On the heels of its announcement of a new $45 million round in funding, Kahuna is planning to do for email marketing what its platform has done for big-data and machine-learning based mobile marketing automation.
This platform expansion brings Kahuna’s capabilities in personalized messaging for mobile to email (and more) with new functionalities leveraging rich context and behavioral data. Kahuna has newly architected its platform to accomplish the following:
Understand each user’s omnichannel behavior with a real-time, person-centric data layer: The platform is able to collect and rationalize data at the individual level for billions of users. The data is constantly refreshed so marketers don’t have to make guesses based on aging personas or segments - they can know the individual behind their many screens. From the mobile app to the in-store POS, Kahuna’s mix of SDKs and APIs can ingest, process, and utilize massive amounts of data from any customer touchpoint to ensure that each message sent - regardless of the delivery channel - is accurately personalized and delivered at the optimal time.
Engage where their users are in a simple, personalized way: The platform provides access to push, in-app, email and Facebook campaigns in the same platform. For each delivery channel, marketers are able to create granularly targeted campaigns directly in the UI or can upload custom segments created in their own backend systems through Kahuna’s new Adaptive campaign functionality. Dynamic attributes such as location or last category viewed, as well as Kahuna’s dynamic deep linking capability, make sending millions of individually personalized messages possible.
Optimize with features that make marketing easier: Kahuna’s machine-learning informed optimization capabilities ensure that each campaign sees the best results and drives revenue through the use of:
- SendOptimally (send time optimization): Uses historical data across all channels to message a user when they’re most likely to engage.
- RevIQ (conversion optimization): Determines the optimal time to follow up with a user after an action has not been completed.
- A to E testing (message copy optimization): Tests up to five copy variants (in addition to a control group). Both conversion and messaging copy optimization will evaluate results in real time and automatically scale up better performing variants and scale down those that are performing worse.
- Campaign analytics (experience optimization): Gives marketers insight into what campaign types and copy are succeeding in producing the desired result versus those that are producing above average opt outs and uninstalls.