Customer Support Re-imagined: Feelings, Emotions and Experiences

Take a dip in the pool of Customer Support with me.

Let’s say you currently work in product marketing or operations for a global corporation. Your work revolves around meetings and schedules — things don't always go your way but your life is fairly predictable — and scheduled. You have lots of time for analysis, planning and testing.

Now, picture yourself in a new role. Take that schedule and throw it at Mars.  Your life is now a non-stop, 24-hour ride; your schedule slows down and speeds up, you have less control over it and it never stops for a break. You're trying to do analysis, but the data is non-stop and you can't stop the test to analyze results. You work in a world based on others’ schedules, needs and emotions.

Welcome to the world of customer support.

In your new role, your goal is to be proactive. But human behavior is unpredictable and forces customer support into a world of reactive tendencies.

Your tickets, social media, customer reviews, and support calls are all data - and you are surrounded by it.  But it's all open ended and undefined. It's thousands and often millions of customer support contacts. It's in data lakes, and buried deep in the history of your company. The leaders at your org care about your customers, but once they take a dip in the data lake, they lose momentum and your long-sought project to do deep analysis dies unripened on the vine.

You have customer satisfaction and NPS scores which you put in the sentiment bucket to gauge how customers feel about your product. Those have helped triage things a bit. You may also have customer success metrics which tell you how often customers do certain things, their habits, their stickiness and their level of adoption and success with your product. That’s definitely a step in the right direction. You may even have a good way of tracking customer testimonials and advocacy.

But if your customer insights are based on an observer asking pre-determined questions and watching for overt pre-defined customer actions -  you're likely entirely missing out on the open-ended emotional component of your customer's feedback. How a customer truly feels about your product is vital to your product's success.  How a customer expresses themselves is the key to their emotions. This can all change on a whim - thus making it impossibly challenging to keep up using predetermined rules.

Customer support professionals want to help customers based on their needs, and their timing, not ours.  We truly do care for our customers and know that customer service is a living, breathing, ever growing, organic entity. We can’t ask customers to slow down, take a break or let us catch up. In this dynamic environment, how can we make informed decisions to provide the world's best service?

What if you had a genie that could grant you three wishes?

What are the three most compelling issues that you would like to know about your customer base if you could analyze and immediately understand every thought and expression that your entire customer base expressed? What three burning questions do you have about your base that would help you to plan your time better, be proactive and make you look like a hero?

My top 3 would be:

• Gaps in service

• Empirical data to drive the product roadmap

• Trending issues that could forecast future problems

Or, would you simply wish for a system-wide comprehensive health check?

What would you unlock in your customer data (that you likely suspect is there) but need the quantitative analysis to prove it out?

What if you could take all of your customer feedback (both internal support requests and external customer reviews) and give it to a genie to tell you what to do next? What if you could augment your customer journey mapping and health scores to measure happiness across all customer interactions in a scientific way instead of relying on genies for your next bonus.

What if you could read every single ticket, chat, text message, phone transcript and ecommerce reviews over the entire lifetime of your (or even of your competitors’) products? And then turn ALL customer interactions into a new and ongoing form of NPS - one based on reliable, quantifiable, and scalable scientific scoring that analyzes the entire audience in near real-time.

How much of your year is spent on thinking and saying how you care about your customers and want to hear from them - but secretly knowing you’re likely ignoring 90% of what they’re saying because you don’t have a genie or the manpower to analyze and track all of this information?

What if you could listen to each and every one of your customers, take in what they have to say, create a meaningful response and impact the product roadmap all at once? What would you like to discover and quantify from customer feedback that absolutely proves the case for your next big thing?

I’m super curious to hear what you would do! Email me at kate@stitchedinsights to share your story and I’d love to include it in an upcoming article on this subject.

About Kate Hobbie:

In Kate's role as a Customer support leader, she has been committed to making customer support the heart of an organization to ensure that the quality of service a customer receives is the deciding factor when choosing a brand.

Your Customer is Trying to Tell You Something, But You Need to Read Between the Lines

We live in an era of customer-centricity.  No one knows this better than customer support professionals. Even before customer service was the new marketing, support professionals had been saying for years that customer support was your secret weapon to uncovering product insight and innovation.

While the business world is shifting emphasis to the insights that can be gained from a deeper understanding of the customer feedback that lives in the service center, the resources haven’t always followed. This is primarily due to the fact that there are three main challenges in support:

1. Volume of data - the thousands and hundreds of thousands of support requests that are generated

2. Manual processes - typically a lack of integration of support tools leads to manual processes

3. Siloed departments and individuals - the lack of integration can lead to lack of communication between both departments and from one support individual to another

Support always seems to be playing catch up and due to the real-time requirements of supporting customers, companies don’t get the opportunity to shut down support in order to catch their breath. If ever there was a use case for machine learning, analyzing the avalanche of data that comes forth directly from customers, this is it.

Equally important is the fact that internal feedback such as support requests and external data such as product reviews are rich with emotion. Yet support teams rarely track this most human form of feedback. We tag top issues or note the level of severity but nuanced emotion goes completely unnoticed by support teams other than to note occasionally that a customer was angry.

Big Data is a game changer for customer support

Not only can we finally catch up (whew!) simply tracking not just the top 10 but the top 100 or the top 1000 issues in support, but we can also finally do a true evaluation of what is most important to our customer base.

Breakthroughs in natural language processing now allow us to bring data science and computational psychology together to expose the nuance in what the customer is telling us. Customers have much stronger feelings about certain parts of their experience than other parts. Their feedback likewise gives us insight into which parts they actually care more about. With these breakthroughs, we now have the opportunity to uncover emotional insights behind the words that a customer uses to explain their problem, or ask their question or request a refund.

Extract quantitative insights from qualitative data

We all know that it’s not only what you say but how you say it. Computational psychology goes far further than simply noting sentiment (sad, happy, mad). Breakthroughs in NLP now allow computational psychologists to identify implied feedback and truly prioritize and identify customer emotions. No longer will the customer who shouts on the phone or types in all caps be given all the attention. We also care about the customer who whispers, for these customers may have far more important things to tell us.

For more information about gaining deeper customer insights, read our Whitepaper.

[Blog by Kate Hobbie]