One Winged Butterflies Don't Fly
I am not advocating putting this to the test, but I’m pretty sure a one-winged butterfly cannot fly. Notice the symmetry too; both wings are identical mirror images.
What does this have to do with Voice of Customer and feedback management programs? Simple: most VoC programs have only one wing that really works: the collection and reporting of data. The other wing, which is understanding and taking action, is underdeveloped, sometimes missing entirely.
It’s missing because it was never purposefully and carefully designed from the start. That’s strange, because the core purpose of any feedback program is to drive actions that improve the customer experience and performance for the company.
I call the two wings of the feedback butterfly: learning and doing.
Just as wing patterns are unique to each species of butterfly, the learning-doing loops differ for each business type.
The five below are a simple example for a commercial company. You must look at the key capabilities your business needs to succeed to figure out which buckets matter most to you.
1) Individual customers.
The first learning-doing loop addresses the concerns of individual customers. Any low score or adverse comment should trigger an immediate and contextually appropriate response. Customers expect a response; it’s why they take the time to provide feedback. Not addressing their concerns or acknowledging their complements is rude, but more significantly, it is damaging to business. Their effort to provide feedback should be matched by your effort to reply.
Where contact details are known, as is the case with most B2B feedback, the reply should be highly personalized; referencing the interaction and the nature of the relationship. This is where a single view of the customer is essential, providing the data to construct a contextually rich reply. It’s where native feedback apps provide a real advantage where feedback data sits alongside transactional and relationship records, providing the rich context personalization demands. AI makes this easier to do at scale.
2) Accounts/segments.
For B2B suppliers, feedback and other signals from individual contacts can be aggregated to provide insights and drive actions that affect a customer as a whole. For example, comments that are repeated across multiple individuals in different parts of the business may signal an issue that is more serious than it looks.
Feedback about challenges several individuals are facing could be a significant upsell opportunity. This aggregation can be extended from individual accounts to cohorts of similar customers. Users that stretch your product are often early warning signs that other, less vocal customers are also facing. These signals can be used to proactively seek feedback using highly targeted, topic specific feedback that drive the appropriate actions.
For B2C, replace accounts with segments and sub-segments.
3) Process.
Customers know which of your processes are broken, problematic or cumbersome before you do – they have firsthand experience. One customer with an issue may be a glitch. When many customers describe the same issue, you have a problem; and one that may cost you business. Again, aggregated feedback uncovers issues.
When feedback is an inherent part of the same system that holds all other customer data, it’s much easier to see which types of customers are affected. And, more importantly, it’s much easier to notify affected customers, even if they weren’t among the respondents who raised the issue.
4) Product.
Product shortcomings are a major cause of customer dissatisfaction; whether that is a physical product badly made, software that does not deliver what it promised or a service that is difficult to access. Feedback can uncover product issues before it shows-up in sales figures. It can also generate ideas for how a product can be improved; a new feature, a simpler way of working or an improved workflow.
In many cases, feedback can be collected ‘in-product’, making it easier for the customer. A question can be tagged to a call-handler notes, an in-app, pop-up survey or an AI driven conversational survey included as part of a service call. And with CRM data providing context, feedback can be personalized, improving response quality and providing further context to trigger immediate action where needed.
5) Market.
Talking with customers is an established and proven strategy when launching new products. The same approach pays dividends for existing customers and markets. Feedback often hints at customer needs that are unmet or poorly met – opportunities to extend the value provided to customers with new products and services.
Building the link between feedback and action isn’t just about assigning owners for actions. It requires changing what’s collected, the learning wing, as well as purposeful design of what actions happen next, the doing wing.
Too many surveys are designed to collect data on what the company thinks is important. The experts build to test what matters most to customers. This leads them to craft highly personalized surveys with questions containing and filtered by context derived from rich CRM data. The best surveys are not driven by a methodology but by a deep customer focus. The goal is not to create a score a CEO can brag about in quarterly reports but to drive real improvements in the customer experience that convert to better financial performance through revenue growth, reduced costs and positive advocacy.
The doing wing needs to mirror the learning wing.
When it comes to the doing wing, many companies place that responsibility with a dedicated customer experience (CX) team. They review the data, report the numbers, decide on the priorities and craft the improvement plans. This can work but experience suggests a better approach: place responsibility with operational teams.
Separating the doing from those that are responsible for the work creates a tension. The CX team blames the operational team for not implementing their improvements. The operational teams blame CX for developing plans that don’t fit with their priorities or don’t reflect their capacity to implement.
Building this capability in operational teams requires three things:
1) Access to data.
Feedback has to be an integral part of the data source the team uses every day. Making teams use another system creates the friction of learning and managing another application and fragments the data. Fragmented data is a great hindrance. The lost context means survey content becomes generic, which drives generic actions that typically fail to fully address customers’ needs. It also massively reduces the impact of AI, which relies on rich context to deliver meaningful insights.
2) Skills.
Taking responsibility for the doing loop, operational staff need to be able to analyze data, build business cases, build improvement plans and manage small scale change. Lean Six Sigma toolkits were standard practice 20 years ago and are making a comeback with AI enabled variants.
3) Leadership.
A wise CEO once told me ‘organizations are shadows of their leaders’. Active involvement (sponsorship is not enough) from the CEO and other leaders sets the expectation that operational teams own the doing. Weak leaders track scores. Strong leaders shape actions.
If you have any interest in driving profitable growth, customer experience should be a lever you use. If you want to improve customer experiences, make sure you have a two-winged butterfly: learning wing and doing wing.
A program with two working wings still needs to know where to fly. Part 3 looks at why a single relationship score can never tell you that on its own and what an actual instrument panel for customer feedback looks like.
Rajesh is the visionary leader at the helm of SurveyVista. With a profound vision for the transformative potential of survey solutions, he founded the company in 2020. Rajesh's unwavering commitment to harnessing the power of data-driven insights has led to SurveyVista's rapid evolution as an industry leader.
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