Analyzing Customers' Social Voices
Nov 25, 2013, 12:08 ET
NEW YORK, Nov. 25, 2013 /PRNewswire/ -- Reportlinker.com announces that a new market research report is available in its catalogue:
Analyzing Customers' Social Voices
Companies are Turning to Social Media Analytics to Gain Customer Insights
Social media contains information and insights that help companies identify issues, threats, trends, sales opportunities, and influential buyers. It provides knowledge about customers, partners, competitors, and employees, and it helps deepen customer and staff relationships. Social media analytics has emerged as a powerful tool to measure social-site traffic, but more importantly to obtain meaningful, actionable, and timely insights.
Introduction
Social media is becoming a core consumer and business-user forum, and companies are recognizing the business value of social media as a marketing, brand management, and customer service and support channel. Social media and sites contains information and insights that help companies identify issues, threats, trends, sales opportunities, and influential buyers. It provides knowledge about customers, partners, competitors, and employees, and it helps deepen customer and staff relationships.
One of the most crucial pieces of knowledge social media provides is customer sentiment, namely how customers feel about a company's brand, campaign, product, services, or customer service. Customers willingly provide this information on social sites, although it is not always handled formally; a status update expressing disgust or satisfaction won't make it into a company's typical CRM system, but it can have significant impact nonetheless. Companies can gauge the depth of this sentiment in the number of comments posted to both their own pages and to those of their customers, and how often they are viewed or passed on.
Social media analytics has emerged as a powerful tool to measure social-site traffic, but more importantly to obtain meaningful, actionable, and timely insights.
Social Media Analytics Drivers
Social media analytics let users "tune" to the social channel in order to "hear" customers' social voices. Tuning involves training the software to filter through complex and disparate social conversations and aim them at particular social sites. The solutions typically use a combination of keyword or key-phrase spotting, like for company or competitor mentions. They often use natural language processing (NLP) for root cause or sentiment analysis, like "what do customers think of the customer service?"
Social media analytics systems are typically intelligent enough when performing queries to identify correlations and context. Simpler applications will require users to ask precise questions, whereas more sophisticated solutions will automatically extract sentiment, pose categories, identify correlated terms to be used, and surface trends.
Social media analytics can uncover unique or otherwise-difficult-to-obtain knowledge about the desires of individual customers and the broader market—factors which are helping drive their adoption. Here are several examples:
• In-depth Market Insights. Customer's social conversations reveal their product or service preferences, including unmet desires. For example, a candle company can determine which scents to offer, and when, by listening to individuals' comments about scents and associations. Also, individuals' self-reported personal information on social sites, such as on their Facebook pages and LinkedIn profiles, contain a wealth of data. Social media analytics enable companies to refine and target their marketing and customer service messaging to them based on that personal information.
• Improved Fan Relationships. Brand advocates, or "fans," represent a small percentage of social media users, but they generate most of the content and serve as "pro bono marketers." To improve reach and deepen relationships, companies can use social media analytics to better understand each fan and apply that knowledge to cater to their particular needs.
• Enhanced Customer Omni-Channel Experiences. Companies have begun to execute "omni-channel" strategies to provide a consistent, high quality, and profitable customer experience, regardless of the channels and devices customers use. For example, if a customer inside a store tweets that he or she likes a particular outfit, social media analytics can pick up the remark and recommend that the retailer tweet back with a special offer to encourage a purchase. But companies have to be careful when acting on this knowledge in order to protect consumers' privacy and to avoid annoying them. Some customers do not expect or appreciate a direct response from a company after they post a comment on social media.
• Unfiltered Real-time VOC. Social comments mined by social analytics give a raw, often emotion-laden, and real-time insight into customers' attitudes, or voice of the customer (VOC). While social data is not supplanting net promoter scores (NPS) or surveys, it supplements them for customer service, market research, and sales performance improvements.
• Consumer-to-Business Insights. Consumer sentiment detected by social media analytics can also help businesses sell to other businesses. For example, consumer products firms use product preferences and perceptions to convince retailers to give them more prominent shelf space.
Social media analytics are also being used by companies to shape other corporate functions that impact marketing and customer service. For instance, banking and insurance firms are listening for signs of fraud and hacking, such as when individuals brag about duping a particular company or cracking their network security. Other companies are tracking and analyzing employee activity and comments on their social intranets to see where they can reduce staff churn and improve their performance and productivity.
Social Media Analytics Trends
The ways in which companies mine social media and use social media analytics applications are rapidly evolving as the channel grows, and as users gain experience with these new applications.
The most important trend is cross-channel integration. Companies are beginning to integrate social media analytics with speech, text, and Web analytics to cover all customer touch-points. Their reasons are threefold:
• To obtain a complete VOC to understand customer opinions and preferences, link their social and "off-social" identities, and provide context to their social comments.
• To provide a higher quality customer experience from the information gathered from customers.
• To detect and proactively address issues, problems, and needs that are often made known on the other channels, like damaged baggage and surly staff, before they "go viral" on social media, at which time companies are in a "damage control" or reaction mode.
Table of Contents
Introduction 3
Social Media Analytics Drivers 4
Social Media Analytics Trends 5
Social Media Analytics Restraints 7
Best Practices Recommendations 8
Representative Vendor Profiles 10
Adobe 10
Dachis Group 10
IBM 11
Kana 11
SAS 11
SDL 11
Semantria 12
Semeon 12
Shoutlet 12
Verint 13
Legal Disclaimer 14
The Frost & Sullivan Story 15
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