Behind the Buzzword: Predictive Analytics
Welcome to part three of our five-part Behind the Buzzword series, where we discuss the definitions and practical application of some of the latest tech industry buzz-phrases in the world of Data Analytics. So far, we’ve talked about A.I. and Big Data, and now we’re looking at a term that embodies what it means to improve decision making: Predictive Analytics.
Taking the Guesswork Out of the Game
Imagine that you are responsible for sales at a company within an industry that was difficult to predict. How can you predict which leads will turn into opportunities, and which opportunities will convert into sales? If only there was a way that you could more accurately anticipate the future so you could better prepare…
That’s where predictive analytics come in! Predictive analytics is a branch of data analytics that seeks to make accurate predictions about future events based on data and patterns. This information can then be used to help improve decision making. This is different than forecasting, because not all forecasting requires Big Data to anticipate behavior. While forecasting anticipates the behavior of many people over long periods of time, predictive analytics helps anticipate the behavior of one person over a short timeline. Not that long ago, to do predictive analytics, companies needed extremely expensive and time-consuming data models, analyzed by a full-time staff of PhDs in Mathematics. Today, cloud and business intelligence software have made it possible for companies of all sizes to reap the benefits of predictive technologies.
Key Drivers for Predictive Analytics
Here are the top-rated reasons organizations cited they will use Predictive Analytics:
|Understanding Customers||Improving Business Process|
|Predicting trends||Drive better business performance|
|Deeper relationships with customers||Make more strategic decisions|
|Predicting behavior||Improve operational efficiency|
In the competitive hotel industry, Red Roof Inn was operating at a fraction of the media budget of its competition. They turned to predictive analytics to help them identify a target audience with the greatest probability to convert and boost sales. During the record-setting winter of 2013-2014, around 90,000 passengers became stranded each day due to airline cancellations. The economy hotel chain realized the value of having hotels close to major airports in times of bad weather. Their marketing and analytics team worked together to identify publicly-available weather condition and flight cancellation data sets. Using this information, Red Roof Inn created a targeted online marketing campaign aimed at mobile device users in the geographical areas most likely to be affected by bad weather. This lead to a 10% increase in business overall and Red Roof Inn emerged as one of the first brands to utilize innovative flight-tracking technology to power its search efforts.
May the Odds Be Ever in Your Favor
This type of data was always available, but without a way for companies to segment and make sense of these massive data sets, the insights always remained out of reach. With cost-effective, innovative predictive analytics, companies can make more accurate and efficient decisions that only a few years ago would only be relegated to an “if only we knew” pipedream. And, as that Sales Manager, you’ll be able to predict which accounts will most likely convert to sales and strategize accordingly.
If you want to learn more about the different ways that data can predict your future, contact SWC.