The "Right" Degree of Automation - SmartData Collective

Social media monitoring and measurement is hard. Knowing what to do with the data, how to respond and how to engage is harder. Being able to scale your response and engagement is even harder. If you are Mom’N’Pop Ice Cream, and you have 300 inbound social media messages per week, you can probably handle them yourself (Quick note: I refer to any piece of social content as a message, whether it’s a tweet, blogpost, video or a discussion forum thread). Now imagine, you are Large Enterprise with 1-2 social media /community managers on staff… Now you can even handle 1,000 messages per week (not every message needs to be addressed, because not every message asks for an action). Now imagine that you start getting 5,000 messages a week. You can hire more social media and community managers. Now imagine you have 20,000+ messages per week, because your product is now sold all over the world, and these messages are coming in every minute of every day, and the volume is growing. What if you couldn’t hire any more people? And even if you could, should you? How do you scale? Or do you answer an ever-decreasing percentage of messages and queries? After all, especially if you are a …

How do you scale? Obviously, if you are a community manager or a social media person, you need to be working cross-functionally with other groups within your organization to provide a seamless experience to those customers reaching out to you via the social web. I blog about SocialCRM a bit, so I don’t need to belabor the importance of the right organizational processes any further in this post. Collaborating cross-functionally and with the customer is a great first step. However, especially if you are Large Enterprise with 20,000+ messages, you can’t manually assign each follow-up, even if the follow-ups themselves aren’t meant to be done by you, but rather spread out through the organization based on the content.

To solve the problem of social media scale, there needs to be a degree of automation. That’s exactly the business problem we are solving with Attensity360 (shameless plug, I know, but it’s actually relevant to what I talk about in the next two paragraphs :). We are in-taking the huge volume of social media content based on specified parameters via the former Biz360 (now Attensity360) platform: that’s listening. We help you understand the larger social media context in order to discover content that is relevant for you, in your business. We are building automation that extracts meaning from each piece of content and assigns it to someone in the organization based on specified business rules (this assumes that you will do the work and figure out your own internal information flow): that’s automated triage. Within this product, we are basing this unstructured data analysis and automated routing on an already existing robust backbone of Attensity technology, which has been delivering these solutions to enterprise clients for years, in their call centers and email services. Of course, there’s no machine intelligence like human intelligence, so we allow for manual tweaks and overrides. Data mining and semantic analysis of that data, for the purposes of automated routing: that’s the type of automation that helps an organization scale its social media engagement and response.

However, automation is a funny thing, mostly shunned by the social media community. Bots (unless it’s a Twitter account announcing breaking news) are an obvious social media faux-pas, and canned, automated responses elicit more rage than satisfaction amongst Twitter denizens. So how much automation is OK, and when is it OK? After all, as we established above, some automation is absolutely necessary, in order to scale. As we are designing the Attensity360 product, the question of automation is something we are actively thinking through. To answer that question, I think it’s important to distinguish between the types of automation you can have within the context of social media:

Process automation, similar to what we do with automated routing, helps flow information from point A to point B, based on a set of decision rules. This type of automation is not only OK, but necessary to use, if you plan to be efficient with a high volume of data.

Response automation, in my definition, is when you send automated and canned responses to customers asking you questions. This is a huge “no-no”, and if you plan to retain a shred of social media dignity, you should avoid it.

Somewhere in between process and response automation there exists another kind of automation. It’s a hybrid of sorts, let’s call it pre-response automation. What in the world is pre-response automation? Well, I did just make up the term, but bear with me – let’s see if we can make it catch on. Your system reads, understands and distributes social media messages in step 1. Then taking it a step further, it looks up a potential answer from either within your FAQ or an external user forum, and queues it up as a potential answer for the person who should be sending this message. This way, you as the company rep, get to send a message that’s automated and personalized at the same time. The thing you are automating is the research that would take you time to look up – time you would’ve spent on a menial task that could be spent on engaging and humanizing your responses. Imagine how many more customers you could talk to then! As long as you are putting human touches on all of your messages, using automation to help you write the straightforward response is A-OK. Of course this only works for fairly straightforward cases, nothing custom or complex. Then there’s no shortcut around research.

So what are your thoughts on automation? What have you seen that works? What level of automation do you find acceptable?

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