Analyzing over 20 mobile app reviews & languages with AI text analytics
20+ apps covered in the analysis process
75,000+ new reviews collected and analyzed every month
In early 2019, Wonderflow started working with a major consumer electronics and hardware company. The scope included coverage of over 20+ local language apps and platforms like Amazon. We speak to Marissa, currently the lead product marketing manager for a range of different apps. We discuss what her work looked like before and how it has changed since she started working with Wonderflow’s AI-driven Natural Language Processing (NLP) solution.
Product or consumer marketers, customer care/experience managers, business analysts, customer insights managers can benefit from the use-cases shared in this case study. It gives a clear example of how AI-driven customer feedback analysis can help you build a better experience for your clients, and can serve many different levels within your company.
Being a core source of customer insight for a global consumer-focused software provider is a challenging job, even on a good day. Marissa, product marketing manager for an entire range of apps, knows this more than anyone. Not only is she asked for insights and reports daily, but she also needs to find ways to continually improve the customer experience and the insights gained from it.
Marissa started working with the AI-based NLP solution from Wonderflow in early 2019. We spoke with her to discuss what her work looked like before and how it has changed.
“I had to cover between 1500 to 2000 new reviews every month in the app stores. I used to collect, categorize, and analyze the reviews myself, back when I only had one app to manage. My most innovative solution was a scraping tool that exported reviews to an Excel sheet. Unfortunately, that didn’t work for the Google Play store.” Marissa recalls countless days where she was scouring app store reviews. The fact that she speaks multiple languages made her job a bit easier, but that was an advantage most of her colleagues did not have.
When Marissa started working her job, a lot of valuable feedback was slipping through the cracks. “I was looking at reviews for four hours per week at a minimum before the Wonderboard, and those hours did not properly cover everything. I didn’t feel it was sufficient, especially country by country as I wasn’t actually able to do proper analysis and give feedback to the team.”
“Going through the reviews was also a pretty depressing task. There was an issue with a migration process, so our rating dropped. People write nasty things when they do one-star reviews…”
Multiple solutions were considered to replace at least parts of the existing process and manual labor. The decision for the Wonderboard was one with an eye on the future. The most significant improvements were the ability to increase the number of business users dramatically and scale the tool throughout the enterprise. Being able to digest such a large amount of reviews from such a diverse group of sources, has given the enterprise a significant advantage.
Marissa is now the lead for a range of consumer apps. With this new role, she is now responsible for more strategic decisions, for which she leverages the Wonderboard data.
“Ramping up the number of reviews we analyze to include over 20 different local language apps stores, that’s a step change in capability we can’t even quantify. We can now spot trends, and the predictive analytics capability shows us how much app sales can potentially be improved if we improve specific functionality.”
“We have added a ton of new users to the Wonderboard from different teams. Each new user is onboarded with care, allowing them to use the tool when they need insights. The variety of users brings forward many use cases, too. One of these is that we leverage the Wonderboard to track how competitors’ products are performing. We have learned so much from new feature launches by competitors, giving us insights for product development.
It is also the leading tool we use when launching a new app or functionality because we get deep market feedback quickly. Distributing this information to the relevant people within our company in a form they understand matters a lot. We have, in general, become much more market-driven and deal-driven.”
The Wonderboard is used by different departments within the company. Users already save time by eliminating unnecessary or duplicate processes. Other key results:
- The company is now able to analyze all customer reviews, rather than picking samples
- Increased coverage of sources to include 20+ local language app store sources (as well as Amazon for their hardware business)
- Increased product sales through predictive analytics, highlighting potential improvements
- Streamlined market feedback process for product launches
- A recent report by independent research firm Ovum highlighted the quick adoption by
- Increase the number of local language app stores
- Ramp up the number of trained business users with 200% in the next 6 months
- Ramp up the competitor analysis to cover all products from their 10 biggest competitors
- Closing the feedback loop with the hardware and software development teams
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.