Buried under the news this morning of their CEO’s decision to step down, another big announcement from the Twitter saw users now able to write direct messages with no character limit from July.
As other articles have alluded to, this seems to be the first step towards creating a competitor to things like Facebook Messenger, and I wouldn’t be surprised to see the functionality grow quickly.
What it signals more to me though is that Twitter seems to be putting an equal focus on themselves as an efficient customer service channel.
Customers Are the Real Winners
A few months ago, they removed the requirement for someone to be following you in order to send you a direct message, and this was certainly a big step forward.
One of the big bug bears of users was that while they may not necessarily want to follow what a brand has to say on channel, they want easy customer service. Connecting with the brand in a manner beyond that interaction ma have been a roadblock.
With the removal of character limits on DMs, the customer service experience becomes almost frictionless, at least as far as the platform goes.
I’m not saying that it’s been impossible or difficult in the past, but for those of us who have used the platform for customer service before, you will know how challenging the character limit has made it to convey issues in a speedy fashion.
We’re talking here about efficiency. Customers not only want their issues resolved accurately, but also quickly. By allowing more characters, it provides the opportunity to communicate a depth of detail quickly, and potentially deliver a solution in less time. The customer can move on and not labour over the issues they have.
There are still the issues of customer sensitive data, and any business with an effective social service policy will have a process in place for moving these conversations offline if required, but for resolution in channel, this is a big step forward.
For brands who maintain one channel for general content as well as support, it also means that they can begin to parse out the two functions into distinct areas and provide better experiences in both.