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Customer expectations continue to rise and grow. Today's customers don't let your company or organization "pass" because you're in B2B, financial services, healthcare, or manufacturing. The greatest companies in the world, regardless of category, are teaching your customers what is possible and what is standard.
Forrester says we've been five years into the "age of the customer": an era of rising customer expectations that will challenge almost any business. Specifically, their analysts say:
“The age of the customer will be harsh and unfamiliar requirements will be placed on institutions, requiring changes in the way they develop, market, sell and deliver products and services.” – @forrester Click to post a Tweet
To succeed in this environment, companies must seek every opportunity to understand customer expectations and continually overcome them, over and over again. The customer experience optimization cycle is also getting shorter and shorter. Remarkable customer experience in 2016 is today's betting table. And in order to keep growing in the face of growing customer expectations, your data and systems must also continually get better.
But data is both a blessing and a curse for today's CX professionals.
Oracle CX has produced a great report called 2018 Smarter CX Insights Report and found that 39% of CX professionals surveyed believe they lack proficiency and preparation for the new, data-rich era of customer experience management.
They know the data is important, but they aren't sure how to match the available data with ground-CX-improvement and enhancement. So what happens instead? They often sit around the boardroom and brainstorm ideas, relying on instincts and anecdotes to guide their initiatives. This MAY work but is not the best approach.
Big Data + Machine Learning = CX . Improvement Formula
But use big data to guide CX decisions as actionable. You just need to know where to look and how to read the numbers.
This has been proven especially true by my friend Christopher S. Penn and his company BrainTrust Insights in their recently published white paper “Turn Complaints into Insights.”
Researching the impact of complaints on your business makes a lot of sense, doesn't it? After all, if you're going to improve the CX, fixing whatever customers are complaining about is a good starting point. In fact, I've written an entire book on the science and importance of complaints, Hug your Haters .
In their study, Penn and Co. analyzed 51,260 customer complaints from a database of credit report customers to see what made consumers unhappy, which complaints were the most emotional, what actions the company took (if any) and what impact those actions have had on the company's bottom line.
They first classified complaints into one of five categories:
- Credit cards and related matters
- Mortgage and related matters
- Fraud and fraudulent transactions
- Data breach and identity compromised
- Bankruptcy and adverse financial events
They then used two machine learning libraries to assess the sentiment and emotional strength of each complaint, producing a matrix of the problem type and size of the problem.
The darker the colors in the table above, the more emotional the complaint is, indexed as anger, disgust, fear, or sadness. The data shows that anger is strongest when consumers complain about credit report investigations, followed by unexpected charges and trouble with fraud alerts. Disgust is highest around problems with closing a mortgage and overcharging fees.
And, there are a number of other issues—almost all of which have operational circumstances that can be changed/repaired—that often trigger emotional complaints from customers.
The team at Braintrust Insights then looked at the actual resolution of these complaints, sorted by issue type, sentiment (anger, disgust, etc.) and intensity (darkest color in the chart above).
Row three in the table shows the most emotional complaints very disproportionately when resolved with some form of monetary relief for the customer. This demonstrates the correlation between intensity and results at the business level and further emphasizes how important complaints are to the health of the company.
How you can use big data to improve your own CX
What do we learn in this example (and I encourage you to Download full report because there's a lot of gold in it) that when you're watching Customer complaints , you don't need to rely solely on claim volume or simple keyword analysis when categorizing and categorizing them. The emotional prism through which this data is screened is readily available.
Second, we know that complaints and emotional intensity are directly related to business results. The most unfortunate often have to be compensated with money, at least in this financial services example.
If you're looking to improve the specific customer experience in your company — and you should be — a great place to start investigating potential changes in particular is to discover what customers do. Yours has the most intense emotions.
Good CX professionals use their instincts and experience to find and fix. Great CX experts have enhanced that expertise with big data and machine learning, looking at the numbers to find bigger truths.
Many thanks to BrainTrust Insights for allowing me to peruse this wonderful report. They have more fun on the way!
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