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Mar 3, 201609:45 AMOpen Mic

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5 reasons predictive analytics can make or break your sales

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For a sales-driven organization it isn’t the size of your data that matters, it’s what you do with it. No longer a discretionary luxury, predictive analytics are now the name of the game for those who seek to utilize customer metrics in a meaningful way to establish a tremendous competitive advantage, gain notable market share, and significantly boost bottom lines. In fact, according to the 2015 State of Sales Report published by Salesforce Research, “smart selling fueled by predictive analysis is expected to jump 77% among high performers,” throughout 2016. Not only that, but high performers are also four times more likely to use predictive analytics.

Just what exactly is predictive analysis? Simply put, it’s the ability to more precisely predict a customer’s future spending based on their past behaviors. Of course, there’s no way to actually predict the future but predictive analysis can give companies invaluable insight that can make or break a CRM system.

If you’re not using predictive analytics, your current CRM system is likely falling short in several areas. Here’s how predictive analytics can help:

1. Forecasting likely customer behaviors

There’s an old saying in sales: “Buyers are liars.” Unfortunately, salespeople are forced to enter notes based on what the customer tells them. Besides these basic notes that are often unreliable, it’s almost impossible for a CRM system to determine a consumer’s actual behavior.

However, predictive analytics software comes with a certain level of assumptions. In this case, the assumption is the future will continue to be like the past. However, behaviors often change. That’s why it’s critical to have a system that can not only change with your customers but also learn and adapt to their new actions to make predictive calculations based on the past, present, and future behaviors.

2. Enhancing customer relationships

It’s very difficult to build a true customer relationship if you have no way of accessing and analyzing their prior behavior with your company. Unfortunately, a CRM system cannot automatically track customer actions. It relies heavily on manual human interaction and cultivation relying heavily on the accuracy of a salesperson’s notes, which are often less than desirable.

In fact, the most common use of predictive analytics is to increase and improve customer relationships. The better you know your customer, the more sales you can ultimately make. Using sophisticated algorithms to reveal how your customer behaves allows you to also better communicate with your customer. For instance, isn’t it nice to hear your name when you walk in to your local coffee shop? Isn’t it nice that they already know what you’re drinking without you saying anything? On a larger scale, this is how predictive analytics enhance a company’s sales efforts. Many direct marketers have it figured it out, sending you offers in the mail that you are likely to actually want as opposed to the ones you consider junk. This is all done with predictive analytics. Another great thing about predictive analytics data is that it doesn’t have to be “big” at all. Sometimes the data can be just a small concentrated section of just a few hundred actions.


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