Toovio: Smart Mobile Marketing leveraging Big Data

Josh Smith, Founder & CEO
In the recent past, Big Data has emerged in the earnest. As the use of data is increasing by the day, being able to store, analyze, and visualize amorphous data in real-time is turning out to be a tedious process. Organizations demand an enhanced solution that can continuously cultivate the actionable set of data from unstructured and transactional Big Data. “Not only cultivating but companies also request a solution that validates the speed at which the data is retrieved,” adds Josh Smith, Founder, and CEO of Toovio.

Located in Minneapolis, MN, Toovio, a SaaS-based marketing solution provider, offers Big Data solutions to help businesses make smart decisions and adapt to current market requirements in the Big Data space. Combining Big Data with machine predictive modeling and decision management, the company’s Toovio platform, a real-time mobile messaging optimization technology, increases the engagement, response and revenue for the marketers. The Toovio platform offers digital mobile subscriber events such as “open app”, “check balance” and “recharge account” to the customers. The essential mobile offers for the consumers are chosen on the merits of predictive outcomes associated with the data characteristics present in a real-time moment. Toovio’s Adaptive Predictive Engine chooses the required events addressed through the Adaptive Predictive Models in the platform. If there are 100 events in the Toovio system then there are equal Adaptive Predictive Models representing one for each event. “From our standpoint, the eminence of predictive algorithms is widely accessible in the platform by means of open source university libraries,” explains Smith. Data is retrieved like ‘needles in the haystack’ through the Adaptive Subscriber Profile and fed into the required algorithms in the model.

Although Toovio uses several algorithms behind the process, the system shows the end-user a decision tree algorithm for each predictive model. Machine segmentation—a byproduct of Adaptive Predictive Models—will show the marketer a unique “segment” of the customers’ most interested and disinterested offer.
For instance, Tigo Paraguay, a telecommunication client, approached Toovio to improve their existing messaging ability by responding instantly to customer event data offers with promotional and engagement mobile messages ‘in the moment’. “The client requested a software platform that could provide real-time testing and learning capabilities as well as machine learning and data mining automation to iteratively find the most predictive data by offer,” explains Smith. Tigo implemented Toovio’s adaptive predictive engine, which enhanced their existing ability and allowed for rapid testing and learning for human driven segmentation. The platform offered targeting as well as continual and iterative predictive modeling through mobile offers. And the Toovio platform was integrated with the billing engine so that the end-users can purchase and start using the product. “Through the Toovio system, the customer benefited speed to market, competitive agility, increased response rates, customer tenure, and average revenue per unit (ARPU) and optimization of profit and revenue,” says Smith
Being a bow hunter, Smith pursues the strategy ‘aim small miss small’. Likewise, “contextual data is our ‘small target’ and we don’t want to miss by much. If we know the data that is most predictive and most discriminate then we ‘aim’ our marketing efforts and strategies at those data elements,” describes Smith.

Our platform is a combination of Big Data, Machine Predictive Modeling and Real- Time decision management

Moving forward, Toovio plans to expand its marketing ability to apply in other sectors. “By the end of this year, Toovio will be partnering with the existing mobile messaging providers to offer solutions for various other industries,” concludes Smith.


Minneapolis, MA

Josh Smith, Founder & CEO

Offers Big Data solutions to help businesses make smart decisions and adapt to current market requirements in the Big Data space