Customer feedback is a means to an end – through closing the loop you’re able to turn it into improvements for your customers. There are two ways to close the loop – individually with customers (inner loop) and then at an organisational level through process improvements that impact a group of customers (outer loop).
INNER LOOP – FOLLOWING UP WITH CUSTOMERS
Explain to customers why you want their feedback – i.e. to improve your service to them
Collect feedback at specific touchpoints in the journey as well as at a relationship level
Define rules around what will trigger alerts including setting rules around prioritisation such as account/customer value
Define the closed loop process internally including the systems and teams responsible for taking action
Enable your teams with training, escalation processes, toolkits and resources to resolve or mitigate issues for the customer.
Deploy a ticketing or workflow system to manage and report on progress, number of open tickets, length tickets are open etc.
OUTER LOOP – ORGANISATIONAL CHANGES
Use key driver analysis to understand the most important issues to customers and how you’re currently performing
Prioritise your areas of improvement, taking into account:
Volume of customers impacted
Value of customers impacted
Manage your project with standard project and program management methodology to ensure the initiatives are delivered
Measure the the customer, operational and commercial impact once the initiative has been delivered
Demonstrating strategic value
The most successful CX programs have buy-in from across the organisation and they’re able to demonstrate how they impact the organisations key operational metrics. If you’re can demonstrate a direct link between your actions and financial performance, you’ll be able to better inform investment decisions to further improve the customer experience.
Always identify as many potential external sources of data that may be linked to the survey data as possible
Work to develop the link between experience data and operational data within your organisation, this can vary widely even within industries
Use business data to assess survey data for bias.
A strong bias indicator is present if (a) the distribution of the auxiliary data differ between respondents and nonrespondents, and if (b) those variables are correlated with the experience data. To test the latter some linkage between auxiliary variables and experience data is necessary, though not for all cases, which could help with privacy concerns.
Consider including paradata metrics to assess things like survey health