At Thematic, we’ve spent years researching, designing and developing our customer feedback analysis platform.
While I’d love for everyone to be using ours, I understand that you might have the resources, time and the data required to build one in-house.
There are benefits to building vs. buying. You can customize it to your needs. You can use it as much as you want!
But: You’ll still need to spend time maintaining and training others to use it. There are also many gotchas that you might have not considered!
So, in this post, I’ll help you get started by answering these…
When you consider using a new solution for customer feedback analysis, you’ll need to make sure it’s accurate and reliable.
At Thematic we take accuracy seriously. We evaluate accuracy on every single dataset, and our approach depends on how much time is available.
There are three main approaches that you should consider.
Eyeballing the results: We use this approach at Thematic for every customer.
First, we try to get to 80% of comments tagged and a maximum 20% untagged, although it depends on the dataset.
Second, we use our solution called Themes Editor to tweak the results as needed, to…
In discussions with potential clients, we always hear the question, “How accurate is Thematic?”
– “Hey, aren’t you the creator of Maui?”– A few months ago, someone I didn’t know approached me at O’Reilly’s AI conference.
– “Yes, I am”, I said, excited that someone still remembered my project, and a little sad too… It’s been almost 10 years since I’ve published Maui’s open-source code repository at the end of my PhD, and approximately 5 years since I stopped participating in its community forum.
This is a story of how instrumental Maui still was in creating Thematic, and how my co-founder Nathan Holmberg and I have commercialized AI research and built a SaaS company…
What do Chief Customer Officers have in common with YCombinator? They are both driven by creating products and services that people want.
Last week, I attended the Chief Customer Officers & Influencers conference in Atlanta. I got a chance to give a keynote on how companies can disrupt themselves through customer insights and this post summarizes some of the key points I made.
Coming to Atlanta from a YCombinator startup meant that I bring an interesting point of view to share with that audience: Silicon Valley startups are constantly disrupting how we approach everyday tasks. …
Last month, I had the pleasure to speak with Jeff Toister (CPLP, Author of “The Service Culture Handbook”) on his webinar on how to improve customer service with unstructured data.
Contact centers often miss out on many opportunities on how to improve their team’s performance and deliver critical insights to the rest of the company, simply because the analysis of mountains of data they collect may seem daunting. As a result, strategic decisions are based on assumptions instead of data. Also, progress is tracked at an aggregate level without a clear understanding of what works and what doesn’t.
Do you gather vast amounts of customer feedback but don’t quite know how to get actionable, meaningful insights from it? You know the ones, insights that would help to influence your customer experience and overall business strategy.
If you keep analyzing your feedback but not knowing how to action it, this post is for you. Getting not only actionable, but meaningful, insights is key, as you can gather plenty of insights but unless you can action them accordingly, they will be meaningless.
Actionable insights are direct, meaningful actions that can be taken from analyzing any type of raw data.
The customer feedback loop is the practice of responding to customers meaningfully when they leave feedback. For example, if a customer complains about being overcharged, the company may respond with an apology and issue a refund.
But not all feedback is customer complaints. Customers also leave feedback when they have a particularly memorable experience. Or they may have suggestions for improvements or feature requests.
What many companies don’t realize is that they can turn this feedback into revenue.
Are you receiving more feedback than you could ever read, let alone summarize? Maybe you’ve used Text Analytics methods to analyze free-form textual feedback?
These methods range from simple techniques like word matching in Excel to neural networks trained on millions of data points.
Here is my summary to break down these methods into 5 key approaches that are commonly used today.
Text analytics is the process of extracting meaning out of text. For example, this can be analyzing text written by customers in a customer survey, with the focus on finding common themes and trends. …
Are you responsible for measuring the progress in improving customer experience? If yes, I’m sure you needed to come up with a rationale on which metrics to choose for this: Is it an all ubiquitous Net Promoter Score (NPS), the traditional customer satisfaction CSAT, or a more recent invention Customer Effort Score (CES)?
Is one enough or should you implement several metrics? Does it actually matter? Here, we discuss the two arguments: Pro and against.
Choosing the right metric matters to the extent that the metric must be meaningful to the specific customer touchpoint you’re wanting to analyze.