Call Center Automation Software Vendor Replicant Raises $ 78 Million - TechCrunch

Call Center Automation Software Vendor Replicant Raises $ 78 Million – TechCrunch

Contact centers have never been a walk in the park for employees, but they have become much more difficult work environments during the pandemic. According to a survey, only 10% of contact center agents achieve proficiency in less than two months. Meanwhile, the volume of difficult calls to contact centers is on the rise, while revenue remains at a staggering rate of between 30% and 45%.

It is in this context that automation products are gaining interest from call center operators and investors. At the more sophisticated end of the spectrum, call center automation promises to solve customer service problems to free agents for more complex jobs. Replicant, a leading provider in the call center automation industry, announced today that it has raised $ 78 million in Stripes-led Series B funding with participation from Salesforce Ventures, Omega Venture Partners, IronGrey, Norwest and Atomic . Sources tell TechCrunch the post-coin valuation is $ 550 million.

“[With the new capital,] we plan to increase investment in our customer success team to acquire new customers, “co-founder and CEO Gadi Shamia told TechCrunch.” We also plan to double our R&D team this year to make our conversations even more efficient and launch new automated channels. We will increase our investments in sales and marketing to capture the significant demand we see. And finally, we will invest in our employees by launching additional professional development programs. “

Shamia co-founded Replicant in 2017 along with Andrew Abraham, Benjamin Gleitzman and Jack Abraham. Shamia was previously the product GM at SAP’s small business solutions group before becoming the interim COO of EchoSign after it was acquired by Adobe. She also helped launch Magneto, a calendar system, and was COO of Talkdesk for nearly four years.

Prior to Replicant, Abraham, who joined eBay in 2011 via the company’s acquisition of Milo.com, worked as a software engineer at Atomic and smart device company Leeo. Gleitzman was a senior software engineer at Hunch and eBay before co-founding several startups, including a “virtual reality therapy platform” called Mona.

“Through [my] work, I realized that the best way to increase agent efficiency and reduce customer and agent frustration is to automate many common tasks and let agents focus on more complex and nuanced calls, “said Shamia.” Gleitzman was one of eBay’s AI pioneers and worked with Abraham and the Atomic team to build a machine that could have an entire phone conversation with a human. “

Replicant aims to automate call flows by integrating with existing systems, including customer relationship management software, to recognize customers by tapping into order history (if applicable) and past calls. The product is capable of capturing, transcribing, and searchable customer conversations, and like some competing service automation systems, Replicant can interact with customers via SMS and Web in addition to voice.

Replicant provides agents with call summaries and measures trends such as overall customer satisfaction, average lead time, competitor mentions, defective products, and upsell opportunities. Customers can draw on a library of pre-built components to design conversation flows using a visual editor. In recent months, Replicant has added support for new languages ​​and conversational skills that Shamia calls “powers,” such as staying online, repeating information “conversationally”, and comparing a customer’s response to a database.

“A key competitive advantage we have in Replicant is the rich and varied data we have accumulated by addressing over 30 million customer service calls across all industries and use cases. Our [product has] tackled everything from hardware troubleshooting for small business owners, food order forwarding to restaurant employees, managing subscription issues for senior callers, to high-urgency scenarios where callers have need for roadside assistance, “said Shamia.”[W]And it turns scenarios that are commonly frustrating – think every time you’ve had to go back and forth writing your name or reading a 15-digit policy number to an agent on the phone – into a task that can be completed efficiently. in seconds with a purpose built model “.

When asked how Replicant manages, stores, and retains customer data, Shamia said the company offers enterprise customers the option to choose a data retention window that “works for them,” usually between six months and two years. For use cases involving electronic secure payments or health information, Replicant offers a service called highly confidential turn, which according to the company draws sensitive data on the conversation turn from Replicant’s database and records.

Replicant also engages in sentiment analysis, a controversial process that involves the use of algorithms to determine whether part of the transcribed audio or text has a positive, negative, or neutral tone. Sentiment analysis systems, both academic and commercial, have been shown to show bias along the lines of race, age, culture, ethnicity and gender. Some algorithms associate blacks with more negative emotions like anger, fear, and sadness. Others discriminate against non-native English speakers, who tend to use cognates, that is, English words that sound similar to the words in their native language, more often than native speakers.

Replicant claims to measure customer satisfaction only by asking specific questions (for example, “How satisfied are you?”) And takes measures to mitigate bias in its systems, including its sentiment analysis systems, as well as the data used to develop these. algorithms. Unfortunately, with no independent audits or studies to carry out, it’s the company’s word against far-reaching academic achievements. This reporter hopes to see more transparency from Replicant in the future.

“Our models are then trained on a variety of industry-specific accents, emotions and jargon, enabling us to achieve results. [high] accuracy of inference on even the most complex service use cases, “said Shamia.” We see an 85% call success rate (measured by expected business outcome) among customers and use cases. “

Automate customer interactions

There is anecdotal evidence to suggest that customer service organizations are embracing automation. A 2020 Harris Poll study, commissioned by AI vendor Interactions, estimates that 46% of customer interactions are automated, a percentage that co-authors predict will rise to 59% over the next two to three years. Early users surveyed for the study cite “soft benefits” such as reduced wait times, faster resolution of customer complaints, and technical support and personalization.

In response to the growing interest of the industry, countless call center automation products have been brought to market in recent years, both by startups like Replicant and by incumbents like Google, Amazon and Salesforce. Replicant competes with RedRoute, Skit and Voximplant as well as Ultimate.ai, a customer support tool designed to automatically satisfy simple support requests.

Expert Market Research predicts that the global call center AI market will grow from $ 967 million in 2020 to $ 3.54 billion by 2026.

“For the past two years, customer service has been under constant pressure as ‘The Great Resignation’ has created persistent agent shortages. And the changes in consumer behavior due to [the pandemic] and supply chain problems have caused huge spikes in call volume, “said Shamia.” Executives now understand that the problem cannot be ignored or outsourced, as customers are unwilling to wait for hours. “

But do customers like, or even appreciate, automated call centers? After all, automation lacks a human touch – it can’t necessarily reduce the escalation of a frustrated caller. Worse still, automation can dissuade customers from interacting with a brand in a way they might trust. A PointSource survey found that 80% of customers would prefer to talk to a human to solve problems. Adding fuel to the fire, 59% of consumers in a recent PwC survey felt that businesses have lost touch with the human element of the customer experience.

And what about call center workers? The metrics might be opposite to them, and simple customer problems, even if they’re probably not the best use of their time, can be satisfying to solve. Then there is the fear that automation will one day take their jobs away.

Shamia recognizes that some forms of automation, such as poorly designed conversational robots, can act as a barrier to customers and agents rather than a solution. But he says Replicant has learned from past mistakes by allowing companies to automate call flows by allowing agents to focus on more challenging problems.

“The pandemic accelerated a trend – contact center automation – that had already begun and exacerbated many of the challenges in the customer service space,” added Shamia. “Automation is now part of the
strategic plans of more and more companies, something that will not change after the pandemic “.

To this end, Replicant, 100 employees, claims to have “dozens” of corporate customers who have used its tools to serve over 8 million customers. Customer business sizes range from hundreds of thousands to millions in annual recurring revenue.

“In most of our deals, we compete with the disbelief that technology can actually achieve the resolution rates our customers see. However, we are also part of replacement cycles for older technologies, “Shamia added.” We also see do-it-yourself solutions … in some agreements or legacy players like IPSoft’s Amelia.

To date, Replicant has raised $ 110 million in venture capital. The San Francisco, California-based company plans to expand its workforce to around 200 people by the end of 2022.

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