Enterprise Data Management
Enterprise data management (EDM) is a set of practices, processes and activities that help companies adopt, manage, and integrate data. Many businesses struggle with enterprise data management, which is why BluEnt’s services focus on data accuracy, security, quality, availability, and management.
But what is enterprise data? It consists of the digital information that flows through your company. This includes both unstructured data (eg., video and image content) and structured data (eg., spreadsheets).
Some forms of data that our enterprise data management will cover include transaction records, customer orders, internal labor stats, network alerts, sales reports, and GPS data.
Big Data Management
BluEnt translates your big data into actionable business information. We observe patterns and understand connections to help you make smarter decisions.
Our big data implementation approach is based on reliable and relevant customer data. We apply analytics and derive insights to understand and predict the behavioral trends of your consumers.
Big data implementation leads to
Improved marketing strategy
Identifiable customer behavior patterns
Identifiable customer needs
Identifiable opportunities
Improved products and services
Faster decision making and execution
Ideas for new products and services
Improved internal processes
Companies that invest in big data management will gain a large advantage over their competitors.
Big Data Analytics and Insights
BluEnt’s big data analytics team gathers insights and decodes big data. Our focus is on helping organizations make profitable, data-driven decisions.
With tools and algorithms, organizations can gather, analyze and transform data into profitable, actionable insights.
Advantages of analytics
Increased revenue
Faster decision-making
Improved marketing strategies and campaigns
Synchronized financial and operational strategy
Optimized internal process
Improved existing products and services
New product and service ideas
Analyzing business data from websites, social networks, business applications or machine logs opens up a world of opportunities. With terabytes or gigabytes of data, BluEnt can deliver what big organizations do with petabytes.
We have the expertise to get rid of the lengthy processes that restrict the entry of smaller enterprises into the world of big data.
Our services include
Sales Analytics
Price optimization
Sales forecasting
Sales force optimization
Inventory management
Promotional codes insight
SKU optimization
Marketing Analytics
Marketing strategy
New product ideas
Product portfolio allocation and optimization
Country and category prioritization
Remarketing strategy
Marketing mix model development
Customer Analytics
Segmentation
Demographics
Acquisition
Loyalty
Retention
Up-selling & cross-selling strategy
Customer buying patterns
Preferences
Spending ability
BluEnt provides our clients with accurate and comprehensive insights. We have a team of data analysts, business analysts and technical specialists who work with your organization and ensure that your critical business decisions are based on the latest, most reliable insights.
Big Data Implementation
We advise clients on how to produce, consume, and govern complex information using the appropriate mix of historical, current and predictive analytics.
We enable our clients to cut through complexities and bring clarity to problem-solving by providing insights that:
Help create new revenue-generating opportunities
Improve operational efficiencies and visibility across the organization
Enable faster problem-solving and decision making
Optimize the return on existing business and IT investments
Predictive Analytics
BluEnt develops reliable predictive models so organizations can better understand their consumers’ future behavior.
Advantages of predictive analytics
Drive Buyer Preferences: Analyze the customer-buying pattern and up-sell/cross-sell related products and services to them.
Demand Forecasting: Analyze the historical sales data and predict demand for a product or service to better manage your supply chain, resources, and inventories.
Improved Pricing Strategy: Analyze the sales data and decide whether to increase or decrease the price for a particular product or service.
Identify Loyal Customers: Analyze historical data to identify loyal customers and develop retention plans for them.
Identify Rewards and Risks: Analyze historical and transactional data of a customer to identify the risk or opportunity associated with that customer.
Forecast Marketing Budget: Analyze the marketing budget of previous years and predict where to spend more to maximize returns on marketing spend.
Better Campaign Management: Analyze the click-through rates of previous campaigns and recommend the best timing for maximum click through.
How it works
Predictive analytics is the process of extracting information from big data and using it to predict future trends and behavior patterns.
It captures relationships between explanatory variables and predicted variables from the past occurrences and exploits them to predict future outcomes. It encompasses a variety of techniques, from statistics and data mining, that process current and historical data.
A well-known application, for example, is credit scoring, which is used in financial services. Scoring models process a customer’s credit history, loan application, customer data, etc., to rank-order individuals by their likelihood of making future credit payments on time.
Want to streamline your processes with data management services? Contact us now!
