Product Evaluation: Oracle Service Cloud Social Experience

Oracle Service Cloud Social Experience 

Our evaluation of the August 2013 Release of Oracle Service Cloud Social Experience is this week’s report. You may be more familiar with the product by its former RightNow CX Social Experience or Oracle RightNow Cloud Service Social Experience names. Oracle acquired RightNow in January 2012 and, without a formal announcement, renamed the product sometime during 2Q2013. One other point about the acquisition, the former RightNow R&D team has continued to develop the product, has continued to work out of the former RightNow headquarters site in Bozeman, and has continued the regular, quarterly releases of the product.

Social Experience is one of three “Experiences” in Oracle Social Cloud. The other two are Agent Experience and Web Experience. Each is aptly named for the channel that it supports. The three share a base of common data (Customers, accounts, cases, and knowledge items, for example) and services including business rules, process management, user management, and reporting. Also, product packaging and pricing puts Social Experience “in the box” with Agent and Web Experience. So, social customer service is really built into Oracle Service Cloud and that’s its key strength and differentiator.

Social Experience has these three components:

  • Communities, which supports internal community capabilities of posts and responses on topic threads. Oracle Service Cloud Social Experience Communities is based on technology developed by HiveLive that the then RightNow acquired in 2009.
  • Social Monitor, which provides capabilities to monitor posts on the social web—Facebook, Twitter, YouTube, and RSS feeds as well as Communities, to analyze the content of monitored social posts, and to interact with social posters.
  • Self Service for Facebook, which lets organizations deploy Oracle Service Cloud web experience and Communities capabilities on their Facebook pages to help Facebook users access Oracle Service Cloud Social Experience Communities and knowledgebase as well as to create cases.

Facebook, Twitter, YouTube, RSS, and Social Experience Communities are the social sources monitored by Social Experience. While these are certainly the key social networks, the product does not monitor some sources that are critical to customer service, particularly external communities, forums, and blogs. These are sources that customers very commonly use to get answers to questions and solutions to problems. That Social Experience doesn’t monitor them is a serious limitation. Oracle already has the technology to address this limitation, technology that came with its June 2012 acquisition of Collective Intellect. Collective Intellect’s IP was social monitoring and analysis technology. Oracle told us that it’s working on integrating this technology with Oracle Service Cloud.

Twitter for Customer Service

On the topic of Twitter, last week, Patty Seybold published, “Four Reasons Why Customers Prefer Twitter for Customer Service,” a report about how businesses and their customers use Twitter as a key channel for customer service. Patty proposes seven best practices for Twitter-based customer service. Oracle Service Cloud Social Experience can help implement four of the seven—Treat Twitter as an Integrated Customer Service Channel, If You Have Lots of Customers, Establish Customer Service Twitter Accounts, Defuse Anger Publicly; Take the Issue Private, Gather Customers’ Ideas for Next-Gen Products. You’ll implement the other three—Set Customers’ Expectations Re: Times of Day You’ll Respond to Tweets in Real Time, Respond within Minutes, and Don’t Use Automated Responses!—with customer service policies, standards, and procedures. Here are the four with brief descriptions of how Oracle Service Cloud Social Experience helps implement them.

  • Treat Twitter as an Integrated Customer Service Channel

Social Experience Social Monitor searches Twitter for Tweets that are relevant to customer service. Agents and/or analysts specify search queries as strings of language-specific terms of 255 characters or fewer. Queries strings may include the exact match (“”), AND, or OR operators. Analysts can save search queries for execution at a later time or for (regularly) scheduled execution.

Social Experience Social Monitor can automatically create customer service cases from the Tweets in search results and automatically appends the info in subsequent Tweets from the same Twitter account to them.

Social Experience captures customers’ Twitter account info within search results and includes them within Oracle Service Cloud customer data.

  • If You Have Lots of Customers, Establish Customer Service Twitter Accounts

Social Experience supports multiple corporate Twitter accounts that it shares among its users. (It supports corporate Facebook accounts, too.) Businesses can create a hierarchy of corporate Twitter accounts for customer service, organizing them in any appropriate manner—by customer or customer company, by products, by customer service level, or by severity or priority, for example. And, Social Experience’s Corporate Twitter accounts can be set to follow customers’ Twitter accounts.

  • Defuse Anger Publicly; Take the Issue Private

Agents specify whether each of their Tweets on their corporate accounts is public or private.

  • Gather Customers’ Ideas for Next-Gen Products

Cases generated from Social Monitor search results can be ideas for next-gen products as well as the representation of questions and problems.

Pretty good, although a bit of content-based alerting on search results could automate Twitter monitoring. Note that these capabilities of Social Experience’s to support Twitter are capabilities that we’ve seen in other social monitoring and analysis offerings, offerings including Attensity Analyze, and Respond, Clarabridge Analyze, Collaborate, and Engage, and KANA Experience Analytics. All of these offerings have been available for a few years. They’re widely-used and well-proven. Any of them can help make Twitter an integrated customer service channel.

Going forward, we’ll extend our framework for evaluating social customer service products to include Patty’s best practices as

Analytics in Radian6

This week’s report is our evaluation of Radian6, the component of Salesforce Marketing Cloud that does social monitoring, analysis, and interaction. Its tight integration with Salesforce Service Cloud—automatic creation of Cases and Contacts—makes it the obvious social-service choice to add to the customer service application portfolio of Salesforce CRM users

Customer social-service is all about monitoring customers’ conversations in the social cloud, identifying customers with questions, problems, and issues, and then interacting with those customers to answer questions, solve problems, and address issues. The number of customer posts and conversations in the social cloud that may be relevant to a business can be very large, ranging to thousands or even tens of thousands per week and, in the extreme, hundreds of thousands per day. Monitoring and analyzing all of them, identifying the (few) posts that require attention, and then handling each one individually and handling all of them consistently are daunting and complex tasks, daunting because of the sheer volume and complex by the diversity and nuance of language, breadth of topics, and depth of emotion (sentiment).

Most social-service products use third parties to monitor social posts, to crawl and search the key social networks and the hundreds of millions of blogs and forums where customers ask questions, get answers, and make comments.  The value-add of these products is in their analytic capabilities, capabilities that can “understand” the content of social posts. Natural Language Processing (NLP), sometimes called text analytics, is the technology that they most commonly use. And, also most commonly, each of them is built its own NLP implementation. Their companies are built on it, too. These NLP implementations are frequently patented and almost always proprietary. They’re the crown jewels of analytics companies. So, the selection of a social-service application usually involves the evaluation and comparison of NLP implementations, a difficult selection of sophisticated and complex technology.

Not the case for Radian6. It takes the opposite approach. Rather than leverage the data collection capabilities of third parties and apply its own analytics, Radian6 does its own data collection (The current version searches and crawls over 650 million social sources.) and leverages the analytic capabilities of third-party analytics suppliers to understand the content of social posts. (Radian does a bit of its own analytics, too, although its analytics are a bit basic and are not built on NLP.) These 14, third-party analytics suppliers comprise what Salesforce.com calls the Radian6 Insights Ecosystem, Insights for short. They apply their analytic technologies to the social posts collected by Radian6.

The 14 are:

  • Bitext
  • Communication Explorer
  • Clarabridge
  • EpiAnalytics
  • Hottolink
  • Klout
  • LeadSift
  • Lymbix
  • OpenAmplify
  • Open Calais
  • PeekAnalytics
  • Soshio
  • The SelfService Company
  • Trendspottr

Let’s take a little closer look at three Insights to get an idea of their capabilities.

  • The Bitext Sentiment analytic perform Entity extraction and sentiment analysis for posts in Spanish (European and Latin American), Portuguese (Brazilian and European), Italian, and English using natural language processing technology (NLP).
  • Clarabridge provides two analytics. Clarabridge Link Sentiment provides sentiment analysis of social posts in Chinese, Dutch, English, French, German, Italian, Portuguese, Russian, and Spanish using NLP; Clarabridge Link Classification applies a Universal Category and Classification model to social posts in Chinese, Dutch, English, French, German, Italian, Portuguese, Russian, and Spanish using NLP.
  • OpenAmplify also provides two analytics. OpenAmplify Cust Svc uses NLP to identify social posts containing potential customer service issues and the topics of those potential issues. OpenAmplify uses NLP to identify sentiment, intention, and topics of social posts.

Salesforce.com offers these Insights like usage-priced cell phone minutes within the subscription licenses and their monthly fees for Radian6 Editions. (Editions are licensing tiers that bundle applications resources.) More specifically, Radian6 Editions include blocks of Insights partner credits. The analysis of one social post by a one analytic application from one partner costs one partner credit. At the low end, Marketing Cloud Radian Basic Edition includes 1,000 Insights partner credits. At the high end, Marketing Cloud Radian Enterprise Edition includes 500,000 Insights partner credits. Blocks of 10,000 additional Insight partner credits are available for a fee of $100 per month. Credits are expire every month (like cell phone minutes).

Insights’ suppliers set up pre-configured deployments of their analytic applications for access and usage by Radian6 licensees at runtime. That approach can be a disadvantage. For NLP based Insights, runtime access means that language models and processing configurations are those implemented by their suppliers for general-purpose usage, not language models and configurations of deployments tailored to the applications and vocabularies of specific businesses and their customers. For example, the Clarabridge Link Classification Insight uses a “Universal Category and Classification” to classify social posts. Analytic processing will still be quite useful, just not custom tailored.

There are also advantages to Radian6’s Insights approach of runtime access to analytic applications. Most significantly, Radian6 lets businesses easily combine and nest these analytics. For example, analysts might use the entity, fact, and event extraction capabilities of Open Calais to find posts relevant to a product launch and then use PeekAnalytics to identify the demographics of those posters. Also, specifying language models and processing configurations for NLP-based analytic applications is complex work, work that Radian6 users do not have to do to get much of the benefits of these sophisticated applications.

The approach to analysis in Radian6 is a significant differentiator and a key factor for selection. Radian6 delivers most of the power of a wide array of third-party analytic applications and the flexibility to use them separately or to combine their processing. Pricing is based on usage. Value is very good.