EP 320 – From Banking to Breakthroughs: Harnessing AI to Transform Home Services – Jingjing Zhong – co-Founder at Superbench

by | May 3, 2024

"I've been moving by myself since I was 17... And each time I managed to pull myself up. And each time I managed to build a community around myself. And I think I was doing well in my own definition. So really, I believe any situation I can do well." - Jingjing Zhong In a revealing conversation on the Asia Tech Podcast, ⁠Jingjing Zhong⁠, co-founder of ⁠Superbench⁠, shared her entrepreneurial journey and the innovative work her company is doing in the home services industry.

Some of the topics that Jingjing covered:

  • Navigating cultural nuances can enhance business growth and communication
  • The transition from corporate to entrepreneurship requires courage and the clarity of ‘why’
  • Emerging technological innovation can solve traditional business pain points
  • Robust data management can lead to better decision-making and increased efficiency
  • The importance of building a business model that scales by aligning closely with customer demands and industry dynamics

Some other titles we considered for this episode, but ultimately rejected:

 
  1. From Banking to AI: Revolutionizing Home Services
  2. The Future of Home Services: An AI-Driven Approach
  3. Empowering Small Businesses Through AI
  4. From Investment Banking to Tech Innovations: Revolutionizing Home Services with AI
Read the best-effort transcript

Read the best-effort transcript below (This technology is still not as good as they say it is…):

Michael Waitze 0:05
Okay, that’s good, because we’re on…Hi, this is Michael Waitze. And welcome back to the Asia Tech Podcast. And normally I ask before we start recording how to pronounce someone’s name just so I get it right, but I did not do that. Wait. It’s okay. We are joined today by JingJing Zhong, a co founder of Superbench. I got it. Thank you so much for coming on the show today. How are you doing, by the way?

Jingjing Zhong 0:25
I’m doing well. Thank you so much for pronouncing my name correctly.

Michael Waitze 0:32
I bet I actually bet. Just based on my limited knowledge of Chinese characters, I bet I could guess what your name means. Okay, got that. It means like, and it’s doubled. Right. So the double, there are two characters in a row. And they’re the same character. And I bet it means something like, quiet or calm.

Jingjing Zhong 0:52
Oh, that’s changing. Yeah. So

Michael Waitze 0:54
I guess, because, because there’s a Japanese name. That’s similar, right? She’s got it’s the same character anyway.

Jingjing Zhong 1:02
Yeah, I tend to tell people phonetically, It’s same as gold or sparkly. Actually, it’s so normally I tell people, right. So you know, the capital city in China. Beijing, right. Drop ‘Bei’ double Jing got it.

Michael Waitze 1:19
Okay, easy. Yes.

Jingjing Zhong 1:22
I’m the capital city. Yes.

Michael Waitze 1:25
Your parents named you…They were serious. They were definitely serious. The shiny thing? That’s great.

Jingjing Zhong 1:31
Well, no, actually, this was supposed to be my baby name. And they just never bothered to give me a full name. I love it. And then it my grandma actually gave me that because when I was born, she was in Beijing having a business trip. So like, Oh, your granddaughter is bored. Do you want to give her a name? She’s like, I’m in Beijing right now. Jingjing for now. Yeah, and then that’s wherever I

Michael Waitze 1:56
like it for now. Forever. Yeah, awesome. Okay, let’s do this. Let’s give our listeners a little bit more of your background for some context. Because you’re you’re not in Beijing for sure. No,

Jingjing Zhong 2:05
not. So I’m certified Chinese. Chinese passport right there.

Michael Waitze 2:14
Oh, wow. Where Chengdu don’t do Oh my god. I was with somebody last night talking about this who was also born in Chengdu and especially going back there today. Anyway, go ahead.

Jingjing Zhong 2:24
Amazing. Well, you should 100% visit

Michael Waitze 2:28
I visited way before you were born. I was in Chengdu in 1991.

Jingjing Zhong 2:33
Right, that was that’s before it was what you’re right. Yes. So I went to us when I was 17. Went to Alabama. That’s why that’s where I learned English. And then I went to LA finish community college, went to Berkeley graduated there become an investment banker because I wanted to make money. And, you know, banking in San Francisco lost my visa in the US because Trump HMV and then went to London finish banking there. After that I just questioned my life because we did a deal. It was gambling deal, two largest online betting company merged together. And once they were together, they just do all the crazy stuff that’s not good for the humanity. That challenged me quite a bit. And that’s when I decided that you know what, I love startup I knew I always wanted to work with people. And I found this company that does cleaning. School unhelpfully. It’s the polar opposite of making money.

Michael Waitze 3:36
Helping people people definitely need cleaning. Go ahead. Yeah,

Jingjing Zhong 3:39
exactly. And so I joined them. So it’s a platform for home services. So I think Uber or home service, so I joined them came to Singapore for the first time with this job. And then from that point on grew helpling from a million to 30 million AR Oh, wow. Yeah, that was two years ago. And then I was 28. And then I decided that I have no dead no dog. No husband

Michael Waitze 4:08
did not just make that up. There’s a three there’s a three Ds you didn’t just make that up. Did you know

Jingjing Zhong 4:12
I did not make it up. It’s actually true that like I was thinking really, I have nothing to lose, you really have nothing to lose, right? So I decided to take some risks with my life and that’s when also when for some soul searching. And then now I’m here.

Michael Waitze 4:28
It takes a certain kind of person to drop out and become an entrepreneur. Right? It’s not for everybody. And it’s not a value judgment either. Right? Some people were talking about this before we started recording some people are just much more comfortable taking the more stable route. What is it about you like where does it come from this idea of you know what, no debt no dog? No. What was the other one husband? Husband? Yeah. We’ll use that later. Anyway, that said like now remind I don’t care, I’ll just take this risk, if worse comes to worse, I’ll go get a job somewhere kind of thing. Like, where does that come from?

Jingjing Zhong 5:05
Um, I guess it comes from a few things because I’ve been moving by myself since I was 17. Yeah, actually five before that, I’ve been going to boarding school, right. So I applied for PR in Singapore, three years ago. And then there’s some place where you need to fill out all your residential address every single place to where you stay six months or more, right? I think they have like 10 different columns. I ran out of columns. And I had to keep adding, keep adding. And I realized, wow, I’ve been going around the world by myself. And each time I managed to pull myself up. And then each time I managed to build a community around myself. And I think I was doing well in my own definition. So really, I believe any situation I can do well,

Michael Waitze 5:57
it’s so funny because this woman that I was talking to last night, also from Chengdu. She just said in passing, because I said to her, are you still friends with all the people you went to boarding school with? Right in China? And she was like, she said, we will. We’re all only children. So we got to be really close. I hadn’t, you know, when I was growing up, right? I understood like the one child policy, but it was so distant to me that I never really thought about it as I got older. And I was actually just about to ask her last night like, Do you have any brothers and sisters before she said that? And I thought, Oh my God, that’s right. Yeah, yeah. There are tons of just only children. And what it does is it makes I presume you’re an only child. No. Yes. Yeah. And that makes you super resilient. Super reserved. My daughter is an only child as well.

Jingjing Zhong 6:42
Oh, you see two different kinds of Pete shores? For sure. Your prince and princesses? Are there other types? That’s the only labor of the household. Yeah, I got it. Right. Yeah. If you go to China, talk to those single child who are still there. Most probably you’re going to meet the Prince and princesses. Okay. But for people who have left home, and they’re still the only child, probably they will behave slightly differently.

Michael Waitze 7:11
Yeah, it makes sense. And I think there’s a personality isn’t like an an embedded personality trait that separates those people. Even if your parents spoiled you like crazy. Sometimes you don’t turn into a prince or a princess if you’re really resilient, and also really just aggressive. Anyway. Very interesting. Yeah, I can see you thinking about it.

Jingjing Zhong 7:29
I felt like it was resilience is something you pick up. For sure. Suffering well.

Michael Waitze 7:37
Yeah. Yeah. Look, I moved around a lot as a kid as well. And I think made me super resilient. Same, same as you. Maybe not as many times. But I remember like, every time I moved, I thought, You know what, I can do this? Yeah, I can do it. Yeah. Okay. Yeah. So talk to me. So you were working at help bling. I liked the name of bling. But now you’re doing something called Super bench. So what talk to me about Super benches, and then talk to you about why. Yeah,

Jingjing Zhong 8:05
so super bench is an AI powered operating system for home services companies. Okay. Think about it like a back end. And whether AI coordinator attached to it. The job here is the AI can help companies to coordinate with their customers and their staff. So give you a scenario, Michael. Now you run a plumbing company. Okay? You have seven plumbers, and 83 customers who needs help next week. Okay, Michael, I need your help to plan their schedule for next week. But you’re smart, you can still figure it out in spreadsheets, right? Like you used to be a banker, you know how to use spreadsheets. Okay. So now you figure it out. You have to call all these 83 customers to tell them that, hey, your schedule is Wednesday morning. If one customer says no, I don’t want it. You have to replan the whole thing?

Michael Waitze 8:58
Too many moving pieces? Yeah. But the reality is

Jingjing Zhong 9:01
that every single customer wants morning.

Michael Waitze 9:05
Yeah, probably because they don’t want to they don’t want impact the middle of their day, I hadn’t thought about it right. But like, let’s get it done by 10 or 11. And then I can do my rest of the desk start a little bit later. But I can end later as well. Whereas if it’s at three o’clock in the afternoon, like I can’t leave my job. And I can’t go back now and when do I pick up my kid and like nothing works anymore. And again, I was having this conversation with somebody yesterday about something else. If one person cancels, it doesn’t just impact that one person. It impacts the entire scheduling and their families and their grandkids and like everything. So it’s a complete nightmare. Is this something that grew out of your work at helping you because it’s the same thing you’re thinking there’s got to be a better way for everybody to schedule I’m gonna go build that thing.

Jingjing Zhong 9:44
Yeah, so it’s not just a scheduling problem. When you want to book service, it’s about as a five component. It’s what they end time where what’s the scope after scope is allowing on pricing eventually, who’s delivering service because that person goes into a hole. So there’s a trust factor there. So five things, right? align all these five things upfront. Otherwise, your sales from the company’s perspective is incomplete. Your schedule, your appointment is not settled, right? So with these five things, you have to align upfront, there’s a lot of backend operations, communication that has to happen to align with what the customer wants. So if we can do this instantly, then I can make that sale instantly, that will improve the conversion a lot more right at that also make end consumers experience much better. So what I’m trying to do is basically that with AI, so let’s

Michael Waitze 10:41
walk through this right? And let’s I like to do this in like me like a two person, like a to customer scenario with like a two plumber scenario, right? In one company. Let’s just do it this way. Yeah. Both of us want to be scheduled at like 10 o’clock in the morning. So somebody has to have no set to them already. That’s about experience. But I can’t be No, I can’t believe it live. I already scheduled the other guy at 10. Right? Yeah, but if anything changes, I can always just pick up the phone or text somebody, I’m guessing right. But you could pick up the phone say, look, I cannot do 10 o’clock for you. And you just go back and forth. You fix it. Two people, one of them’s not so satisfied. One of them is not everybody wins, but most people win. Yeah. But that communication part is actually really important. No, it is 100%. And it goes all the way around to so the plumbers have to be, you know, spoken to the dispatcher suggests we spoken to end on the client. Sorry, I interrupted you. Yeah,

Jingjing Zhong 11:34
yeah. 100%. But the thing is that what, for example, if you want to schedule a haircut appointment, right, you go to your barber, you’re like, I want to get a haircut took you like, oh, 2pm and book, what about three? Right? It’s right

Michael Waitze 11:48
all the time. All the time, all the time. But

Jingjing Zhong 11:50
you don’t get upset. You kind of understand it, because people are busy too. Right? But the key is that if they don’t tell you, sorry, 2pm doesn’t work. Instead, they wait for three hours then tell you Sorry. 2pm doesn’t work. Now, that creates frustration, frustration,

Michael Waitze 12:06
regrets, anger, yes. serious anger. Why don’t you tell them? But if

Jingjing Zhong 12:11
they tell you right there on the spot, instantly, that’s acceptable.

Michael Waitze 12:15
So what does it look like? Yeah, I may not be happy, but at least I’ve been told, right. And this happens all the time. My barber I go in, and I’m like, Can I do it now? And they’re like, Well, we’re super busy today. How about tomorrow? And I can see the schedule. Fair enough. I just do tomorrow, two o’clock, and I walk out. But how does it work with AI? I’m really curious about the process. Do you don’t even Yes, yes.

Jingjing Zhong 12:35
So basically, for example, Michael, you want to book a cleaning for next Wednesday morning night? Yeah. Okay, submit a request, an AR would take your address, your zip code. And then and also your time you were requested, the end time and the job that to be done, right? And then we’ll go to the backend and take the all this information. And it’s a traditional engineering process to it’s a rule based matching, we’ll figure it out. Okay, number one, who is free? Number two, out of all the people who are free? Do we have someone who can get the job done? Number three, who’s the closest? And if we have someone come back? Yes. If we don’t have someone, we’ll figure out who’s the best person for the job and come back to you with the proposed time. Can

Michael Waitze 13:18
I ask you a question about this? Yeah, I do this all the time. And tell me you haven’t had this experience. You get into a grab or an Uber, right? Yeah. And the driver is just so good. Yeah, you don’t I mean, like, she’s so nice to you. And she’s really polite, and she’s driving just fast enough, but not too fast. You just have a killer experience. And you just say, Do you have a card? Because in grab like you can’t, you can’t order the person? Ah, yes. You don’t I mean, so for me. And again, you said it’s trust, right? This is really important to me. If I’m going to let somebody into my house, at some point, I want the same guy to cut my hair. Right? Like when I walk into the barber, I’m not like anybody can cut my hair. And it’s the same thing for plumbing, because that’s the example we’re using. Is there a way to use the AI to understand that not only is somebody available, somebody’s in my neighborhood, someone’s available at that time somebody has this skill, but it’s the same person to do it last time, and I want that person back kind of thing. Yes,

Jingjing Zhong 14:14
they are customers coming in just straight up asking, Hey, I like unko. Yeah, well, he’s very good. When is he free? Then we just check his schedule. And then we recommend a slot where he’s free. Got

Michael Waitze 14:26
it. And if you built all this tech, yeah, this is really complicated. No,

Jingjing Zhong 14:31
it’s not that complicated. Really, it’s rule? Yeah. Because the whole matching algorithm, it’s a static static rule based matching. Got it. Okay. Okay, you can do it with the spreadsheet. So the thing is that okay, the reason for me it’s not that complicated is because I’ve done it with people and process and data I hopefully, right. Yeah, we have an army of people to ensure this instant back and forth happens a The West you lose customers the moment they have to weigh for No, that’s a hard no. Yeah, they can they can get, they can get a note instantly. And if you recommend a different slob, likely they will be okay with it. Right? We have to make sure this time the speed is the key here for sure. And that’s what we’re trying to do with AI. Do

Michael Waitze 15:20
you hear about did you read? And I’m trying to remember where I read this. But did you read about this story where Amazon is shutting down some of their stores that they have where you’re just supposed to walk in, pick products up off the shelf, put it in your own bag, and then just walk out? And then you get a receipt and a bill afterwards? Have you heard about these stores?

Jingjing Zhong 15:36
I’ve heard of these stores? They’re shutting it down. They’re shutting

Michael Waitze 15:38
some of them to I think unless we can check this when we’re done recording, but I’m pretty sure I read this or heard this somewhere. And one of the reasons why right was because it was supposed to be a massive cost savings for them, right? Because it was all AI enabled. Yeah. And all, you know, machine learning in the background. And apparently what they had done was because they had cameras and sensors in the store. Right. So apparently what they had done was they had hired an entire like team of people in like Bangalore somewhere in India, to watch the camera footage in real time. And just like write down, that guy bought Q tips, that guy just bought shampoo, that guy just bought this. And that’s why it was taking like a few hours to get the receipts to people because they wanted to confirm.

Jingjing Zhong 16:21
Really, because

Michael Waitze 16:22
it was that hard of a problem. What you’re doing is different, but I just thought it was really funny that in this whole AI hullabaloo that even Amazon with all of the resources that they have, couldn’t at least get it done yet, but it’s different than what you’re doing. I just thought it was a funny story that I wanted to share with you. Because it just reminded me, I

Jingjing Zhong 16:39
assume that probably was their MVP, for sure. They’ll come back with it for sure. Yeah. Yeah, I think for for AI, right. There are a lot of challenges building with generative AI as well. Right? For example, multi agent framework. Maybe just for everyone’s purpose, right, like so. A generative AI if you ask it to do one single thing, it’s very good, right? For like, if you like your job as a math teacher, now you have, sorry, this is a terrible as terrible math. Your job is to create a beautiful paragraph. could use this to fit into some Taylor Swift song. Right? One job fair? Well, however, you can say that your job is Taylor Swift’s marketing manager plus her Graphic Designer Plus her accountant impossible that Miss nating. Yeah. So if you want to create like Taylor Swift, best assistant, you have to create different agents for different roles specifically and pieced together then you get one thing, right. So but this is what we call multi agent, each agent has its own role. However, if one rely on another person’s cues to do their job, right, one person hallucinates 10%, the second person will hallucinate. 20% and the third person by the end of it, you’re going to get

Michael Waitze 17:59
a bunch of agents basically. Yeah, exactly.

Jingjing Zhong 18:02
Exactly. So this is the problem with multi agent framework. So this is a challenge that no one really, really have solved it yet. And so everyone’s trying ways to make it better. But yeah, to be

Michael Waitze 18:16
fair, we have the same problems for humans, right? Like if I’m working in Morgan Stanley, and I say to the guy sitting next to me, can you please take care of this thing? For me? He’s like, I’ll do it. But he kind of didn’t want 100% understand what I said, but didn’t ask the next question. And then he goes to the other office until some later to do the other thing. And then it goes until somebody else to do something. By the time it comes back to me, it’s all wrong. And I’m like, why? So it’s not Yeah, it’s not even that easy to solve for humans. We’re talking directly to each other and are meant to be educated. I think this is gonna be really hard to solve with tech. Can I ask you this too, though? Yeah. And again, just because you use plumbing as the example. Yeah, these are kind of fundamentally small businesses. But there are a few challenges here. I think some small businesses try to like write their own software, like I’ve done it myself, kind of thing. Like, I’ll just write my own scheduling spreadsheet or scheduling software. But then, which is hard to do and hard to maintain. And as things change, it’s like hard to keep up. Yeah. But on the flip side, because they’re small businesses, they don’t have like an IT department. So how do you how do you handle that? Because to me, and you’ve mentioned this to me, right? I’m like, This is not my idea. But I think if you’re a small company, you’re not putting tech into it. You’re dead. At some level? No. Yes,

Jingjing Zhong 19:25
yes. So either they’re stuck at let’s say, five headcount and just making you know, a few few 1000s a month, or the moment they start scaling, they realize that the bigger the revenue it is, the smaller the margin will get. Yeah, your net economic doesn’t make sense anymore. And that’s when they will start thinking about what part of it goes wrong, right. So if they write their own software, a lot of times it because there are a lot of operational gaps, and they try to fix it with people and when they write software They tried to write software for the people’s gaps, right. And that’s when the kind of band aid solution. So if you don’t ever change the process the operations, and you tried to buy a different tech to fix as a stopgap measure, it would never work. Right. That’s called customized solution. And so that’s why a lot of companies when they want to grow, they also have to restructure the whole how the company wants to the org structure. Yeah. So. And that’s when, when what that’s why for these mom and pop shop, when they go through digital transformation is so difficult, because they were realized, it’s not just implementing tech, it’s also pushing process also people and the moment tech into something that people used to do they feel threatened, right? You will have resistance from the ground like, oh, this technology is not good, because it takes our customers information. No, if they feel threatened.

Michael Waitze 20:58
Right, which is fair. But again, the implementation stuff is always more complex, I think, than some of these companies, at least initially realize. Because you’re right. It’s not just inputting text, I mean, tech, and then keeping all the business processes the same at all, actually, it’s my effect when you input tech into a business. And we saw this even at Morgan Stanley and Goldman Sachs, the whole, the process is different, because now you can do things you couldn’t do before you can do them better, you can do them faster, you can do them in a more productive way. Yeah. But the whole flow changes, because now you can like do this thing beforehand, because it already has the information that maybe you got afterwards. It’s just a different business flow. And how does that work in these small companies? Like how do they even get their heads around this?

Jingjing Zhong 21:45
Well, they just basically hire more people to kind of the problem until their margin is so thin, right? So for kind of, in my industry, Ali’s for home services, it’s such an operational heavy business, right? So you realize that companies 99% of the time, they run the whole operations through chats, every single thing, like who goes to where who should take this customer, everything’s through conversation is a discussion amongst the team. And so the source of the data, that’s where it’s crucial. It’s from customers conversation and internal conversation, right? If you’re able to aggregate the raw data from the source, and then pass them in the right way, then you don’t need people, let’s say coordinators in the middle to coordinate, right? Yeah, if you have these, if you can extract the raw data and present it in a way that every single department the moment they log into the system, they know that they don’t have to talk to each other anymore, because they can just see it, they don’t have to check Hey, is is he really on the way? Does he have a job? Can Can Jim takes this job, right? Then that way that really fill in a lot of communication gaps, and also for them to hire more people.

Michael Waitze 23:04
So what does that mean? Does that mean you connect your system, your back end operating system, right. And I love the fact that you call it an operating system? Because from a business perspective, those are the best businesses, right? You’re not building a product. You’re building a plan. Yeah. And that’s way better, I think. Sorry, did I interrupted you go ahead?

Jingjing Zhong 23:19
No, no, not a problem. So yes, it is a goal to build a future of operating system. So if you think about it from the past, right, we call it service now for Asia, right? Service now is the operating system for service industry. They allowed you to have, let’s say customer information, CRM, and also the supply the workers information, like calendar, everything in one place. So you can do invoicing, customer acquisition, assigning jobs, notifying jobs, doing payroll everything in one place, right. The problem with that is that it’s so complicated. It’s a huge onboarding process with data ingestion. Yeah, problem, right. And then companies, they have to have a separate it in order for them to kind of use software like this. I believe in the future, an operating system should be something that’s super easy for people to come on board, right? You just have raw data, ingest it done. And for people who are using it, they don’t need to know where to go to find the information. They just ask. So it’s not going to be click this button. Step one, click this button. Step two, click this button, step three, cancel and then do 123. Right. It’s like, can you help me to understand who went to Michael’s home last time? Who fix Michael’s plumbing issue last time, right? When is this person free? Next, right. Assign this person to Michael on next Wednesday morning. Yeah, that’s it. Yeah. I believe that’s the future of operating system. So is this going to be a platform potentially If we tried it, right, we build a platform, but I realized, maybe that’s not going to add so much value, we still have it. But what’s really going to be important is the data how clean the data is. Because that will determine whether your AI can do the job or not.

Michael Waitze 25:20
What type of in or I’m just thinking about the implications here, right? So what type of interaction would say like a plumber have? And again, we’re just going to use this the whole time, right? So when his job is finished, when he’s actually done the job? Does he does he just say like, Okay, I finished at Michael’s apartment, everything’s done. Do you know what I mean? Does he have to click something? And if he doesn’t do that, because you’re talking about clean data, right, I think about this all the time. If I get and I’m thinking about sitting on the portfolio trading desk with Goldman Sachs, if a client sends me an order, right, yeah, for 6758, which, if my memory serves me, correct, is Sony. Right. But I put an order for 6578. It’s all wrong. Yeah. Right. And we built a whole bunch of technology around that interaction to make sure that we were never wrong. Yeah, because it’s fatal. Cummings not fatal, but it’s still bad. Right. So how do you ensure that all the data that you want to be cleaned is clean? Do you know what I mean? After the work is done? Or anywhere in the process? Yeah, cuz that’s tricky. No.

Jingjing Zhong 26:22
So there’s two parts. Number one is, you need to have clean data to begin with. So the data cleaning and data ingestion problem. Second part is to keep the data in sync and constantly updated. Right? So the updating data part, you need to first figure out, are we using people to updating it right now? If it is, how can we automate that process? How can we trigger people to best updating the data? If people are updating that literally, they have to go in Google Sheets to key in, obviously, you’re going to get tons of mistakes? If you just ask people send me send your whatsapp question, Michael, how was the plumbing? And if you don’t reply, then I will send a message to let’s say, the plumber, did you finish? Right? Let’s say your appointments from three to 6pm. At 6pm. I’m going to send both sigh a message. So for you, it’s like oh, the company is like actually checking whether they whether I’m satisfied with the service on the plumber is like, oh, did you finish? Let’s say if they extended an hour, let’s say it’s an hourly service, then I would know, right? Like, oh, if plumbers reply at 630, saying that I just finished then I know that this job actually took them longer. Then I went off, maybe I’ll notify the next customer. Sorry, the last job lasts longer. He’ll be 30 minutes late. Right? So

Michael Waitze 27:41
I love this. So let’s run through this again, just really quickly from a flow perspective. Yeah, I put in an order I need some work done in my house, I put it in an order your system grabs it, it does all this work in the backend to see, do I want the same person that had before? What neighborhood? Am I in? How much did I pay? Like what is what is the skill is necessary to do this? And is anybody in that area available at the time that I want? Let’s just say that that works. But now your your operating system now has all of that data, it knows that that’s been agreed upon service, right between me and whomever you’re sending in it also knows the times. It also knows that if they’re coming at nine o’clock in the morning, they’re probably going to be finished by 11. You can actually have a time based event that sends a sends a text to me because I’ve allowed you to that that says, Hey, how was your experience today? If I even if I just wrote back? Okay. Yes, you know, it’s done. Yeah. And then that triggers internally going, Okay, now I can take that data, put it into my real database know that, like that thing happened at this price at that time by this person with that payment? Yes,

Jingjing Zhong 28:42
exactly. Okay, triggers payment. If your reply, not okay, immediately, you’re gonna get a call from some from somebody on the ground, offline, offline experience feedback, right? In a future. The key for companies to have good retention is to collect this feedback loop. And how do we link it up? Is one just by asking the customer how was the job right? You incentivize customers to tell you exactly what happened. If if they just said okay, you can ask more questions. Did you like to hear arrive on time? You know, the heat quote dude, this amount Exactly. For example, like aircon cleaning a lot the upsell you on the spot? Right? Did he upsell

Michael Waitze 29:26
for air conditioning? Cleaning? Really? What’s the upsell?

Jingjing Zhong 29:29
Yeah, so they will say it again. So chemical washing so normally an air cleaning costs like $50 but the moment is chemical washing that 5x That’s the average order per trip. Yeah, I’m not kidding. I love it. I thought otherwise for aircon cleaning, imagine right that goes through. They have to go through eight houses a day in order for them to break even if they can upsell is three houses.

Michael Waitze 29:57
Got it. Of course it’s five times the price or 40 I’m sorry, that’s whatever it is. Okay. Yeah. Really interesting. So what’s the status of what’s the status of super bench right now.

Jingjing Zhong 30:08
So we have a for design partners at this point in time. So for clients, and we’re building with them, what I want to do is to really, so we’ve ran some tests with our clients. So because we’re booking customers in instantly and scheduling them instantly, we were able to increase the conversion from 20% is like an industry standard. So from inquiry, hello to pre event pay confer confirming event, right? from about 20% to 50%. Okay,

Michael Waitze 30:40
that’s more than a little. It’s a lot.

Jingjing Zhong 30:43
I mean, imagine your marketing dollar, the ROI is so much higher, because now you can have you spend the same money, but you acquire a lot more customers, because conversion is much higher. So we want to expand this with all the AWS six design partners that we will have will have I want the whole industry be like, What are they doing? Why are they why? How can they spend so much money on marketing that? Well, because the CAC is really low? Guess what? Because the conversion is insane. And I think we want to experiment a lot more with this piece. We want to see conversion, uplift, sales, uplift, but also on a cost saving side because sales and scheduling. It’s about 80% of the total conversation that I have got it. So if we can automate this, that’s a huge cost of initiatives for these companies as well.

Michael Waitze 31:33
And when did you start actually working with these partners? Like, is it a year ago? Is it recently?

Jingjing Zhong 31:41
So we officially registered the company in Singapore in September last year. And we finished kind of ideating in October ish. And we really started this year,

Michael Waitze 31:51
January. It sounds like it’s going really well. And have you raised any money? Yes, I

Jingjing Zhong 31:56
did. So yeah, I finished fundraising in January. So I will say we actually started in January. Wow.

Michael Waitze 32:03
And this is before you saw these conversion changes, and the customer is coming on board. So somebody who saw this actually believed in it. Yeah.

Jingjing Zhong 32:11
Yeah. Because I solve this with people and process that hopefully. Yeah,

Michael Waitze 32:14
no, no, I get it. It’s not shocking for me that it did. It’s just that sometimes the venture capital community or the even the angel community can be a little bit slow and understanding things, right? Even if you know it’s going to work, right? If you if you go in with 100% pure passion, and like I’ve already done this over there still sometimes are a little bit slow and saying okay, because they’re so risky. It’s just been my experience anyway.

Jingjing Zhong 32:37
I guess I’m lucky. People, I do tell people that I feel like I’m lucky in during my fundraising journey. Right, like, because I know a lot of people, I think a lot of people are talking about creating luck. And I think I leverage that quite well back then when I was in helping so I know a lot of people in Singapore. And that really helped.

Michael Waitze 32:57
Yeah, I I kind of like to use the word fortunate unless you’re going to define luck and fortune as the same thing, right? Because I think you could definitely create your own fortunate pneus. Right, but just like working really hard, being really smart and doing the right things. And the other thing as well as I think people that have I want to back up for a second. I think charisma is something you can’t buy, you can’t teach. And you can’t learn by just don’t think you can. I think you either have it or you don’t. And maybe that’s one of the fortunate aspects of you is that there’s a certain amount of charisma there that when you walk in the room, people feel like, I think I can trust her. She knows what she’s talking about. No,

Jingjing Zhong 33:42
thank you, I think, yeah, I guess this is like part of luck. You know, previously when I was recruiting cleaners at helpling. So during COVID, we recruited a lot of Vietnamese cleaners, because you know, they use a clean hotel, they don’t have a job anymore, when train them repurpose them for home cleaning. Obviously, I don’t speak Vietnamese, I speak Chinese. And then this one lady, she came in, she saw and she doesn’t really speak English as well. She says, You have good face.

Michael Waitze 34:14
But tell me this. I think a kid learns really early on in their life. Whether they and they don’t understand the word charisma, right? But this idea that they can just kind of figure out a way to get things done, and get the things that they need. And I think that as you continue to get older than you realize, oh, that’s the risk that everyone’s talking about kind of thing. And then you once you learn how to employ it, then you’re unstoppable, like unstoppable.

Jingjing Zhong 34:44
I think a different way to say this is know your strength. You’re creating leverage based on strength. Exactly.

Michael Waitze 34:50
Yeah, right. Same thing. Yeah, same thing.

Jingjing Zhong 34:54
Same thing. Yeah.

Michael Waitze 34:55
Okay, look, let’s do this. There’s so much more to talk about, but I want to leave a little bit on the table. All right, because if you started in January of this year, and what did we end of April? Yeah, it’s four months. I want you to commit to coming back on like in October. Please, please. Because I want to see what because I want to see what happens now that you’re not testing revenue. Do you have clients on board? Yes, it seems working, things are going back and forth, things are gonna get way more complex, right? It feels like, Oh, it’s just this rules based thing, and it’s gonna be okay. But there’s always things that are unanticipated. Yes, I’m sure you’re gonna be able to solve them. But I want to find out how that happened. And what happened and like, whether somebody came and asked you if you wanted to raise more money, and all these other things that happen after you’re in market. Remember, we talked before we started recording about, the more experience you have, the more context you have, and then the more things you can learn? Yeah, so I know you did a whole bunch of really great stuff at helpling. And now you’re employing a lot of that knowledge now at the bench. But now it’s your own. Yes, I want to see what happens. Is that cool? Yeah,

Jingjing Zhong 36:07
that’s cool. I love this too. It’s like keeping myself accountable when I need to come back with a million arr. Yes.

Michael Waitze 36:16
You can. No, it’s not a problem. Okay, let’s do this. I’m gonna thank you. JingJing Zhong, a co founder of Superbench. That was awesome. I cannot wait to come back into this again.

Jingjing Zhong 36:25
Awesome. Thank you so much, Michael.

 

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