By Ian Jacobs, senior analyst, Datamonitor

[EDITORS' NOTE: This is part of a series of posts that began here, dissecting a two-page chart that appeared in CRM magazine's June 2009 issue on social media. The digital edition of that issue can be found here, and a standalone image of the chart itself can be seen here. (Click on the “View Full Size” button at the top right of that page.) To view all posts in the series, please add this RSS feed to your RSS reader.]

JUNE 7, 2009 — Like all who have bravely gone before me in this experiment, I feel I must thank Josh Weinberger, CRM magazine, and destinationCRM — not just for giving me the opportunity to blather on and on (and on), but also for being foolhardy enough to tackle a project as ambitious as a Social Media Maturity Model.

Virtual hats off to you guys. Let no one say you lack chutzpah!

The ambitious nature of the model itself makes dissecting it a daunting prospect. As Christopher Carfi alluded to in his June 3rd post, any one of the throughlines in this model could form the basis of 30 days of meaningful discussion.

(Oh, and Chris — Thanks for setting the bar so high for the rest of us poor schlubs. A video? With onscreen highlighting? Come on — have pity on us poor, technologically deprived analysts!)

Since I only get one day for my soapbox, I’m going to try to tackle a reasonably small segment of the model: some of the ways that customer service might change that are not explicitly detailed in the model.

I have two main areas to expand on:

1. social media–focused service as a driver of improved product development; and
2. community-assisted service or user-collaborative service.

Service-driven product development: As an analyst covering the contact center and CRM space for many years, I’ve always pointed out that companies large and small are missing a tremendous opportunity for continuous improvement in product development by not using all the data they gather in their customer service operations. In the same way that Google is arguably a more-effective tool for predicting flu outbreaks than traditional epidemiology, contact centers can be an excellent predictor for identifying aspects of a product that demand improvement.

Note that I am not talking about user-driven design of products—others have put forth that idea [see detail from the Social Media Maturity Model, left, which makes a reference to the product design aspect in the top-left "Sales" quadrant], and while I have many issues with that concept, it’s simply a different beast than what I’m talking about here.

I’m referring to the untapped motherlode: If companies mined the data that they were sitting on in all those megabytes of recorded customer calls, they would have a much clearer idea of what problems were costing them precious dollars in customer service. They could focus future development efforts on fixing those issues and reduce the volume of costly customer support contacts.

I understand the structural limitations that get in the way of companies doing this type of proactive product development today. Contact centers ‘own’ their data. But even if the contact center identifies a product problem (or a pricing problem, for that matter, or even a Web-site-design problem), there’s little the contact center can do about it. Not only does the contact center not “own” those areas of the business — but without some involvement, vision, and direction from higher up the corporate ladder, the center doesn’t even have much influence in those areas.

Social media, however, can change this equation.

By making silos and their attendant structural hurdles visible to customers, social media can provide a great impetus for companies to tackle those flaws. Think about a Facebook-like customer-support site: If 500 customers have similar problems with a product and post to the support site, the last 400 to arrive will see that their issue is inherent to that product. The visibility of the problem intensifies the urgency for a solution. If that sounds like product development and product improvement driven by a desire to avoid corporate embarrassment — well, it is. Embarrassment can be a powerful motivator; just ask the collections industry.

User-collaborative service: Frankly, I was really quite surprised to not see something in the Social Media Maturity Model’s service category on community or peer-to-peer service. [See detail of the chart, right, for a closeup view of that quadrant.] While my first point in this blogpost — service-driven product development — may belong in the farther reaches of the model’s time scale, user-collaborative service is already happening.

In a formalized, online social network sense, there are sites such as Get Satisfaction, a site that calls its function “people-powered customer service.” The site itself acts as a neutral space — i.e., not a company-sponsored or -controlled site — in which regular customers can exchange ideas, and get help with or tips about product- or service-related issues.

The Get Satisfaction site allows companies to participate on essentially an equal footing with customers, and knowledgeable customers are as likely (and often more likely) to be the ones providing support to other customers. Some very large companies, including Adobe, use the site to help their customers and to help arm their expert customers to help each other. And hundreds of other companies should probably be paying attention to this social media–driven support concept since their products are being serviced via this medium. [Editor's Note: Get Satisfaction was one of CRM magazine's 2009 Rising Stars. See our coverage here.]

But a specialty support site is not a requirement for this more-collaborative approach to customer service. It is happening on Twitter, as well. Caltrain is the commuter train that runs from San Francisco to San Jose, right through the heart of Silicon Valley. Thousands of people use the train to commute to and from their jobs every day. Service delays, trip cancellations — even the status of the scarce space on the train cars that accommodate bicycles — all command great interest from Caltrain’s riders.

Caltrain’s Web site provides a published schedule, but it’s a fairly static page and has no facility to provide real-time travel alerts or advisories. Even if Caltrain’s site did provide real-time notices, there was no mechanism to have those notices sent to riders.

The @caltrain Twitter feed came to the rescue. The @caltrain account on Twitter identifies itself as “community-supported Caltrain notices, one tweet at a time.” Interested Caltrain riders receive an email key that allows them to email tweets that then get posted to the @caltrain account. As I type this blogpost, there are some train delays and the tweets are flying, giving the 1,500 or so followers of the feed real-time updates on what is going on with their commute. Users helping other users, creating some social form of community support.

That is the user-collaboration element. But this is not simply a case of the lunatics taking over the asylum. Caltrain officials themselves use the @caltrain feed to provide information — they preface their tweets with an upper-case “O” to identify themselves. There’s a very good reason for the company to get involved in this effort: The social media–driven communications are often faster than the mechanisms of corporate communications will allow.

An example: In early June, a train hit and killed someone in California. This caused massive and widespread delays throughout the system. The Twitter feed not only kept passengers informed of the delays, but of the actual cause. And it did so much more effectively than Caltrain’s own communication system.

I saved a tweet from that day:

@caltrain: Power of twitter: passengers on my train knew details of delays before our conductors did

Admittedly, user-to-user support for public transit is not quite in the same league of complexity as user-to-user support in the realms of home networking or automotive repair. But the underlying concept can work across all sorts of verticals, especially if the companies get involved on the users’ terms as Caltrain did by joining in the user-generated efforts of the @caltrain feed.

In fact, that’s really the key of what I see missing from the model: Users will collaborate with each other to help solve issues and companies will need to get involved on the community’s terms, not their own. It’s a major shift in mindset, and one that may cause some wrenching growing pains, but it’s coming.

Bonus Topic (or, “Continuing the Torture”): I know I promised just two issues, but I have another idea — minor, and not as well-formed — that I’d also like to throw out to the four winds.

The model actually has a slot for preventative service, but it seems to be the result of direct engagement with and continual feedback from customers. That does seem to be one of the logical conclusions from the trends that are pushing service out of the realm of formal customer service organizations (i.e., contact centers) and into a more social domain. But the model also seems to imply that these changes are taking place exclusively because of the flourishing social media — and that may be overstating the case.

These changes are not happening in a vacuum. Being a bit o’ geekiness myself, I would argue that pervasive computing and ubiquitous computing can and will also have a role in the transition to preventative service. When some manufactured object can tell the company it needs servicing/upgrading/fixing, the company can push that service proactively, either through computer-to-device communications or through proactive contact between the company and the customer. This happens now in some enterprise technology departments, at least in the machine-to-machine realm (although those systems aim for self-healing), so why should consumer-focused goods be any different?

Obviously, pervasive computing will also not drive preventative service on its own. There’s some undefined field of overlap between socially mediated customer service and support and technologically automated service and support. Just something to watch for on the edge of the five-year time frame spelled out by the model.

Finally, while my mother never literally told me, “If you can’t say something nice, don’t say anything,” that cultural message sank into my brain somewhere along the line. So I want to be clear that I am not just about pointing out ideas missing from the model. I also want to heap some praise on the model: CRM magazine has done a stellar job of putting a stake in the ground and allowing this conversation to unfold.

Bravo, folks.

Ian Jacobs (ijacobs@datamonitor.com) is a senior analyst at Datamonitor and an ASBPE-award-winning columnist for CRM magazine. He can be found on Twitter at @iangjacobs. For more on his perspective on social technologies in the enterprise, see his Customer Centricity column from CRM magazine’s June 2009 Social Media Special Issue.]