Video: How to analyze customer data
Published on — Written by Wonderflow
Part 2:Here, we go through the steps needed for an all-around customer feedback analysis.
- Data handling
- Data Analysis
What dangers are hidden in data handling? How easy is it to do your data analysis? Can a report cloud your insights and, by extent, your judgment? Not if you know what you are doing. Watch the second part to learn all about scrappers, NLP and more.
This is a complete guide on how to turn the satisfaction of your customers into actionable insights.If you enjoy this type of videos, subscribe to Riccardo Osti’s channel in YouTube
So the big question here is: how can brands learn more from customers? Simple. They need to read what they say and hear what they tell them. The sum of all these messages from customers is what we call Customer-Feedback. Typical sources of customer feedback are product reviews, customer care records, call logs from the call center, et cetera. Surveys, questionnaires, and focus groups are also customer-feedback, but for several reasons, they are not as good as the messages that are voluntarily generated. You can see why here.
There are four key steps that compose this process, which are:
We recommend hiring an external company or an experienced consultant to run an assessment, followed by a strategy workshop. This workshop should be for the key decision-making unit of the company, potentially including the CEO, the CMO and so on. I always found it beneficial to have the c-levels understand where the company stands now and consequently aligned on where it should be.
- Data Handling
It comprises all the steps, starting from finding where the customer feedback is, to the point where it becomes available to be analyzed. Thinking that this step is simple, it’s the biggest mistake that a brand can make, because every imperfection in this first phase has consequenced throughout the entire process.
The goal is to have customer feedback processed and interpreted as humans would do, but ideally more consistently, and at scale. This first analysis can be followed by a data enrichment phase, where results are visualized in a comprehensive way, and even used to make predictions about future customers’ behaviors and performance.
The components of a reporting system usually are a dashboard, an app or an export system that can be connected to internal visualization tools. Having good tools in place is important, as data becomes usable only when correctly visualized.
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Wonderflow empowers businesses with quick and impactful decision-making because it helps automate and deliver in-depth consumer and competitor insights. All within one place, results are simplified for professionals across any high-UGC organization, and department to access, understand, and share easily. Compared to hiring more analysts, Wonderflow’s AI eliminates the need for human-led setup and analysis, resulting in thousands of structured and unstructured reviews analyzed within a matter of weeks and with up to 50% or more accurate data. The system sources relevant private and public consumer feedback from over 200 channels, including emails, forums, call center logs, chat rooms, social media, and e-commerce. What’s most unique is that its AI is the first ever to help recommend personalized business actions and predict the impact of those actions on key outcomes. Wonderflow is leveraged by high-grade customers like Philips, DHL, Beko, Lavazza, Colgate-Palmolive, GSK, Delonghi, and more.
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