Shampoo brand Clear capitalized on AI-powered predictive modeling to help soccer fans anticipate the outcomes to their matches and thereby alleviate their anxiety.
Objective:
Clear is the leader in dandruff shampoo in Indonesia but has fallen in terms of the overall share. The brand was looking for a way to strengthen its connection with its primary audience, men with active lifestyles or soccer enthusiasts.
How could Clear make these connections and better associate itself with its audience than its competition? By finding a way to integrate itself into the lives of these men on a more regular basis. And how to do that? Premier League soccer matches.
While soccer has always been a part of Clear's strategy, the brand shifted gears and focused on a different aspect of the viewing experience: anxiety.
Anxiety is a natural emotion, but the feeling of heightened anticipation can be overwhelming. Sports enthusiasts commonly feel anxiety as they watch sporting events, which can be manifested in physical responses. Extreme cases of this would be a heart attack and reckless driving, while milder cases would be increased consumption of fatty foods during sporting matches (a.k.a., stress eating). But if you can reduce a fan's anxiety levels, he or she will have a more enjoyable viewing experience.
The brand wanted to strengthen its connection with this audience by integrating itself into the viewing experience of soccer games and increase its engagement with fans.
That's what Clear set out to do with its data-driven approach.
Target Audience:
Clear identified the soccer fans of the country as its primary audience.
Clear found that soccer matches are a rollercoaster of emotions, being full of anxiety, nervousness, and high drama both from a player and fan perspective. Indonesian football fans undergo much physical and mental stress while watching their favorite teams as they play and in all the drama that takes place off the pitch.
This situation presented a perfect opportunity for Clear to help relieve consumers' tension by introducing someone knowledgeable who had a calm head and was there to help them at any time — someone who could give football insights and in-depth data in an instant.
Creative Strategy:
Soccer is the most popular sport in Indonesia, with daily search trends often dominated by the events of Premier League matches.
Clear's strategy was to decrease fans' in-match anxiety by using artificial intelligence and machine learning to predict outcomes through social media. Anxiety results from an unknown outcome, and Clear could reduce this anxiety through its predictive model.
Clear partnered with Goal.com, Premier League, and Opta to design and develop an algorithm that would predict outcomes during a soccer match, which would be translated into real-time social media content to reduce fans' anxiety.
Fans could still enjoy the excitement of the match without being overwhelmed by the unknown nature of the sport.
Context:
2020 was the launch year for Clear's campaign, called: "Headsmart."
To execute this challenging effort to reduce fan anxiety across 50 Premier League games, Headsmart had to proceed with four steps:
Overall Campaign Execution:
To execute this technically challenging solution to reducing fan anxiety across 50 Premiere League matches, Clear had to execute in four phases. First was building out the underlying technology through a partnership between Goal.com and Opta.
Clear used Opta's Live Win probability model, powered by machine learning (ML) and artificial intelligence, which offered a real-time forecast of the outcome of a live football match.
The model followed significant match events such as goals or red cards and five additional variables such as the time remaining and historic performances over the last four years. The ML-AI engine simulated all these variables of a game over 100,000 times to forecast the game's outcome in real time.
With the predictive algorithm in place and the machine learning behind it to improve its accuracy over time, Clear develop a three-phase media strategy to deliver contextual messages to soccer fans across social media channels.
During the pre-match phase, Clear delivered pre-game probability ads, along with polls and quotes, across social media channels such as Instagram and Twitter.
The live-event phase of the campaign was the most demanding, as this was when Clear delivered real-time probability updates to fans through the Live Win probability model. These updates on social media would be the backbone of Clear's effort to increase touchpoints with soccer enthusiasts, ease their anxiety, and better connect them with Clear.
After the match, Clear stayed connected with fans by sending out post-game recaps and analysis in partnership with Goal.com. These three phases ensured that Clear was in step with soccer fans throughout the lifecycle of a match.
Mobile Execution:
Mobile was a big part of Clear's strategy. Soccer fans in Indonesia often searched for information about their favorite teams and upcoming soccer matches digitally through their mobile devices. Through Goal.com, Twitter, and Instagram, Clear connected with these fans through various pieces of content pre-match, during the event, and after the match. Especially during the game, these soccer fans were very engaged and focused on watching the matches. When there were short breaks in between, what they usually did was check their mobile devices. Therefore, the platforms that Clear chose to focus on were the ones they could access quickly and frequently, like social media platforms.
Opta's ML and AI-powered Live Win probability model was at the center of all Clear's efforts. The probabilities of wins and losses generated from Opta were converted into tweets, captions, and images that could reach soccer enthusiasts.
Clear's campaign drove excellent results in terms of reach, engagement, and prediction accuracy.
In total, across the 50 different matches, Clear reached 14 million Indonesians, 87 percent above the expected reach. During this time, Opta ran 225 million simulations, resulting in 454 pieces of content created for social media (23 percent more than planned). This was done with a 75 percent accuracy rate for all predicted outcomes.
Clear's engagement rates for the top 10 posts exceeded its previous campaign baseline by 24 percent, coming in at 9.7 percent. Its top Twitter post came in at an 8.12 percent engagement rate, which was 62 percent higher than the benchmark.
Social media sentiment polling discovered that 80 percent of respondents were aware of Clear and 48 percent said that the match was made more appealing due to Headsmart. Finally, 21 percent said that their anxiety was reduced due to Clear's Headsmart campaign.
