Top CRM Reviews

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Using Social Media Marketing and Social CRM tools and techniques of the Xuropa Platform, you can easily inject your software into online conversations. This has proven to accelerate software sales and build advocacy in your marketplace.
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Der Screencast erläutert die Integration von Social Media in das Customer Relationship Management
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An Evening With Paul Greenberg. Paul captivates the crowd with his take on Social CRM at Enterprise 2.0 – Boston.
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Loaded Technologies (loadedtech.com.au) held the Customer-centric Business of the Future Event, Sydney – June 7th 2011. Joey Parsons, Vice President of Operations and Customer Success at SugarCRM Inc, presented the step-change in Customer Relationship Management and introduced SugarCRM’s latest release, Sugar 6.2.

A Practical and Results-Oriented Knowledge Management Platform

The contemporary customer is a smart and learned one. He is not the one to fall into baseless traps without concrete evidence. The worth of a good or a service has to be proven to enjoy the customer’s patronage. As businesses aim to provide better quality services to the customer they try to implement various methodologies to make things simple and fast. However these systems fail to coordinate and execute a cohesive function resulting in dissatisfactory customer service delivery. The customers are provided with inconsistent and poor service which affects the business prospects adversely.

The facility of aweb self service and chat service is invalid as the customers are not provided with prompt and updated information. The demand for these services is more as customers seek immediate resolutions. This means communication between the customers and the business has to be extremely flexible and transparent. The agents have to be provided with tools that help in locating the information and responding accurately and quickly. The business processes have to demonstrate high levels of versatility and agility to address all customer issues effectively and deliver unmatched customer service quality.

Agents have to be prepared to face any challenge and use the knowledge management resources wisely and effectively to find the correct solution for individual issues. As per the traditional mode the content was written by authors who did not interact live with the customers. As a result the resolutions that are stored in the knowledge base are universal in nature and do not meet the customers’ needs effectively. The existing knowledge is ambiguous and fails to achieve the desired results. Thus every business needs to employ knowledge management software that showcases prominent and realcustomer experience management capabilities.

Theknowledge management software develops a knowledge base that is based on the interactions between the agent and the customers. Thus each resolution that is created is unique and customized to meet the customers’ needs precisely and thoroughly. It boosts integration and collaboration amongst the various applications and systems for optimization of content and creates a knowledgebase that can be used practically.

The software facilitates the content to be captured while the agents interact with the customers and provides real-time tools for streamlining and automating the creation of content. The motive of delivering flawless customer service experience can be wrecked in the absence of a regularized knowledge management strategy. This strategy possesses capabilities and provides high visibility with enormous benefits.

See how you can use social media to build stronger relationships with your customers and find new prospects.

Marketing That Delivers – www.neolane.com Marketers attending the 140 Conference in Boston share their thoughts on Social CRM. Contributors: Casey Cheshire, Digital Marketing Manager, EF Educational Tours Twitter: @CaseyChesh – Blog: www.caseycheshire.com Wayne Kurtzman, Senior Marketing Analyst Twitter: @WayneNH – Blog: beyondthe.biz Christine Major, Marketing Communications Manager, Awareness, Inc. Twitter: @cmajor – Blog: www.christinemajor.com Captured by: Neolane, Inc. Twitter: @neolane – Blog: Blog.Neolane.Com http
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In this Video we talked about Luke’s social media tour and how his events focus on different aspects. Social Media Marketing & Monitoring in New York Wednesday 12th October. Social CRM in New York Thursday 3rd November. Social CRM in Paris Tuesday 6th December. The top takeaways from the Social Media Marketing & Monitoring event in London. We also talked about what companies need to pay more attention to today when it comes to social media, and what they are missing. blog post: www.mattiasgronborg.com
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Social CRM Tools brings the world of Social Media into Salesforce.Com by allowing you to seamlessly integrate and import Facebook, Twitter, and LinkedIn information of your leads, accounts, and contacts into Salesforce.Com. In this demo of Social CRM Tools you will learn how to look up, search, capture, and import Facebook Info about on Your Contacts & Leads. Download for Free at www.socialcrmtools.com. Also available on App Exchange.
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Volume vs. Meaning: Effective Customer Listening Requires More Than Keywords

Is it your job to listen to and analyze social media messages and direct customer feedback about your product, brand, or service? Are you leading corporate initiatives that leverage consumer-generated content to uncover meaningful insights about your business? Effective listening and insights analysis allows you to track not just the volume, but also the meaning of online conversations across a complex web of consumer interaction channels.

One of the most common approaches to making sense of customer conversations is to track the presence of keywords within a defined universe of brand conversations (e.g. forums, communities, social networks). While this method highlights text where individual keywords are being used, this approach is unable to automatically evaluate comments for topics, themes, or sentiment. Nevertheless, many companies have implemented keyword systems as a first step to help sift through large volumes of consumer-generated content on the social web. These same companies have then typically hired people to manually read, categorize, summarize, and report on keyword search results at a considerable expense, and with questionable accuracy.

Keyword-Based Online Customer Listening: Fraught with Bias and Subjectivity

The process of selecting and tracking individual keywords in a sea of unstructured content is fraught with bias and subjectivity. Through a combination of personal experience and research, as business user can assemble groups of words that – if contained in a text record – are indicative of a category or sentiment (e.g., “meaning”). For example, a retention analyst attempting to track customer attrition might set up searches for the words “cancel,” “leaving,” and “switching. However, this approach will likely return false positives and miss many records that do not contain the specified combinations.Moreover, this approach does not provide any information why customers are dissatisfied or at risk. To obtain these insights, the analyst must manually read all the messages flagged.

The way people indicate attrition risk may include hundreds if not thousands of different word/phrase combinations. Further, just because a message contains the word “cancel” in the text, that fact does not necessarily indicate an attrition risk. For example, someone could say, “I had to cancel my credit card because I lost it. Could you please call me so I can change my billing information?” Such a message would be included in the example above, even though the customer does not actually want to cancel service.

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In terms of sentiment analysis, keyword-based solutions similarly perform tagging functions based upon libraries of positive and negative words. These “one size fits all” libraries offer the lowest level of accuracy as there are – once again – too many variations on how a customer can express positive or negative emotions in a post.

The value of keyword-based monitoring systems is akin to web search or press clippings for the Internet – i.e., the tracking of brand mentions across a generic, predefined universe of media sites to gain a general sense of volume and buzz across the widest possible spectrum. This information can be helpful for high level corporate metrics and general public relations tracking. However, the effort required to read flagged content – and analyze it for topic and sentiment – is significant, and is often accompanied by human subjectivity and fatigue that contributes to the degradation of the resulting insights. Different people rarely read, interpret, and categorize content in the same way; while individuals are notoriously inconsistent and not motivated to deliver insights from this monotonous process. As such, most attempts to leverage keyword monitoring solutions for detailed analysis are flawed.

Natural Language Processing:A More Accurate Approach to Listening

If keyword-based monitoring systems doesn’t sound like a fit for you, it’s time you consider a Natural Language Processing (NLP) -based customer listening solution.NLP is a scientific approach that enables software to discover and match author intent to a virtually limitless set of words and phrases. NLP-based listening systems assign weights to words and phrases, as opposed to simple “exact match” keyword logic. In the attrition risk example, the word “cancel” will most likely produce a strong weight, and be a good indicator of an attrition risk, however, the other words that appear with it (e.g. would, like, to, please, me, subscription, service, etc.) would also be assigned a weight, all of which would be used to score a verbatim record as true or false for a thematic/sentiment category.

NLP-based processing also relies on machine-learning, whereby the system is given examples of text that are “true” for every category if interest. The system then “bubbles up” words that a user would have never thought of to enter in as search words, but are present in the examples with statistical frequency. This approach helps eliminate bias, produces a much smaller percent of false positives, and also increases the recall (number of messages true for a category).

You’re probably wondering how a machine can automatically create the expansive weighted word lists and associations that correspond to individual categories. In a small sample (a few hundred), a human will categorize the messages with a higher degree of accuracy than any machine. However, when you give a human 100,000 to categorize, they will suffer from fatigue, thus greatly reducing the accuracy. Systems such as Overtone’s OpenMic® have been built to leverage a small sample of human categorization, but then take that sample and use machine learning to categorize the rest. This hybrid approach using humans to train a machine produces categories that are much more accurate (minimizing false positives) and find more mentions (maximizing recall) than simple keyword searches.

NLP-based approaches to text classification enable business users to create categories that center on a theme, as opposed to just a set of keywords. Categories like Sentiment, Loyalty, and Attrition Risk are not reduced to a collection of representative words, but rather, an overall set of weightings, and statistically significant word cues that suggest a topic area. Clearly, NLP-based systems perform better than keyword-based systems. The superiority is not slight, it’s considerable.It doesn’t apply to just a few categories; it applies to nearly every category.

Keywords do of course have their place. For example, tracking categories that don’t really contain a theme (e.g. competitor names, product names, etc.) are best handled by simple keywords.But when it comes to accurately categorizing the theme of a message to inform trending and root cause analysis, an NLP-based solution is the way to go.

Capgemini, Attensity and Pegasystems are pleased to announce the launch of their exciting new Social CRM Proposition: “Social Insight Into Action: When Social CRM Meets Business Process Management”. The explosion in social media usage means that customers are increasingly connected and empowered. A customer can post a comment about a product or company that can quickly influence the views of thousands or even millions of people online. For most organizations this represents both an opportunity and a threat. Previously, there was no reliable way for an organization to analyze social sentiment and crucially turn that insight into action. However, we have now developed a way that enables our clients to not only listen — but analyze and respond to — what customers are saying on a near real-time basis. Three industry leading organizations — Capgemini, Attensity and Pegasystems have combined their expertise to create a solution that combs social media sites and integrates with an organization’s existing CRM and BI systems. The result? The ability to cut right to the core of what customers are actually saying, respond to negative feedback by fixing problems at source, and identify new sales leads or process improvement opportunities. To learn more or take Social Insight Into Action for a ride, contact Dan.Truman@Capgemini.com in the first instance. Alternatively, contact the key representative from each partner organisation:- Patrick.James@Capgemini.com Russell.Prince-Wright …