Companies that can target specific consumers in real-time based on factors including their current location, past purchasing history, and demographic information with strategic offers planned using pricing revenue optimization gain significant marketplace separation over companies that continue to use conventional retail marketing tactics. Mosaic brings world-class predictive ML analytics and model development capabilities to our clients in the retail sector, enabling them to be more data-driven in all facets of their business for a competitive advantage.
AI and LLMs are not just a technological leap; they’re a strategic imperative. By embracing this evolution, businesses gain a distinct advantage—staying ahead of the competition, enhancing stakeholder experiences, and optimizing both time and costs. In this white paper, we explore our top LLM business applications.
A hospitality technology disruptor was developing a new sensor suite to detect when a guest was smoking inside a property and distinguish it from approved activities such as cooking. They engaged Mosaic to build time series classification models to identify and alert on smoking events from the streaming sensor data.
Mosaic helped a nationwide retailer model the price elasticity of demand across their product catalog, empowering them to optimize prices and maximize SKU revenue.
Given a set of nodes & connections, which can abstract anything from transportation networks, connections between customers, knowledge graphs, or molecular structures to computer data, graph analytics provide a helpful tool to quantify & simplify the many moving parts of dynamic systems.
Summary Our white paper explores the processes and opportunities presented by NLP for social media in extracting valuable data to drive improved operational and strategic decisions for R&D efforts. Natural language processing (NLP) is one of the most promising social media data processing avenues. It is a scientific challenge to Read more
Both descriptive analytics and machine learning models can benefit greatly from using geographic data analysis to solve segmentation use cases.
We sat down with Senior Data Scientist Alex Tennant for his perspective on the opportunities and complexities of NLP and how Mosaic is paving the way for the consistent evolution of this powerful technology.
Mosaic used NLP algorithms to automatically extract various insights about people calling into a customer call center. We created a process to identify at-risk customers that called the previous day based on the transcript of the call.
In our whitepaper, Mosaic explores deep learning , including when to use deep learning over machine learning using practical examples.
Text data presents a tremendous opportunity to benefit all stakeholders of an organization – investors, employees, processes, and the all-important customer – if the organization can find a way to sift through this data in an automated way to extract key information and solve specific challenges. In that case, they could learn about their firm and start optimizing the way they operate.