Lawn Care Brand TruGreen Is Using IBM Watson Advertising’s AI To Plant Repeat Business

"This test with Watson Ads is a perfect entry point for us to explore AI-powered marketing," says TruGreen CMO Kari Rajaniemi.

The role of artificial intelligence in advertising is leaping from the experimental stage to something more commonplace, as all marketers want to reach “the right person, at the right time, at the right place with the right message.”

That was the impetus behind lawn care services chain TruGreen’s expanded use of IBM Watson Advertising’s AI tools to target specific customers with ads recommending specific offers related to local conditions.

TruGreen boasts 2.3 million commercial and residential customers with 260 lawn care branches in the United States and Canada, plus about 35 franchise locations. To reach those people and businesses with a timely message about their individual lawn care needs, the IBM Watson ads takes in many factors that might come into play, such as weeds, thin grass, dryness, lack of growth, or grass discoloration.

“At TruGreen, we are constantly looking for new and innovative ways to interact with consumers,” said Kari Rajaniemi, Chief Marketing Officer, TruGreen. “We have long enjoyed a partnership with Watson Advertising, and this test with Watson Ads is a perfect entry point for us to explore AI-powered marketing. Our TruGreen team ‘educated’ Watson, and I’ve been impressed with IBM’s ability to create an interactive campaign that understands our brand and our customers’ needs. We’re excited to see where this could take us.”

Here’s how it works: Consumers can get a personalized lawn plan recommendation by simply starting a “conversation” within TruGreen’s AI-powered ad, which employs a series of dialogue prompts. As the conversation continues, the AI-powered ad guides consumers using images, videos and other interactive buttons that are relevant to the topic at hand.

For example, if the consumer is dealing with discoloration in their yard, they can select the “grass not green” option, which will kick off a conversation with Watson to learn more about their specific lawn care concerns. Alternatively, the consumer can type in “How can I get my lawn looking great?” and Watson will respond with a series of questions to get clarity on the specific lawn needs.

An IBM Watson Ad uses AI to start a dialogue with a a prospective TruGreen lawn care customer.

Based on the data provided in the conversation, the Watson Ad will recommend a personalized TruGreen lawn plan or provide information about TruGreen’s line of service offerings, from Mosquito Defense to Tree and Shrub Care, “to help the consumer make their lawn the envy of the neighborhood.”

This example of using AI in terms of recommending the best time for a consumer to check out personalized lawn service seems to carry the weather intelligence that’s part of IBM Watson Advertising’s history to a much broader degree — recent examples include the AI ad platform’s work with H&R Block during tax season and a Valentine’s Day promotion with 1-800-Flowers.

So what kind of triggers are used to personalize recommendations? Is it that someone has to opt-in to receive these recommendations via The Weather Channel and other apps in the IBM Watson Advertising network of publishers/apps? Or is it triggered by weather conditions? Or a series of intersecting factors?

A rep for IBM Watson Advertising told GeoMarketing that the Watson Ad creative adapts to the user’s current weather condition or whatever zip code they are searching. Therefore, specific ads will surface during the corresponding sunny day, cloudy day, clear night, cloudy night with related creative.

“However, the user’s current weather condition does not trigger a specific lawn recommendation because the recommendations in the Watson Ad experience are based on the user’s inputs about their lawn conditions via the buttons or conversation,” the IBM Watson Advertising rep added. “Since those recommendations are part of the ad experience and not the overall app, they wouldn’t opt in to receive recommendations since it’s not an app notification.”

About The Author
David Kaplan David Kaplan @davidakaplan

A New York City-based journalist for over 20 years, David Kaplan is managing editor of A former editor and reporter at AdExchanger, paidContent, Adweek and MediaPost.