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 the name of the game, helping firms use customer metrics to establish a competitive advantage, gain market share and boost bottom lines. What is predictive analysis? Simply put, it’s the ability to predict a customer’s spending based on past behaviors. Of course, it’s not magic, 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,” says data-driven marketing authority Lang Smith of Cloud Signalytics, a proprietary predictive intelligence software platform.

Lang offers five ways predictive analytics can help a CRM-based marketing engine achieve more:

1. Forecasting Likely Customer Behavior

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. Often, however, behaviors 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 past, present and future behaviors.

2. Enhancing Customer Relationships

It’s difficult to build a customer relationship if you have no way of accessing and analyzing their prior behavior. Unfortunately, a CRM system cannot automatically track customer actions. It relies heavily on manual human interaction and the accuracy of a salesperson’s notes. The most common use of predictive analytics is, in fact, to increase and improve customer relationships. The better you know your customer, the more sales you can make. Using sophisticated algorithms to reveal how your customer behaves allows you to better communicate. For instance, isn’t it nice when your local coffee shop already knows what you’re drinking without you saying a word? On a larger scale, this is how predictive analytics enhance a company’s sales efforts. Many direct marketers have it figured it out, sending offers you are likely to want, rather than ones you consider junk. This is all done with predictive analytics.

3. Maximizing Marketing Budget ROI

No matter the size of your marketing budget, it’s best to make sure the audience you’re targeting wants what you’re selling before spending those funds. On its best day, a CRM system can only give you an educated guess. If you want to maximize your marketing dollars, solely using a CRM platform is not the best direction. But, with predictive analytics, you can maximize return on investment, no matter the budget. For example, if you seek to spend $10,000 on a campaign to 10,000 customers or prospects, predictive analytics will curate that audience to consumers who want what you’re offering at the time. Conversely, CRM solutions alone have limited filters that prevent a business owner from drill-down targeting of the correct audience.

4. Allowing Data-Driven Decisions

The core success benchmark of any company is its numbers. A CRM system cannot show you exact sales numbers broken down by each individual customer over time with any ease. A significant amount of training is usually involved in trying to access and formulate these tasks. This often requires a lot of time, which means less time spent making actual sales. Fortunately, good predictive analytics software will allow you to identify where your money is being made and which areas of your business are lacking.  It should also be able to provide you with a customer spending list based on what you’re asking for. Adept systems can categorize all your customer spending and break it down in an easy-to-read format that allows you to make predictions.

5. Formulating Offer Intelligence

Unlike a predictive analytics platform, CRM systems cannot recommend specific offers that are unique to customer spending habits. This is a huge downside. It is very difficult to maintain and engage repeat customers without knowing what they want. CRM solutions are mainly a lead-management system, but who wants leads when you can have buyers?

Lack of quality data is usually the greatest barrier a sales-driven organization faces when implementing predictive analytics. Lang underscores that “getting the most out of a predictive analytics platform requires there is actually available data on customer spending habits, the attributes of the products or services they’re buying (other than the ‘people who buy this also buy this’ type of model), date ranges of their spending, and how much they spend on an average.” Some demographic information wouldn’t hurt either, he says.

With predictive analytics in your arsenal, you can expect to grow sales revenue and overall company profitability in kind.

Business and branding expert Merilee Kern is an influential media voice who serves as chief public relations and communications strategist for multiple agencies. She also is the executive editor of "The Luxe List.” Merilee may be reached online at www.TheLuxeList.com.