The complexity of customer engagement
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In the last few years the amount of customer ”interfaces” or ”touchpoints” has increased significantly, thanks to social media and mobile applications. Back in the day you had your corporate website and that notorious, often empty, feedback mailbox at your store. And the feedback you got was complaints.
Today you need to have a Facebook page, Twitter account, LinkedIn company profile, top management must be in LinkedIn and customer service is using live chat tools, and you may need Pinterest, Instagram, Foursquare, Tumblr, YouTube, Vimeo, Flickr, or a number of other services to make sure you reach all your customers and give them a chance to engage with you, not to mention mobile-optimized responsive webpages and mobile applications. Your customers decide where they want to find and engage with you, not the other way around.
And yes, you need to listen to them as well. But then again understanding your clients is more important than ever before, even though it seems like many organisations are only focused on new customer acquisition, even if upsell is known to be so much more efficient and cheaper.
It’s a ball game that takes a lot of time and effort, not to talk about understanding who your clients are, where they hang out, what and who they talk to, etc. They do the complaining out in public, at Facebook, to their friends or anyone who wants to listen. They look for sympathy, comments, likes, support, a shoulder to cry on – something that most companies are not accustomed to offer. Many of us lack the resources to do so, fair and square. Nothing much you can do about it. And no, I’m not touching social media automation or outsourcing the work to media agencies here, nor am I touching the issues related to outsourcing the customer service or media monitoring.
I’m talking about engaging them in a way that is easy for you to monitor, and it’s private instead of shouting it all out at Facebook. I’m talking about controlled and automated customer feedback and marketing possibilities that makes both you and them happy, and even give you the opportunity to use your clients to carry your brand torch and get them to expand your reach to their friends and like-minded potential new customers.
A while back I was talking to a global bluechip who told me that for one of their products they have 25 million customers, and on average, they each send one customer support message per quartal. That’s 25 million support requests per quartal, a staggering 100 million messages per year that you’re supposed to read and react to! What makes it even more extraordinary is that these messages come from numerous different channels; text messages, email, in-device feedback functionality, call centers, social media messages (a number of channels), via partners, and from designated customer feedback surveys.
Guess what? All the information goes to the same database – it is saved there in various formats, by various types of people and automated processes, and in different languages even. This all makes the (big) data incomprehensible, and the best option for this company is to do data mining in the form of text searches. Searching for words related to certain topics, excluding words that relate to what is not being looked for. Sounds to me like they’re guessing rather than making smart decisions based on exact information, right?
Now, this is something I plan to help them with, to get the kind of data that is not just a massive database of random quotes, but structured data and actionable analysis on it. I sometimes feel like there’s all this useless data that we could just delete, and start the process all over by structuring the process when collecting it. In some cases even deleting the data and starting all over would be easier than trying to restructure and analyse the existing one.