Case Study: How Viable’s AI analysis saves Latch’s product team 936 hours a year

annual hours reclaimed
product roadmapping
10 seconds
reviewing the analysis each week

Latch’s products have modernized and simplified building management, but their process for analyzing product-related feedback from their customers was laborious. Latch was looking for a way to do more with less. They decided to trial Viable’s experience analysis platform on their customer support tickets to see if it could improve their process while providing time and cost savings. Quickly, our technology became a linchpin in how they analyze customer feedback — and delivered significant time savings for their team to the tune of 936 hours per year

Challenge: Too much feedback, not enough time

With a national footprint, Latch receives enough customer feedback that it takes their product and customer teams 12 to 18 hours every week to analyze their support tickets to ensure they are delivering a best-in-class experience. 

First, a member of the customer support team extracts the data into a spreadsheet and cleans it up with pivot tables – an arduous and manual process that would give most humans nightmares. Then, the product managers for each product - App, Web and physical products - organize and facilitate a meeting to review the data to identify new, urgent, or recurring themes, as well as any week-over-week changes. These sessions include the relevant PMs, the customer support team member, and a product designer. After that, the same PMs do the final synthesis and, in partnership with the product designer, make recommendations for how to resolve the feedback. In total, it took roughly 18 hours/week to analyze their help desk data and make it actionable. And they would repeat this process. Every. Week.

Latch’s VP of Product, Si Dhanak, knew this work was critical, but wished it took fewer resources. With an interest in GPT-3, he began looking for a way to free up his team’s time and budget. 

Solution: AI-powered qualitative data analysis to eliminate blind spots

Si integrated his customer support data directly with Viable - eliminating the need for spreadsheets - and was blown away by his first report. Viable’s natural language models built an analysis that read like a human wrote it, not an AI. Unlike most data analysis tools, the report went beyond simple sentiment analysis to detect and remove any noise, cluster the data, analyze it, and then present the most important themes - each with a summary, week–over-week change, meta tables with profiles of the customer giving that feedback, and direct customer quotes to support it. Every theme is also tagged with an urgency level based on churn risk given the language used. He knew this would revolutionize how his team synthesizes customer feedback. 

“Viable quickly became our blind-spot-preventer,” shared Dhanak. “When managing a product, you need a variety of channels for gathering insights… Viable is the ultimate tool in your arsenal to ensure you’re listening to your customer feedback and eliminating any blind spots.” 

Apart from the software, Viable’s value proposition and top-tier customer service also impressed Si. 

“The Viable team provides white-glove service. They made the process of getting our reports so seamless and simple. It was also very inexpensive to get started, which is critical for us right now as we’re entering a downcycle in operating expenditures.” 
Impact: Major time and cost savings across departments 

Beyond providing human-level analysis, Viable helped free up 18 hours of his team’s time weekly. That works out to 936 hours per year where his team can now focus on solving customer problems and build a best-in-class product, instead of sifting through unstructured data to identify customer problems. 

“Viable’s report effectively mimics a laborious and manual process I was running at Latch,” he shared. “Before, it took 6 people on my team 18 hours a week to analyze and generate a report of this fidelity, plus my own time reviewing the analysis. Now, I review the latest Viable report in 10 seconds, once a week.”

Going forward, Latch’s product team plans to leverage our AI’s analysis to interpret their app store reviews, and will begin incorporating it into product roadmapping. Other departments have also expressed interest in leveraging this technology. As proven by their product analysis, Viable’s reports stand to benefit groups across the company: so long as the department has qualitative data, Viable can help.

Curious to see what insights our tool can surface with your qualitative data? 

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