Friday May 31, 2013

Improving Customer Experience for Segment of One Using Big Data

By Irem Radzik, Senior Principal Product Marketing Director -- Fusion Middleware

Customer experience has been one of the top focus areas for CIOs in the recent years. A key requirement for improving customer experience is understanding the customer: their past and current interactions with the company, their preferences, demographic information etc. This capability helps the organization tailor their service or products for different customer segments to maximize their satisfaction. This is not a new concept. However, there have been two parallel changes in how we approach and execute on this strategy.

First one is the big data phenomenon that brought the ability to obtain a much deeper understanding of customers, especially bringing in social data. As this Forbes article "Six Tips for Turning Big Data into Great Customer Experiences" mentions big data especially has transformed online marketing. With the volume and different types of data we have now available companies can run more sophisticated analysis, in a more granular way. This leads to the second change: the size of customer segments. It is shrinking down to one, where each individual customer is offered a personalized experience based on their individual needs and preferences. This notion brings more relevance into the day-to-day interactions with customers, and basically takes customers satisfaction and loyalty to a new level that was not possible before.

One of the key technology requirements to improve customer experience at such a granular level is to obtaining a complete and up-to-date view of the customer. And that requires integrating data across disparate systems and in a timely manner. Data integration solution should move and transform large data volumes stored in heterogeneous systems in geographically dispersed locations. Moving data with very low latency to the customer data repository or a data warehouse, enables companies to have a relevant and actionable insight for each customer. Instead of relying on yesterday's data, which may not be pertinent anymore, the solution should analyze latest information and turn them into a deeper understanding of that customer. With that knowledge the company can formulate real opportunities to drive higher customer satisfaction.

Real-time data integration is key enabling technology for real-time analytics. Oracle GoldenGate's real-time data integration technology has been used by many leading organizations to get the most out of their big data and build a closer relationship with customers.  One good example in the telecommunications industry is MegaFon. MegaFon is Russia's top provider of mobile internet solutions. The company deployed Oracle GoldenGate 11g to capture billions of monthly transactions from eight regional billing systems. The data was integrated and centralized onto Oracle Database 11g and distributed to business-critical subsystems. The unified and up-to-date view into customers enabled more sophisticated analysis of mobile usage information and facilitated more targeted customer marketing. As a result of  the company increased revenue generated from the current customer base. Many other telecommunications industry leaders, including DIRECTV, BT, TataSky, SK Telecom, Ufone, have improved customer experience by leveraging real-time data integration.

Telecommunications is not the only industry where single view of the customer drives more personalized interaction with customers. Woori Bank  implemented Oracle Exadata and Oracle GoldenGate.  In the past, it had been difficult for them to revise and incorporate changes to marketing campaigns in real time because they were working with the previous day’s data. Now, users can immediately access and analyze transactions for specific trends in the data mart access layer and adjust campaigns and strategies accordingly. Woori Bank can also send tailored offers to customers.

This is just one example of how real-time data integration can transform business operations and the way a company interacts with its customers. I would like to invite you to learn more about data integration facilitating improved customer experience by  reviewing our free resources here and following us on Facebook, Twitter, YouTube, and Linkedin.

Image courtesy of jscreationzs at FreeDigitalPhotos.net

Wednesday Apr 17, 2013

The Value of Enterprise Specific “Social Data” - Social Data within Social Customer Relationship Management (Social CRM)

This is the first in a series of guest posts from Don Springer, VP Product Development for Oracle Social and Pat Ma, Principal Product Marketing Director for CX and CRM on the value of leveraging social data across your enterprise.

Lately, we have been meeting with marketing, sales, services and IT executives at very large Financial Services, Consumer Products, Retail and Technology companies. They have all made significant progress in deploying social customer relationship management (Social CRM) capabilities, but are looking for more automated and powerful ways to socially enable their external customer facing functions. In essence, they want to do more with their Social Data. With enterprise data growth expected to continue at 40% through 2020, driven by consumer generated content, getting value from this data is becoming increasingly and strategically important.

In this post, we’ll cover the basics of first implementing a Social CRM approach, and the value your enterprise specific social data. In a future blog post, we will cover more advanced “next” steps in how to leverage social data within your enterprise’s Big Data Analytics, Business Intelligence and Customer Experience Management deployed applications and systems.

Below is a diagram that highlights a general process for leveraging Social Data as part of an overall Social CRM approach. Think of this as a process that tracks your social efforts across your customers’ life-cycles, starting with listening and point-to-point engagement to more broadcast communications efforts in a repeatable and flexible fashion.

Social CRM Process

chart

1. Listen.  The enterprise wants to listen to what people (customers, prospects, and influencers) are saying about their brand on social media channels.

  • Your customers are talking about your brand on social media channels. They are posting, tweeting, commenting, sharing, complaining and liking your brand.
  • Through Social Listening, the enterprise should figure out what their constituents are saying en mass, analyze sentiment, hear what they like and don’t like about your product, and know if they intend to purchase your product or not.
  • Your social listening approach needs to be accurate and filter out the irrelevant “noise”, to get to pure customer signal for analytics and engagement.

2. Engagement (1-on-1) The enterprise wants to engage with relevant social signals to interact with their customers, and determine how those 1-on-1 engagements perform. 

  • This can be done by asking your customers various questions, responding to their posts and comments, and creating engagement applications like contests and polls. 
  • Your social engagement should be used to listen and respond to social posts. Social posts should be automatically categorized by your Listen engine and flow from multiple social networks into one “inbox” designed to make managing your community easy and efficient, within your appropriate business function (sales, marketing and support).

3. Content and Apps (within your Enterprise’s Social Assets) The enterprise should leverage the lessons learned from your 1:1 engagements to scale what works within relevant content and apps you create, whether it’s user-generated contests, polls, videos, or other interactive content.

4. Publish (message through your social channels’ communities) The enterprise should continue to build on its learning on all your interactions with your fans and followers to publish and amplify relevant content to multiple social media channels.

  • Create great looking landing pages and publish to multiple social networks or embed on any website. 
  • This should be done specifically within your various channels focused on marketing, sales, service, and commerce.

5. Managed Workflows The enterprise should develop and deploy specific workflows so your assigned business functions (Sales, Marketing, Service and Commerce) are communicating the right message to the right customer at the right place and the right time.  

  • Social media teams are growing and becoming more global. Why take the risk of someone in your organization publishing off-brand information?
  • By using your listening engine to auto-tag customer signals, managed by function appropriate workflows, you can better control your points of communication (1:1, through content, apps and publishing) to improve ROI.

6. Analytics. The enterprise should create a culture that always analyzes your results and metrics to quickly capture lessons learned to establish a continuous improvement process.

  • This will enable you to show ROI on all your social media investments, pre, during & post-campaign across your owned & earned media to improve social performance.
  • This helps you optimize your efforts over time to get more lift and value from your resource and communications spend.

Makes Sense?

Once your enterprise has this Social CRM approach in place and functioning, you can take the broader “next” step to amplify your social value through integration into your other core applications, which we’ll cover in a future post.

To whet your appetite, you can socially enable your enterprise by creating a 360o view of your enterprise customers (both content and profile) to support:

  • Business analytics across all forms of structured (customer transactional and behavioral data), semi-structured (enterprise text sources that capture your internal customer conversations via chat, email, call center, etc.), and Social CRM unstructured data for:
  • Big Data insight discovery – finding insights you did not know existed
  • Business Intelligence - developing dynamic, real-time dashboards, reports and alerts for rapid decision-making.
  • Customer Experience Management applications already deployed and in use by your enterprise’s Customer Service, Sales and Service/Support functions for near real-time action (customer experience management).

Thursday May 31, 2012

“Big Data” Is A Small Concept Unless You Can Apply It To The Customer Experience

There’s been a lot of recent talk in the industry about “big data”.  Much can be said about the importance of big data and the results from it, but you need to always consider the customer experience when analyzing and applying customer data.

Personalization and merchandising drive the user experience.  Big data should enable you to gain valuable insight into each of your customers and apply that insight at the moment they are on your Web site, talking to one of your call center agents, or any other touchpoint.  While past customer experience is important, you need to combine that with what your customer is doing on your Web site now as well what they are doing and saying on social networking sites.  It’s key to have a 360 degree view of your customer across all of your touchpoints in order to provide that relevant and consistent experience that they come to expect when interacting with your brand.

Big data can enable you to effectively market, merchandize, and recommend the right products to the right customers and the right time.  By taking customer data and applying it to product recommendations, you have an opportunity to gain a greater share of wallet through the cross-selling and up-selling of additional products and services.  You can also build sustaining loyalty programs to continue to engage with your customers throughout their long-term relationship with your brand.

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