Connect Beyond: Exploring Tomorrow's Technology Today

Dive into the transformative world of retail with host Margarita Lindahl, as she is joined by Dr. Vladimir Rubin, CEO of ADEAL Systems, and Jens Michael Pohl, Panasonic sales engineering manager. Discover how generative AI and automation are reshaping customer experiences and enhancing personalization. Learn about practical applications, such as interactive digital signage, and the challenges of data integration and cultural scepticism. Tune in to see how technology is revolutionizing retail while maintaining the crucial human touch.

You can find us on other channels:
Website: CLICK HERE
LinkedIn: CLICK HERE

What is Connect Beyond: Exploring Tomorrow's Technology Today?

Welcome to Connect Beyond, Panasonic Connect Europe's podcast, where we delve into the forefront of technology, innovation, and human connection. Each episode guides listeners through the evolving landscape of tech solutions, featuring insightful discussions with industry leaders and experts. As we navigate the dynamic realm of technology, Connect Beyond aims to keep listeners informed and inspired, encouraging a deeper connection with the latest innovations and trends. Tune in, broaden your horizons, and engage in the conversation of innovation and connectivity with us.

Welcome to another episode of our podcast, connect beyond.

Today, we delve into the exciting topic of the future of retail, how generative AI and automation are reshaping customer experiences.

I'm your host margarita, being joined by two fantastic guests today, Doctor Vladimir Rubin, the CEO of Adidas Systems, and Jens Michael Pol, Panasonic senior manager and technical field engineering.

Welcome everybody.

Hello Margarita.

Thank you for having us today.

Hello Margarita.

My pleasure, Vladimir.

You have a strong background in IT architecture and data driven solutions as to your previous various roles in consulting companies such as Gupgemini, McG and others.

And in 2017, you became CEO of your own company.

Ideal Systems managed to grow into a well known brand with more than 50 employees by now, focusing strongly on big data and AI services in retail.

So tell us please, what is it?

What motivates you within this technology area?

What raised your interest in exploring the intersection between AI, automation and retail?

Thank you for the question, Margarita.

So first of all, during the whole my life, the technology was for me like a hammer to hammer the nails.

But I would say that technology is so developed right now that it can solve real world problems and challenges.

And it's fascinating.

On the other side, I am absolutely passionate about automation because it really allows people to focus on creative tasks to make different jobs, which more creative, more interesting.

And AI today provides incredible assistance in predicting future trends.

And nowadays it also plays a crucial role in generating knowledge and new content and finishing with retail.

Retail is a very dynamic sector and somehow it touches every person's life in some way.

And this is also extremely fascinating for me.

So this combination together, AI, technology, solving real world problems, plus retail, I think that this is an incredible combination for the future and for building the company.

Quite interesting, Vladimir, back to our second guest, Jens.

Jens, we are Panasonic colleagues and know each other for the last 13 years.

I've always perceived you as almost a master when it comes to sales engineering and creation of customized solutions for your retail segment.

And the topics of AI and automation in retail were obviously on your agenda for many years already.

Even though the topic of AI is around for almost 70 years, it started to dominate the news headlines and LinkedIn feeds since two years, making generative AI accessible to everybody.

What is your view on this?

How is generative AI enhancing customer interactions, enabling also AI driven personalization in retail?

Yeah, Margareta, good question.

Thank you.

You know, I'm working with real customers in the real world.

So usually my aim is always to find the real use cases, to find real integrations and to make stable solutions.

So when I look, for example, in computer vision, computer vision is a good topic where you can say, this works very nicely with AI.

All analytics on computer vision are today can nearly do nothing without AI if you want to do it proper.

So far this is a nice example here when it comes to more like human interaction or things like this, and you say ah, we want to do a chat GPT, what's good?

But there still you need to have a look if the output is really, really good, if the output is what you really want to say, sometimes you also have to have a look at how can we provide a better solution and how can we do it overall for the customer that he needs it.

So my main thing here is it's nice, it's really good, and we have to have a look how we can integrate it to a customer, that it becomes a stable solution at the end.

And this is a trend I see, and the trend will follow and there will be new and more solutions coming up in the future.

Jens, you have mentioned it already.

Tell us about some retail solutions incorporating generative AI with an increased customer service in the store, on site.

Yeah, what we did, what Rajmi and me, and also of course his great team did, we had a discussion about digital signage.

And what I always use as a word is most of signage, what I see is more or less a bit boring with boring.

I mean, it is just showing some content that has been planned maybe six or twelve months ago.

So somebody says, oh, we make a marketing plan in summer, we gonna sell, I don't know, lemonade.

And then they show lemonade.

And this is planned in winter or beginning of the year.

So what we thought is, how can we do this and make it more interactive?

And this was at the end, the starting point.

We generated profiles, store profiles for our showroom, and said, okay, we have a certain number of people in the room, we have a certain age, gender and other topics, and we have weather data.

And then out of these data we generate slogans that make it look more interactive.

And not only look, it is more interactive than the marketing plan from winter, in summer.

All those possibilities in place are certainly amazing.

But what about the challenges?

What could be possible approaches to address those challenges?

Vladimir, do you want to go first?

Yes, certainly.

Margarita.

While the potential of AI and automation is quite vast, we must navigate through both technological and cultural challenges.

So technologically we address data integration and data quality issues in order to minimize data chaos and noise.

And for example, we used to adopt different kinds of low code solutions for more efficient data cleaning.

Processes.

Also, we should prioritize the customer identity issues and the respect for personal data in compliance with GDPR rules, since we're dealing with, with data and with best amounts of data.

So we strategically, for example, in this concrete project, we strategically use only essential demographic and geographical information, such as age, gender, number of people, weather conditions, along with anonymized transactional data.

The other direction are the cultural issues.

On the cultural front, I would say skepticism remains to be a barrier.

I used to look at this area for quite some time, and there is still skepticism there.

So many companies or people still don't really believe that this technology is within their reach, and that it can be advantageous without massive investments or extensive project timelines.

And in order to overcome this, we implement, for example, agile and lean methodology, which allows for a more adaptable and iterative introduction to these technologies.

Yeah, so far, from my point of view, I see that Vladimir has a very good kind of opinion from his technical side and a lot of experience.

I can, of course, don't have the depth what he has in experience, but what I always see is that people are first of all overestimating a new tool they have, and they try to approach a problem and just try to do the same they did before, only with AI, or they're not looking at the processes.

What I always see is you first of all have to clearly mark what you want.

And this is already the point where somebody says, as a company, ah, we want to integrate AI.

The question is, for what so far, we should really focus, and for what do we want the AI function, for what do we implement them, and what is the, at the end, what is the outcome for it?

So AI is also a chance to say, okay, we are looking what we are doing, what's always good, and in addition, we are then updating our processes and use them with AI, because then it becomes efficient.

And last but not least, what Vladivir says is completely, of course, important.

First of all, check your data, and you have to make sure all the data you are using for training and you are using in your system should be good.

So there's a lot of work before doing AI.

And it's like with every tool you need for your company, if you want it proper, you have to start designing properly.

Yes, I believe this is just another great example for the famous Amara's law.

So we tend to overestimate the effect of technology in the short run, but underestimate the effect in the long run.

So this is exactly also going in this same direction and in relation to automation and human touch.

When we talk about the human perspective within the game of growing automation, how can we find the optimal balance between streamlining processes and sustaining personal interaction in retail?

So I would say striking the right balance is indeed crucial.

And I would say that automation should be seen as a complement to and then, rather than the replacement for human interaction.

Although I'm a technical person still, I want to underline it.

Data and analytics and artificial intelligence.

They excel in the processing of large volumes of historical data, in identification of various patterns and predictions.

These tasks are challenging for humans, but when it comes to content generation, generative AI, for example, creates drafts, creates new content drafts that are then refined and approved by human experts.

This is the approach that we followed in this particular case of this project, and moreover, to finish the answer.

I would say that personal interaction with customers in certain scenarios is absolutely irreplaceable, and it remains a cornerstone of customer service excellence.

So I propose to look at AI as very intelligent, very helpful assistance to human beings at this point of time at least.

Vladimir, I completely agree so far.

The point is the real problem in retail today is a lack of stuff, and any job we can support by using AI is a real win for our retailing customers.

So they have to try to find a way how we can manage with less stuff, the same amount of work at the end, or even more work cause maybe more customers coming in.

So far I completely agree.

We have to see that we keep human touch.

That means there, the employees are there.

But for many, many tasks, we can have a look where we can support them with AI and where we can make even better and easier approach for people.

For customers dealing with AI.

Let us stay on the topic of human and AI collaboration.

Vladimir, how do you envision AI and automation completing human sales associates rather than replacing them?

Are there any strategies to ensure a seamless collaboration?

Sure there are strategies.

AI and automation are absolutely essential in streamlining customer segmentation and product recommendations.

But what does it bring to the sales representatives?

It enables sales associates to set the priorities to focus on relevant customers or relevant areas where they are most needed.

There are various examples from the practical projects in life.

Sales representatives used to focus on the customers of category a.

They know them personally, they make phone calls with them and so on.

But what about customers of category b?

Yeah, they are not yet so important, but they will become category a customers at some point of time.

High potential customers.

This is where AI, for example, and customer segmentation can give a good advice.

The other thing is no churns should be overlooked.

During the last years, we were speaking with hundreds of meterstand companies in Germany and I always ask the question, could you tell me this statistically, what is the customer churn?

How many customers are leaving your company during the last month?

80% of these companies could not give me the number.

So the technology gives the possibility that no churns are overlooked and that for example, salespeople can identify the champion customer who is becoming dormant.

And the key is for sure to facilitate partnership where AI handles the data heavy lifting, allowing human associates to apply their intuition, their relationship and their communication skills where they count the most.

Okay, let's touch upon the topic of changing consumers behaviors.

Obviously consumer behavior is constantly changing.

So how can AI and automation assist retailers in adjusting to changing consumer habits, particularly within an omnichannel setting?

Yes, thanks for this great question.

The life would be so easy if the behavior would not be changing every day and every minute.

Maybe some practical ideas from my side.

Also ideas coming from AI and data science direction.

So one thing that we are doing quite a lot is predictive analysis of consumer behavior.

So we are predicting the next best of our next order date, also predicting what would be the best products or product categories that can be bought.

The other thing is the second topic.

I'm a big friend of process mining technology and it helps incredibly in the tracking of omnichannel customer journeys.

So continuous tracking what customer is doing, what are the steps through all the touch points?

Yeah, so far I think so.

Same.

But what we shouldn't forget is that people really change every day.

What we learned in the past was people started mobile phones, so then they learned in corona a lot about QR codes, about online ordering and stuff like this.

So the people are changing and the question is always about interaction.

How can you interact with people in a store?

I see gestures might be something coming up where you can do with gestures, getting information about products, things like this, or maybe what also could be an option one day for getting the omnichannel thing, when somebody has a question about a product and he can ask somebody who's now in the store.

Certainly there is this famous saying of that there is nothing more constant than change.

So we need to embrace surely change in future even more, and look forward to all those interesting possibilities coming up.

And that brings us to the end of our conversation.

Thank you very much Vladimir and Jens, for your great insight today into the future of retail and the transformative role of AI and automation.

It has been truly a revealing discussion and to our audience look forward to more captivating discussions on the tech topics and innovations that matter.

Join us next time for another insightful investigation into the technologies shaping our future.

Until then, keep engaging, keep innovating, and stay connected with us.