Allowing Marketing to Achieve More with AI
Coredata AI is the world’s leading AI and BI platform used by the top marketing and advertising firms as well as marketing teams in a wide variety of industries use it to better understand their consumers and drive campaigns that are more efficient and effective.
How Coredata AI Helps the Marketing Industry?
Better Customer Profiling
Coredata AI provides a real-time, unified picture of all your customer data by connecting to any and all of your data sources (transactional, interactional, external, structured, or unstructured) from a single platform. Many of our clients that comprise small data teams and non-technical business users use Coredata AI for advanced customer segmentation to determine user behaviors, especially with regards to content and devices on which consumers use the product.
Introduce Automation
The true difficulty lies in creating a recommendation engine that not only functions without any errors but also provides tangible benefits to the company. Since a recommendation engine that isn’t in production is useless, Coredata AI helps customers create their own personalized recommendation engines from scratch. Because of the platform’s thorough implementation and model tracking tools, recommendation algorithms can be relied on to keep providing value over time.
User Actions & Desire Outcomes
In the past, marketing identification was performed manually using inefficient heuristic models. Coredata AI’s machine learning-driven marketing attribution models assist in bringing marketing teams into the modern AI era. Our multiple clients, based on a digital train and coach technology platform, increased their marketing acquisition dashboard creation efficiency by a factor of three by using Coredata AI.
Accurate Forecasting
Even though most companies have some customer retention measures in place already, you can’t avoid customer turnover entirely. Create algorithms that can spot at-risk users with an accuracy of 80% or higher using Coredata AI. The tool can be used to create boost models, which can then be used to make accurate forecasts about which consumers should receive, which marketing materials and how they will respond to them
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