“Captain! We’ve got a whirlpool on our side!” comes a cry from behind you.
“Captain! There’s a giant monster on our side!” comes a shout from another.
If this situation sounds familiar to you, you’re either the captain of a ship in ancient Greece or the owner of a small to midsize business listening to customer feedback. Either way, you’ve thought to yourself, “They can’t both be right.”
But can they be?
And if they are—if these conflicting reports carry equal weight—what do you do? Are you just moving out of the frying pan and into the fire?
I know I’m mixing my metaphors, so let’s leave Scylla and Charybdis and take a step back to focus on what we’re actually talking about here: conflicting reviews data.
Who do you listen to when you get conflicting reviews?
Just because two reviews are contrary to each other doesn’t mean one’s right and the other’s wrong.
If we look at the Grecian example from earlier, both sailors were describing an accurate situation: Their descriptions just differed based on their own experience/vantage point.
Much like our ship captain, rather than picking a right or wrong side you have to accept that your customers experience multiple truths.
When you’re listening to customer feedback and one customer conflicts with another, however, it’s difficult to act on the information they’re providing and even harder to use that info as leverage for client nurturing.
To avoid alienating your customers, you have to better understand the root causes behind their varying customer experiences.
By digging deeper to understand the “note behind the note” while listening to customer feedback, not only will you be better equipped to differentiate between the symptom and the actual problem, but you’ll also deepen your relationship with that client.
4 steps to charting the reasons behind different customer experiences
Step 1: Find the key differences in the reviews
Take a look at the two situations below:
|Scenario 1||Scenario 2|
|Customer A||The product was very intuitive.||The product was too complicated to use well.|
|Customer B||It was hard to use the product.||The product was too simple and didn’t have enough functions.|
In both scenarios, there’s a key disagreement.
You might be inclined to believe that one scenario is preferable (after all, Scenario 1 includes a positive review of your product), but in both situations you have an adjustment to make (and, as we’ve stated, all customer feedback can be right).
Step 2: Look at who is doing the reviewing
If you missed it when it first came out, stop for a second and read this article on the importance of collecting reviews data.
Are you back? Good.
Now you know the importance of collecting demographic data while you’re listening to customer feedback, which will help in this stage of understanding the differences between your two customers.
So, how do you go about breaking down this data? One option is to use artificial intelligence (AI) software to organize and analyze the customer data at your disposal.
In fact, 42% of respondents from a 2018 Gartner Digital Markets survey (full survey results available to Gartner clients) stated that they currently use AI for customer segmentation, while 45% use it for customer review analytics.
AI isn’t the only option—you can use CRM software or go through the data manually—but it is the easiest solution.
Once you’ve collected the data, it’s time to do a bit of soul searching. Ask yourself who is your ideal buyer? Then ask which of the customers you’re hearing from is a closer fit to that target persona.
Step 3: Determine if it’s a trend or a single instance
Go through each piece of information you’ve received while listening to customer feedback, regardless of scenario.
Now, count how many customers have provided similar feedback.
If only one customer says something, it’s still valid. If 100 people say the opposite, that doesn’t mean that the single customer with the original feedback didn’t have a legitimate experience.
Instead, think of it as a way of figuring out how to approach the problem at hand.
Let’s say 99 people enjoy a certain facet of your product, but one person says they don’t. Addressing that issue requires a drastically different problem solving approach than if 50 people enjoy that same facet but 50 people don’t.
Step 4: Keep the conversation going with your customers
You should be following up with your customers when they leave reviews, whether they’re positive or negative.
Doing so will help you better understand the reasoning they have for both the issues they’re talking about and how they expect them to be resolved.
So when is the best time to talk to them? According to a recent Gartner study, about two to three months after they leave the review.
This far out, the customer doesn’t remember granular details that can inhibit a deeper understanding of their experience. Instead, the customer remembers salient points and can more accurately speak to their emotional and logistical journey.
That higher-level conversation—and it should be a conversation rather than, say, a survey—will help you understand the note behind the note and provide a broader understanding of why they left a particular piece of feedback.
Plotting your course after listening to customer feedback
Now that you’ve got all this knowledge, what are you going to do with it?
All of the information you’ve gathered will be crucial in helping you figure out how to move forward with any necessary adjustments.
Your first step is to determine whether the feedback was part of a trend or simply an infrequent occurrence.
- If it was a trend, be prepared to make some broader changes.
- If it was the result of a single situation or an infrequent occurrence, you’ll need to focus on individual experiences.
Regardless of what direction you go, you should alter something.
For the latter, you should focus on addressing those individual concerns, whether they are about the onboarding process or usability. This would be a great time to employ your customer advocacy program to address these touch points.
However, if it’s a trend, the process becomes a bit trickier.
Let’s go back to our scenarios from earlier. Looking at each of these will help you develop an understanding of the broader methodology necessary to navigate these conflicting reports:
|If Customer A is closer to your ideal, congratulations! You seem to understand your target demographic. However, you still need to take a look at the challenges Customer B expressed.
If Customer B is closer to your ideal, try to figure out what Customer A understood or was able to intuit that your ideal customer couldn’t.
What was Customer A using your product for—was it in any way different than Customer B? What qualities does Customer A display that Customer B doesn’t?
The conversations that you’ve had while listening to customer feedback will help answer these questions and give you a much deeper understanding of their experiences with your product and company. Perhaps the issue is that Customer B had a poor onboarding experience and requires a slower, more granular demonstration.
|If Customer A—who believes your product is too complicated—is your ideal customer, then perhaps you need to sit back and think about what your ideal customer is actually using your software for.
You might have built an overly robust product. The specialized tools could be too specific for a universal use and a scaled model that eliminates non-essential features could help.
Alternatively, it could be an issue with the user interface (UI) preventing them from navigating the product, so making the user experience more streamlined could be the correct course of action.
In this case, engaging with your customers as a whole will give you a better sense of next steps.
If Customer B is your ideal customer, then you need to ask yourself similar questions. What purpose do you think your product serves? Does it match with your customer’s expectations?
Perhaps you’re not hitting enough of your customer’s pain points. Alternatively you might offer the features they don’t think exist on your product, but your UI makes it harder to find. Again, keeping that conversation going will prove crucial in formulating a strategy for customer retention and success.
What to sail away with
All feedback is a sign. Whether it’s a veritable Grecian chorus telling you they’ve noticed a trend or a single Tiresias warning you about an oncoming storm, the voice of the customer should be your guide.
By directly engaging with them, you’ll learn exactly how important it is to listen and understand who they are and where they’re coming from and what course corrections you need to make as a result.
Results presented are based on a Gartner study conducted to understand adoption and investment plans of AI in digital commerce. This study also sought to understand the value and success of AI in digital commerce and its challenges. The primary research was conducted online from June 4 to July 17, 2018, among 307 respondents in North America, Latin America, Western Europe, and Asia-Pacific.
Qualifying organizations span various industries excluding Healthcare. Companies were required to have primary technology approach for digital commerce as ‘Custom built commerce platform’ or ‘Packaged commerce software solution’ with some (>$0 USD) revenue generated from digital channels in fiscal year 2017. Companies were also required to be currently using or piloting AI in its digital commerce. The sample represents organizations in US/Canada (n=86), Brazil (n=35), France (n=30), Germany (n=31), UK (n=30), Australia/New Zealand (n=30), India (n=33) and China (n=32).
All respondents were screened for involvement in strategic decisions for digital commerce within their organization.
Quotas were applied for countries, industries and enterprise-wide revenue from digital channels for fiscal year 2017.
Artificial Intelligence: AI is a combination of advanced technologies that change behaviors without being explicitly programmed, based on data collected, usage analysis and other observations. Machine learning is a key technology category driving AI and includes techniques such as linear regression, decision tree, Bayesian networks, and deep neural networks.
The study was developed collaboratively by Gartner Analysts and the Primary Research Team who follow Commerce Technologies & Experiences.
Disclaimer: Results do not represent “global” findings or the market as a whole but reflect the sentiment of the respondents and companies surveyed.
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