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  • Customer analytics techniques boost sales and service strategies

    While the technology of customer data mining continuously improves, organizations still need the human factor of customizing system outputs to drive business goals. Continue Reading

  • How customer service analytics enhances the customer experience

    Customer service is arguably as important as sales in the enterprise when it comes to maintaining and expanding the business; here's how analytics can help. Continue Reading

  • Peer into the future with predictive analytics software

    Predictive analytics is an old concept finding new life with software that can gather information on customers, predict interests and actions and support better business decisions. Despite established uses for the concept itself, companies using predictive analytics software face numerous challenges.

    Most data analysis can't yet be automated, for example. And while social media is in the future for predictive analytics software, incorporating it is an unwieldy process at present. This three-part handbook looks at some of the opportunities and obstacles predictive analytics software faces. The first two articles take an in-depth look on social media listening; the concluding article examines the usefulness of predictive lead scoring. Continue Reading

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  • How supply chain partners can look for success through analytics

    Supply chain partners that look for ways to share data have a far better chance of successfully predicting customer demand and other variables that lead to success. Continue Reading

  • How do IoT analytics enhance customer experience with quality data?

    IoT analytics helps companies create a better customer experience by providing quality data that allows for the reduction of costs and a more efficient work day. Continue Reading

  • Data analytics strategies and tools incite positive customer journeys

    Once upon a time, marketing and sales departments considered customer data analytics capabilities a nice-to-have but not very well understood shiny new toy. That's all changed. Today's highly competitive marketplace demands that successful companies differentiate themselves from the pack in more complicated ways. Data analytics strategies are seen as the lifeblood of effective marketing and sales campaigns designed to not only identify, target and convert prospects into customers, but also ensure brand loyalty with superior service that enhances the customer experience.

    Miner Corp., a loading-dock services company, depends heavily on fulfilling its service-level agreements in a timely manner, yet the company's human-driven process of dispatching field service technicians was in disarray and compromising SLA requirements. By automating the dispatch process with an application that embeds customer service analytics into another application that manages customer data and services issues, Miner was able to shave significant time off each of about 300 daily service requests. "Today, we don't rely on tribal knowledge. It's all systematized," CIO Mirza Chughtai said.

    Also featured in this e-book chapter by Executive Editor Lauren Horwitz is travel website company TripAdvisor, which capitalized on customer data analytics by using several business intelligence tools to gain insight into its users and the pathways they choose while on the site. In the process of improving browsing efficiency and converting more user pathways into sales, TripAdvisor also managed to reduce worker headcount by 70%. "With automated tools, you need fewer people and you make the people you keep more productive," noted Eric York, who handles the company's revenue optimization.

    Yet, there are hurdles along the way to achieving a unified customer experience, especially as companies struggle with integrating incoming data from multiple communication channels. One analyst still sees most companies' attempts as trial-and-error. Find out how the data analytics strategies of Miner and TripAdvisor overcame those obstacles.

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