Companies have increasingly turned to chat and chatbots to enhance their customer service experiences by providing constant access to support for customers. However, early efforts for complete automation left customers frustrated as their concerns were not properly addressed in many chat interactions. Businesses have now adopted a hybrid approach that reduces case volume for customer service reps by automating the initial contact with chat interactions and then introducing a human layer. Loris is an AI-powered conversational software platform that empowers customer service agents with real-time support during digital interactions (email, chat, SMS). The rapid adoption to support remote work has also opened up a global pool of talent for customer support options and in many cases, reps are conversing with customers from different cultures and backgrounds. Loris integrates with the leading customer service platforms like Zendesk, LivePerson, Twilio, and Salesforce as an automated layer that coaches reps by adding context, empathy, and understanding of intent-based language. The platform can improve the productivity of agents within weeks while leaving the customer with a positive brand experience. Loris’ solution is completely no-code and can be integrated in minutes. The company, founded in 2018, is seeing traction with partners in e-commerce, marketplaces, and financial services. Platform partners are seeing a 50% increase in the number of conversations that can be handled simultaneously (concurrency), 20% increase in customer satisfaction (CSAT), and 25% reduction in time spent on interactions (handle time).
AlleyWatch caught up with Loris CEO Etie Hertz to learn more about the business, the company’s strategic plans, latest round of funding, which brings the total funding raised to $19.1M, and much, much more…
Who were your investors and how much did you raise?
Loris, the conversational AI software that assists human agents in real-time to make customer support more human, empathetic, and scalable, announced its $12M Series A funding round. The series was led by Bow Capital, with participation from ServiceNow Ventures and existing investors Floodgate and Vertex Ventures.
Tell us about the product or service that Loris offers.
Loris brings better conversations to the world by enabling brands to scale human experiences with their customers. Loris is a conversational AI platform that guides customer support agents in real-time during digital conversations (chat, SMS, email, etc) with empathy techniques and intent-based language suggestions that improve productivity metrics and positive customer outcomes. Loris’s no-code software integrates with most customer service platforms (Zendesk, LivePerson, Salesforce, etc) and provides business leaders with a dashboard view of conversation insights to inform product, service, and promotional decisions.
What inspired the start of Loris?
Fast-growing startups reached out saying that they were seeing a significant shift in the way they were communicating with their customers. Specifically, moving away from phone conversations and into digital channels such as messaging, chat, email and SMS. Along with this increase in demand for digital support communications developed a challenge for brands to maintain the balance of quality and efficiency – for example, maintaining consistent tone, empathy, and accuracy of responses as they quickly scaled their customer support workforce to meet the demand.
How is Loris different?
Most AI companies in the industry tend to route customers to self-service with automated responses; Loris is focused on guiding human agents every step of the way.
Most natural language processing (“NLP”) software can identify topics, some can detect the generic sentiment in messages. Loris combines NLP with a deep understanding of the customer support domain and dynamically detects customer intent, tracks aspect-based sentiment throughout the conversation in real-time, and predicts the conversation’s positive or negative outcome.
Loris is the only AI company bringing together all of these attributes with a no-code solution that integrates with most existing customer support platforms.
What market does Loris target and how big is it?
Loris clients are digitally native, fast-growing companies – largely in the eComm, marketplace, and fintech sectors.
What’s your business model?
Software-as-a-Service
What are your post-COVID office plans?
Loris has a hybrid working model for local teams, with two offices, one in New York and one in Tel Aviv with local employees coming into the office 1-2 days or more, based on their preferences. Additionally, we have a growing fully-remote workforce.
What was the funding process like?
The fundraising process is always hectic with unexpected turns along the way.
We operate in a very interesting and growing space that has drawn interest from most of the top-tier VC community. We were lucky to be able to meet with the top investors in the country and find the right partners for us.
What are the biggest challenges that you faced while raising capital?
Investors typically look for companies that fall within their investment thesis. While conversational AI is a broad category on the list of many venture capitalists, in many ways we are creating a sub-category in this space from scratch. There have been enormous advances in natural language processing that enable us to do things that were pretty unthinkable just a short time ago. For investors who dabble in AI and NLP and don’t spend a lot of time in our world, there can sometimes be a bit of a learning curve and education required during an investor presentation – which is challenging when meeting times are limited.
What factors about your business led your investors to write the check?
Put simply, we are a growing company in an increasingly explosive market. Early versions of our product gained traction with some of the most well-known and fastest-growing brands in the country.
What are the milestones you plan to achieve in the next six months? Where do you see the company going now over the near term?
One of the features that strongly resonates with our clients is our real-time classification of their customers’ intent (the topics and keywords associated with the end user’s messages). We are working on making the process of training and deploying these models radically faster.
And on top of customer intent, we’ve built a best-in-class sentiment classification system that delivers a real-time understanding of customer sentiment (a five-point scale of negative, neutral or positive sentiment as they write to customer support agents). In the next several months we plan to update our platform with aspect-based sentiment detection. No other company to date has been able to bring this technology to the mass market before. It has been reserved for large enterprise companies, with teams of in-house data scientists.
And on top of customer intent, we’ve built a best-in-class sentiment classification system that delivers a real-time understanding of customer sentiment (a five-point scale of negative, neutral or positive sentiment as they write to customer support agents). In the next several months we plan to update our platform with aspect-based sentiment detection. No other company to date has been able to bring this technology to the mass market before. It has been reserved for large enterprise companies, with teams of in-house data scientists.
The combination of our focus on merging customer intent with sentiment understanding and delivering an easy-to-use configuration system to our users is extremely powerful. It will continue to improve the sophistication of language suggestions presented by Loris to users, and provide a dashboard of aggregated insights to CX managers to improve their policies, products, and promotions in ways that will improve customer outcomes and reduce churn.
So our 6-month goal is that a CX manager can go from an idea on how to handle a particular type of customer request better to testing it and training agents to use it in the same day. For instance, if you have a specific appeasement or churn avoidance process that agents should follow when trying to retain a customer, we can predict the appropriate time to use this workflow and test the efficacy of different approaches. This is a huge advancement compared to the tools and processes they use today to implement this type of change, and can serve immediate bottom line impact as we’ve seen with one of our pilot users of this functionality – Slice.
“We originally came to Loris with a mission to improve our agent’s productivity and to ensure that even newer agents could ramp up faster,” said Enis Haskaj, Director of Operations at Slice, which was an early user of Loris technology. “Appeasements were not an initial focus. However, the impact that Loris demonstrated in just six weeks has been incredible, with a reduction in credits issued by 36% and a projected hundreds of thousands of dollars in savings for our business. We now plan to further roll out Loris to additional channels.”
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
The approach varies greatly by how much runway a company has and how much they have left to prove in order to achieve their next round. In addition, with the market turning, most should assume a much longer fundraising process. Folks raising money should back into the date and milestones they need to figure out how best to get there.
Starting discussions and building relationships with investors who may be relevant should probably happen sooner. Depending on how constrained they are on time, operators may want to explore venture debt and shift their sales motion into prepaid (at a discount) to strengthen their cash flow if possible.
What’s your favorite outdoor dining restaurant in NYC?
Lola Taverna in Soho is probably the outdoor spot I have enjoyed the most since the start of COVID.
