Recently, we spoke with a client who was asking questions about our predictive learning algorithm – specifically how the system would bid on keywords with little to no data. Because QuanticMind is the only company employing these methods and technology, he found it hard to believe.
And, I don’t blame him.
But, Guillermo leaned over and told me to write down “SEM is not a random walk.”
It took me quite a while to understand our application of Natural Language Processing (NLP) to SEM. NLP is not easily explainable, and no one else in our market uses such technology. Using five different sorting and clustering algorithms, computers take hold of the task of grouping similar keywords, rather than manually by people. Using these clustering algorithms, we can use the existing keywords to inform bids for new keywords or longtail keywords and by not taking an average of the grouped keywords. Instead, by independently calculating and predicting the proper bid for each individual keyword. Anyways, I digress.
At the time, I didn’t know what Guillermo meant by “SEM is not a random walk.” I had never heard that term in the context of the stock market or finance, but I understood the meaning. After the call, he explained how the stock market is, in fact, a random walk. It’s informed by trends, but algorithms can’t make predictions or account entirely for good or bad business decisions. Precedent can only inform the stock market in so many ways. While there are a few similarities, SEM does not fall into this category. Why?
…Because the nature of SEM is to measure and track consumer behavior. The ability to predict this activity is what gives sophisticated marketers an edge over competition.
This is precisely why we import and require at least 1 year of historical data in order for us to effectively implement NLP. This historical data is what our system uses to predict what the activity on a keyword may be year over year, month over month, day over day, and even by the hour.
Because of the market predictability, SEM is not a random walk. There’s a path that’s been carved out by the thousands, or millions, who have used the keyword before you. And, while the path may change over time, it generally stays the same. When you’re using QuanticMind, you have both a flashlight and a map, so that walk turns out to be rather nice.