Currently, there are data forecasting models, in specific markets, that use Google Cloud’s machine learning technology. The model is trained to use the data to predict customer search interest in, for example, cold and flu products.
These predictive insights help marketing teams to be more proactive in their marketing strategy and planning.
This data becomes a great tool, which will help us to be more assertive in our marketing strategy, with information on search trends, to obtain a more detailed image and capture the interest of users.
Today, these data are helping the health industry and we have as an example, what the pharmaceutical company Bayer is doing, since through a prediction model, it showed that the cold and flu season began at the beginning of May in Australia, with more cases than usual for this period.
The data indicated a 50% increase in flu cases nationwide. While the previous search strategy relied on coverage with keywords in generic terms, related to Bayer’s cold and flu product Redoxon, the new model allowed for a breakdown of the data across all states and showed where and where when searches were up or down, and in turn revealed emerging, product-relevant search trends.
From there, Bayer could adapt its marketing strategy, using automation, to add new keywords and optimize ad copy. This way you can ensure that the most effective, engaging and personalized ads will reach the right people at the right time. As a result, Bayer will be able to see effective paid search, an 85% increase in click-through rates year-over-year, and a 33% reduction in cost-per-click compared to the prior year. Ultimately, he has experienced a 2.6x year-over-year increase in traffic to his website.
In this sense, the data prediction models can be integrated into the marketing strategy of the practice, since these can help us understand what type of diseases are to come and therefore, what would be the profile of patients that we will be receiving.
Font:
Boltuch, T. & Donew, K. (2022, 8 November). How Bayer used machine learning to predict cold and flu trends. Think with Google. https://www.thinkwithgoogle.com/marketing-strategies/automation/machine-learning-predictions/
