Elevating E-Commerce with AI: A Conversation with Digital Genius Co-Founder Bogdan Maksak

Unlock the secrets to elevating your e-commerce customer service with our latest guest, Bogdan Maksak, the dynamic co-founder, CEO, and CTO of Digital Genius. 

As we delve into the AI revolution in e-commerce, Bogdan reveals how their cutting-edge platform is not just responding to customer enquiries but predicting and resolving them even before they arise.

Picture this: over half of customer service tasks effortlessly managed by AI during peak business times, ensuring your customers feel heard and helped without delay. Our chat with Bogdan serves up a treasure trove of insights into enhancing the customer journey from browsing to post-purchase satisfaction.

Imagine a shopping experience so tailored that it feels like your digital concierge knows you better than you know yourself. That's the world Bogdan and his team are crafting through AI-powered customer service, where every interaction is an opportunity to impress and retain. 

We discuss the power of real-time AI interventions in scenarios like delivery delays, offering solutions straight from the chat interface. This isn't mere convenience; it's critical infrastructure for growing businesses aiming to scale without a hitch. Bogdan takes us through the seamless integration of AI with various systems, painting a picture of a future where efficient, proactive customer service is the cornerstone of e-commerce success.

Wrapping up, Bogdan shares his philosophy on transformative thinking and its role in achieving breakthroughs in business. It's about the courage to make bold moves and the vision to see beyond the horizon. 

This episode isn't just a conversation; it's an invitation to embrace the transformative power of AI in your e-commerce operations. It's a glimpse into how strategic, big-picture decisions can drastically enhance not just your customer service metrics but the entire shopping experience. 

Join us and be inspired by Bogdan's insights into the potential for mega success when the focus shifts to ambitious, strategic innovation.

Transcript

Speaker 1: 0:33

Welcome to CX Diaries. Cx Diaries from the Customer Experience Foundation is our podcast where we talk to the people at the sharp end of CX and Contact Centres, the movers and the shakers, the innovators, the disruptors and the people delivering in the real world who share their stories of the personal journey through our industry. This week, I'm delighted to be joined by Bogdan Maxak, who's co-founder, ceo and CTO of Digital Genius. Bogdan, welcome, it's a pleasure to have you with us today. That's quite a lot of job titles.

Speaker 2: 1:05

Hi, thank you for having me today. Yeah, indeed, I've started as a CTO at Digital Genius and then gradually moved up to be CEO, and you know, like in any startup, you're varying so many hats. I could easily expand that with five other titles, and that would probably represent only 80% of what I do.

Speaker 1: 1:25

Right, okay, so give us a overview of the Digital Genius solution and how it specifically benefits e-commerce, businesses, etc.

Speaker 2: 1:34

Yeah, so essentially, at Digital Genius, we have a platform where we have conversational, generative, visual AI, but powered by very deep integrations for e-commerce.

Speaker 2: 1:46

So what that means for an end consumer if you have placed an order online and, let's say, the order is delayed and you reach out to customer service over any channel, whether that's voice or social media or chat our AI will understand what you're talking about and will actually see what's going on with that particular order, will perform some actions like expedite the shipping, give you the new estimate delivery date, make sure you've got all the information that you need, or we perform any actions to resolve your problem. For the brands, that means you know whenever they have a peak in customer service volume that often happens in e-commerce with Christmas, valentine's, any other sales they do or if you're very fast growing business, you no longer need to, you know, have that massive headache of bringing stuff temporary stuff on board, training them and then laying them off at the end of that peak. You know it can just essentially automate over half of your customer service using the AI.

Speaker 1: 2:53

So what are some of the common challenges that you see e-commerce businesses have when it comes to customer support and how your solution supports them with that?

Speaker 2: 3:03

I mean, I think the number of three use cases are you know, where is my order, where is my refund, how do I return on, or maybe some product quality issues? Yeah, and a lot of businesses invest into so many other tools, like having a tracking link, having some proactive communication, and they think, yeah, this will help resolve like those problems. They'll go away and guess what? They don't. Usually there's always something going wrong, whether that's a carrier problem where something doesn't get delivered on time or doesn't get delivered at all, whether it's something on the customer side or a warehouse blows up, there's too many orders, things are continuously going wrong and leads to customers reaching out about one of those topics and, yeah, that creates massive headache for the customer service manager.

Speaker 2: 3:54

On, how do you handle that peak? How do you handle that? The common answer is you know you would go out and look for additional team members, but you can't scale that quickly, you can't train someone overnight, you can't project that financially, and then you know you don't always get the best people. You know I've heard from some of our customers when they prepare for the peak, and a half of the temporary stuff they get at the end of it don't even make it because you know either they're not good or they quit. So yeah, it's a big problem.

Speaker 1: 4:29

So let's just unpack that a bit more. So you touched on wisdom refund returns. They are the big, big contact drivers for many e-commerce businesses. Could you perhaps give us some real world examples or case study of any e-commerce businesses? That seems some good improvements from putting in your solution.

Speaker 2: 4:50

Yeah, we have a range from purely e-commerce or e-commerce other businesses like market places examples being like on my Teresa to retailers that call on the Barrett. We have pretty much similar problems but depending on how far they are now joining, we resolve between like 30% to 70% of all their customer service volume, and that's just on the customer service side of things. There are also use cases in pre-sales where customers reach out because they are looking for some advice on what product to buy or some of the characteristics of those products, and that totally opens up like a different area of optimizing for conversion so that you know whenever they have visitors on the store you know they're more likely to buy. We've seen some very good results there too.

Speaker 1: 5:51

So what sort of data and information does your solution analyze and look at to provide accurate and efficient customer support?

Speaker 2: 6:02

Well, I think that's a really key question because with any AI or with any human being, they're only going to be as good as the tools you give them. If you don't empower it, it's going to be pretty useless. And this is at the core of what Digital Genius is all about. We've been doing this for over 10 years now and we very quickly learned that AI on its own is only going to be that helpful if you don't provide it enough of integrations so you can actually perform a refund or cancel an order or start an investigation with the carrier, If you don't provide it those tools you know. Yeah, you can answer some FAQ questions. They can maybe lead you to some self-service tools, but that is not the experience that makes customers feel like, wow, I want to buy again from this business. Therefore, we've built the platform powered by those deep integrations so you, as a brand, you can easily enable those types of actions for your AI.

Speaker 2: 7:13

Nobody likes doing integrations for everyone. That's like an area that rather like avoid. We know it's not easy to get resources for that. It's not easy for customer service team to advocate that this is a high priority. So, therefore, what we've done is we've pre-built a lot of those integrations. So you, as a customer service manager, you don't need to get any development resources from your IT team.

Speaker 2: 7:38

It's already everything pre-built for you, and that's the key here. That's what makes a huge difference between a chatbot that you interact with and it's a common bad chatbot experience to a chatbot that is like wow, my problem solved. For some use cases, we are able to provide better responses than the customer service agents because we have that data, because we have those integrations, and it's not so easy for customer service agents to quickly analyze lots of data or to perform all those actions on the carriers, for example. Therefore, we are moving from having chatbots that are, first of all, customers hate or, secondly, only getting as good as human. We actually get into chatbots. That could be the next generation of experience that even better than the customer service agents provide today.

Speaker 1: 8:37

Yeah, and I imagine that it's not just speed but it's the accuracy as well. That's important, that's improving on the human doing it.

Speaker 2: 8:47

Yeah, I mean the accuracy comes in two directions, right. First of all, is AI being accurate about understanding what the question is about, or AI being accurate in the response that it generates? When it comes to generative AI, we've all seen those examples of generative AI hallucinations and it is a problem still within the AI community. But that's again where a vertical oriented solution like ours, because we're focused on e-commerce, is a lot more powerful, because we already put a lot more safeguards knowing what type of things can go wrong in the e-commerce domain, what kind of hallucinations that I can produce in e-commerce domain and we've already put that to the gen stat. So that type of accuracy is very much manageable. It's on the AI side. But when you look at again the quality of things, which is tangent to accuracy the second part of it again the deep integrations is super key here because you want the AI that can provide you the information you're looking for. It might be accurate If the AI tells me my order is still being processed.

Speaker 2: 9:59

That's accurate information. But that doesn't really help me as a consumer. Sure, you just told me there's just more delays, but all I really care about is will it arrive on time? Maybe I've ordered that as a gift for someone. Maybe I'm going on a trip sometime soon, so I don't want just accurate information. I want information that really resolves my problem or addresses my ultimate goal. Here and again, deep integrations into the warehouse systems, into the carriers, is the key here to get there, and that's something we learned early in our journey and we've built a whole platform around that insight.

Speaker 1: 10:46

Amazing. Security and privacy are important considerations for many e-commerce businesses. How does your solution ensure the protection of customer data and other sensitive information?

Speaker 2: 11:01

Yeah, I mean I think in general. There's obviously the question about the generative models. Are they going to release some private information on information they've been trained on? In our domain, the way we use that is slightly different. We do not train generative models on any past historical conversations. Therefore it will never spit out somebody else's details from some training data it was trained on. We have a slightly different approach. We use generative models from the beg provide this live, google-like open AI to fine-tune and to make the responses that we generate more personalized, but it's never trained on the brand's historical data when it comes to generation. So there's never that case of some historical data coming out. And obviously all the integrations and everything else comes with a high degree of security policies and security standards. I would say in our domain, in our use case, it's not so much of an issue again because of the fundamental design of the system.

Speaker 1: 12:16

Okay, so what sort of feedback do you get from the e-commerce businesses that have adopted your solution? How is it helping them improve their customer service, etc.

Speaker 2: 12:26

Yeah, I mean, first of all, we are massively releasing the VR clouds, so we are automating, sometimes more than all of the customer service agents combined. Yeah, and it's a huge relief for the team, it's a huge relief for the management that they can plan ahead. But secondly, we're seeing also increase on the customer loyalty where when we can deliver those really good personalized responses addressing the problem, those customers are more likely to come back and buy again. So it's not just about the efficiency gains, it's also about providing the experience that makes our customers, or our end customers, come back and buy from this brand again, because it's a great experience.

Speaker 1: 13:20

And taking that further, in what ways does this sort of solution assist an e-commerce business in personalizing customer interactions, delivering a more tailored shopping experience? How does this all help?

Speaker 2: 13:33

Yeah. So I would say there are two key kind of use cases. Number one is pre-sales. So I'm an end customer. I'm maybe going to run for a marathon and so I'm browsing for some shoes for some trainers I'm not sure which ones would be the best fit for me in terms of my goals. So our AI takes all the product catalog and then is trained by the product experts, who really know all the key attributes of different products and what are the important factors when it comes to different decisions, and one day is able to have a conversation or fully conversational interaction with you to ask you some more questions like you know, where are you going to be running, where are you going to be training and then ask you about, like, your preferences on the fit and the questioning and things like this, and then recommend a very personalized product to you.

Speaker 2: 14:31

So that's on the pre-sale side of things and on the post purchase side of things. You know it's all about A being proactive, so we don't want to wait until a customer reports a problem, like I had the knowledge of my Wi-Fi over the weekend and I wasn't sure what was going on. Have I not paid my bill? Is it something on my phone. Is it the problem with my provider? Now, two minutes later, I get a text message saying we are sorry, there is some problem in your area. We'll keep you posted. And half an hour later I got a text message it's fixed now. That's the experience I want as a consumer for anything I interact with. We're delivering the same proactive customer service experience for e-commerce. If you see that you've reached on something like, we tell you once it's delivered, we might initiate the refund. Even sooner, we proactively tell you if something's been canceled, if something's out of stock, if it's delayed, if the carrier lost it somewhere. We continuously trying to be on top of things before you even notice the problem. And then, if you do notice the problem and reach out through those deep integrations, we fully resolve it. If I need to return something, I'm not going to be just pointing to some return portal. Actually, our AI will generate the return label right there for you, especially on mobile, where majority of the traffic is today, like I've been switching between millions of tabs and losing the conversations and then going back and forth corporate and other numbers between different tools, like in our conversation. Just give me what I need to do. Give me that return label. If I need that to send it back, we give me that QR code and that's what we're delivering because of those deep integrations with the whole e-commerce ecosystem.

Speaker 2: 16:18

Now we have hundreds of integrations from the carriers to the e-commerce platforms, payment providers, so that the customer just in the chat doesn't need to leave the chat. In the chat, they're full problems resolved. If I get an order that is stuck somewhere by the carrier, the tracking page still stays in transit, which is a very common kind of misleading problem that leads to people coming and asking what's going on. Now we're not going to tell the customer, yes, it's still in transit, and keep them waiting. We can see on the carrier with all our integrations that it's stuck somewhere, it's not moving anymore, and tell the customer.

Speaker 2: 16:57

The idea, indeed, is to start behind the scenes of your launch and investigation with the carrier, so the agents don't need to do that, and then we just offer the customer do you want the refund or replacement? All they have is to choose and then we perform the refund straight away. So, again, they don't have to leave that chat. All of that problem is resolved right there because of those integrations and that's why we can provide the best experience when it comes to AI in the context of customer service.

Speaker 1: 17:26

What about the scalability of this sort of solution? How well do you accommodate these e-commerce businesses as they grow?

Speaker 2: 17:36

Well, it's generally quite naturally scalable. Obviously, as you're growing from maybe serving just one market to serving like an advantage of the markets, there are more integrations that are involved because of our deep integrations approach. But because they're continuously something that we developed, we continuously just roll it out for everyone. It's very naturally part of the journey. Again, if you look back at some of our customers who grew rapidly on being one of them, we started working with them when they were relatively small. Now they are a multi-billion company, a public listed company.

Speaker 2: 18:15

A lot has changed between then, but the solution itself because it's AI and TAC it's naturally super scalable. We just had to keep on adding more integrations with just more carriers in different markets or with some new warehouses and things like that. It's super scalable by its nature and because of our approach that we don't come in charge for integrations. Integrations is like the nature building blocks of our platform and this is what we embrace. So if you roll out to other markets, we'll just release more carrier integrations into those markets for free, and so it's very easy for the brand to manage that. And that's again the power of using AI to address this problem, because it's super scalable, like all that attack.

Speaker 1: 19:10

And what about time to implement? I know that's often a concern for any business not to see comments about the time it takes to implement any new platform. How are you addressing that and supporting?

Speaker 2: 19:24

that Well, again, because everything is pre-built. This is where focus makes all the difference. We have pre-built AI, we have pre-built integrations, connectors into everything. So during COVID times we went live with some retailers over the weekend, like they signed on Friday on Sunday. We were live because they were very desperately looking to turn on all those automations. They had, you know, huge problem they were not ready for COVID type of volumes. So the platform is super pre-built in all its components and therefore we can go live from a couple of days to a couple of weeks, depends on how fast the customer wants to go. Yeah.

Speaker 1: 20:11

Amazing. What are some of the APIs or other metrics that e-commerce businesses should be tracking and monitoring and working against when using this sort of solution, and how that helps them measure their impact on customer support and business success? What are some of the APIs you recommend they look at?

Speaker 2: 20:31

Yeah, I mean, I think the GPI's that they already look at are things like average handling time of a customer service case, csat of those interactions. First response time is another one. But I don't think first response time is super representative because you can give them a first response, but that first response doesn't really resolve some of the problem. Like I mean, is it really that useful? Is it really the KPIs you focus on? So I think first response time is, yeah, it's kind of important, but I think the resolution one is way more important. But when it comes to then AI, how AI plays into this, obviously we accelerate that first response time by like 95% because the AI is gonna reply super fast immediately. We accelerate the resolution time or case handling time and then CSAT. In some of the use cases where we can provide those super deep integrations, we can even outperform the agents In some of the use cases where essentially we're given same information. It will be roughly the same CSAT as they already get.

Speaker 2: 21:45

And nonetheless, the proactive pieces is where you can help to look at things like deflection or things like cases to orders ratio.

Speaker 2: 21:59

You even optimize how you're already handling the customer service today, but ideally you don't want to have people to reach out to you to begin with, because everything is just smooth for them. And that's where being proactive if it doesn't resolve any case can reduce that cases to orders ratio, so that KPIs is crucial. Not that many companies are looking at that as a key metric, but this is how you scale. If you wanna grow super fast, ultimately, to estimate your costs you need to be on top of that cases to orders ratio. And then there is the pre-sale side of things, which is obviously to do with this convergence. And last point, which I think everyone is struggling with, is to understand the impact of great customer service on lifetime value. It's not a straightforward one, but ultimately a customer service department if they can prove that they're not there just to handle problems, but they're actually there to increase lifetime value of the customers, they'll be viewed as a different team.

Speaker 1: 23:19

Yeah, Okay, so what's the future? What are the developments and features that you are planning to bring to the solution and further benefit these e-commerce businesses? What's coming up next?

Speaker 2: 23:33

I mean, I think, first of all, from the consumer point of view, people will be buying more and more online. If you think of like cinemas right Like back in the day, people would only watch movies in the cinema. Now we only go to the cinema as a special occasion because we have amazing like Netflix and Prime and TVs everything at home is so well positioned. Similarly, I think in the future, consumers will only be going to stores on some special occasions. Everything will be so seamless to get things online and return them and try them that, like you wouldn't wanna waste your time on going to a show. That will be the change in the consumer experience. The AI will also be getting on me better.

Speaker 2: 24:22

You know we might have another breakthrough, like we had the breakthrough with child GPT. It seems like to happen at least like once every 10 years. Now maybe accelerate it. So AI will obviously be as good as you know we saw in the movies. I'm not talking about matrix. I don't think anytime soon we're gonna be having a problem where we are taking over the world. But you know, the imaginable best experience we can just talk to the AI and fully understand you and resolve everything for you. I think that's coming in the future and not very distant. So I think that's gonna be the custom experience, that's gonna be the tech, and then you know, from the brand's perspective, I think the best brands will be the ones who embrace it and provide a kind of experience, and I think most majority of it is just the question of who will be first to get there.

Speaker 1: 25:17

Amazing. And finally, Bogdan, what advice would you give to an e-commerce business that doesn't have this? It's perhaps considering the adoption of an AI ticketing solution to improve their customer support processes for the first time. What advice would you give them?

Speaker 2: 25:33

Yeah, I mean, I think generally we see that you know those who are thinking big picture, those who are ready to make, you know, decisions that are transformative in other ones who you know get amazing results. And often you might get stuck in a mentality of incremental improvements where you spend a lot of time, a lot of effort and a lot of money without really moving the needle too much, whereas when you do zoom out and you look at the bigger picture, like how can I actually get transformative results here and make some bold decisions is when you win, is when you achieve mega success. So I would recommend zooming out from that and look, you know, at incremental improvements by looking at the bigger picture, how to get there fast.

Speaker 1: 26:27

Amazing and, bob Dan, it's been fascinating to have you with us today. I've thoroughly enjoyed listening to this transformation story that you're able to deliver for both organizations and their customers. Hope our listeners have found this as insightful as I have. You can find out lots more about customer experience foundation at cxoorg. We hope you can join us next time on CX Diaries. Thank you.