting?

Contextual targeting allows advertisers to deliver relevant ads to cannabis consumers based on the context of the webpage they are visiting. Using page content, metadata, and keywords as clues for ad placements, contextual targeting identifies pages that match search intent and places ads relevant to the page content.

Keyword contextual targeting identifies pages that match specific cannabis related keywords and serves your related dispensary or brand ad to the potential customer. 

For example, if a user is reading an article about the different types of terpenes, the ads served on the site could be for a dispensary or cannabis product sold in their area. 

Contextual targeting isn’t new and has been used for years in TV, radio, and print. There’s been a resurgence due to the fact that consumers do not have to opt-in to share their data for contextually targeted ads to reach them.

How do contextual ads work?

Contextual targeting is commonly applied through the demand-side platform (DSP) which manages finding websites and apps to place your ads and delivering them. Here’s how the DSP and contextual targeting work together: 

  1. Advertisers select parameters for targeting – your ads will only show up on websites that include cannabis keywords or topics that are selected. 
  2. Analysis of pages in your ad network – crawlers analyze web pages in the ad network to find those that are relevant to your keywords and topics. 
  3. If you win the bid, your ad appears on those relevant sites – a potential customer visits a related web page then the content is served to the ad platform. The platform matches a website with your targeting requirements and the ad will appear on the site. 

Lookalike Audiences and AI

A lookalike audience will use first-party data to understand your current customers and those similar to your current customers. It targets people who are likely to have an interest in your business and can build a larger audience base for retargeting. 

Advertisers will analyze first-party data to understand recent transactions and what preceded those transactions – web pages or contextual categories. Media lookalikes, or pages/categories similar to where customers visited before transactions, is where display ads will be placed for relevant products and services. These are based both on the context and the past transactions. 

By using the first-party data and past on-site behaviors, it allows advertisers to reach new audiences without the use of third-party cookies. Advertisers should work together with a partner that has access to larger data sets on commerce data and transactions. 

Semantic Targeting 

Semantic contextual targeting uses machine learning and algorithms to scan content to understand its true meaning. When using keyword targeting, the essence of the article may be missed. 

How does it work?

  • Content is scanned and is categorized 
  • Categorization is based on context and semantics (meaning)
  • User visits web page, content on the page goes to the ad server, then relevant ads are matched to the keywords and page content 

Semantic contextual targeting utilizes natural language processing (NLP) to analyze language and understand the context and meaning of web pages. This helps advertisers understand the content as a whole and not just search by keywords as with typical contextual targeting. It can allow for more advertising platform opportunities as AI helps to find the most relevant content for cannabis companies. 

For example, apple could refer to the flower name, a company, or a product. Context surrounding the word will determine the correct meaning of that keyword. AI can understand the sentiment and context of the web page and determine if your ad should be placed. 

Machine learning and semantic targeting doesn’t just apply to text. Images, video, and audio can be scanned and analyzed to understand meaning behind it. This opens more options for advertisers to determine the context of a web page and to also advertise with video, connected TV (CTV), and over-the-top ads (OTT). 

Why Your Cannabis Business Needs Contextual Ads?

Because of privacy laws like GDPR, the death of the third party cookie, and Apple’s privacy announcement, contextual advertising is having a comeback. But what are the benefits to contextual ads?

  • Highly relevant – ads are always relevant to the content the consumer is already looking for, reading, or watching. Reach users when they are browsing about a specific topic in real time instead of targeting past behaviors. Customers are more likely to respond positively which could lead to a conversion or sale. 
  • Privacy-friendly – doesn’t use cookies or collect information about users it isn’t vulnerable to changing privacy regulations 
  • Brand safety – by understanding what is on the page that the ad is being placed next to, you can ensure your ad aligns with what your customers want to see and won’t be placed next to inappropriate or noncompliant content
  • Target niche context – you can input specific phrases into your DSP to narrow the web page context even further

While there are plenty of benefits for contextual targeting, it’s not the only option for your cannabis business. Let’s take a look at comparing contextual vs behavioral targeting. 

Contextual vs Behavioral Targeting 

It’s tough to determine which is better when comparing contextual to behavioral targeting for cannabis businesses. There are pros and cons to both methods and each can be used for different campaigns with different key performance indicators (KPIs)

Contextual targeting can be easier to initially set up, it’s brand-safe, and doesn’t require cookies or permissions for ads to be placed. Ad dollars may go farther by serving contextually relevant ads to niche audiences placed on smaller cannabis and CBD-related publishers.

Behavioral targeting will allow cannabis brands and retailers to serve personalized ads and is great for retargeting purposes, but can be seen as a privacy concern for some consumers.

Interested in learning how these targeting methods can work for your cannabis business? Contact us today to learn more.