In today’s world of online reviews, email surveys, chat-bots, mystery shoppers and call centers there is never any shortage of customer feedback coming in for customer experience-focused companies.
The problem we face now, is how do we make sense of all the feedback (data) that is coming in
Below are 6 steps to follow to develop a solid strategy for making sure you receive maximum insight and effect from your customer feedback to do feedback analysis.
1. Collect all your customer feedback in a single environment
One of the biggest challenges in any strategy of dealing with customer feedback, is that reviews, comments and survey results are constantly collecting in a LOT of different places.
This makes it extremely time consuming to continuously track and make sure you are responding to or even hearing all of the feedback that is being left for you by your customers,
By using a solution that pulls all of this content into a single place, you can not only save yourself a ton of time when it comes to monitoring and keeping track of all of your customer feedback, but you can also have the right environment to start using more technical techniques to really do the feedback analysis to give you maximum insight.
2 & 3. Analyze ALL of the customer feedback and identify patterns.
In just about every form of customer feedback your company is getting, there is both qualitative and quantitative data. You’ll get quantitative data in the form of star ratings or NPS scores, and qualitative data in the form of open text responses.
Start by identifying and grouping feedback based on key topics surrounding the customer experience (i.e. crowd, price, events, etc.) and start to identify average ratings and patterns surrounding these topics.
This will be simpler for the quantitative data fields, but to really see everything you should be analyzing the qualitative feedback data as well. For example, in many cases people will leave reviews online where they may give you a 5-star review, but still mention something that bothered them in the paragraph they wrote.
To really analyze the quantitative data, you can use data mining techniques to help you analyze and tag every time certain topics are mentioned in the feedback responses.
Once you have everything segmented properly, pay attention to the average rating the reviewers gave you when they mentioned these topics. This gives you an instant metric to track what people like the most and what they like the least, and without you even having to read every single review yourself!
4. Perform sentiment analysis.
In many cases like in chat and call logs, c-sat surveys, and even online reviews, there is no score that customers are giving you, so you may have to create one. The most effective way we see to do this, is to perform what analytics professionals call sentiment analysis.
If you can pinpoint what the sentiment around each of the topics you are tracking is, then you can assign a rating to each topic that is mentioned, and get an extremely detailed insight into what people think about their experience.
5. Communicate your findings and act!
Once you have performed the customer feedback analysis, make sure you are relaying the information to the right people in your organization. For example, you should send reports on your findings on feedback about cleanliness to the person in charge of sanitation at your company, since this feedback means the most to him. This is the person most able to be the catalyst for change nit his area, but since he has never been the person in charge of reading the reviews before, he never was seeing the real impact his role was having on the customers.
When everyone in your organization has detailed and easily accessible information about the area they are in charge of, then you have an environment where each of these decision makers can base forward decisions off of real data, thus leading to a much more positive customer experience.
6. Track these numbers over time
Lastly, it is incredibly important to continuously track this data over an extended period of time. The end result is you will be able to see how each topic is being perceived by your customers before and after you make changes, and understand whether or not the changes you made worked.
In addition, you can create goals to exceed your ratings each year in specific areas, which creates a unifying element to your company and drives further innovation to create the best customer experience possible!
If you can employ a strategy like this one at your company, then you will truly understand all of the important things your customers are trying to tell you, and have a proven strategy to realize continuous improvement of your customer experience!
If you would like to learn more about customer experience strategy, or see how we are helping companies create better experiences for their customers, reach out to us at sales@tatvamanalytics.com or by filling out our form on our Contact Page.
Tim works as the VP of Sales and Marketing at NetServ Applications and oversees the development and client relationships for NetServs’ proprietary product Tatvam. Tatvam is a Customer Feedback Analytics product that leverages technologies like Machine Learning and AI to help companies monitor and improve their customer experience. Tim both manages the product log and the development teams to ensure they are consistently innovating and delivering a true value-add product, as well as continuously works with Tatvam customers to help them improve their data strategies and customer experiences.
