Gartner’s Magic Quadrant series analyzes technology vendors in specific markets and presents each one’s competitive positioning in a four-quadrant chart.
Optimove experienced a 60% growth in revenue during 2017 and increased its client base by more than 50% to over 300 customer-centric businesses.
“We are excited to be included in Gartner’s Magic Quadrant for Multichannel Marketing Hubs,” said Optimove’s founder and CEO Pini Yakuel. “I’d like to take this opportunity to thank our partners, clients and employees. This is one more acknowledgement that all of our hard work and commitment to excellence and innovation is paying off.”
Optimove’s offering for its Relationship Marketing Hub has grown considerably in 2017, with the new visitor’s lifecycle, that extended the scope of the predictive model and campaign automation capabilities. The visitor lifecycle stage was added to many more Optimove functionalities, including: (1) Self-Optimizing Campaigns – highly-advanced machine learning system that enables marketers to engage their existing customers with the right message at the right time; (2) Time Travel Analytics – a tool that leverage the Markovian philosophy of snapshotting data and providing different database states continuously, and allows marketer to use these customer data snapshots to conduct time-related analysis, such as comparing complex user segments both to themselves and each other, across any time period; and (3) Optibot, the first-ever marketing optimization bot, that bridges the gap between data science and the art of marketing by serving marketers with one-click actionable insights for the continuous optimization of marketing activities.
The company plans to continue disrupting the marketing technology space with its innovative, scientific approach. As part of the company’s product roadmap, Optimove is continuously researching and developing its Master Predictive Customer Modelling algorithms. In Q3, Optimove will be adding narrative elements which will allow marketers to understand their customer data in a more intuitive fashion, by adding “story-telling” capabilities that help explain why and how customers are behaving, and where to focus marketing attention.
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