July 5, 2022

Voyantis’ predictive growth OS raises $19M to help online businesses achieve profitability

NY Tech featured our launch on their website! Find out what our founders, investors, and customers have to say about our predictive growth operating system, which empowers online businesses to achieve sustainable LTV-based growth–while overcoming privacy challenges and ever-growing costs of acquisition

June 23, 2022

Growth at all costs? Not anymore!

This post by our CEO, Ido Wiesenberg, goes over how from changing consumer behaviors and expectations to restrictions and limitations from ad networks and operating systems—we have seen that growth at any cost is neither efficient nor scalable for brands. This is why ROI and profitability should be considered a primary metric for all brands.

March 10, 2022

Using Data To Scale Marketing

This post explores how there are plenty of marketing decisions, as well as general business decisions, that can be made through data analysis. After all, the greatest of marketing teams cannot perform miracles based on intuition alone, but they can get much closer when they leverage their data appropriately!

January 2, 2022

Why Growth Strategy for Your Brand Needs to Revolve Around High-Value User Acquisition

This post discusses how changes between ad networks and operating systems led to lower ROAS, and decreases in scalability. What growth teams need these days is a future-proofed solution to all these challenges.

March 3, 2022

How to use predictive user acquisition for long-term success

This post by Voyantis’ CEO covers how marketers can use predictive UA to clear some of the hurdles that are leaving them working in the dark. These hurdles include scalability/profitability concerns, and plenty of other restrictions and limitations. Changing times may have led to complications in UA. But technology exists to guide growth teams towards profitability.

December 17, 2021

Reasons Behind The Drop In Scalability For Brands And How To Navigate This New Normal

This post covers how leaders need to redefine the way data is used in their organization. This can be done by building stronger data structures and using probabilistic and predictive data models to cover the blanks being created by the limitations, restrictions and other obstacles being thrown their way.