Aaron Lee, is the Co-Founder and CEO at Smith.ai, a platform that mixes AI and human intelligence to supply 24/7 customer engagement with live North America-based agents to capture and convert more leads.

Aaron can also be the Ex-CTO of The Home Depot and co-founder of Redbeacon, which was acquired by Home Depot in 2012. He’s a founding engineer on Google Video & led YouTube monetization.

What initially attracted you to computer science?

I used to be an enormous fan of video games and computer graphics once I was younger, and that fascination pushed me to check computer science. My first computer was the Apple IIe – I feel you possibly can still buy old models off of eBay, however it’s nowhere near the capabilities of today’s computers. It had a 6502 microprocessor and 64KB RAM (for context, my current laptop has 64GB of RAM, 1024 times more). But I loved that computer because I used to be coding within the assembly language, and I used to be capable of program games on that computer.

That zeal from a really young age prompted me to check Computer Graphics for my Ph.D. In the long run, it served me well. A fun fact, after I graduated from Princeton, I almost took jobs with Nvidia and Activision, because I used to be enthusiastic about their upcoming game World of Warcraft. But on the insistence of a friend, I joined Google as a substitute, where I had the really worthwhile opportunity to be the founding engineer for Google Video, and later worked on YouTube’s monetization features.

Your first startup RedBeacon was a web-based home services platform that connected consumers with contractors for his or her home maintenance, repair, and remodeling needs, and was later acquired by Home Depot. What did you learn from this experience?

That have taught me how one can construct and scale an organization, the myriad of challenges SMBs are facing, and ways to cultivate a stellar company culture.

Up until RedBeacon, I had only worked for enormous corporations – throughout my time at Google, the corporate grew from 2,000 to twenty,000 employees. With RedBeacon, I used to be constructing and growing the corporate myself and we were a small team. I needed to find out about each component of constructing a business, like creating and marketing a product, finding customers, and hiring. I feel because I had that have and learned a lot about what it requires, I used to be more successful with Smith.ai.

I initially began RedBeacon because I saw a niche out there. I used to be personally frustrated by how hard it was to seek out a contractor, and I noticed that contractors felt the identical way. They wanted a better option to find customers. Afterward, once I was the CTO of Home Depot, it became my job to talk with these home services pros to know the challenges they were facing, and the way technology inside the Home Depot umbrella could help. Those personal conversations helped me understand that much in the identical way growing and scaling a startup is hard, being an SMB is equally difficult – there’s lots you will have to navigate, and infrequently are people given explicit guidance on what it takes to run a business.

One other area where Home Depot excels is providing plenty of training and promotion from inside. During my time there, I worked closely with the previous CEO, and my mentor, Frank Blake, and he instilled this desire in me to take into consideration how we support and encourage our team. After I later founded Smith.ai, I attempted to construct that culture from the bottom up. We provide plenty of training to our 600+ employees and check out to advertise from inside wherever we will. Something I’m very pleased with is the undeniable fact that nearly every specialized team and management role is filled by employees who moved on from frontline roles to customer success, recruiting, training, product, and sales. Promoting individuals who know our business and do good work for us has helped us elevate the corporate and be more successful.

You’re an angel investor in multiple start-ups including NerdWallet, what differentiates successful founders from average founders?

I see a number of common characteristics amongst successful founders:

First, they should be great salespeople who can sell a mission or vision even once they don’t have anything. You have got to give you the option to persuade smart people to follow and join you. A lot of the “overnight successes” take years to make and you will have to be keen about the underlying mission.

Second, great founders are all the time resilient. In startups, you encounter more downs than ups, and you will have to be persistent and adaptable to changes. You furthermore mght should be willing to maintain grinding and determine a option to accomplish lots with only a few resources.

The last trait could appear somewhat contradictory and counterintuitive, but it’s essential to be stubborn and yet willing to listen and course-correct. I feel oftentimes founders get misunderstood because they consider the current and future at the identical time. But with the ability to find that balance and knowing which instinct to follow in a given situation is essential.

Are you able to share the genesis story behind Smith.ai?

As I discussed, my experience with RedBeacon and Home Depot exposed me to the challenges that SMBs face. One problem I encountered consistently from hundreds of pros was that it’s hard to be good at your job should you don’t have time to do it. There are only 24 hours within the day, and should you deal with your specialty, it could possibly be hard to find time for the opposite components of running a business, like responding to customers as quickly as they’d like.

In the present solutions to this problem, there wasn’t anyone that felt prefer it addressed this challenge. Most virtual receptionists, answering services, and traditional call centers relied on scripts. We’ve all experienced how they feel forced, distant, and inflexible. Nevertheless, SMBs need a cheap option to manage this problem because they lose out on worthwhile revenue in the event that they ignore it. I noticed that if we empowered agents with AI tools, we could offer a greater service that didn’t feel like the standard outsourced agents. So in 2015, I left Home Depot to tackle this issue and construct this technology with my co-founder, Justin Maxwell.

Smith.ai offers greater than webchat, what are among the different features and use cases which are offered?

We provide multiple services to be certain that businesses can engage with their customers on different mediums. The primary product we delivered to market was virtual receptionists. When a customer calls one in all our clients, that decision gets routed to a human Smith.ai agent who handles the shopper interaction. Our clients can personalize their greeting and tone, so it looks like an extension of the business. We later built on this offering with Live Web Chat, which is powered by AI but in addition fully staffed by humans to be sure that that no message goes unanswered. Our clients integrate it into their web sites, and it allows website visitors and potential customers to directly message a business 24/7.

We saw significant traction with these tools and located that more of our customers were searching for support with outbound sales. Fast follow-up is the important thing to securing latest business, and data shows that to convert 90% of leads, sales teams or outsourced providers have to make five call attempts! So in 2021, we launched one other tentpole product, Outreach Campaigns. Our agents have the identical support as virtual receptionists but are trained as sales development representatives. With these solutions, we’re supporting businesses with every form of customer engagement: inbound, outbound, calls, and messages.

What are among the machine learning algorithms which are used?

We have now built proprietary, in-house AI capabilities in order that we will offer the perfect possible service to our clients. One in every of the important thing ways we use AI tools is to support our virtual receptionists and outreach campaign agents. For every call, we offer them with prompts and relevant information that’s tailored to the particular business and conversation. Our AI can also be trained on over eight years of proprietary customer engagement calls, so our models have turn into very sophisticated at navigating all of different nuances of a business. One personal example I really like is that our model can understand different meanings of the word “gross” – it has very different implications in a legal context than in a house services context! Before, we used to present all the relevant information to our agents directly, but we found that individuals were overwhelmed by that, so over time we adapted our AI tools so it will give agents select tailored prompts based on the flow of the conversation. That way, agents could provide callers with the best details, while also collecting the relevant information, and knowing exactly what to say at the best time.

We also transcribe and record calls using Assembly AI’s technology, so if a client opts in, they’ll have a searchable record of all caller engagements. As a part of these transcriptions, we’ve incorporated technology that robotically identifies and blocks out personally identifiable information (PII) like Social Security numbers and bank card numbers. One other very talked-about feature with our agents is that we use algorithms to dam over 20 million spam calls – a service we provide free to our customers.

How does Smith.ai integrate with existing platforms comparable to Salesforce or Slack?

A part of our operating philosophy is that no tech exists in a vacuum. To offer value, you will have to integrate with the opposite tools and platforms that individuals use. Ultimately, what we’re offering is ease and expediency. With integrations, when one in all our agents talks with a customer, we will update all the relevant platforms with key information – we will put call transcripts in a CRM, book a gathering through Calendly, or arrange other automations with tools like Make or Zapier. It’s making the method as smooth as possible to work with us. That’s why we have now a team of solution architects who be sure that that our services may be integrated into other tools, and help our customers with the initial setup.

Are you able to share your views on why agents working in unison with AI offer a greater experience than agents working alone?

This can be a topic I’m very keen about, so I’m glad you asked! AI is the key sauce that permits our agents to feel like a natural extension of a business, moderately than an outsourced operator. AI is a robust tool – it allows us to provide very tailored and personalized responses to customers. Often, our clients have nuanced customer interactions: they’re coping with a high-value situation, or something very emotional, like a flooded house or divorce. Human agents, guided by AI, best navigate these interactions because compassion and emotional intelligence are innate and ever-present. AI helps agents feel supported – they know that they’ll have guidance on what to say or do next in a conversation.

What’s your vision for the longer term of AI for customer engagement?

I feel we’re still within the early days of this technology, and businesses might want to determine how one can maintain the connection between humans and AI to optimize efficiency without sacrificing personalization. Technology is indisputably a worthwhile tool for customer engagement, but I would like to caution against fully automating customer support with AI. Many interactions are very straightforward, but there’s an equal number that requires a better level of emotional intelligence, and AI isn’t equipped to traverse these by itself.

There are methods that AI will undeniably be helpful. For instance, AI answers the phone and directs callers to the suitable extension, or one AI copilot converses with one other AI copilot to schedule a follow-up meeting. We’re still very much within the early stages of technical advances for customer support, but I’m excited to see how AI can support each efficiency and personalization. Nevertheless, I still firmly consider that to succeed in the complete potential of customer engagement, we still have to foster human-AI collaboration.