Doing Closed Loop Customer Feedback Management Right

Thoughts on doing "Closed Loop" Feedback Right

Lots of "good news" is associated with "closed loop" customer feedback processes.   Loyalty, retention and better insights into customer behavior are high amongst them.  Yet closed loop processes turn out to be stubbornly difficult to implement. In the past I've talked about the 5 challenges enterprises face in trying to implement closed-loop feedback processes. 

1. Corporate hierarchies and information flows.
2. "Ownership" of the customer.
3. Out of context data.
4. Customer survey processes and platforms not designed for "loop closing". 
5. Managing the feedback itself.

All five challenges have to do with managing customer feedback.  Collection of feedback is, today, a given for most enterprises.  So, organizing the business to utilize feedback, designing processes that "close-the-loop" and selecting the tools and technologies to use for feedback management has become the real challenge. 

The new question:  What is the appropriate level of process for your enterprise to ensure the maximum advantage from customer feedback?

The answer:  It depends.  And, some of the dependencies are:

- Size of your customer base
- Value of a customer relationship (revenue, profit, reference ability, etc.)
- Dispersion of customers (Geographic, market vertical, etc.)
- Size of your enterprise
- Diversity of your enterprise (#business units, products, markets served, etc.)
- Dispersion of your enterprise (geographic, market vertical, etc.)

Generally speaking, the less complexity inherent in your customer base and enterprise, the less customer feedback management process you'll need.  As a consequence less resource will be needed for managing customer feedback, as well as for acquiring tools and technology.  The opposite is also true.  More complexity equates to more CFM investment.

How to organize for CFM?

• Define your KPIs, potential actions based on those KPIs, ownership of the actions and tracking of the effect on KPIs based on actions taken. 
• Segment customers based on revenue, geography, profitability, reference ability, and other descriptors you have in your databases
• Segment the people in your enterprise based on role and responsibility so you will know who potential "loop-closers" are.
• Determine who gets what customer feedback
• Design loop-closing actions (i.e. tasks based on specific feedback)
• Monitor your KPIs over time for change

For big, multi-business, multi-product, multi-location enterprises this process is very involved and often facilitated by management consulting firms like Bain, Accenture, IBM consulting and others.  It’s also a very big ticket item. 

For mid-size firms it can be much simpler, though still complex and consulting assistance may or may not be needed.

For smaller firms this process can be an in-house or a vendor assisted effort.

Some additional thoughts

Keep in mind that feedback collection processes may already exist and could be providing much of the data you need.  It may also be that existing data collection processes will need to be revisited.  Many data collection tools (survey monkey, zoomerang, key, and others) stop at data collection and don't really support implementation of loop-closing processes or management of feedback.  If you are using such products now and want more feedback management capability you may want to considering upgrading to more sophisticated CFM platforms.

CRM systems can play a valuable role in managing customer feedback.  But, they also present a set of challenges when combined with CFM tools.  Specifically integration.  And, often the CRM system itself will need redesign (new fields for feedback data, new processes for tasking).  The CRM system will likely need to be adapted to accept specific data streams from your feedback process and then kick off tasks for the people assigned to close the loop.  You should expect to use a fair amount of I/T support if you plan to use CFM in conjunction with CRM.

QuestBack and some other vendors - offer CFM systems that perform data collection, analysis, and action assignment / management capabilities.  These vendors offer a less complex and typically more cost effective approach to upgrading data collection processes to CFM processes.  They are especially valid for smaller firms with less complex customer profiles and organizations, less I/T capability, and smaller budgets.

A final thought

To be successful with CFM, like with any other business process, it's important to understand what you want to achieve within the context of who you are and your existing capabilities.  Selecting relevant KPIs is also important.  Much has already been written about CFM KPIs (see anything on Net Promoter), so I won't go into that here.  But, if you think through your customer feedback needs, your ability to manage using feedback and the capabilities of your CFM tools, you can overcome the challenges and begin closing the loop with your customers more often and to good effect on business growth. 

Contextual Insight - The Basis for Taking Action on Customer Feedback

Don't do statistical analysis based Customer Feedback Management. 

Every now and then someone produces a really insightful analysis that is both relevant to business managers  and captures the essence of your particular company's solution, in this case QuestBack.  Bruce Tempkin of Forrester Research - via his Blog, Customer Experience Matters, has done just that. 

In the post below, Bruce makes the point that contextually relevant customer feedback doesn't necessarily need to be proven statistically significant to be both highly valuable and immediately actionable.  In fact his point is that contextually relevant feedback, when delivered to precisely the right individual, is both very valuable for its insight and immediately actionable, without any statistics based analysis focused on key drivers.  It's a great read.  I encourage you to visit his blog for the whole article.

http://experiencematters.wordpress.com/2010/02/08/market-research-needs-less-statistical-analysis/


"Contextual Insight" - The Key to effective feedback management systems

Bruce Tempkin - The respected Forrester Research analyst coined this term in a February post on his blog - "Customer Experience Matters".   He defines it as:

Business Context + Relevant, timely data = Actionable insight

Some examples of contextual insight might be:

• An indicator on an information request form suggesting a short term need by a prospect, when delivered to a salesperson
• A "detractor" rating given by a client on a net promoter survey and delivered to an account manager
• An "unsatisfied" rating given by a visitor to a web-site, when viewed by the web master

Contextual insight is always feedback, filtered by some characteristic in the data giving it business context. It is always insightful to a specific role in your enterprise, if delivered in a timely fashion to that person.

Achieving Contextual Insight without in depth statistical analysis.

Customer insight has typically been the province of market research organizations. But, market research organizations aren't often equipped or structured to rapidly generate and deliver highly granular, context relevant, data to business end users. In fact their processes often mitigate against doing so.

But, Business still needs actionable, context relevant and timely insights about customers and prospects.

Feedback Management technology makes Contextual Insight actionable. It allows businesses to pre-determine who should receive specific of feedback and when. Techniques include automated role notification (alerts) and CRM based task assignment. Most feedback management applications include some analytics capabilities which enable rapid, though not automated, action taking on feedback. Most feedback management applications dovetail with more traditional market research tools. And, therefore can be viewed as complementary to the marketing research function.

Some applications (like QuestBack) include the ability to synch up survey based feedback with customer profile and actor profile information.  This allows really powerful alert processes to be fully automated once a survey process is in place.