Praveen Nara, CEO of Tech.us, explores AI’s impact on retail marketing and advertising. Praveen discusses leveraging AI for personalized consumer experiences, ethical use guidelines, and AI’s future in marketing. He shares insights on hyper-personalization strategies for retailers, AI’s role in engaging different generations, and its broader societal impact. A conversation bridging the gap between cutting-edge AI technology and practical applications in retail and advertising.
Episode Transcript
Announcer: Attention, marketers! Get ready to transform your advertising strategies with Bigeye’s new 2024 National Research Study, Retail Revolution. This in-depth report explores the rapidly changing retail landscape. You’ll find valuable consumer insights across key areas, including shopping behaviors, direct-to-consumer brands, sustainability, brand collaborations, retail advertising, influencer marketing, and AI. To download your free copy of Bigeye’s Retail Revolution, go to Bigeyeagency.com/retail-revolution. That’s Bigeyeagency.com/retail-revolution. Reshaped by technological advancements, new consumer preferences, and global events, Bigeye’s Retail Revolution is your guide to the future of retail marketing and advertising. Join the Retail Revolution!
Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS:
Praveen Narra: Hyper-personalization can benefit retailers, with up to 74% of consumers being more inclined to make repeat purchases from the brands that offer those personalized experiences.
Adrian Tennant: You’re listening to IN CLEAR FOCUS, fresh perspectives on marketing and advertising, produced weekly by Bigeye, a strategy-led, full-service creative agency growing brands for clients globally. Hello, I’m your host, Adrian Tennant, Chief Strategy Officer. Thank you for joining us. The rapid advancements in artificial intelligence and automation are transforming the retail landscape, reshaping how consumers shop, interact with brands, and experience products online and in-store. Bigeye recently published the results of a national study called Retail Revolution, navigating new consumer expectations and technology-driven innovation. We surveyed over 1,400 U.S. consumers aged 18 to 76, yielding new insights about the behaviors and attitudes of today’s shoppers. The report highlights a gap between brand marketers’ enthusiasm for personalized advertising and AI-driven technologies and consumers’ deep concerns about data privacy and the potential misuse of their information, plus AI’s impact on employment. To help unpack some of the results from the Retail Revolution report, our guest today is an expert in artificial intelligence. Praveen Nara is the CEO of Tech.US and has over 30 years of experience in enterprise software development and management. Under his leadership, Tech.US has executed over 1,300 successful AI, SaaS and mobile projects. Fittingly, Praveen started his career in the retail industry and has gone on to become a successful serial entrepreneur. To discuss how AI can support retail marketing and advertising, I’m delighted that Praveen is joining us today from San Jose, California. Praveen, welcome to IN CLEAR FOCUS.
Praveen Narra: Adrian, it’s my pleasure. Thanks for having me.
Adrian Tennant: Well, could we start by having you tell us a bit about your career and role at Tech.us, please?
Praveen Narra: Absolutely, Adrian. At Tech.us, we’ve been in business for over 24 years now, and we have successfully completed over 1,400 software projects. Some of the customers we serve include NBCUniversal, Synopsys, Tony Robbins, and many startups and small to medium-sized businesses. And we’ve been doing this AI for a long time before AI became cool. And as you know, AI became mainstream in the last couple of years, especially since the release of ChatGPT. But we’ve been doing AI for almost eight years in our business. And in fact, we built an AI-based chatbot, kind of like a mini chat GPT for a multi-billion dollar healthcare company over five years ago. And since then, we have built dozens of AI-based systems from healthcare to data analytics to computer vision and several other use cases.
Adrian Tennant: Well, as you know, we’re most interested in retail, marketing and advertising. So could you share some examples of how you’ve been helping clients leverage AI in these verticals?
Praveen Narra: I’m glad you asked that question. To speak specifically about retail industry, we are currently working on an AI recommendation engine that I believe is a game changer. And we packed it with features that address the most pressing challenges that retailers face today. At its core, our recommendation engine is about really understanding and anticipating individual customers’ needs. And the problem online retailers face today, Adrian, is that cart abandonment rates, for example, can be as high as 70% and the churn rates can be as high as 82% in some sectors. So what our AI does is it predicts these behaviors, allowing retailers to intervene with targeted offers and personalized experiences. Our AI recommendation engine is designed to help e-commerce businesses, not only thrive in today’s competitive landscape, but it’s also built on cutting edge technology using, at the risk of going and being a little technical, there is something called two tower architecture and also using generative AI. And what sets this AI engine apart is its adaptability. It supports 35 different AI based recommendation engines and integrates with leading e-commerce platforms like WooCommerce, Shopify, Magento, et cetera.
Adrian Tennant: As I mentioned during the introduction, Bigeye recently published the results of national research we conducted with over 1,400 consumers aged 18 to 76. Insights about the adoption of and attitudes toward retail technology feature prominently in Retail Revolution. Nearly half of respondents believe AI technology can improve their shopping experiences. Gen Z, those consumers aged 18 to 26, and millennials, those aged 27 to 42, are the most optimistic, with well over half thinking this way. Praveen, how can retailers leverage AI to create engaging and personalized experiences for these tech-savvy generations while also considering the preferences and concerns of older shoppers?
Praveen Narra: That’s a great question, Adrian. So if you think about Gen Z and millennials, they love novelty. They want to use AI-powered virtual try-ons, augmented reality product placements, or even AI-generated style guides to make shopping more fun and engaging for them, right? So the goal should be, in my opinion, to provide those interactive and immersive experiences. And if you think about examples of how other retailers are already using it, if you think about L’Oreal, they have an app and the app is called Style My Hair, and it uses AI to simulate different hairstyles and colors on live video of the user, allowing them to virtually try on and look how they’re going to look with different hairstyles. Nike offers Nike Fit. It features AI using a smartphone camera to scan customers feet to recommend the right shoe size and ensuring perfect fit for their foot, etc. And so I feel like gamifying these buying experiences By offering this novelty and also rewards and challenges and even social sharing options would be great ways to engage Gen Z and millennial users. But if you think on the other hand, older shoppers, right? they are a little skeptical about AI and providing them more transparency and control I think is the way to go and that should start in my opinion from being upfront about how the business is using AI for example letting the shoppers to know how their data is being used and to personalize their experience and give them options to just opt out and adjust their settings if they’re not interested in opting in. And there are other companies like Best Buy for example, they have a great way where users know exactly how Best Buy is using personalized recommendations and they can opt out. So, giving that freedom and flexibility to the users, depending on who they are, what their preferences are, and making it easy for them to buy from you, I think is the way to go.
Adrian Tennant: Love that. Knowing the audience and giving them options. Well, we asked our study respondents to imagine the world in 2030. Well over two-thirds of consumers believe that AI technology will personalize most shopping experiences within the next six years, customizing recommendations based on previous purchases. Praveen, what strategies should retailers adopt now to prepare for the shift towards hyper-personalization in the coming years?
Praveen Narra: Hyper-personalization, I believe, is one of the great benefits of artificial intelligence. Because if you think about, until now, emails that go out from retailers, they’re usually same emails that go to all users, or in some cases, they’re personalized based on categories. But what AI offers is hyper-personalization based on individual users’ purchase history and their preferences and likes and dislikes. And so there is research that actually shows that hyper personalization can benefit retailers with up to 74% of consumers being more inclined to make repeat purchases from the brands that offer those personalized experiences. I think that should be a focus for most retailers. But if you think about it, many retailers don’t have the data that is necessary to offer those personalized experiences because many retailers don’t even gather the data that is necessary. So I would say the first and foremost thing is to invest in data infrastructure that is robust and I believe it has to be permission-based so that you’re collecting the data based on users’ preferences and then capture the data so that you can use it to train your AI models. Also, I do believe that AI powered recommendation engines like the one we are currently building would be great examples because you can offer very personalized experiences. People who bought this also bought these other things, right? That’s one of the AI recommendation system that you can have. People who viewed these products also viewed these other products so that you’re introducing new products to the users based on their browsing experience. And there are 35 other recipes that we call. AI recipes that you can use to offer personalized recommendations. So I think as long as the businesses are being ethical about what data they’re using, how they are giving people to opt out and opt in, and then use those experiences to offer personalized buying choices for users, I think it’s going to be an awesome experience for retailers.
Adrian Tennant: Praveen, I love the idea of AI recipes. That sounds really cool. Now, we’ve talked about the retailer side of the equation. Obviously, they’re the ones that are most likely to have access to that first-party data. What are the potential challenges we may face as marketers and advertisers?
Praveen Narra: Well, I think the biggest challenge that marketers and advertisers face today is the privacy, right? And that’s why GDPR, CCPA and all these privacy laws are being enforced because people want privacy and they want choice. And as long as retailers provide opt-in and opt-out choices for them and provide the privacy and data security that is necessary, because we are seeing millions and millions of consumers’ data is being breached in even large organizations. So people are concerned about their privacy. So giving tools and choices necessary would be very useful. The other thing to consider is over personalization, right? So yes, you need hyper personalization so that you are helping the users to make the right choices easily without spending too much time browsing. that is really useful. But over personalization can cause kind of like creepy intrusion to some users. So you don’t want to be too aggressive with your personalization. It’s a fine line that retailers need to walk where they’re helping the users make the right choices without invading their privacy.
Adrian Tennant: Staying with what the future might look like, our Retail Revolution study asked a question we first asked back in 2021. That year, just over half of respondents, 53%, believed that by the year 2030, retailers will use robots for various tasks in their stores and AI for managing inventory, reducing the need for human staff. This year, the percentage agreeing with the scenario jumped to 73%, almost three quarters. Praveen, what factors might have contributed to the expectation that AI and robotics will be so commonplace in retail?
Praveen Narra: I’m not surprised at all with that statistic, Adrian, because we have all seen the rapid progress of AI and robotics capabilities in the last few years. And that has also become more affordable and accessible to businesses. Just a few years ago, we were predicting that some of the things that are happening with image creation and audio and robotics would take several years. But because of the progress in AI and the chips, thanks to NVIDIA, there has been an acceleration in how quickly businesses in AI were able to achieve some of what they have achieved. I think having that capability, for example, from improved computer vision capabilities for autonomous robots and sophisticated natural language processing for chatbots, et cetera, are making it possible for businesses to implement advanced AI and robotics. And of course, we have huge labor shortages today. So I do believe that more and more businesses are going to use AI and robotics in their businesses.
Adrian Tennant: Thank you. Let’s take a short break. We’ll be right back after this message.
 | Sachiko Scheuing: I am Sachiko Scheuing, the author of “How to Use Customer Data: Navigating GDPR, DPDI, and a Future with Marketing AI.” My book provides a practical and user-friendly guide to ensure your data-driven marketing complies with GDPR and other regulations. I break down key concepts and explain how to balance customers’ privacy concerns with the latest innovations in data-driven marketing. As an IN CLEAR FOCUS listener, you can save 25% on “How to Use Customer Data” when you order directly from my publisher at KoganPage.com by entering the exclusive promo code Bigeye25 at checkout. Shipping is always complimentary for customers in the US and the UK. |
Adrian Tennant: Welcome back. I’m talking with Praveen Nara, the CEO of Tech.US. We’re discussing AI’s impact on retail marketing and advertising. In Bigeye’s study, we found that 53% of Gen Z respondents regard the use of AI in retail as extremely or somewhat good, while 49% of Baby Boomers, those consumers aged 60 to 76, consider it somewhat or extremely bad. Why do you think there’s such a stark generational difference in the perception of AI?
Praveen Narra: That’s a good question. So if you think about Gen Z, they have grown up with smartphones and social media and ubiquitous internet access. You know, there are some studies where people get more stressed about not having internet access than not having access to food. So I think for Gen Z, it has become imperative to have access to technology, and AI is simply another technology integrated into their lives. Whereas for Baby Boomers, for example, they may be less familiar with AI’s capabilities and applications, leading to more skepticism and fear of the unknown. And if you think about Gen Z, they embrace augmented reality filters in apps like Snapchat, et cetera, and trying their makeup, virtually experimenting with hairstyles like we discussed about. So I think that created more familiarity with what AI can do, whereas Baby Boomers prefer to go in store and consult with sales associates and personalized recommendations, they may not be as super impressed with what AI can do. If you think about movies and media, Gen Z grew up with movies like Iron Man and Big Hero 6, etc,. that portray AI as helpful companions and problem solvers for the world, whereas Baby Boomers, right? You may remember Terminator and 2001, A Space Odyssey, movies like that, that depict AI as a potential threat to humanity. So I think that would have some level of subconscious fear in Baby Boomers about AI’s threats.
Adrian Tennant: I think you’re definitely onto something there. Yeah, generationally, big, big difference. Let’s zoom out a little. We’ve been talking about retail and advertising and AI. What’s your take on the ways that AI could actually contribute to society more broadly?
Praveen Narra: I think AI can have huge potential for society’s benefit. I think, like we discussed, enhanced personalization can have a major impact in how much time is saved. Think about Google searches, right? We used to do Google searches for most of the information. Now we can ask LLM whether it’s chart GPT or Gemini or other tools that are out there specific questions and it gives you personalized recommendations for the search query that you’re looking for. You can also have more personalized buying experiences. For example, Stitch Fix uses AI algorithms to curate clothing selections for customers based on their styles and profiles and etc. So that I think is going to be a huge benefit, saving a lot of time and energy for users, even on things like Netflix, right? When you are given recommendations that Netflix knows that you’re going to love the movies, you’re spending less time browsing, more time enjoying that movie experience. But if we think broadly, I think healthcare is one area where AI can have a huge benefit. It can assist in diagnosis, treatment planning, and drug discovery, and potentially leading to faster and more accurate healthcare decisions because In cases like cancer, early detection, early intervention can save lives. So I think healthcare can literally save millions and millions of lives and is already starting to doing that. If you think about how Google’s DeepMind AI has been used to detect eye diseases, with same accuracy as human experts. So I think there are huge potentials there. And I believe that AI is going to be ingrained in everybody’s lives so much that eventually I believe there’s going to be invisible AI. You take AI for granted. You don’t even realize that you’re using AI, but you are benefiting from it.
Adrian Tennant: That’s interesting. Well, obviously some of us feel that way already about internet connectivity.
Praveen Narra: Exactly.
Adrian Tennant: Praveen, you have three decades of experience working with clients across multiple sectors. What skills and expertise do retail marketers and advertisers need to develop to leverage AI most effectively?
Praveen Narra: I think we already spoke about some of these experiences. And my recommendation to marketers is there are many options in how AI can be leveraged, but some people are a little bit concerned. And so the goal should be to start small, but think big. Don’t feel pressured to overhaul your entire marketing strategy or retail strategy with AI overnight. Begin with a pilot project. I’m a big believer in agile methodology where we do sprints. So you take a solution that you want to build, but build the core functionality first, test it out with your users, see how they are benefiting from it, get feedback and bring that feedback loop into how you’re implementing your next step. For example, a small e-commerce business could do an AI-powered email marketing platform to personalize their product recommendations and see how that’s going. And the benefit with a tool like this is you can A-B test. You can divide your segment into two or even multiple segments. Try one segment where they’re getting AI-powered email marketing emails, but the other group is getting regular emails that you have been sending for last several years. And now see, okay, is it helping with AI-powered emails or is it not helping? And trying multiple times, tweaking how you’re using AI can help you understand how you can benefit from it. And also I am a big believer in solving real problems that your customers face. Don’t just use AI because it’s the hottest and coolest thing that everybody is talking about and there is a lot of hype in the market. Identify the real pain points that your customers are facing or inefficiencies are currently existing in your business and then figure out, okay, here are the problems that I want to solve for my business and for my customers. And let me figure out how AI, or for that matter, any technology can solve that problem. Sometimes customers come to us, Adrian, wanting to build an AI tool. And when we really talk to them and understand what they’re trying to achieve, sometimes an Excel spreadsheet is a solution. So if an Excel spreadsheet is the solution, a simple tool that everybody knows how to use, use that, right? Why invest in AI just because it’s the latest and greatest and most hyped about? Use a tool that has the least resistance that is efficient for your business and get the gains that you can get from that technology.
Adrian Tennant: Very wise advice. As AI becomes more integrated into marketing, do you think we should be developing ethical guidelines to ensure responsible use?
Praveen Narra: Absolutely. I think for AI to become mainstream, we need to absolutely address those ethical guidelines. Because if you think about it, any technology that comes into the marketplace, it has pros and cons. Good people use it for good cause and bad people use it for bad cause, right? So I think AI is also a tool that will be used both for good and bad. And we are already seeing some benefits, but having those ethical guidelines will help AI to be used in the right way. And even by good businesses, I think having that transparency to disclose when AI is being used in marketing and campaigns and customer interactions lets people know that, okay, you know, it’s an AI. Sometimes it may not be perfect. And if they want, give them a chance to opt out. right there are situations where you call customer service line and there are questions after question after question about select this like that instead of that you know you may want to offer an option to press zero so that you’re actually able to talk to a real human being right And I believe another area that we care a lot about in AI world is fairness and non-discrimination. Because you feed previous data that AI feeds on to learn how to do things, If the data itself has some level of discrimination, let’s say loans not being given to certain ethnic groups, for instance, right, that bias will be learned by the AI as well. So businesses need to understand how to build AI tools that avoid biases based on race or gender or age or other sensitive attributes. And of course, most important thing I believe is giving the users freedom and choice to opt in or opt out of data collection and use of AI.
Adrian Tennant: Of course, many businesses are still hesitant to fully embrace AI due to concerns about the opacity of the source data used to train the large language models. Praveen, what’s your approach to these issues when you’re consulting with your clients?
Praveen Narra: That’s a great question especially enterprise companies are very concerned about what data is being used to train their models and the thing is first and foremost if you have your data you know how you collected the data and use the data that you collected based on your privacy policies and ethically right that would be the first thing that we recommend customers to look for and second thing is there are commercially usable data sets that are available out there and choose the ones that have the right license for commercially usable purposes, right? So there are some data sets that are provided on the internet. The data is there, but certain data sets are allowed to use only for research purposes, right? So it’s important for businesses to pick and choose the right data set. And also look at the business that is providing the data set. What are their privacy policies? How are they gathering the data? So I think once you address that, yes, there is hesitation about using AI, but my recommendation to retailers and any business out there is don’t be a bystander in this AI boom, because this, I believe, is one of the rarest opportunities where you can really take your business to a whole new level. There are certain times where there is a huge shift in how the world works, especially during industrial revolutions. We have seen the first industrial revolution with steam engines when transport to farther distances was possible based on railways, right? And the business boomed. Industrial Revolution II was created by electricity, and electricity created a lot of business. If you see GEs of the world, Whirlpools of the world, they created appliances and electric bulbs, et cetera, that made these businesses become super successful. And then if you look at third industrial revolution created by computers, you look at the biggest companies that exist today. Apple, Google, Microsoft, Facebook, these are all created by third industrial revolution. And now we are in the fourth industrial revolution. And I believe we are already seeing the biggest beneficiary of the fourth industrial revolution, which is NVIDIA. We have seen how quickly it skyrocketed 10X in less than two years. And so that acceleration is going to happen in many other industries because of AI and robotics and other technologies that are powering the fourth industrial revolution. I encourage entrepreneurs to embrace AI. Don’t procrastinate. Don’t be afraid. You’re going to make some mistakes, but make those calculated mistakes. There’s nothing worse than a great idea in a closed mind. So if you have an idea where you can use AI to take your business to the next level, serve your customers better, try to implement it, but start small, you know, iterate, learn from your experiences and then implement those.
Adrian Tennant: OK, for marketers who have yet to develop an AI strategy for their business or team, how do you recommend they get started?
Praveen Narra: I think like we discussed about start small and think big, right? There’s a guy called Keith Cunningham. He is the real rich dad in the Rich Dad, Poor Dad book that Robert Kiyosaki has written. He essentially licensed the content, at least some content to Robert Kiyosaki. Anyway, so I was part of his chairman’s council where he taught business lessons to us. And one of the things that he taught me was something called thinking time. And the way thinking time works is you come up with an empowering question that you ask yourself, and then you spend 30 to 40 minutes writing every possible solution and answer for that empowering question. And the empowering question is structured in this way. How might I blank in spite of blank? So it goes like, how might I achieve the goal I want to achieve in spite of roadblocks, challenges or hesitations or whatever the case is, right? And so if you write an empowering question like that for your business related to AI, how might I, for example, how might I use AI in my business to, whatever the goal is, to improve customer satisfaction or to improve my profits or revenues, whatever that is, in spite of whatever challenge you have. my lack of AI knowledge, my lack of AI experienced employees in my company. And then if you spend 30 minutes or 40 minutes, write every single possible answer for that empowering question. I’m sure you can come up with many ideas. And then what you do is once you come up with 20, 30, 40 different ideas, then you pick what are the best ideas from that and start implementing those first. And I believe that, you know, any business, if they spend some time thinking about strategizing about how they can use AI and start implementing small and get feedback from their customers, I think they can start benefiting from AI.
Adrian Tennant: Where do you see AI in marketing and advertising headed in the next five to 10 years?
Praveen Narra: I think when it comes to marketing and advertising, I think the biggest thing is definitely personalization. People are going to expect the advertisements, the marketing messages and emails, everything to be personalized. If a business is not going to personalize their marketing materials and advertisements to their users, people are going to be frustrated. Like, why are you showing this to me? It’s not relevant to me. And anytime any business wastes a user’s time, a customer’s time, I think they’re going to be less enthusiastic about doing business with them. So I would say talk to your customers, find out what their challenges are. And many businesses use surveys and quizzes to understand what users like and dislike. And once you identify that, definitely you can figure out how AI can be used to improve the business. So I would say definitely learn from your customers, implement AI, iterate and be a fast learner. And also there’s always some low hanging fruit in any new technology. Think about what is the low hanging fruit that I can benefit from first before I reach higher. Sometimes people go after shiny objects, some really complex AI implementation. Yeah, that’s great. You can probably set that as a long-term goal, but try to benefit from immediate ways AI can benefit your business. And that potentially increases the revenue and profits that you can reinvest in building more advanced artificial intelligence.
Adrian Tennant: Great conversation. If listeners would like to learn more about you or Tech.us, how can they contact you?
Praveen Narra: They can visit www.tech.us and they can contact us there. And we also have several e-books and guides on AI, how businesses can use AI in their business. They are free to download, so you’re welcome to download those. And if you are a retailer and e-commerce business that has anywhere from 10 million to 500 million dollars in revenue, then we’d be happy to schedule a one-on-one conversation with you on how AI recommendation engines can be used in your business to increase revenues and profits. And we’d also be happy to demo our AI recommendation tool with 35 different AI recipes that could potentially benefit your business. And there is no cost or obligation to it. So I would encourage your listeners to take advantage of that. And to do that, they can send an email to info, I-N-F-O, at tech.us, and we’d be happy to offer a free consultation to them.
Adrian Tennant: That’s great. Thank you so much for doing that, Praveen. We’ll be sure to include those resources in the notes for today’s episode. Praveen, thank you very much for being our guest on IN CLEAR FOCUS.
Praveen Narra: Adrian, it has been a great pleasure. Thanks for having me.
Adrian Tennant: Thanks again to my guest this week, Praveen Nara, the CEO of Tech.US. You’ll find a complete transcript of our conversation with timestamps and links to the resources we discussed on the IN CLEAR FOCUS page at Bigeyeagency.com. Just select Insights from the menu. Thank you for listening to IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.
TIMESTAMPS
00:00 – Introduction to Bigeye’s Retail Revolution Study
00:59 – Importance of Hyper-Personalization in Retail
03:26 – Introduction of Praveen Nara, CEO of Tech.US
04:25 – Examples of AI Implementation in Retail Marketing
06:10 – Consumer Attitudes Towards AI in Retail
07:05 – Leveraging AI for Gen Z and Millennial Consumers
09:24 – Consumer Expectations for AI Personalization by 2030
12:11 – Challenges Faced by Marketers and Advertisers in AI Implementation
13:53 – Consumer Expectations for AI and Robotics in Retail by 2030
16:56 – Advertisement for Sachiko Scheuing’s book
17:07 – Generational Differences in Perception of AI in Retail
19:34 – Praveen Nara’s Insights on AI’s Contribution to Society
22:01 – Skills and Expertise Needed for Effective AI Implementation
24:00 – Importance of Ethical Guidelines in AI Use
27:01 – Addressing Concerns About Source Data in AI Training
30:46 – Getting Started with AI Strategy in Marketing
33:07 – Future of AI in Marketing and Advertising
34:57 – Contact Information for Tech.US and Free Consultation Offer
36:20 – Conclusion and Thank You
