How loyal are customers? What motivates them? Who is likely to stay and who is likely to leave? By applying sentiment analysis, business users can optimize marketing efforts and cultivate their entire customer base effectively. Building data visualizations through real-time visual data mining helps marketers quickly identify more cross-sell and up-sell opportunities, take action to prevent potential churn, and allocate immediate resources to incoming leads.
Who is most likely to commit fraud and cause losses? What is the most cost-effective marketing? Analyzing Big Data from one or more sources gives business users the chance see the big picture quickly by comparing billions of records in seconds. Incorporating information from social media, survey results, numeric purchasing records, and demographic reports lets businesses truly know their customers and respond to them appropriately by offering the right products and services at the right time.
Where should resources be allocated? What is a particular customer segment likely to do next? How much business can be expected in the future? When customer information is visualized in graphs and charts, analysts can understand customer information immediately, which means they can quickly identify customer needs, adapt product road maps, and formulate business strategies that are based on actual customer knowledge.
What business processes are not working and why? Where can IT be more efficient? Actuate's business analytics software has an intuitive user interface, which makes working with data fast and simple for your entire organization. Every table, chart, diagram, tree, and map that you create is dynamic and recalculates instantaneously as you drag and drop in new data segments to be analyzed. Actuate helps make information discovery more transparent and useful, allowing virtually anyone in your organization to engage in Big Data analytics without IT dependence.
The U.S. Library of Congress archives every tweet for historical purposes. That’s some serious Big Data!
58 million = the estimated average number of Twitter tweets per day.
5 = the number of days it takes for 1 billion tweets to be tweeted.
By the time you finish reading this sentence, over 9,100 tweets will have already been tweeted.
Even users without a statistical background can proficiently:
Gain valuable customer insights through:
User-friendly interface increases the efficiency of the data life cycle:
Minimize risk with maximum security:
With a FREE trial of BIRT Analytics, discover the advantages of fast visual data mining and predictive analytics. Finally, eliminate the need for IT assistance and data scientists. Start your own 30-day FREE trial now!