Many of today’s organizations base their business decisions largely on structured data such as credit card transactions and earnings reports. This type of data is often easy to search for and analyze, existing in predefined formats that help companies determine which benchmarks need to be met or exceeded in the future.
However, this information doesn’t tell them what makes their customers tick and how to attract and retain them. The reality is that most enterprises are sitting on top of a treasure trove of untapped customer data packed with valuable, yet unearthed insights. That’s where contextual AI comes in. This technology that allows algorithms to process and perceive information in the same way that humans do.
Today, there is a growing number of customer intelligence platforms that are utilizing AI and machine learning to understand, resolve and evaluate structured and unstructured data across enterprises.
Contextual AI and customer intelligence
One company making waves in this space is Palo Alto-based Idiomatic, which just announced the closing of a $4 million seed round led by Freestyle, a venture capital firm specializing exclusively on seed-stage companies. Idiomatic plans to use the funding to further expand its solution offering and accelerate its reach in consumer internet, ecommerce, retail and technology markets.
With extensive experience at companies that handled massive amounts of complex data, Chris Martinez and Kevin Yang founded Idiomatic in 2016 with the goal of eliminating the pain points associated with collecting customer feedback. The two knew there was a large market for a tool like this. After all, studies show that over 87% of senior business leaders cite customer experience as being their top growth engine, but only one-in-three feel equipped to address it.
“The most common types of feedback we analyze are customer support tickets, satisfaction surveys, reviews and queries through social media,” Yang told VentureBeat.
Idiomatic then cross-references with other metadata available, like customer segments or geography. To date, Idiomatic has analyzed more than 100 million pieces of customer feedback for their clients.
Martinez explained that Idiomatic’s proprietary technology incorporates the context of each business into high-performance natural language processing models. This allows Idiomatic’s AI to analyze customer feedback with higher accuracy than human experts working at those companies.
Thanks to data integrations with customer support platforms such as Gladly, Salesforce and Zendesk, as well as cloud-based survey, review and social media platforms, Idiomatic has the ability to consolidate data spread across multiple systems. This technology then converts that feedback into understandable labels for each channel in real time, even for larger corporations.
Although numerous customer-focused companies now collect millions of customer data points from various digital sources, Idiomatic claims that very few can efficiently analyze disparate feedback in order to enhance the customer experience.
“None of our competitors take the time to create novel AI for each business they work with,” Marinez said.
Idiomatic’s competitors in the space include UserVoice, Clarabridge, Qualtrics and InMoment.
“Idiomatic classifies customer feedback more accurately and granularly than other platforms because we incorporate unique business context for each client into our machine learning models,” Yang said. “We are the only solution in the market that creates novel training data for each business we work with.”
Yang and Martinez cited companies including Pinterest, Instacart, Upwork and HubSpot as Idiomatic clients.
“Working with these industry-leading customer experience teams has taught us what insights matter and we’ve been baking those insights directly into the product so that all of our clients can benefit,” said Yang.