Why Companies Need Technology for Crowdsourcing Their Social Media Response

Guest post by Ashley Verrill.

I read a report recently that found 47 percent of people have used Facebook, Twitter and other social media channels for customer service. And these people aren’t just airing grievances. They actually expect a response. This presents a huge challenge for mega brands that receive thousands of mentions on any given week.

I’ve reviewed myriad technologies that enable companies to effectively filter out and respond to many of these mentions on social media. They use keyword identifiers to extract relevant messages and route them to a support rep or community manager to respond. While this does make the process more efficient, it can’t scale to meet the demand for some companies (without having to hire an army of responders). And what’s more, I would argue it’s more valuable in the marketing and building word-of-mouth context for people other than companies to get involved in these conversations.

Consider what best-selling author and customer-service thought leader Micah Solomon told me during an event I hosted last year called “Is Customer Service the New Marketing:”

Customers are interested in marketing, but they don’t believe what your company says about itself unless it matches what they and their friends say about you.

For these reasons, I wrote an article recently for GigaOM about why I think companies need technology that essentially lets them crowdsource their response on social media. It enables them to better scale their engagements, and they can foster positive word-of-mouth by empowering real customers to talk about them.

How did I propose this technology work, and to whom would these social mentions be crowdsourced to? I suggested essentially that developers mimic tools from the customer community space – or discussion threads where customers already respond to each other’s questions. My hypothetical software would just move these conversations from the community to social media (or rather unite the two).

Customer community members are ideal candidates for responding for companies on social media for a few reasons. Here’s an excerpt from my GigaOM piece:

  • For one, they’re already enthusiastic about your products and so can be good brand ambassadors;
  • and two, they’ve proven their zeal for answering questions from other customers already.

This hypothetical technology could still leverage all of the tools that make communities so effective – things like gamification and automated alerts. Also, social listening tools could filter out messages that would be better suited for an employee response. This could include messages from customers that are particularly angry or questions that would require a technical expert.

This opportunity isn’t just about customer service. Every time someone mentions your brand on Pinterest, Linkedin, Facebook or another social channel, it creates an instant opportunity to start a conversation. The more a brand can foster these engagements the better – especially if you can ensure your top advocates are the ones leading these conversations.

So what do you think? Do you see companies every wanting to crowdsource their response in this way?

Ashley Verrill has spent the last six years reporting and writing business news and strategy features. Her work has been featured or cited in Inc., Forbes, Business Insider, GigaOM, CIO.com, Yahoo News, the Upstart Business Journal, the Austin Business Journal and the North Bay Business Journal, among others. She also produces original research-based reports and video content with industry experts and thought leaders.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s