When it comes to social media, there’s a widely held belief that automation is wrong and that all engagement should be human and one-to-one.
When talking about automation, social media gurus and consultants will offer the following reasons why there may be something wrong with automation:
- Bots, which are fake, automated Twitter accounts, attract bots, giving accounts the aura of popularity while never reaching a real human being.
- The platform shift from conversation to broadcast is a symptom of what marketers measure. They measure actions, such as tweets, retweets and link clicks, which discourages dialogue because conversations aren’t valued on the action scale.
- As soon as you start thinking about people in terms of numbers and how many followers they have as a guide for interacting with them, there’s a good chance you’ve already lost them.
While these are valid points, they’ve also got business owners and marketers questioning the value of automation in the social space and wondering whether it’s destroying the fabric of social media’s early promise.
And while I can agree—to a point—that it can be bad when it’s implemented wrong, I’m also a supporter of automation and disagree that it’s “stealing social’s soul.”
The User Responsibility That Comes With Automation
The main reason for any form of automation is to make lives easier.
For consumers, simple solutions like coffee makers with auto settings, cruise control on cars and smartphone app updates make life easier.
For businesspeople, automated functions like email list cleaning, targeted updates based on online demographic use, and filtering of leads versus service issues versus queries allows us to scale more effectively instead of having to manually carry out these chores.
But as useful as these automated functions are to get through our days faster, there’s also the ever-present danger that automation can be abused or rendered ineffective for one simple reason: user responsibility.
For instance, while cruise control for a car can take the stress out of driving, it can also make you lazy when it comes to being aware of the road around you. And while targeted updates based on an audience time online can help laser focus your content strategy, it can backfire horrendously if a national tragedy strikes.
User responsibility is key for any part of our daily decision-making process, but that’s especially true when it comes to automated actions versus manual ones. Automation is hugely effective and beneficial but only if the user respects the flexibility that automation offers.
Combining Automation With Engagement
One of the main reasons that social media automation is seen as bad is the fear that it will cause social platforms to shift from being conversational tools to conduits for social proof measurement as a success metric.
And to a degree, there’s some truth behind those fears: The popularity of such tools as Klout and Triberr, where social reach and impressions are driving factors of success, merely strengthen that point of view.
Thankfully, these are the kind of soft metrics that businesses and smart marketers alike are beginning to separate themselves from.
[clickToTweet tweet=”Smart businesses use both automation and engagement to connect with their target audience.” quote=”Smart businesses use both automation and engagement to connect with their target audience.”]
So while social proof can be a metric of popularity, which itself can be viewed as a metric of authority, it’s increasingly being seen for what it is—usually fluffed-up numbers with very few actions behind them. But automation can help with identifying insights that inform marketers to be smarter and more effective.
For example, let’s say you want to AB test the acceptance of a new product on the market. You know who your target audience is, but you aren’t quite sure what will tip them from being potential customers to researchers of your product to actual customers.
So you use automation to find out:
- You craft a series of messages across different content providers—email, video, blog posts, social network updates—and program them to go out at the same time and then at different times.
- You use PURLs (personal URLs) to track actions on each message and each channel.
- Your filtering software cleans out the bounced emails, the non-shared content and your low-traffic blog posts.
- It then analyzes the content that worked, what times were best, where, and on who, and it essentially details what your strategy should be for the full launch.
But that’s just part of the story.
Using text analytics software, you can track all the pieces of conversation around each delivery method—how it made recipients feel, what the overall sentiment was, where a sale would have occurred had there been just the slightest change in information available, who sways your audience’s decision and more.
So instead of simply relying on the data—as strong as it is—from the automated AB testing, you’re combining these results with human intelligence to discover how we can identify the nuances of otherwise unimportant phrases, if left to technology.
And that’s where automation both benefits and is benefited by engagement through conversational insights.
While automated data and research leaves only the strongest lead opportunities, conversational insights can enhance that research by diving deeper into the context that could allow for other opportunities outside those identified by automation.
Now – is that really such a bad thing?