Two Intriguing Brands Embodied By People

I recently had a series of conversations about how the public perceives two brands that I  find intriguing: Bob’s Red Mill, a natural foods producer based in Oregon, and Hyperloop, a platform for rapid long distance transportation that is being implemented by a number of organizations all over the world. I took some notes—and created this post.

To me, the common thread between Bob’s Red Mill and Hyperloop is that they both let the people behind them represent them. It makes their value propositions credible in a way that clever writing and a huge creative budget can’t.

Bob and Elon.png
Bob (L) and Elon (R). (Photo credits: Bob’s Red Mill / NASA)

Here’s a look at the values, origin story, and iconography of each. Continue reading “Two Intriguing Brands Embodied By People”

How you benefit from customer comments you were pretty sure you didn’t want

Due to a misunderstanding, at the last minute before takeoff an airline refused to allow a pair of special-needs passengers to fly. This upset the passengers deeply and stranded them at an unfamiliar airport.

No one should have been surprised that intense criticism of the airline spread rapidly via social media, portraying them as bad-guys even though the incident was (arguably) a one-time mistake by an isolated group of employees.

This wound up being a good thing, because:

The airline discovered this issue, apologized to the would-be passengers and their families, refunded their money, offered them additional free flights, and came up with a new process to keep the problem from recurring. All-in-all, the airline—our hometown favorite here in Seattle, Alaska Airlines—took a regrettable mistake, and did everything possible (considering it was after the fact) to make it right with those affected. In this way Alaska Airlines also earned positive PR by showing they’re the kind of company that owns up to their mistakes and jumps on an opportunity to do the right thing when they can.

> Read more about the “special needs passengers stranded by Alaska Airlines” incident

> Another great PR turnaround story:  FedEx responds after delivery guy caught on video throwing computer equipment over a fence

This post isn’t about Alaska Airlines—it’s about the other guys

I’m pleased to see more and more stories about companies turning customer complaints into positive publicity. But this post is for the other guys, anyone who isn’t sure they have the right attitude, either individually or organizationally, to handle all customer criticism in a positive way.

Poster child for the other guys: Continue reading “How you benefit from customer comments you were pretty sure you didn’t want”

Making the Scene With SharePoint 2010 Enterprise Social Media Features

Social sharing - how is it different in the workplace?

I discovered an interesting video recently while helping a client demonstrate how users of a SharePoint document management system can share information about the documents they are managing. The video is by Michael Gannotti, a technology specialist at Microsoft, and it apparently shows how Microsoft uses SharePoint 2010’s social media features in-house. The video covers other SharePoint 2010 features as well, but I found 2 segments particularly relevant.

Social Media features in SharePoint (from timestamp 6 minutes 49 seconds to 15 minutes 50 seconds):

  • people search — users can find people who are experts on the subjects they’re researching;
  • publishing — via wikis, FAQS, and blogs;
  • user home pages — users can fill out their own profiles, add types of content, see their friend and group feeds;
  • viewing other users’ pages — users can find out more about co-workers and their work;
  • adding meta-information — tagging, liking, and adding notes or ratings to alert others about the relevance of content to oneself, to a project, or to a topic; and,
  • publishing (blogging) options — users can post to SharePoint either via a rich web-based text authoring environment or direct from a Word document.

Using One Note For Sharing (from timestamp 17 minutes 34 seconds to 18 minutes 34 seconds):

  • can create the equivalent of wikis and FAQs;
  • is web-editable;
  • may be better for printing; and
  • can also be used offline.

Here’s his video (hosted by Vimeo):

Other resources

Another useful resource concerning social media in SharePoint 2010 is this blog post by Microsoft Senior Technical Product Manager Dave Pae at TechEd earlier this month: http://community.bamboosolutions.com/blogs/sharepoint-2010/archive/2010/06/07/live-from-teched-overview-of-social-computing-in-sharepoint-2010.aspx. This also links to a post about social search which not only discusses the types of content (including meta-information) which can be searched, but also covers phonetic search capabilities: http://community.bamboosolutions.com/blogs/sharepoint-2010/archive/2010/06/07/live-from-teched-in-new-orleans-what-s-new-in-enterprise-search-in-sharepoint-2010.aspx.

Unwittingly funny GOP social media experiment failed by being generic

A recent US Republican Party social media experiment misfired not because of poor moderation, as some critics have assumed, but because site managers failed to recruit and motivate the right community. This post explores ways to create an open, uncensored forum that can more constructively represent both loyal followers and potential converts who were (presumably) the intended targets of the site.

Saying they want to “give the American people a megaphone to speak out,” last week GOP Congressional leaders announced a new web site, AmericaSpeakingOut.com, an open “town meeting” where everyone has an “[o]pportunity to change the way Congress works by proposing ideas for a new policy agenda.”

Despite an enthusiastic introduction by GOP leaders, wackiness ensued. Notable submissions on the site included unlikely suggestions, like: Continue reading “Unwittingly funny GOP social media experiment failed by being generic”

Cloud-seeding: SaaS data classification via Panda Security’s new anti-virus offering

Panda Security recently released (in beta form) what it claims is the first cloud-based anti-virus / anti-malware solution for Windows PCs. Not only does it sound like a clever tool for data loss prevention, but it demonstrates another way in which information service providers can aggregate individual user data to develop classifications or benchmarks valuable to every user, a mechanism I’ve explored in previous blog posts.

In essence, every computer using Panda’s Cloud Antivirus is networked together through Panda’s server to form a “collective intelligence” for malware detection and prevention. Here’s how it works: users download and install Panda’s software – it’s a small application known as an “agent” because the heavy lifting is done on Panda’s server. These agents send reports back to the Panda server containing information about new files (and, I presume, related computer activity which might indicate the presence of malware). When the server receives reports about previously unknown files which resemble, according to the logic of the classification engine, files already known to be malware, these new files are classified as threats without waiting for manual review by human security experts.

Security Camera
Sampling at the right time and place allows proactive decision making.

For example, imagine a new virus is released onto the net by its creators. People surfing the net, opening emails, and inserting digital media start downloading this new file, which can’t be identified as a virus by traditional anti-virus software because it hasn’t been placed in any virus definitions list yet. Computers on which the Panda agent has been installed begin sending reports about the new file back to the Panda server. After some number of reports about the file are received by Panda’s server, the server is able to determine that the new file should be treated as a virus. At this point all computers in the Panda customer network are preemptively warned about the virus, even though it has only just appeared.

According to Panda’s April 29, 2009 press release:

Utilizing Panda’s proprietary cloud computing technology called Collective Intelligence, Panda Cloud Antivirus harnesses the knowledge of Panda’s global community of millions of users to automatically identify and classify new malware strains in almost real-time. Each new file received by Collective Intelligence is automatically classified in under six minutes. Collective Intelligence servers automatically receive and classify over 50,000 new samples every day. In addition, Panda’s Collective Intelligence system correlates malware information data collected from each PC to continually improve protection for the community of users.

Because Panda’s solution is cloud-based and free to consumers, it will reside on a large number of different computers and networks worldwide. This is how Panda’s cloud solution is able to fill a dual role as both sampling and classification engine for virus activity. On the one hand Panda serves as manager of a communal knowledge pool that benefits all consumers participating in the free service. On the other hand, Panda can sell the malware detection knowledge it gains to corporate customers – wherein lies the revenue model that pays for the free service.

I have friends working in two unrelated startups, one concerning business financial data and the other Enterprise application deployment ROI, that both work along similar lines (although neither are free to consumers). Both startups offer a combination of analytics for each customer’s data plus access to benchmarks established by anonymously aggregating data across customers.

Panda’s cloud analytics, aggregation and classification mechanism is also analogous to the non-boolean document categorization software for eDiscovery discussed in previous posts in this blog, whereby unreviewed documents can be automatically (and thus inexpensively) classified for responsiveness and privilege:

Deeper, even more powerful extensions of this principle are also possible. I anticipate that we will soon see software which will automatically classify all of an organization’s documents as they are created or received, including documents residing on employees laptop and mobile devices. Using Panda-like classification logic, new documents will be classified accurately whether or not they are of an exact match with anything previously known to the classification system. This will substantially improve implementation speed and accuracy for search, access control and collaboration, document deletion and preservation, end point protection, storage tiering, and all other IT, legal and business information management policies.