Google Ads Machine Learning: Foottraffik's Dispensary Advertising Delivers – Cashinbis


We know dispensaries are frequently looking for compliant ways to advertise so we’re always on the lookout for different approaches. And we were recently surprised at a new addition to the dispensary advertising field: machine learning.

Foottraffik, one of the industry’s leading dispensary ecommerce growth agencies, is combining the reach of Google with the intelligence and efficiency of machine learning. 

Now, Google Ads are underused by dispensaries. Despite being the most commonly used form of pay-per-click advertising, dispensaries still think they can’t leverage this platform to get the word out.

Thankfully, Foottraffik has shown that, yes, dispensaries can advertise via Google Ads

The team has been running ads for over four years. And now, they’ve added machine learning to their Google Ads management service to make their high-ROI offering even better.

Dispensary Advertising with Google Ads Machine Learning

According to the company, Foottraffik’s new AI software connects real-time trends to client Google Ads campaigns, effectively supercharging performance and increasing revenue by up to 25%. 

By using a combination of real-time weather data, social media signals, and historical data from previous ads, their new Google Ads machine learning technology is able to create new models on which to base their copy and bid strategies. Because this modeling produces dynamic strategies that respond to shifts in demand and trends, they generally yield greater returns.

Founder and CEO Guillermo Bravo adds that “As dispensary advertising is limited, it’s great that we can offer a highly effective and reliable channel for dispensaries to reach their local customers. The software will give dispensaries a competitive advantage in their local market by maximizing their advertising spend and increasing conversions and revenue. Foottraffik has never had a Google Ads campaign shut down in over four years, and we are happy to announce even more functionality when

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