In Annalect we harnesses the power of AI to enhance value creation, handle large-scale data, and deliver comprehensive business evaluations to our clients. In this article we share our thought and current approach to AI.
Overall, leveraging AI prediction and segmentation algorithms empowers businesses to gain deeper insights into their customers and make data-driven decisions to improve customer retention and drive company growth.
In the pursuit of technological advancements and staying ahead within technological possibilities, Annalect has embraced artificial intelligence (AI) across a range of our solutions. Over the past few years, Annalect has significantly increased its focus on AI technology to elevate the value we offer to clients and in order to effectively manage the ever-growing volume of data.
In 2017 we embarked on a transformative journey to revolutionize the fundamental approach to data handling and methodologies, particularly in solutions like Marketing Mix Modeling (MMM). This marked the initial step on a path that involved leveraging cloud computing and AI initiatives to deepen the company’s solutions and enhance the speed of delivering results, data based consulting, and recommendations.
Today we use AI several use cases:
- Handling huge data volumes and cleaning of data
- To make better prediction
- Generating Analytic marketing performance solutions for customer data analytics
- In our Digital bid modifier algorithms
Deep dive: MMM/Agile MMM
Today, Annalect employs one of the most advanced model setups globally and has gained international recognition for its methodology and outcomes. As one of the pioneers in the field, Annalect launched a fully automated agile MMM setup, which delivers a complete business evaluation to clients on a monthly basis. This setup incorporates API integration for both client and media data, enabling seamless connectivity.
The solution comprises over 60,000 lines of code, allowing Annalect to deploy new releases and adjust the scope of its work across customer projects daily. Inspired by machine learning, our MMM approach aims to measure and understand the interconnections between data. With the constant influx of data and the need for detailed insights, ML has played a revolutionary role in expanding the nuance of Annalect’s MMM solutions. For instance, MMM historically focused on analyzing the impact of larger media channels, but today we can dissect individual media formats and campaigns in isolation.
Deep dive: CRM Insights Platform:
Our platform is built on the latest AI and machine learning algorithms, empowering us to accurately predict customer churn and engagement. By combining historical customer data with real-time behavioral information, our models identify patterns and trends indicative of high-risk churn or engagement within a client’s business.
- AI-driven segmentation based on customer behavior
- Forecasting individual customer engagement or churn
- Build, analyze, and activate custom target groups directly within marketing platforms
- Affinity scores for communication and customer offers
- Track customer engagement over time
AI prediction and segmentation algorithms analyze customer and behavioral data to make predictions about future customer behavior and segment customers based on their characteristics and actions. Supervised machine learning algorithms are trained on labeled datasets, while unsupervised algorithms uncover patterns in the data without the need for labeled information. Once trained, these algorithms can predict future customer behavior, such as the likelihood of churn or purchasing a new product. They can also segment customers into different groups based on their attributes and actions.
As we in Annalect continues to embrace AI, it sets a remarkable example for our aim to continuously seeking to unlock the potential of cutting-edge technology to deliver exceptional value, understand customer behavior, and propel their growth strategies for our clients.
Read more about our AI powered solutions:
Examples of our solutions benefitting from using AI.