conDati Blog

Forecasting for Better Marketing Outcomes

Always-on Forecasting to Help You Predict Results and Tailor Marketing Strategy

In our recent blog post, "Is Marketing Ready for Artificial Intelligence?", we mentioned going  deeper into today’s applications of data science for marketing. These AI-fueled applications not only give you a competitive advantage, they help you get a head start on your 2020 business goals. Let’s dive into the data science application of forecasting.  

Beyond Big Data: Toward Real Insight

Marketing professionals today are inundated from all sides with hype about the future of big data, AI, and machine learning.

Whether the takeaway is better reporting, concern for job security, or mathemagical seeming insights, everything boils down to big data and the mysterious “black box” of AI and machine learning.

How to Choose the Best Model for Marketing Prediction

First in a series on how and why conDati choses the prediction models we use to improve your marketing performance.

Marketers have had to rely on instinct and experiential knowledge alone to produce winning, hopefully profitable campaigns. In addition, months would go by without any solid information and when they did get numbers, accuracy was always a problem.

Modern marketers will make smarter bets in 2018

Hoping to Leapfrog the  Competition by Connecting Siloed Data and Implementing Machine Learning and Predictive Analytics

The typical large enterprise uses 90 or more marketing and analytics tools, while SMBs and Mid-Market companies employ between 10 and 25 martech tools to manage marketing operations and drive revenue. That’s a lot of systems for any company to manage. The results are dreaded data silos, which at best provide partial insights, and in the worst case overlook critical

Getting to Know Julia [Language] over the Summer

Meet Josh Papermaster, University of Texas, Austin. Josh sat down with us to talk about his experiences interning for conDati. He discusses what he learned and his favorite memories. 

Top 5 “Must-Have” Categories for your MarTech Stack Tool Chest

In 2011, the inaugural MarTech Stack Landscape identified about 150 companies servicing marketers. Even then, one would have expected all those vendors to consolidate as the industry grew and matured. Instead, the martech landscape has fractured into 50 or more categories, populated by more than 5,000 vendors, fully half of which are brand-new venture-backed start-ups. Every marketer now needs to evaluate hundreds of tools, representing every new approach to customer acquisition, to find