Big Data jumps to the cloud
Big Data-as-a-Service offers quick, inexpensive, targeted analytics
Kevin Walker's sales team was buried under information. Internal records, news reports, third-party data sources.
Take a simple question like “Which customer should I call first?” The sales team might want to reach out to a customer who has just hired a hundred new employees, or the one whose equipment is ready to be replaced – but that requires going through all those information sources and then prioritizing.
The information is coming in fast, at high volumes, in a variety of formats. It's too much for human beings to handle – it's a job for Big Data analytics.
(Ubuntu 13 challenges Windows 8)
Walker could have opted for an in-house analytics solution. He's the director of global vertical marketing at Dell, and the company has plenty of computing resources at hand.
But instead he decided to get his Big Data analytics from SaaS vendor Lattice Engines. Going with the cloud, he says, allowed him to get up and running faster and cheaper. The entire setup process took just two weeks, he says. In addition, he says, Lattice Engines specializes in just this one area.
“The fact that you're doing something within a vendor's core competency is going to have a better outcome,” he says. “It allows us to scale globally, as well, and aggregate data from other cloud-based services.”
Today, sales people can prioritize their work based on how likely it is that a customer is ready to make a purchase. The system can even make suggestions about what, specifically, the customer may be looking for. Or what a customer might need and not even know.
[ALSO: 7 steps to Big Data success]
“Maybe other customers like them have purchased a certain security tool,” Walker says. “The customer might not even know that they have that security weakness.”
And the analytics began paying off quickly. According to Walker, for every dollar he spent on the tool and associated expenses, he's gotten $30 back. “I expect to see even better returns when I roll out globally,” he adds.
These kinds of results are making a lot of companies look at Big Data analytics. Cloud-based Big Data services can work well for small companies and startups that don't have the budgets for building their own systems, says Joe Pignatello, senior manager of business information management at CapGemini. But they also be a good fit for larger companies, especially those who need to move quickly to take advantage of business opportunities.
There are some downsides, however. As with any cloud service, companies have to do their due diligence for security and compliance. In addition, they have to be careful not to end up with a collection of Big Data silos from different vendors that don't play well together.
A thousand point solutions of light
Most large enterprise vendors have general-purpose Big Data analytics, but specialized vendors are springing up with focused solutions that address just one part of the Big Data puzzle.
They tend to tackle the lowest-hanging Big Data fruit, are fast and inexpensive to deploy, and have easy-to-use dashboards or fit themselves easily into existing corporate workflows.
Take MaintenanceNet, a cloud-based analytics vendor that serves a very specific audience – technology companies that want to get more revenue out of their maintenance and support plan sales. Comstor, a networking equipment distributor, saw a 30% gain in its overall service business last year from higher renewal rates and overall growth as a result of its use of MaintenanceNet's analytics platform.
“Until the metrics and data can be accessible, a lot of your intuition and assumptions prove to be inaccurate,” says Chris Fender, Comstor's director of service sales. What made the cloud-based service particularly attractive for Comstor was the ability to expand the tool to the hundreds of resellers who are its partners.
“If we needed to deploy technology, hardware or software, to the partners' premises, it would be very costly and challenging to manage from an IT perspective,” Fender says. “It's a type of application that is really only feasible in a cloud-based environment.”
One fast-growing segment is that of website analytics. Google Analytics provides a set of traffic data points for free, but it won't tell you, say, how old visitors' kids are. That's one of the answers that analytics vendor Sailthru provided to Totsy, an online retailer specializing in sales to women with young children.
“Sailthru's Big Data approach meant that we could use her browsing behavior to infer what ages she tended to shop for and in what categories,” says Totsy CEO Lisa Kennedy. “We've seen this provide meaningful lift in both click-through and conversion while being operationally simple to execute.”
Deployment is easy because all customers have to do is add a little snippet of code to their websites.
Another easy-to-deploy tool is marketing analysis from Santa Monica, Calif.-based Convertro. It takes a few minutes to install the code. The company doesn't just look at website behavior, but also pulls in information from media companies and other channels to find out how effective a particular advertisement or marketing channel actually was.
Online men's clothing retailer Indochino used Convertro to figure out when a mobile visitor was the same person who had earlier come in via a browser on a personal computer.
“The big piece is being able to associate that individual as one individual,” says Antonio Guzman, the company's manager of digital marketing. “We're also interested in understanding which channels really drive influence and purchase behaviors or other behaviors we're interested in.”
In the past, performance reporting would be based on the first click on an ad, he says. Now, Indochino can look at a transaction and see all the touch-points that led up to the customer making the final purchase decision.
“The big question is which marketing channels are contributing how much to revenues,” says Tom Cole, CEO of Beau-coup, an online party retailer that is also a Convertro customer.
“We are now able to very precisely allocate our marketing budget because we now have a very good view of what each channel is contributing,” he says. Cole says the increase in marketing ROI has been “significant” as a result, but declined to provide specific numbers.
Big Data-as-a-Service offers quick, inexpensive, targeted analytics
Kevin Walker's sales team was buried under information. Internal records, news reports, third-party data sources.
Take a simple question like “Which customer should I call first?” The sales team might want to reach out to a customer who has just hired a hundred new employees, or the one whose equipment is ready to be replaced – but that requires going through all those information sources and then prioritizing.
The information is coming in fast, at high volumes, in a variety of formats. It's too much for human beings to handle – it's a job for Big Data analytics.
(Ubuntu 13 challenges Windows 8)
Walker could have opted for an in-house analytics solution. He's the director of global vertical marketing at Dell, and the company has plenty of computing resources at hand.
But instead he decided to get his Big Data analytics from SaaS vendor Lattice Engines. Going with the cloud, he says, allowed him to get up and running faster and cheaper. The entire setup process took just two weeks, he says. In addition, he says, Lattice Engines specializes in just this one area.
“The fact that you're doing something within a vendor's core competency is going to have a better outcome,” he says. “It allows us to scale globally, as well, and aggregate data from other cloud-based services.”
Today, sales people can prioritize their work based on how likely it is that a customer is ready to make a purchase. The system can even make suggestions about what, specifically, the customer may be looking for. Or what a customer might need and not even know.
[ALSO: 7 steps to Big Data success]
“Maybe other customers like them have purchased a certain security tool,” Walker says. “The customer might not even know that they have that security weakness.”
And the analytics began paying off quickly. According to Walker, for every dollar he spent on the tool and associated expenses, he's gotten $30 back. “I expect to see even better returns when I roll out globally,” he adds.
These kinds of results are making a lot of companies look at Big Data analytics. Cloud-based Big Data services can work well for small companies and startups that don't have the budgets for building their own systems, says Joe Pignatello, senior manager of business information management at CapGemini. But they also be a good fit for larger companies, especially those who need to move quickly to take advantage of business opportunities.
There are some downsides, however. As with any cloud service, companies have to do their due diligence for security and compliance. In addition, they have to be careful not to end up with a collection of Big Data silos from different vendors that don't play well together.
A thousand point solutions of light
Most large enterprise vendors have general-purpose Big Data analytics, but specialized vendors are springing up with focused solutions that address just one part of the Big Data puzzle.
They tend to tackle the lowest-hanging Big Data fruit, are fast and inexpensive to deploy, and have easy-to-use dashboards or fit themselves easily into existing corporate workflows.
Take MaintenanceNet, a cloud-based analytics vendor that serves a very specific audience – technology companies that want to get more revenue out of their maintenance and support plan sales. Comstor, a networking equipment distributor, saw a 30% gain in its overall service business last year from higher renewal rates and overall growth as a result of its use of MaintenanceNet's analytics platform.
“Until the metrics and data can be accessible, a lot of your intuition and assumptions prove to be inaccurate,” says Chris Fender, Comstor's director of service sales. What made the cloud-based service particularly attractive for Comstor was the ability to expand the tool to the hundreds of resellers who are its partners.
“If we needed to deploy technology, hardware or software, to the partners' premises, it would be very costly and challenging to manage from an IT perspective,” Fender says. “It's a type of application that is really only feasible in a cloud-based environment.”
One fast-growing segment is that of website analytics. Google Analytics provides a set of traffic data points for free, but it won't tell you, say, how old visitors' kids are. That's one of the answers that analytics vendor Sailthru provided to Totsy, an online retailer specializing in sales to women with young children.
“Sailthru's Big Data approach meant that we could use her browsing behavior to infer what ages she tended to shop for and in what categories,” says Totsy CEO Lisa Kennedy. “We've seen this provide meaningful lift in both click-through and conversion while being operationally simple to execute.”
Deployment is easy because all customers have to do is add a little snippet of code to their websites.
Another easy-to-deploy tool is marketing analysis from Santa Monica, Calif.-based Convertro. It takes a few minutes to install the code. The company doesn't just look at website behavior, but also pulls in information from media companies and other channels to find out how effective a particular advertisement or marketing channel actually was.
Online men's clothing retailer Indochino used Convertro to figure out when a mobile visitor was the same person who had earlier come in via a browser on a personal computer.
“The big piece is being able to associate that individual as one individual,” says Antonio Guzman, the company's manager of digital marketing. “We're also interested in understanding which channels really drive influence and purchase behaviors or other behaviors we're interested in.”
In the past, performance reporting would be based on the first click on an ad, he says. Now, Indochino can look at a transaction and see all the touch-points that led up to the customer making the final purchase decision.
“The big question is which marketing channels are contributing how much to revenues,” says Tom Cole, CEO of Beau-coup, an online party retailer that is also a Convertro customer.
“We are now able to very precisely allocate our marketing budget because we now have a very good view of what each channel is contributing,” he says. Cole says the increase in marketing ROI has been “significant” as a result, but declined to provide specific numbers.
