Maximize Social Media Effectiveness with Data Science. An Insurance Industry White Paper from Saama Technologies, Inc.

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Maximize Social Media Effectiveness with Data Science An Insurance Industry White Paper from Saama Technologies, Inc. February 2014

Table of Contents Executive Summary 1 Social Media for Insurance 2 Effective Usage of Social Media Data 2 The Ideal Social Media Solution 4 Social Media Analytics in Saama s Fluid Analytics Engine 5 Customer Engagement 6 Campaign Sentiment Analysis 7 Topic Distributions 9 Performance 10 Maximizing Social Media Campaigns 11 Conclusions Learn More

Executive Summary Social media campaigns can be used as an effective means to promote an insurer s brand and increase customer engagement. A common challenge for insurance carriers is measuring the effectiveness and maximizing the ROI from such channels. In addition, insurers need to consider how best to integrate social media as part of a larger marketing campaign. As the usage of social media continues to rise, insurance carriers need to understand how best to leverage its power for their competitive advantage. Saama Fluid Analytics Engine helps insurance carriers mine social media data and provide contextual and prescriptive analytics vis-à-vis marketing campaign business metrics. KEY TAKEAWAYS Challenges in social media marketing Integrating social media campaign with traditional marketing campaigns (direct & digital) Saama Fluid Analytics Engine-based» social media analytics & ROI model 1

Social Media for Insurance Social media is no longer just used merely for connecting with friends and family. It has become a powerful medium for reaching potential customers, influencing the market, extending your brand and listening for informal feedback. In fact, it can be a very powerful two-way communication tool. The increased usage of social media presents unique opportunities and challenges for the insurance industry., which is still learning how to best utilize social media. To improve social media performance, insurance companies must assess their current level of social media monitoring maturity and determine the technologies and techniques that will best help them optimize their social media marketing strategy. Effective Usage of Social Media Data Among all the insurance carriers that are using social media channels, only 12% feel that they are using them effectively. A large percentage of organizations have shown interest in the use of social media, but have difficulty measuring the value and impact of social media for advancing their business. 2

Businesses are looking to social media data to find answers to these questions: How are customers responding to the latest advertising campaign in our market? How does our campaign stack up against the competitor? What are the valued service attributes in our category? Which messages are our competitors delivering in the marketplace? What are the comments that our public relations team should address? How accurately does the comment reflect upon our brand? How do we measure the added value of brand reputation through our business partners? What is the social media sentiment toward the company? Gartner s 2013 U.S. Digital Marketing Spending Survey found that investments in content creation and social marketing totaled 21% of digital marketing budgets. Forty-seven percent of survey respondents see content creation and curation as the top role of their social marketing teams. 3

The Ideal Social Media Solution A robust social media analytics solution should be capable of: Measuring customer opinions and sentiments to identify positive and negative aspects of the most discussed topics Measuring social media engagement effectiveness based on customer sentiment Identifying weaknesses and strengths to optimize and improve marketing campaigns Measuring conversational buzz and volume Offering better customer insights to anticipate and prepare for customer needs, wants and satisfaction Combining data collection, text analytics, Natural Language Processing (NLP) and dashboards into a single comprehensive solution 4

Social Media Analytics in Saama s Fluid Analytics Engine Saama s Fluid Analytics Engine helps businesses synthesize, analyze and gain actionable insights based on diverse data sources such as social media, syndicated data and other unstructured data, as well as a company s in-house data. Saama s social media analytics have the capability to identify the current state of a brand in social media and provide actionable insights to business issues. The ability to discover customer sentiments, uncover hidden trends and envision future opportunities is fundamental for insurers to establish a successful social media strategy. To determine the type of analytics capabilities needed, insurers need to be aware of the technologies that are involved in the complex areas of social media and analytics. Unlike standard business intelligence and reporting, the integration of social media analytics opens up a wealth of data insights. Gartner has observed many companies lacking social media strategies or starting to build these strategies in 2012. To help with this, Gartner provides these best practices to help companies avoid risks around social media and drive greater returns from their social media initiatives. Your strategy should: Stipulate how social media will be used Designate who is responsible for content creation Establish who will monitor the content 5

Customer Engagement Millions of customer interactions are taking place daily in social media, which is emerging as the next frontier for customer engagement and interaction. To benefit from a competitive advantage, it is crucial for insurance companies to fully utilize their collective social media data. Saama helps you investigate customer engagement by measuring the effectiveness of marketing campaigns through tracking changes in the volume and buzz of social media conversations. Our solution effectively uncovers customer engagement insights by comparing the conversational volume and buzz between campaign periods to support campaign engagement optimization. 6

Campaign Sentiment Analysis To thoroughly grasp social media activity and impact, insurance companies must have the capability to listen to all the relevant social media channels. Saama s expertise in text analytics and natural language processing can assist insurance companies with data quality and organization into an appropriate structure for analysis. Customer sentiments are typically distributed in three categories: Positive, neutral and negative. Customer sentiments can be further represented by the following emotions: Anger, disgust, fear, joy, sadness and surprise. The customer sentiment analysis can be combined with internal data to produce additional insights into customer and prospect behavior. Saama s analytics solution is capable of handling Big Data, aggregating and analyzing data from multiple sources. Off the shelf tools or applications are simply not able to provide the same quality of insights. Net Promoter Score and Social Sentiment Studies have shown that the use of social computing can have a positive effect on customer loyalty, customer experience, customer satisfaction, positive recommendations and sales. 7

Net Promoter Score (NPS), a common customer sentiment index, is based on a simple survey that asks consumers to rate their customer service experience on a scale from 0-10. It measures the loyalty between a consumer and provider and helps answer how likely it is that a consumer would recommend a company to a friend or colleague. Based on their responses, customers can be classified into three groups: detractors, passives and promoters: detractors passives promoters rating = 0-6 rating: 7-8 rating: 9-10 nps = % promoters % detractors Prior to the emergence of the social web, NPS was the best way to capture online customer sentiment. You can discover the true sentiment of your page by analyzing the frequency of positive and negative comments, classifying them into social sentiments and looking into actual comments for more insights. This analysis provides a more comprehensive measurement than traditional NPS for indicating how a company is performing with regards to customer satisfaction. Tracking this over time allows you to more accurately measure the effectiveness of your marketing campaigns and initiatives. 8

Topic Distributions In addition to sentiment analysis, the ability to perform campaign topic distributions for individual campaigns is a fundamental aspect of identifying areas that were well received, as well as those areas needing improvement. Saama pinpoints the commonly discussed topics in social media conversations by the frequency of keywords observed. Our social media analytics system then determines and allocates the topics captured via comments/tweets. Our analytics approach further classifies the result from topic distribution and sentiment analysis to enhance the relevance of this information. For example, the diagram below shows customers are satisfied with the way a company currently handles policy, management, price and coverage. However, the areas of claim, service and promotion mainly consist of negative sentiments. 9

Performance Social media analytics becomes more robust when combining the analysis with internal customer data. Our data integration capability can gather information from social media and combine that information with internal customer data for analysis. For example, performance changes for key metrics such as new customer rate, new contacted rate, new quote rate, page visit rate, renewal rate and total sales during a campaign period can be compared to information acquired through social media analysis. A campaign that shows high conversation volume and positive sentiment with a significant increase in performance (page views) for the campaign period will serve as a conceivable prediction of that campaign s success. 10

Maximizing Social Media Campaigns Social Media Campaign ROI Most businesses will be reluctant adopt new marketing strategies unless they have a general idea of the ROI associated with it. However, in the case of social media, companies are jumping on the bandwagon and using it for marketing purposes without having appropriate ways to measure the performance and ROI. The social media campaign ROI model enables marketing professionals to examine the profitability of underlying social media marketing strategy. The following metrics are needed for computation: Total number of visitors reaching the goal page Total product revenue Total number of social media visitors reaching the goal page Cost of social media campaign Note: The goal page is driven by business and is based on customer buying patterns. Revenue per Goal Page Revenue per Goal Page = Target Product Revenue Total Visitors Reached Goal Page Social Media Revenue Revenue = Revenue Per Goal Page X Social Media Visitors Social Media Profit Profit = Revenue Marketing Cost Social Media ROI ROI = Profit Marketing Cost ROI = [( Total Product Revenue Total Visitors Reached Goal Page X Social Media Visitors Marketing Cost ( Marketing Cost [ 11

Conclusions Saama Fluid Analytics Engine enables businesses to understand the correlation between diverse data sources such as social media, syndicated data and other unstructured data and a company s in-house data. It uses machine learning and data science methods to combine three core pillars: Business Strategy, Domain and Data all solving a given business problem and enabling fact-based intuition for businesses. Questions that cannot be answered by traditional analytics and BI systems are solved iteratively by Saama Fluid Analytics Engine, giving new actionable insights to build disruptive business models that can transform your organization. Learn More For more details about this project, or to learn more about Saama s solutions for the insurance industry, contact us at Insurance@saama.com or visit us online at www.saama.com/industries/insurance/ Connect with Saama Technologies Web: http://www.saama.com Twitter: https://twitter.com/saamatechinc Facebook: https://www.facebook.com/saamatechnologies LinkedIn: http://www.linkedin.com/company/saama-technologies Authors Abhishek Peraka Wen Yi Zhang Saroja Yalamarthi Jyostna Shiramshetty Sherry Huang A White Paper from Saama Technologies, Inc. 900 East Hamilton Avenue Campbell California 95008 www.saama.com 2014 Saama Technologies, Inc. All rights reserved.