Finding the right keywords for your website can make all the difference in increasing traffic and gaining profitable customers. Our global financial services client had tens of thousands of search terms that attracted users to their website, but to gain any traction on themes and appropriately prioritize their investment, they needed a way to automatically sort search terms into broader concepts. Their legacy process required heavy manual intervention and intense effort by their marketing and analytics team. The sheer volume and method of management prevented appropriate analysis and left money on the table.
Concord's data science team engaged to analyze the current state and develop a plan to make long-term keyword management more profitable and manageable. Our team implemented a combination of supervised and unsupervised learning data science models. For all uncategorized terms, the supervised learning model suggests existing categories and the unsupervised learning model suggests new categories. This revolutionary approach allows our client to focus their time on approving new term assignments and category suggestions, revealing a wealth of profitable new business categories for their search marketing program.
Our solution featured a simple interface using Google Cloud and Google Sheets powered by AWS Athena and Databricks to process the data and run models.
We successfully improved our client's keyword search categorization to reduce manual effort, save cost, and identify profitable new search categories.
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