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Aktana Launches Suggestion Engine Designed For Sales People In The Field

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Aktana has launched its suggestion engine designed for sales people in the field

Aktana’s technology provides data insights into sales activity that learns from interactions with a decision-based engine on the frontend and a backend that uses machine learning to determine better go-to market strategies. In all, it is meant as a virtual assistant for sales reps.

The service has multiple uses, such as giving guidance about what customers to call in a geographic region; categories to pursue; and which customers with whom to engage that competitors may not be reaching.

Aktana is designed to augment CRM systems that use suggestions to outperform competitors. Co-Founder Jack O’Holleran said CRM systems do a great job of capturing account information that reps need. Aktana is trying to live in that ecosystem.

Aktana started off as a project for NASA to optimize scarce resources, such as wind tunnels and computer resources, said O’Holleran. The company changed direction when they realized there was a better application in a top-line-driven area. In late 2011, the company raised $5 million in venture capital funding from Starfish Ventures.

Aktana competes most closely with Lattice Engines and has some overlap with a company like InsideSales.com. But more important is how Aktana is representative of a new wave of data analytics companies that in some respects can’t be classified according to any particular category.

Data and its uses are adding a new dimension to the way we think about how our physical world interacts with the digital one. Data is the bridge that ushers in new ways to think about our resources. It’s now less about an app being always on and more so about latency. It’s less about physical servers than virtual ones. Aktana also fits in this digital plane, using data in a manner that forces companies to think more dynamically about the way they conduct sales. The data is not static anymore. It’s fluid and is creating new dynamics as the interactions are analyzed and presented in the context of a sales call.