It’s Back! The Best Customer Service Survey Ever — Version 2.0

Well, well, well… a lot has changed in one year in customer service, and we want to know exactly what and how much.

Last year we run an extremely successful survey to determine where the Customer Service market was, what people perceived as the big issues, how they were implementing channels (including the new – then – social channels) and what were the plans for the future.

We had a tad over 400 qualified answers and we published the results under the sponsorship of KANA Software.  In case you don’t remember what the results were, here is the deck we used at CRM Evolution to present the results together with Mitch Lieberman.

It was so successful, and so interesting, that we are redoing the survey.  Version 2.0 is now ready for your answers — and we are also collecting data on mobile service in addition to social and traditional, as well as a couple of extra questions (surprise! but you will want to know what these are, trust me).

Please click here, take the survey (it is not long, should take no more than 10 minutes) and share your opinions.  We are trying to increase the number of responses from last year if we can.

We are going to close the survey on August 23rd, right after CRM Evolution, and we aim to have the report ready for KANA Connect in mid-September.  If you complete the survey and give us your email address we will be happy to send you a copy of the full report when available.

What do you say? Take the Survey? Please?

disclaimer: this should go without saying, but just in case.  KANA Software is a client, has been for some time.  I even worked with them for a short time during my blue period (in between analyst gigs).  I know them, they know me – and they know better than to try to control this research.  This is my project, my report, my study – and they are nice enough to pay me for the privilege of running it.  If you think that either the survey, the data from the survey, the analysis, or the report will ever made it under their control — well, let’s just say you are more likely to rent the super-collider for a weekend of “fun with atoms” than to be right about that.  I will never distribute the data from the report to anyone, nor will I ever give control of the content of the survey to anyone.  Period.  As I said, I hope it goes without saying… but said it anyways. So there, it’s said. Savvy?

Knowledge Management and Customer Satisfaction

We all know the statistics, right?

  • most dissatisfied customers will eventually tell 9 other people about their problem
  •  only 4% of dissatisfied customers actually complain to the company
  •  satisfied customers tell 5 to 6 other people about their positive experience

and many others like it (it costs more to get a new customer than to retain an existing one, etc.)

The again, what if —

What if Knowledge Management could help you reach higher levels of customer satisfaction?

What if Knowledge Management could help you retain existing customers?

What if —

Well, I took this “what if” questions to heart and started exploring that a little bit.  In the final installment in the series sponsored by Coveo about how Knowledge Management is changing Customer Service I wrote one more post: How to leverage Knowledge Management in Customer Service to Ensure Satisfied Customers.

It is a short-ish (my standards) post exploring how you can use KM better to resolve the two perennial problems in Customer Service: knowing the products and knowing the customers.

Please go ahead and read it, and either comment there or come back here to let me know what you think.  I will also be publishing this series as an ebook later this month, and will collect all my writings on Knowledge Management to be published together at the end of the year as well (just letting you know, in case you missed some of them).

Thanks for reading.

A Social Knowledge Framework

Following up, and wrapping up actually, on the short series I have been publishing on social media as an interim (but essential) step towards collective knowledge I’d like to cover a draft version of the framework I see for social knowledge.

You hopefully have been keeping up, reading all about the evolution to social knowledge, the definition for social knowledge, and some of the other writings about knowledge management I have been publishing around the world (thanks to my sponsors for this topic: Coveo, Moxie Software, and Stone Cobra).

Now, publishing a framework in a blog post is not bound to be very effective – after all, you can build entire methodologies around frameworks (and you know that a methodology is not a short 2-pager or anything close to that).  However, I feel that discussing the high points of what is necessary for a KM solution to evolve into a social knowledge solution is very important.

I spend a lot of time talking to people (vendors, practitioners, consultants, influencers, and thought leaders, and more).  In these conversations these past few months a common element or issue has been showing up more and more: what to do about collective knowledge.  The quick rise in social networks and communities has brought a very big problem to organizations: there is a lot of value (potentially) in those channels – but we are not sure how to leverage that.

As I have been saying for a while, and most recently in previous posts in this series, this is an evolution – not a revolution.  You won’t be able to get value from using social channels and communities unless you prepare your systems to take advantage of that.  With that in mind, here are the top six things you have to remember as you embark on the road to social knowledge:

Subject Matter Experts.   The key to both social and collaborative knowledge is to have the right experts at hand.  The evolution of knowledge is to focus more in those subject matter experts, be able to identify them, have them accessible and use their knowledge to answer questions and update content.  The evolution towards social knowledge will need a solution that can “manage” these subject matter experts as the source of knowledge and maintenance of that knowledge.

Collaboration within Established Workflows.  Just because we are going to use people instead of static knowledge bases, which still won’t disappear, does not mean the need to generate and maintain entries into those bases goes away.  The established workflows for content generation and maintenance need to be upgraded to both reflect the use of different sources as well as more relaxed flows for dynamic, constantly shifting knowledge.

Aggregation.  Of course, once we have several sources for knowledge the issue of federated knowledge bases comes up very quickly – and while important, it is not as critical as being able to aggregate the real-time knowledge from communities and SME.  Definitely a framework to migrate forward in knowledge must include a way to aggregate all this knowledge: static and real-time, and the in-between use of SME.

Multi-Channel.  As much as I would hope this goes without saying, I am still getting calls and inquiries from customers that are not sure if they should use one source of knowledge for all channels (in their defense, they do think it is a good idea – they are just not sure of how to do it, or if their solution can do it).  This goes without saying now: single source of aggregated knowledge for all channels.

Three “R”s.  The concept of the three R’s (right answer, right channel, and right time) talks to timeliness and accuracy more than it does to being able to distribute over multiple channels (see point #4 above).  Under the assumption that we can distribute to all channels equally, the next consideration is making sure the right answer at the right time reaches the intended recipient – being able to deliver (leveraging real-time knowledge from SME) is a key feature of these evolved scenarios.

Evolutionary.  Proposing an evolution from current KM to social knowledge and eventually to collective knowledge means migrating existing solutions to the new models. This migration requires the new solutions to temporarily support the old models to ensure a graceful transition (especially when using federated knowledge bases with partners or non-traditional contributions to the knowledge base).

Can you see the framework taking place? Can you see what elements you need to adjust and change in your solution? How to evolve?

Did I miss something? Would love to hear what you have to say below.

What is Social Knowledge?

Expanding on the issue of social knowledge I started last time, thanks to my friends at Moxie and my sponsored research model, I want to take it one step further.

We explored last time what is the path to social knowledge and how today’s shifting paradigm of knowledge management makes it possible.  We talked about how the upsurge of user empowerment generated by the advent of social networks and online communities made social knowledge possible where similar endeavors failed before.

What we did not do is define social knowledge – or how to make it work.  I want to take the next two posts to do just that.  Will start with a definition this time and present a framework to embrace it in the next installment.

Here is a diagram that shows the progression to Social Knowledge, and how it begins to integrate communities.

timeline to social knowledge version 2

That last chart? That’s a play on my continuum model – but that is a very different topic and model; just know that social knowledge is a stepping stone towards implementing continuum in lieu of cycles (read more here if you want, but come back because we are just getting started).

Now that we have put social knowledge into the proper context as one part of the evolution towards collaborative knowledge, let’s define what we mean by social knowledge.  I wrote some time ago a pseudo-definition for social knowledge that read:

Tapping into communities and subject matter experts, social knowledge moves away from the traditional knowledge-in-storage model of accumulating “stuff” in knowledge-bases to getting the information directly from the knowledge owner that has it.

This knowledge is used, cataloged, indexed and used again – but only as long as it is the right answer – after that, new answers become “the right answer”.

Within these statements we have all the elements that make social knowledge work.

At the baseline social knowledge is the realization that knowledge bases don’t contain all the necessary information.; while in certain instances (e.g. financial services and regulated industries) it may be necessary to have an “official” version of knowledge, in the real world knowledge is augmented each and every moment during usage; this is one of the driving forces for online communities.

The more you use knowledge management as part of your customer service endeavor, the more knowledge changes.  The number of intricate combinations possible for use of any product of service by the large number of customers using them is astonishing. 

Even if there are “recommended” uses for the product, customers will always try new things and new combinations; as an example, I doubt very much that the inventors of duct tape thought it would be used one day to make clothes and other findings – yet, my daughters are living proof that is the only recognized use of duct tape (for them).  Everything they ever needed to learn from how to use the product to make what they wanted to make came courtesy of YouTube via non-official videos of other people making the same things.

Organizations began to realize some time ago that the source of the answer lies within those experts, called Subject Matter Experts or SME, and their use of the product or service.  This is marking the shift in knowledge from Knowledge-in-Storage (KiS) to Knowledge-in-Use (KiU) we are seeing, and the beginning of social knowledge.

One caveat, whereas users still remain the ultimate source of how the product should be used, this is not an excuse to dump all knowledge management efforts in the path to creating user-only knowledge solutions.  SME are a part of a total solution, not the only solution – there have been some organizations who have recently tried to outsource one-hundred percent of their knowledge management to communities with mixed results – at best.

However, the same model of communities and tapping into communities powered and populated by users can be used internally.  SME can live within the enterprise as well as outside, but without the right technologies is hard to impossible to find them in a timely manner to use their knowledge.

Social knowledge does not just happen via external communities, it must also occur with internal SME in internal communities and eventually ending up in hybrid communities (see the chart accompanying my last post for more of this evolution).  That is the next step, the evolutionary model of collective intelligence.

It would be simplistic to say that is the only definition for social knowledge, but since it is the first step in a multi-iterative paradigm shift we need to add some of the elements that are necessary to make it work.  Since a formula would have too many variables for any one organization to account for, I prefer to use a framework or template approach.

Alas, that is the next post on this series.

I want to know something from you though, are you seeing this shift in knowledge beginning to take place in your organizations? Are customers demanding more knowledge than you have access to?

The Story of Social Knowledge

I know I have been writing a lot about Knowledge Management lately, but this is a very exciting time and the paradigms are shifting as I have mentioned. 

The old model of creating and storing knowledge to eventually using it (maybe) is disappearing in favor of knowledge generated and maintained by users and communities. 

I covered a lot of this before within the sponsored research model I use and you can find all of the links from my blog – but when I was discussing one of the components I wrote about before with my friends at Moxie we discovered there was a missing step.

I talked about Collective Knowledge as the ultimate goal for this paradigm.  This is where communities populated by interested parties help each other by providing the necessary knowledge.  The main difference with today’s model of KM is that the communities essentially become the replacement for the knowledge-bases over time.

One of the things we discovered working through that model with Moxie was that we needed to cover the interim steps to get there.  This is what this post is about.  Telling the story of Knowledge becoming social knowledge and eventually collective knowledge.

There are four stages for the use of Knowledge in Customer Service:

  1. Disorganized.  During this stage, there is no knowledge management to speak of.  Either there is a collection of documents, or maybe a knowledge base exists – but it is incomplete, obsolete or never used. The “knowledge” generated and used at this stage comes from user’s minds – they know what they need to say to answer the most common questions and they may know who to ask for a one-time answer  as they find the need.  There are no documented processes or solutions to effectively manage generation and maintenance of knowledge – thus, each person becomes their own model of KM.
  2. Accessible. This is the first model used for KM in the customer service world (and still remains the most common model).  During this stage the organization creates structure out of the mess that the organization has.  Segments of users are known and the general idea of their knowledge needs is also known or discoverable.  Processes are in place for users and agents to create, access, and use similar-but-different versions of the answers (more complete for agents, a summary for customers) usually contained in a single knowledge repository
  3. Social. The interim step to collective knowledge.  This is the stage we are beginning to see implemented today leveraging communities, using tools for socializing online, and generally understanding the there is a mixed state between the ultra-advanced model of communities providing solutions and companies using single-repositories; that model is social, where users can easily access via social tools and technologies to contribute their knowledge to the organization – and in turn benefit from accessing the same community for their needs.
  4. Collective.  I won’t restate what I said about collective before, but the summary is that once an organization masters leveraging their own people and known subject matter experts to create internal “communities of practice” they find new ways to work and to leverage also their customers’ knowledge, their partners knowledge, and virtually any knowledge that exists in the world with the end purpose of generating more value for all stakeholders: employees, partners, customers and anyone else involved in making the organization successful.

This is a very condensed summary of this evolution and the beginning of the description of the interim step from Accessible to Collective Knowledge; we will explore a few more details about this in the next few weeks, please stay tuned!

In the interim, I’d love to hear your thoughts about this – have you found this interim step necessary? Are you working in deploying this? What are your thoughts in the overall shift in knowledge paradigms?

Please use the comment box below to expand this conversation and – well, grow our collective knowledge.