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A Different Approach to Customer Feedback: Gaining Insights from Chat Conversations 

Zareh Khachatoorian | Aug 8, 2017 689 views No Comments

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The moment of truth: I hear that term often in the world of customer experience. It describes when a customer makes a decision – to search for an item, to look for options, to speak to a representative, to fill their shopping basket or check out. But what if that moment of truth was the moment they decided to leave your site? Will you know why?

They say that the customers you should be worried about are not the ones who complain on social media or leave a negative survey, but the silent ones. The ones who leave out of frustration only to take their business elsewhere. No feedback.

So, then, how does a brand get a true picture of customer sentiment or find out what really needs to be improved in order to satisfy customers? Here are some insights I’ve learned throughout my journey for gathering and analyzing the Voice of the Customer data.

1. Starting Point

From the vast collections of unstructured data gathered from ever-expanding omni-channel solutions, a brand can end up with a byproduct of millions of conversations and chat logs, millions of touchpoints. So you have to start with a macro-view of the data — an unbiased point of seeing everything – and then mine and extract insights to tap into the feedback in a very customer-centric way.

It is common practice for a business to analyze customer feedback by starting with a taxonomy of questions or variables based on what the company thinks is important or relevant. That’s all well and good, but the outcome is going to be very narrow and skewed. They will be missing the big picture, and therefore may not see a particular set of customer insights that would be vital to the brand’s improvement and growth.



Or, if starting with only an A/B comparison, you stand the risk of not getting the whole story. For example, if comparing the performance of two different web pages on the site, you might be dealing with two different kinds of visitors, so of course you’re going to get different results-that don’t have anything to do with each other. Therefore, the conclusions that are drawn may be completely false.

2. To Survey or Not?

Surveys are helpful, but certainly not the end-all of customer feedback. They are given to customers after the fact – after the pain point has been addressed.

If you analyze the real-time, actual customer conversations, you will see the customer’s genuine feelings and see the heart of the matter. Two other drawbacks in analyzing surveys: they tend to come from a company’s biased questioning, so the real question at hand may not be addressed; and the customer takes the survey with an impression that their responses won’t be read, thus why spend much time on it?

With the understanding that surveys are inherently biased towards respondents who are willing to participate in surveys (i.e. self-selection bias), a brief analysis of a major telecom captures such disposition. Survey respondents with deeper levels of engagement, measured by the number of customer messages sent, were 233% more likely to participate in surveys vs. respondents with lower levels of engagement. The overall survey population was disproportionally representative of visitors with deeper chat engagements. Thus, data driven decisions were made alongside of alternate and more inclusive program metrics.

3. Critical Insights from Chat

Chat conversations arise out of pain points when customer self-service experiences don’t give them the assistance they need, so what transpires are a goldmine in terms of what you should do to prevent those pain points in the future. When the brand looks at the raw data that comes from the touchpoints of when the experience has failed, then you will truly see what needs to be improved. Without this knowledge, you’ll be missing the mark.

A major subscription-based retailer that sells pre-built bundles online, leveraged live chat to provide real-time, shopping assistance. Text clustering of such digital conversations revealed that a certain percentage of consumers expressed interest in acquiring a single product only. Based on this feedback, this major retailer created a particular purchase flow only accessible via live chat referral. This resulted in a 20% increase in single product units, leading to the creation of a new pre-built bundle to further drive measurable increases in subscription-based revenue

Additionally, a major telecom provider completed a website redesign to help continue to drive customer experience transformation. A notable increase was observed in the number of customers who inquired about the installation fee, post redesign. A usability analysis was conducted and revealed that the cost of the installation fee is now increasingly emphasized, using bold font. Based on this feedback, targeted optimization was performed, applying a different treatment to the display of the installation fee. This resulted in a 36% improvement in issue deflection and a 6% increase in customer satisfaction.

Learning from Moments of Truth

When customer feedback is viewed from the inside-out, the brand can learn from agent-side analytics to automatically train, tune, and optimize self-service channels, thereby creating moments of truth that lead to more conversions and increased customer satisfaction.

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