Predictive Analytics is the practice of looking for patterns within systematically compiled data in order to anticipate behaviors and trends. Predictive analytics can help sales and marketing professionals build models and ideal customer profiles, as well as information which can then be used to increase sales, retain profitable customers and understand which customers aren’t a good fit.
While nobody can actually predict the future, they are some clear trends in the predictive analytics market that are driven by the acquisitions that Salesforce has made in the market. Salesforce has an estimated 3.75 million users on their platforms – which mean they have more business per user data available than almost any company in the world. This incredible amount of data allows for better machine learning by predictive analytics software.
How Predictive Analysis Works
A rising buzzword in CRM and marketing circles, Predictive Analytics can sound a bit like magic. Our computers are going to simply “know” when someone is ready to shop for our company’s products and will automatically feed those perfect leads to our sales team.
Naturally, it’s not quite that simple, but that’s the aspiration. Marketers today are looking to use big data and machine learning to bridge the gap between the anonymous masses of the Internet and those customers they know are likely to (and would welcome the chance to) engage.
An auto insurance company, for example, might use predictors (variables) like age, gender, location, and driving history to assess the risks a specific policyholder presents.
Predictive Analytics works when multiple data points can comprise a forecasting model. These variables need to be germane to the behaviors in question: for example, age might be a determinate factor in whether or not someone could potentially shop for the latest LEGO set. Which movies that person recently attended could help predict which LEGO set they might like, and so on. A variable that perhaps isn’t that useful, in this example, might be someone’s height.
That said – we don’t actually know. There may well be a correlation between someone’s height and LEGO purchases. That’s where we turn to computer modeling to tell us.
Using the power of machine learning, a model can be leveraged to predict future probabilities with an acceptable level of reliability. Rather than banking on human guesses, or presumed if-this-then-that logical suppositions, computer analytics look for unbiased, actual patterns within large data sets and work to identify leading identifiers for behavior.
Scientists have used such modeling for many years in weather forecasting, medical prognoses, and geological research. As computing power and our access to data has increased, more and more can be applied to predictive analytics – including customer behaviors.
Salesforce.com is uniquely positioned to lead the industry. Not only does Salesforce.com itself have millions of customers, their customers have data on billions of their own customers – all stored in the Salesforce cloud. While in the past a given company could see (to some degree) what behaviors its established customers evidenced, Salesforce has the potential to pool behavioral information across multiple industries and thousands of companies. Likewise, browser and operating systems track individual behavior with increasing detail. The Internet of Things will no doubt yield yet more predictors on which to base models. We have access to more data than ever before.
Salesforce.com has made number of acquisitions in this emerging industry and will no doubt bring their sizable R&D muscle to bear in the years ahead. While initially available only to enterprise-level companies with the resources to devote to predictive analytics, Salesforce.com may well be able to popularize the capability as well.
While all of this has obvious privacy implications, and we are all right to suspect the self-serving agendas of commercial companies, predictive analytics could help just as well in recognizing when an individual isn’t ready to, say, buy a new pair of designer shoes.
Imagine a world in which the only ads you see are those that genuinely interest you. The goal and promise of predictive analytics in the marketing world is to identify those ideal customers who are ready to speak with us.
Please let us know if you have questions about predictive analytics or would like to learn more about ourSalesforce services.