November 26, 2020
Product development is a challenging endeavor. You need to carefully evaluate each feature to determine whether it will provide enough value to justify the cost of adding it to your product.
Of course, that is easier said than done, so sometimes it can feel like you are stumbling in the dark trying to make a correct guess. But it doesn’t have to be that way.
Your customers are already talking about what they want. They discuss it on Twitter, on online forums, and even with your support staff. All you need to do is listen to what they are saying.
And that’s where text analytics comes in. You can’t possibly go through all those tweets, forum messages, and support tickets manually. But an AI can analyze all that data in a matter of hours and give top-notch results.
Let’s to discuss how you can use text analytics to:
- Create a minimum viable product (MVP) that your customers will love.
- Improve your product by fixing the most common issues that come up in customer support requests.
- Decide which requested features to prioritize and create a solid product roadmap.
Want to find a product-market fit?
Text Analytics for Customer Research
Product development should start with extensive customer research. You need to make sure that you are solving a problem that is “painful” enough for people to pay for your solution.
The best way to do that is to go where your potential customers hang out online, observe them in their “natural habitat”, and try to identify patterns in the conversations they are having.
Text analytics makes this much easier because it allows you to analyze an incredible amount of data in a short period of time.
For example, we recently did a project with Studeo - a leading e-learning Finnish platform - where our goal was to learn more about the concerns that people have regarding the Finnish education system.
We have analyzed an astonishing 280,000 tweets and identified five key concerns:
Data like this is extremely valuable to a business because it offers insight into what the customers care about the most. Consequently, it enables the company to prioritize features that will provide the most value to the customers. This eliminates the “stumbling in the dark” process, reduces research and development (R&D) costs, and leads to a better product.
Now, imagine if you used text analytics to analyze relevant Twitter conversations before you started building an MVP. What if you could get a full report with a breakdown of the common trends, topics that come up over and over again, and even the most frequently used words and phrases?
This would provide clarity that would help you build a product that truly meets your customers’ needs. Or maybe you would realize that your product idea wasn’t viable to begin with and move on to something more promising. One way or the other, customer research powered by text analytics can save you weeks, months, or even years that you would have otherwise wasted developing features (or even an entire product!) that no one cares about.
Text Analytics To Improve Products
The most straightforward way to improve an existing product is to address the issues that come up again and again in customer support tickets. Text analytics can help you identify what the most common problems are so that you could prioritize fixing them.
This will not only make the product better but also decrease the customer support team workload, enabling them to respond to requests faster and give more attention to each customer.
It’s worth noting that text analytics is especially valuable when you already have a solid user base and the volume of customer support requests is getting too large for you to go through manually.
Text Analytics To Develop a Roadmap
Creating a product roadmap can be quite a challenge. When your customers demand all kinds of new features, it can be difficult to decide which feature requests should be ignored and which ones should be fulfilled. After all, you want to be responsive to customer feedback but you also need to deal with the reality of limited resources.
Indeed, you only have so much time, energy, and money at your disposal. This means that deciding to develop one feature automatically means deciding not to develop all the other features that could have been built using those same resources. At least not now.
Moreover, product roadmap mistakes can be extremely expensive. Choosing the wrong feature means paying the development team to build something that doesn’t add anything to the bottom line. You can only afford so many mistakes like that before. No pressure though, right?
Fortunately, text analytics can help you make more informed decisions when it comes to creating a product roadmap, thus decreasing R&D risks. You can use it to analyze feature requests that you get via email or livechat, Twitter conversations that revolve around your product as well as those that revolve around your competitors’ products, and the answers to open-ended customer surveys.
This will allow you to see the big picture:
- Which feature requests come up most frequently?
- What are the customers saying about your product?
- What are the people who are using your competitors’ products saying about them?
It’s much easier to make the right decision when you have data on the feature requests as well as an overview of your niche.
Most importantly, text analytics allow you to co-create your product together with your customers. Co-creation remains a sure way - if not the best way - to build a product that people love. Moreover, engaging in a co-creation process will naturally build you a solid core community of enthusiastic users.
What Text Analytics Solution shall you choose?
So how can you get started with text analytics? You have two main options: text analytics software (software, SaaS and platforms) and full-service text analytics.
With software solutions, you pay a company to rent their tools.
You then collect the data. You will sometimes need to get another software to do so, especially if you aim at scraping social media.
Then you spend time learning how to use the software, maximize your output.
You train - or partially train - the AI to recognize relevant patterns, synonyms, feelings and draw conclusions from the analysis’s results.
There are quite a few great text analytics software solutions out there, but they all require a significant investment in addition to acquiring the software in terms of time and knowledge.
With full-service, you pay a text analytics company to do all the work for you. That’s what we offer here at DrAI:
- We collect the data.
- We analyze the data.
- We interpret the results.
We then come back to you within 1-3 days with a complete report that includes not only the analysis results but also actionable business insights and recommendations that you can start implementing immediately.
This allows our clients to complete their projects much faster than they could with text analytics software.
For example, when researchers from the Co-Creating of Service Innovations In Europe (CoSIE) program needed to analyze over 3,000 online forum messages, they quickly realized that using text analytics software would take too much time and put them at risk of not adhering to their tight schedule.
So they decided to use DrAI full-service text analytics instead. As a result, they were able to submit their manuscript the very next month.
“DrAI saved me a couple of months and gave better results,” shares Jussi Kokkola from the Turku University of Applied Sciences.
So how can you find a product-market fit?
The best way to build a great product is to co-create it with your customers. They are already talking about what they want. All you need to do is listen. And text analytics can be the competitive advantage that helps you do that.
Want to learn more about our services? Feel free to book a demo anytime. We would love to talk to you!