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Acer America
Acer America Corp. is a computer manufacturer of business and consumer PCs, notebooks, ultrabooks, projectors, servers, and storage products.


333 West San Carlos Street
San Jose, California 95110
United States


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November 18, 2015 |

New SaaSMAX Service Offering Automates Partner Research

Partner Optimizer, for vendors with large partner channels, scans partner websites for information about product offerings, certification, partnerships, and more, and puts it in a file vendors can upload to their CRM systems.

SaaSMAX Corp. has good news for channel pros tired of providing profile data about themselves to multiple vendors via multiple tools. They may not have to much longer if things work out the way the San Diego-based company hopes.

That’s thanks to a new service called Partner Optimizer that SaaSMAX, whose main product offering is a SaaS solution marketplace, quietly introduced recently. Aimed at IT vendors with large partner channels, the service draws on proprietary Web crawling technology and the analytical horsepower of IBM’s Watson Analytics solution to scan partner websites for relevant information about product offerings, certifications, partnerships, vertical expertise, and more. It then drops everything it finds into a file that vendors can upload into their CRM system.

In development since January, Partner Optimizer is based on technology SaaSMAX initially created for its own use. Matchmaking cloud vendors with partners is the company’s stock in trade, and the more it knows about resellers the better job it can do. Few channel pros have the time or patience to provide that information themselves, however, so SaaSMAX created a way to collect it without their assistance. Pleased by the results, they’re now offering the service to other vendors with similar needs and challenges.

“What we realized was that this was now a solution that has value that extends way beyond the SaaSMAX community,” says company CEO Dina Moskowitz.

Indeed, SaaSMAX is far from the only vendor that has trouble motivating partners to keep their profile data current. “One of the biggest pains that channel chiefs complain about is their partners don’t ever update anything,” Moskowitz says, adding that partners often leave out salient details about their competencies and specialties as well. Paying people to gather that information is costly, though, and can take months.

“By the time you get done pulling that data together it might be obsolete,” Moskowitz observes.

Partner Optimizer automates the data collection process and gives channel managers a more complete understanding of their partners, typically within four to eight weeks. “You’re getting a holistic view that before this you never really had the time or inclination to be able to pull together,” she says.

Vendors can then use that data to target their channel recruitment and engagement efforts more precisely. Rather than promote an archiving sales campaign for financial services firms to all of their partners, for example, they can focus on resellers with experience selling that specific solution category to banks and insurance companies. Partner Optimizer’s “Recommender Engine” helps users identify appropriate partners and rank them by key characteristics.

SaaSMAX piloted Partner Optimizer with several vendors before making it broadly available, and while Moskowitz won’t name them at least a few have “hundreds of thousands” of partners. Generally speaking, she continues, firms with 10,000 or more VARs are likeliest to find the service cost-effective. Though more affordable than collecting data manually, Partner Optimizer is “not inexpensive,” Moskowitz says.

Partner Optimizer client engagements are presently customized, one-off projects requiring direct consulting and support from SaaSMAX, but the company ultimately aspires to offer an online self-serve version of the service with subscription-based pricing. For now, Moskowitz believes SaaSMAX has the market for this type of offering pretty much to itself.

“We haven’t seen anything that’s providing this kind of data in an efficient, automated way,” she says.

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