| Stock Ticker |
| ATG | 1.55 |  | 0.2 |
| NetSuite | 6.3 | | 0.3 |
| Salesforce | 22.83 | | 0.87 |
| Selectica | 0.9 | | 0.02 |
| Intervoice | 8.24 | | 0.02 |
| CDC | 0.7 | | 0 |
| eLoyalty | 2.25 | | 0 |
| Rainmaker | 0.84 |  | -0.01 |
| SupportSoft | 1.96 | | -0.03 |
| Pegasystems | 10.09 | | -0.16 |
| Vignette | 7.52 | | -0.17 |
| SPSS | 22.28 | | -0.62 |
| Chordiant | 2.19 | | -0.08 |
| APAC | 1.35 | | -0.05 |
| Tekelc | 10.63 | | -0.4 |
| HP | 31.83 | | -1.2 |
| Astea | 2.63 | | -0.1 |
| Oracle | 15.4 | | -0.6 |
| NICE | 17.65 | | -1 |
| SAP | 29.7 | | -1.79 |
| Amdocs | 16.78 | | -1.14 |
| NCR | 13.32 | | -0.91 |
| Teletech | 7.28 | | -0.52 |
| Unica | 3.36 | | -0.24 |
| LivePerson | 1.5 | | -0.13 |
| RightNow | 5.8 | | -0.58 |
| Epicor | 3.59 | | -0.37 |
| Interactive | 5.79 | | -0.6 |
| Sykes | 14.89 | | -1.55 |
| Convergys | 4.06 | | -0.46 |
| ClickSoftware | 2.06 | | -0.24 |
| ICT | 2.86 | | -0.42 |
| Nortel | 0.43 | | -0.09 |
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As of 3:48 p.m. on 11/20/08 |
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A brave new way of looking at knowledge
By Kate Leggett, Director of Product Management at KANA
My husband is a gamer. We have an Xbox 360, a Wii to play g-rated games with our 3 year old, and the PS3 is on his shopping list. His last-generation Xbox props up the TV in our bedroom and I just donated his PS2 to Goodwill. It is now midnight, and he has been playing hard for the last 3 hours – a habit that he has adopted since he brought the Xbox 360 home months ago.
I asked my husband what it is that draws him to these games. He told me that he likes the advanced graphics and scenarios, but what motivates him to turn the Xbox on night after night is its on-line social aspect – the coming together of gamers with different backgrounds. Every time he logs in, the first thing he does is to check which ones of his friends, many of whom he has never met in person, are on-line and willing to join his team, to collaborate with him to solve a scenario, and to compare how his achievements rank against the rest of the community’s.
It is his birthday soon, and I wanted to surprise him with a new game. Not being a gamer myself, I initially did a google search on popular Xbox games which overwhelmed me with too many results. Thinking back to the way that Xbox gamers operate, I realized that I was approaching this quest the wrong way. So, I narrowed my search to sites that had a large online community of gamers who I thought could help find something that my husband would like.
One site stood out in my search. It asked me to enter some basic information up front – like his age, the types of gaming consoles he had, other games that he liked By answering these questions, I got a clear listing of suitable games, ordered by price, and with embedded consumer ratings. In fact, the site even recommended the best game for me based on my husband’s past purchase history.
The site also included links to a searchable discussion board where additional product information and peer reviews were posted. I read through all the material available, asked a couple of questions which were immediately answered and I was able to quickly choose the perfect gift for him.
I often think about this experience when I am at work - not because I have an interest in gaming, but because I work at a knowledge management company, and am often called to recommend best practices for the deployment of these products.
These knowledge management products must be implemented in such a way to be successful with this new generation of customers; customers who rely on on-line social networking and tribal knowledge of others instead of expert advice to guide them through their lives. They use sites like myspace and YouTube to connect to others, blogs to read news, customer ratings to purchase new products, and discussion groups, forums or wikis for first-line customer service.
One of our marquee customers initially implemented a traditional customer service solution which we were called upon to modify in order to address these exact issues.
This customer uses a knowledgebase as a repository of all expert advice, and which is made available in a read-only fashion to customer service agents and to customers via a self-service web portal.
This customer also implemented a traditional authoring workflow. In this model, a knowledge author writes an article which is an answer to a question that he believes a customer will ask about a particular product or service. This article is then routed to a reviewer, who has the authority to approve it to be added to the knowledgebase or to reject the article back to the author for corrections.
They then coupled a reporting solution to their knowledge base so that their administrators could understand the types of questions that customers were asking, and to pinpoint the most frequently used solutions as well as knowledge gaps which exist within the knowledgebase. These are found by looking for questions that were asked which yielded no pertinent solutions. Administrators then recommend that authors write topics to fill in these knowledge gaps.
The challenge this organization faced was the relevancy of knowledge that their customers had access to as knowledge authoring was being done by someone who was not on the front lines, constantly fielding questions from their customers. As well, their linear authoring flow introduced a time delay between when solutions were written and when they were available to customers.
We recommended them to take several steps in creating dialog and a sense of community between their customers, agents and knowledge authors, with the aim of providing more timely and relevant content to their customers. The hope was that this approach would ultimately make their customers more trusting and more loyal, as it is only when you have a receptive customer base, can you be successful at marketing and selling to them.
As a first step, we appended a feedback forms to all their solutions, asking their customers whether the solutions helped solve their question. The knowledge solutions were then reworked to make them more in-line with user demand.
We then opened up the knowledge base to power authors so that they could publish directly to it without the needing the content to be routed through a review process. In this way, information was made instantly available to their customer base which they found especially useful when, for example, new hi-tech products were released where agents fielded repetitive questions for which answers did not yet exist within their knowledgebase.
Once “instant publishing” was working smoothly, we asked them to push the knowledge management envelope just a bit further by adopting a “just-in-time knowledge management” philosophy. If a customer service agent is unable to find the right solution to a customer’s question within a knowledgebase, the agent is able to author a new solution on the fly, right after having helped a customer. This allows the solution to be captured with the customer’s point of view in mind, and in his exact vernacular. Agents are also able to modify existing solutions to correct mistakes or to make them more pertinent to their customer base.
In this model, solutions are not subjected to an arduous review process, but are reviewed as they are reused by other agents. This ultimately focuses the agent’s energy in reviewing and perfecting only the solutions that are the most frequently used. What also happens is that agents collectively take responsibility for the quality of solutions within their knowledgebase as if an error is found, it is instantly corrected. And, appending the name of the agent who last modified a solution helps recognize agents who contribute to the knowledgebase. This adds an additional level of peer-pressure in ensuring that solutions are the best they can possibly be.
This organization went a step further in reaching out to their user community by integrating their knowledge base with a discussion forum. This allows their users to recommended information to be added to the knowledge base, ensuring that it organically grows with customers changing demands.
This organization also realized that they have groups of expert users who know the product as well as their customer service agents, and now allow their expert users to post content directly to the knowledgebase, in effect, turning each knowledge solution into a wiki. Expert user contributions are identified and can be rated so that poor contributors can be restricted to adding knowledge content, and star contributors are recognized.
Knowledge management solutions like these are not suitable for all industries, but in the verticals where this model makes sense, like hi-tech or retail, collaboration between users and agents help evolve and perfect knowledge content in parallel with your customer’s needs. It also helps build a sense of community around your brand, allows you to differentiate yourself from your competitors, and keeps customers loyal by providing accurate and on-topic answers to their questions.
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