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Monetizing Big Data with Hadoop By @MapR | @BigDataExpo [#BigData]

Learn how Big Data and Hadoop can help you more effectively target your audience

The Telecom Marketing Journey: Monetizing Big Data with Hadoop

Forget the funnel. Your customers no longer adhere to that nice, neat linear purchase model.

Stop looking at the calendar. They don't need yet another holiday offer, event-themed promotion, or long weekend sale.

Don't plan on following them around like a heartbroken teenage sweetheart either. Many of your customers (current and potential) will send your emails straight to spam, unsubscribe from newsletters, block ads and refuse to share their locations with you. (Well, they might share some data, but only if you promise a big discount in return.)

So what's a marketer to do?

Cheer up! Communications Service Providers have the most important tool necessary to communicate effectively with customers: Big Data.

McKinsey's DataMatics 2013 survey found that companies that extensively use customer analytics are more than twice as likely to produce above-average profits as those that don't. Their customers are much more likely to be loyal, and they also are far more likely to successfully acquire new customers than their competitors who aren't putting Big Data to work.

So let's get started.

Connect with your customers
If you only reach out to your customers during the traditional sales events - Super Bowl, Black Friday, Cyber Monday, Labor Day - you're competing with everyone else's obligatory event-driven marketing. Instead, look to your data to discover daily opportunities to engage with customers and offer them something of real value. Engagement doesn't require you to be clever or cute or amusing. Sure, customers may share a funny commercial with their friends, but they'll actually act on an offer that arrives at the right time, in the right way.

Big Data can predict when customers want something from you, and it can be used to fuel data-driven applications that respond quickly and correctly to customer needs - be it relevant content, a pointer to a product or an offer to help. You're doing it right when the entire interaction feels seamless and natural. You're doing it wrong when the customer instantly clicks to close the message box or email.

You also want to avoid coming across as spooky or snoopy. If your attempts to engage make customers wonder whether you're spying on them, or collecting far too much information without their permission, you'll lose them in a flash.

Journeys, not funnels
Marketers are moving away from the sales funnel concept and replacing it with the idea of "journeys." Rather than herding customers through an ever-narrowing range of options, as per the funnel concept, a journey follows customers across potential sales channels. You can (and should) be there when the customer begins to research a product or service, downloads information, browses forums, takes a look at the product in a store or downloads an app, and asks for input on social media.

But being there doesn't mean following a customer across websites with display ads. Instead, think of the process as a series of interactions between your company and the consumer that provides you with an opportunity to learn. A recent study by McKinsey indicates that companies who use intelligence gained from journeys achieve a 15-20% reduction in cost to serve, a 10-20% boost in cross-selling, and a drop of 10-25 points in churn.

When working with the journey model, resist the urge to analyze every bit of data available. Focus on critical touch points - the moments when customers are engaged or enraged. Cross-selling a service to a well-served customer, resolving an issue, simplifying a process, and rewarding loyalty are good places to start.

CSPs already have all the data they need to begin the journeying process. To put that data to work you'll likely need to find a way to bring the data silos together, identify the unique touch points that drive your customers, and plotting out the potential journeys that your customers will take. Your emphasis here should be on making predictions, rather than figuring out what happened historically. Think predictive, not reporting.

Big Data and Hadoop
To extract predictive insights from data, you need people with analytical skills and solutions that enable those people to work with all types of data in flexible ways.

Big Data also needs to be front and center in the marketing process, not a process used primarily to understand how you're doing or how you did. Recent analysis by Gartner indicates that by 2020, Big Data will be part of the baseline of enterprise software. Gartner's analysis also indicated that organizations are replacing their early implementations of big data solutions, as first generation tools are simply not able to manage the massive amounts of data smart enterprises collect now.

Apache Hadoop is a framework that was engineered specifically to handle Big Data generated by the most successful Internet companies. Hadoop enables enterprises to augment traditional data warehouses with newer types of data and richer analytics. Enterprise distribution of Hadoop adds essential functions such as security, improved search and efficient disaster recovery as well as performance enhancements.

Enterprise-ready Hadoop brings additional benefits to the marketing department. Hadoop makes it easy to build new data-driven applications that free up resources from existing systems. Data can be cost-effectively captured and stored from every touch point in an organization, from structured, unstructured and semi-structured sources, and analyzed holistically enabling marketers to gain deep insights across the entire customer journey. Data analysis can be as granular as needed to reach customers in the most effective ways possible.

Make your customers happy
We're nearing a balance point where conversations between brands and customers are actually becoming a reality. For a long time, brands talked "at" customers. Then brands focused almost exclusively on listening. Now we're finally ready to have a true conversation, and marketing needs to think carefully about what to say and when to say it.

In marketing's quest to reach out consistently (and constantly) to their customers, it's easy to forget that relentless attempts to engage can become profound annoyances. Use Big Data's power wisely. Connect intelligently, not intrusively. Modern marketing should be driven by a need to produce a mutual exchange of value.

If you're interested in learning more about Hadoop, sign-up for free on-demand Hadoop training from MapR.

More Stories By Sameer Nori

Sameer Nori is currently the Sr. Product Marketing Manager at MapR Technologies. He has 10+ years of experience in the technology industry in marketing, sales and consulting. He has an executive MBA from the Fuqua School of Business, Duke University. His domain of expertise is in business intelligence and analytics.

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