While customer relationship management (CRM) applications already collect terabytes of useful customer information for businesses, even deeper insights are on their way thanks to a developing new trend of predictive analytics capabilities being integrated into CRM.
The big draw, says James Kobielus, an analyst with Forrester Research, is that companies will be able to use existing CRM data to vastly improve critical one-on-one interactions with customers. Another key benefit, he says, is that it will help companies generate additional sales when customers contact them by analyzing incoming customer data in real time.
You’ve likely seen this when you buy something online and the vendor’s Web site displays other items that you might be interested in purchasing, based on what you’ve already placed in your shopping cart.
It’s the same idea with CRM that includes add-on or built-in predictive analytics when a potential customer arrives at your company’s Web site to make a purchase, Kobielus says. “If you offer this product at this price at this time, are they likely to buy it? You make a targeted offer to a customer based on what they are shopping for. The likelihood that they accept that offer will determine if you can maximize customer retention, sales and profits.”
Predictive analytics being tied in with CRM is something Kobielus says is showing up more and more in the marketplace as vendors respond to businesses that demand more from their CRM systems. For example, a customer contacts a company’s call center with an order question or a concern, then once the caller’s inquiry is resolved, the call center agent could be equipped to offer the caller some kind of special purchase opportunity based on their account information and prior purchases. All of this would all be visible on the call center agent’s screen.
“We are seeing [some of] this in CRM now and we will see more of it,” Kobielus says. “CIOs should be thinking about it because CMOs are thinking about it.”
The impacts are clear — businesses could potentially see increased revenue by utilizing the customer data they’re already collecting by using it more effectively, Kobielus says.
Luckily for busy IT leaders, this won’t be a completely new technology to learn and implement. Instead, it’s essentially an offshoot of existing business intelligence (BI) initiatives, which use analytics to mine, scour and sort corporate data for patterns and uses that aren’t easily visible to the naked eye. But here it is being tied in directly with CRM apps to drive their value even more.
Another offshoot of this, Kobielus says, is that the CRM apps and predictive analytics tools are being connected more closely with social media platforms such as Facebook and Twitter to help businesses leverage information gathered from customers.
That’s allowing companies to broaden their CRM data so they can more effectively target their marketing resources to customers, he says. “It’s very much a topic that’s heating up,” Kobielus says.
In the meantime, as these kinds of predictive analytics features are introduced, companies will need to figure out their approaches to incorporating the right ingredients into their own infrastructures. That will take research, detailed inquiries and discussions with teams from marketing, IT and other departments, as well as market research and more. It’s not something you’ll be able to jump into with little thought. You’ll want to know your goals before you take the first steps so you can achieve adequate payback from your investments of time and resources.
“You need to be ready for this and make sure that your CRM system will be able to handle this kind of thing,” Kobielus says.
Some vendors will offer predictive analytics as an embedded feature in their products, while others will offer it as an add-on to their existing products, according to Kobielus. “Some older systems will have to be replaced, or you’ll have to license separate additional software and integrate it with your CRM to make this work.”
It’s still in its early stages as CRM vendors look to find new ways of mashing all these different tools together, he says. There is still work to be done to find the best mixes of tools and data. “The black art in all of this is determining how a human being is going to respond in predictive circumstances when they are presented with an offer from a company.”