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Tapping into Social Media Data Maturing the Customer-Centric Approach to Business Evolution

Originally published 28 December 2011

In the past five years, the evolution of social media and its influence on business has been unprecedented. The bottom line message is: The customer is no longer outside the organization; the customer is now shaping the organization.” If you want to thrive in this economy as a product or service, your approach to evolving the business requires a “customer-centric” approach.

What does customer-centric mean? Providing a superior customer experience across an organization’s product and services, providing the customer with indisputable value and satisfaction is the simplest form of being customer-centric. One can argue that most organizations today adopt this approach, but the reality is there are only a handful who have really embraced the concept and made gains. There are others who have tried and failed, and yet others who probably have a lip-service approach.



Figure 1: Lifecycle Approach to Customer-Centric Evolution

Figure 1 illustrates the lifecycle approach to customer-centric evolution. It shows that following customer acquisition, the biggest hurdle to cross is creating a value quotient with the customer. This is a very crucial step, which in the past was accomplished by multi-channel marketing with mail, catalog and coupons. That strategy was great with a product- or brand- driven customer strategy, but now the equation has shifted customer-driven product and brand creation strategy. This fundamental shift has created the need to treat the customer as a stakeholder in the business. In order to get this approach correct, you have to understand the “new” customer, who is very social media savvy and can be very influential about your products and/or services to a large network or crowd of people.

To understand the social media impact and integration, there are a few terms to learn a few important underlying concepts or surrounding themes:
  • Crowdsourcing: First coined by Jeff Howe in a June 2006 Wired magazine article "The Rise of Crowdsourcing,” crowdsourcing is a concept where people form Internet communities of shared interest. The basics of the concept revolve around the fact that degrees of separation between individuals have reduced greatly because of the Internet, and this has created a virtual “crowd.” Traditional crowds have long been a powerful force in creating and paving ways for a brand and its associated products and services. The new “crowd” based on communities forms a very powerful vehicle that can be tapped by an organization in helping drive the creation of its products and services. The net result of such an endeavor will help foster brand loyalty and increase the market presence from WOMM (word of mouth marketing). To see this type of activity in action, see www.ideastorm.com.

  • Word-of-Mouth Marketing (WOMM): This kind of person-based marketing is not new. Before the mass commoditization of telephones and television, there was a marketplace in every community, and it had a wide range of products and services. The vendors in this marketplace relied upon a loyal set of customers, who would bring in new customers in form of friends and family.  Today we call this word of mouth marketing. The difference today is that WOMM behavior happens on the Internet and in community forums, shared interest Websites and personal Websites such as Facebook, LinkedIn, Tumblr. This behavior is a key trend that needs to be measured.

  • Long Tail: As a statistical term, the long tail is a disruption to the normal Pareto or Gaussian distribution, where the larger population of the statistic rests in the tail.  The long tail was popularized by Chris Anderson in an October 2004 Wired magazine article, in which he mentioned Amazon.com and Netflix as examples of businesses applying this strategy.

    The long-tail strategy is driven by volume of business at lower cost, resulting in higher profits. This model has been since embraced by a number of organizations.
In order to embrace the “new” type of customer, organizations need to understand these three concepts and apply them to their business models. Such an exercise will help establish a business case for creating the program popularly called “voice of customer.”  This type of a program will create a sense of stakeholders among the customer base and foster a growth of community around the business, thus enabling the brand to succeed in new markets, in new products and new services areas. This model is not something that all organizations can benefit from, but conducting an experiment will always provide a basis for making the determination.

To the benefit of the organizations, there are several technology innovations that have happened in the past five years including the following: Hadoop and its ecosystem (Mahout, R, PIG, HBase), Cassandra, Google MapReduce, data warehouse appliances (2nd and 3rd generation), high-speed disk arrays, and in-memory technologies. All these put together in solution architecture will enable the technology platform for social media integration into the organization.

Tapping Into Social Media

Using the fictitious company of Acme Inc., let us now look at tapping into social media and how it will benefit any organization that deals in the service industry.

ACME Inc. has decided to implement a program called “voice of customer.” This program aims at promoting better understanding of the customers and their sentiments expressed in conversations with the call center representatives across channels including email, chat, surveys and phone conversations.  

To accomplish this program, ACME Inc. has to follow the steps outlined below:
  1. Establish several contact points or listening posts to hear and understand the customers and their solutions / grievances.  The first important step in understanding the customer is to “listen” to the customer.

  2. Extract the data from these listening posts, and examine the trends expressed in these conversations.

  3. Integrate the result set into reporting and analytics engines via data integration.

  4. Visualize the trends and metrics from the same.

  5. Provide the data to relevant business users to derive the intelligence and understand the customer intelligence.
Fast forward to the next step: ACME Inc. has implemented a technology solution platform that can provide a rich insight into “sentiment analysis.” The software can capture speech and convert the same to text, and further perform analysis of the data within the text to gather the sentiment of the conversation. Following this step, the software will categorize the conversation tone as positive or negative and the associated keywords and trends that led to the inference.

While this is a huge step in connecting to the customer, the unfortunate scenario here is:
  • The customer sentiment expressed in the conversation is not categorized based on the context. For example, the customer makes the following statement: “I have been very frustrated with a particular service offering and the number of times I had to follow up for the same. I’m not going to engage in the pursuit any further as there is minimal support. I’m very disappointed.” In this situation, the sentiment analysis software will help verify that the sentiment is negative, the reason is minimal support, and the customer is disappointed.  What the business user will miss here is the big picture that text mining and analytics will look at – the customer is unhappy with certain services as he had to follow up and received minimal support. He is unhappy in this context and wishes to cancel the said service. This big picture is contextual in nature, but there are several soft links here – how many more services the customer holds and might cancel, how many other people in his network this customer might influence, and how many other customers have expressed such concerns and canceled services. Unless this gap is addressed, the value from the voice of customer initiative is deemed primitive.

  • The second listening post is that customers will follow up the conversation with emails. For example, a customer writes an email with this information:
From: john.doe@myfreecountry.com
To: msvcs@Acme Inc.com
Subject: Customer Service Feedback

Dear ACME Inc.,
For the last 30 years, I have been a customer of your services. While the relationship has had its share of highs and lows, in the recent times your customer service team has been performing very poorly. The response times have been lagging, there is a lack of urgency to close questions, and the intent is to sell more services and not address issues. While I appreciate the self-service channels you have opened, this direct channel has deteriorated. Should this trend continue, I will be forced to consider other alternatives.

Sincerely
John.Doe

In this email, there are several key issues and associated sentiments and comparisons. If the customer had written this email and then within a 30-day time frame followed up with a call to let ACME Inc. know that he was moving on, there was time to react had the email been parsed and an alert raised on potential attrition.

Why is this important? It’s important because if John Doe has 50 friends who hear his story, chances are ACME could experience loss of all 50 customers, or over a period of time, loss of groups of customers that will lead to revenue loss. Now if John Doe were to express this in a social media forum, there is brand reputation at stake and more possible customer attrition.

To increase more actionable insights, ACME Inc. should go beyond just sentiment analytics to integrate data across multiple channels including email and social media analytics. Not only will this bring better insights, but also it will provide the organization with ability predict and model customer behavior and be prepared to react better when such situations arise. Additionally, the data and analytics will enable the business user community to better address their knowledge base and better aid their customer interactions.

An Integrated Approach




Figure 2: High-Level Integration Approach
 
Figure 2 shows a high-level integration approach where we combine processing structured data from OLTP/ODS systems, process the ETL rules, and process unstructured data from sentiments, email and social media channels. The advantage of combining the data from both the sources is we can get a holistic view of the customer. The linkage between the different types of data will be enabled by the existing master data management and metadata collections.

Enabling Better Cross-Sell and Up-Sell Opportunities

Consider that ACME Inc. has concluded a campaign for a new integrated portfolio services plan to its customers. The campaign has resulted in several calls from the customer community to call center and business services teams. In this scenario, there is need for real-time access to the customer, campaign and social media / listening post data.  This integrated data set will provide a clear roadmap for additional cross-sell opportunities. Such data can be analyzed and visualized in an all-in-one-mashup that can be consumed by the business service executive or call center executive. This will result in better customer experience and drive a true customer-centric approach. The end result will be measured in gains in revenue for the organization.

Example

Caller Customer - Name: John Doe; ID: 123456AZFSCST

Campaign: NMSCSWW-3456XX2011

When the customer calls, the system loads in the information and provides the following data:

Customer LTV
Last Transaction Date
Last Product Purchased
Last Campaign Responded To
Customer Stickiness
Customer Life Events
Customer Cross Sell Opportunity
Customer Social Media Affiliations and Presence (as Traceable or a generic Customer behavior model)

When presented to the business services executive or call center executive, this data will form a guiding portal for them to understand the customer, his/her current situation, the relevance of the call, and answer questions with a more focused, customer-centric approach, thereby providing an excellent customer experience. There is more data that can be extracted from the content management, contracts and other financial data that can help provide an enriched customer experience.

Business Benefits

The business benefits from the integration exercise include:
  • 360 degree view of the customer

  • Revenue leakage identification and recovery

  • Cross-sell and up-sell opportunities

  • Better customer connect
As shared in this article, the power of integrating social media data will enable the evolution of a customer-centric approach to build business brands.  Better connecting to the customer enables a better wallet share and creates a sense of importance for the customer.  

SOURCE: Tapping into Social Media Data

  • Krish KrishnanKrish Krishnan
    Krish Krishnan is a worldwide-recognized expert in the strategy, architecture, and implementation of high-performance data warehousing solutions and big data. He is a visionary data warehouse thought leader and is ranked as one of the top data warehouse consultants in the world. As an independent analyst, Krish regularly speaks at leading industry conferences and user groups. He has written prolifically in trade publications and eBooks, contributing over 150 articles, viewpoints, and case studies on big data, business intelligence, data warehousing, data warehouse appliances, and high-performance architectures. He co-authored Building the Unstructured Data Warehouse with Bill Inmon in 2011, and Morgan Kaufmann will publish his first independent writing project, Data Warehousing in the Age of Big Data, in August 2013.

    With over 21 years of professional experience, Krish has solved complex solution architecture problems for global Fortune 1000 clients, and has designed and tuned some of the world’s largest data warehouses and business intelligence platforms. He is currently promoting the next generation of data warehousing, focusing on big data, semantic technologies, crowdsourcing, analytics, and platform engineering.

    Krish is the president of Sixth Sense Advisors Inc., a Chicago-based company providing independent analyst, management consulting, strategy and innovation advisory and technology consulting services in big data, data warehousing, and business intelligence. He serves as a technology advisor to several companies, and is actively sought after by investors to assess startup companies in data management and associated emerging technology areas. He publishes with the BeyeNETWORK.com where he leads the Data Warehouse Appliances and Architecture Expert Channel.

    Editor's Note: More articles and resources are available in Krish's BeyeNETWORK Expert Channel. Be sure to visit today!

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