I subscribe to Bruce Temkin's Customer Experience Matters blog. Its a good resource for folks who are "doing" customer experience. In a recent a post and report titled: "Use Customer Insight To Close Four Loops" Temkin made the argument that there are four distinct feedback loops that organizations need to evaluate and act on. As a proponent of Closed-Loop feedback management I am very much in agreement with Temkin's four feedback loops and approaches for "Closing" those loops. The Temkin article can be read here. He uses restaurant chain feedback as an example. Text Analysis can contribute to implementing loop-closing processes for each of Temkin's four loops. The four feedback loops include:
- Immediate Response
- Corrective Action
- Continuous Improvement
- Strategic Change
- Immediate Response. Temkin - Rreach out to a restaurant customer who responded on a survey that "the bathroom was dirty" and help take care of her ongoing concerns.
How Text Analysis can help.
- In the immediate response scenario, feedback from customers of this type is typically delivered directly to the store manager, who then responses to the person providing the feedback or acts on solving the problem. Text Analytics only provides limited help in this instance documenting the issues a customer or customers are having.
- Corrective Action. Temkin -Get the manager or employee to clean the bathroom in that restaurant.
How Text Analysis can help.
- Though immediate corrective actions are likely being spawned by the immediate response process handled by store managers, taking broader corrective actions that prevent issues from re-occurring is something Text Analytics is very good at helping with. For instance, if dirty bathroom is a regular occurrence at a particular restaurant or group of restaurants then there may be a training, process or staffing issue that higher level management needs to address. Text Analysis can also help understand what "dirty" actually means. i.e. is it full trash cans, dirty floors, dirty stalls, etc.. Text Analysis can often pinpoint what the most severe issue actually is, making it a lot easier for senior management to provide specific guidance to store managers on corrective actions to take.
- Continuous Improvement. Temkin - Create new process for restaurants to check and clean bathrooms on a regular basis.
How Text Analysis can help.
- Similar to corrective actions, Text Analysis can help a lot with continuous improvement efforts, by continuously monitoring and reporting changes in topic sentiment about various aspects of, in this case, bathrooms, Soap dispensers , hand dryers, cleanliness of sinks, floors and toilets. All these topics that can be monitored for changes in sentiment (and using Etuma, can be filtered by region, district or restaurant as well) , enabling proactive management of "dirty" bathroom issues across the restaurant chain.
- Strategic Change. Temkin - As part of new restaurant formats, design bathrooms so that they don’t require as much time from employees to keep them clean.
How Text Analysis can help.
- Here again, Text Analysis can be very helpful in the strategic domain, by providing insight about what "dirty" actually means for customers, which in turn informs how to strategically change for the better. For instance, if "dirty" often means un-flushed toilets, a strategic change could be to install self-flushing toilets in the restaurants.
Temkin's bottom line: Make sure to build out four closed loops.
My point: using Text Analysis makes it a lot easier to determine which actions to take to "Close" each loop. Also, actions taken will be supported by data, as text analysis is providing statistically meaningful support for the insights being generated. The result being that its much more likely that customer issues will actually be addressed in such a way as to improve VOC.
A couple of additional points....
Automated Text Analysis provides continuous and on-going evaluation of feedback. When people have to do the evaluation of feedback without text analysis, they can be inconsistent, or if there is lots of feedback, only base their analysis on samples. So, for organizations who want continuous improvement, continuous monitoring is necessary.
Changes in topic sentiment are difficult for people to identify unless the change is dramatic. Automated Text Analysis solutions (such as Etuma) are able to assess and document changes to topic sentiment over short periods of time based on changes in the relative volumes of topics discussed in received feedback.
So, by all means, close Temkin's four feedback loops. But, by using automated Text Analysis, closing loops will be quicker, smarter and less effort than otherwise.
