The Retail Story

0:00 Hey, everyone.

0:01 Welcome back to the retail story, a podcast series that explores how technology is transforming retail, both from the business and consumer perspectives.

0:13 This is the part two of my conversation with Shahin, head of product management e-commerce at Extra.

0:22 If you missed the part one of this conversation, please follow the link in our playlist below.

0:27 So we begin our second part.

0:30 I hope you enjoy it.

0:32 There may be differences or maybe you know, contrasting comparisons between how personalization and done is done in fashion, like only the fashion part of retail and how it is done in electronics.

0:46 And how do you think hyper local or online offline?

0:54 you know, focus and strategy is different for both fashion and our domain, which is consumer electronics.

1:01 So, from my perspective again, so I always think about this, this, this thing really intrigues me when I think about it, right?

1:12 So there’s an I Q and there’s an E Q, right?

1:16 a person has an, has his own I Q has his own E Q as well, right?

1:21 And with respect to collecting data, what we usually do is we, we, we try to attack the I Q element of this customer to say that, ok, customer, you have basically purchased this in the past, this, in the past, this in the past.

1:40 And then that is where we probably stop.

1:42 And I know this is probably going a bit too advanced in terms of a thought process.

1:47 This is something that just intrigues me.

1:49 I, I don’t know, I mean, we are living in a world of a, I, I don’t know anything can happen in the future.
1:53 This is the element that probably somehow gets lost in translation is this person’s E Q at, at, at that, at that point of time because again, every, let’s say every motion of a customer is being dragged at this point of time, right?

2:11 So to say as an example, I’ve been, I’ve been a customer who’s, who’s, who’s been buying, let’s say iphones all my life as an example, right?

2:23 And probably that is my data at this point of time.

2:26 But me as a customer, my, my heart is also telling me that I need to change and and I am, let’s say directly or indirectly looking at other brands as an example that is now that is my E Q element which needs to be factored.

2:40 Once we marry this, let’s say E Q and I Q part, I call it marrying E Q and I Q of a customer, then I, I really don’t see a difference between of course, there are difference in trends between, let’s say fashion versus technology or digital or digital as, as an example or, or, or appliances, et cetera.

3:05 The the point is as long as we gather the data.

3:09 Right.

3:12 The the kind of personalization that we would do for, let’s say fashion versus consumer electronics is not gonna be really different per se.

3:24 According to me, at least trends may change how we communicate how we market certain elements would be different.

3:32 So, so the how when I say how the how of marketing probably sector would change but purely from a personalization, I really don’t see a lot of difference with respect to how I would personalize for consumer electronics, my data would be different.

3:51 Again, of course, everything is based on data, my data for fashion is different, my data for consumer electronics completely different.

3:57 My and again, it’s also about getting this consolidated data.

4:02 So slightly again on a gray zone because we are talking about consolidating data across, across the world, across, right?

4:13 It’s again, we’re talking about something that’s really superficial.

4:18 So, but from a trend per from let’s say from a personalization perspective, the methodology of personalization, the base methodology of personalization for me does not, this is me personally saying it does not differ for let’s say a consumer electronics versus fashion data that is supporting this personalization would change and how we execute, let’s say the personalization would change how we execute the end point of the personalization.

4:46 But personalizing shine to say this is shine identifying China shine in consumer electronics versus identifying China shine on fashion would still remain the same part, right.

4:57 Right.

4:58 Very, very suit, I mean like relevant here.

5:02 both E Q and I Q very important while we are using personalization and tools to make sure that the customer experience is enriched, enhanced and they come back again and again, it’s just it’s so, I mean, I think in, in this world of competition, it’s all about repeat customers.

5:22 It’s all about loyalty, not exactly as loyalty points, etcetera, but loyalty towards a brand.

5:29 see one thing that determines especially retail digital space is price wars and this is known to everyone.

5:37 Right.

5:37 So price was price war is something that as, as retail competition is something we can’t get over.

5:44 To be very honest, it it’ll be there forever and the more the competition the bigger the price was would be so the only differentiator would be to basically get repeat customers back.

5:58 And personalization is one important element with respect to how we get these repeat customers back or loyal customers back to us.

6:06 Right.

6:07 And that’s where I would be, you know, interested in knowing how retailers can differentiate themselves and build top of the mind you know, brand recall or how would you make sure that a customer who’s coming to extra dot com comes back and back and back?

6:26 Yeah, so, as I said, right, from a price perspective, sometimes it’s not very easy to match prices, right?

6:35 It’s all.

6:36 Again, this, there’s always this there’s, there’s always one devil fighting the other.

6:42 So I basically want to give the best price to a customer.

6:44 At the same time, I need to take care of my margins.

6:46 I need to take care of my profits, etcetera.

6:49 So otherwise we will not run as a business.

6:51 If you just basically run flat with any kind of pricing, then then there’s no point running a giant business as an example.

6:59 So the, so the differentiating factor over here should be to give the right dosage of personalized, let’s say experiences to customers, right?

7:12 And that can be an experience can be with the way you talk to a customer as an example when you talk in stores, right?

7:24 I, I, I’ve worked in, let’s say industries and stores where the feedback that has been coming from customers would be merely to say that nobody, you know, I would basically enter a store and they would, they would, they wouldn’t be anybody to greet me to just ask me if I need help.

7:41 There are two, there are two kinds of people as well.

7:43 There are, there are, I think mostly with, I think with respect to fashion industry, maybe this is like, sometimes the help is like, oh, they, they’re too helpful.

7:50 They, they basically want to get too involved with your over personalizing, right over personalizing in, in consumer electronics.

7:57 Retail is the other way around.

7:58 Sometimes the support that is really required from a customer standpoint is not there, right?

8:04 And and let’s call it an assistant or we call it live assistant on online.

8:08 So as experiences from a customer standpoint, just imagine what is the way?

8:14 So if a customer is basically browsing through a category for a long time, so you basically go through smartphones and you are recording when I say you’re recording, you’re basically you, you are, you have these analytics on this customer to say that he’s been, he’s a logging customer.

8:27 He’s been looking at smartphones like for the last 14 days, he’s not bought anything, right?

8:32 Maybe he’s not able to find what he’s really looking for.

8:35 So how, how can it trigger, trigger a con conversation with him and that you don’t just be an email to say the customer or why not, why, why you, why are you not coming back?

8:44 You’ve been looking at the website for the last 14 days and that’s almost like a group to say that who are you to basically ask me to come back?

8:50 Right.

8:51 But, but, you know, even if, if he’s coming back on the 15 day, if he’s still coming back on the website, we identify him that he’s basically been looking and looking, he’s not able to find something.

9:00 We basically pop a live assistant to say that are you, I mean, are you looking for something?

9:06 I mean, probably we can help you and it all depends on language, et cetera.

9:10 So this is what we call as personalized experiences to identify customer, to identify customers needs and satiate these needs rather than basically just tell them.

9:21 Oh, here’s the new, you know, Samsung S 22 or iphone 15.

9:27 Everyone in the world, everyone in Saudi Arabia, please go and buy it, right?

9:31 This is like almost trivializing me as an individual to say that to don’t you know that as an example, don’t you know that I’m not an iphone customer.

9:41 Why the hell are you sending me this kind of or communication?

9:45 Right.

9:46 So this this is already, I mean, this should already have been a differentiating factor.

9:53 This I think going forward in the world of A I where data price was price was and all of these elements will continue to be major deciding factors.

10:07 I think giving customers the right personalized experiences through multiple channels, whatever that is not, and not differentiating a customer between online versus offline.

10:22 These I think are the elements that would determine the success of retailers going forward more than anything. very true.

10:34 As you rightly pointed out like A I and machine learning artificial intelligence playing a huge role right now.

10:43 And how do you see that the future of consumer electronics retail would be both digitally and offline and how A I N M L or maybe better, newer technologies would impact that.

10:59 So I am a bit of a late adopter of Chad GPT, right.

11:03 I mean, recently been obsessed with chat GPT, trying to challenge Chat GPT to understand what can, what can you do?

11:14 What all can you do?

11:15 What all can you basically?

11:16 And of course, I mean, I can proudly say that I’ve still found things to say that they don’t still identify this, but again, this is again, probably asking them for more.

11:26 I wouldn’t call them personal, but very specific information which I’m almost certain they wouldn’t be able to respond.

11:32 But there are certain instances where they’ve given me better responses than what I would have responded in, in, in that scenario, right?

11:39 As an output as an output because I’m looking at, right.

11:44 So so and again, what is this?

11:48 What is that?

11:49 But it’s again, a lot of data, it is just data being compiled and mined in such a way that compartment because I don’t know, I mean, this would be like massive amount of data.

12:02 I, I don’t know the amount of data that and I don’t know where this amount of data things go to be very honest.

12:07 So from, from those perspectives and you know, as an example, I would always think what would be the next step for an iphone or a or, or a mobile phone for that matter, it keeps getting bigger, either it becomes bigger and becomes a tablet or a laptop at some point of time.

12:21 or it basically just becomes invisible and you know, it becomes a chip in your head or, or basically, you know, a partner that is walking besides you, an invisible partner beside you.

12:32 So again, technology in itself is turning out to be limitless, the kind of things that we are hearing nowadays.

12:39 A lot of things are very sophisticated, I think probably accessible to only the higher eons of mankind per se.

12:48 We are still living more close to reality.

12:51 Those kind of people, I’m still talking about those kind of people not talking about the superficial people who have already evolved to the point that they can probably figure out how to have an invisible mobile phone as an example.

13:03 So technology and, and, and, and again, so this, this, this leads to a point of where is business leading to where is where is retail leading to per se?

13:14 We talk about meta words, we, we talk about me.

13:17 And so every as an example, when this, when these words come out, this would be first on their agenda in terms of they wouldn’t know really how to implement it.

13:31 What is the effort that is required is this really is, is really required for, for me as a business.

13:36 But that would be there, you know, let’s say hard hard line for, for the year of the, for the, for the forthcoming year to say that we need cleaning as a technology.

13:46 And I think, I think especially with me as an example, although there’s been a lot of investment, there’s also be a lot of I think issues that have come out with metaverse with respect to privacy per se, with respect to the amount of and again, you know, it’s about metaverse mingling with crypto getting into that s own Blockchain.

14:09 So, so there’s a lot of buzzwords that are running around at this point of time from a, from a, from a retail standpoint, how retail is gonna evolve is very interesting with respect to what kind of products especially in, in digital and even let’s say home appliances.

14:26 I, I think as I said, we have, we almost have talking fridges, we have fridges that order on its own sort of a refrigerator which basically figures out what its cottons are.

14:36 And then it, it not necessarily tells us what, what needs to be done.

14:41 It basically goes on to a website where it would check again for price parity to say that this is the store that is basically giving me eggs for 10 rather than, you know, 20 and then self ordering it, right?

14:52 So this is the kind of technology that you’re talking about where can technology go?

14:58 So the evolution of products, right?

15:00 And from a retailer’s perspective, it’s there.

15:04 So, so this is products as per se, then we have technology that is evolving personalization with respect to recommendation engines.

15:11 How further can recommendation engines work based on the data?

15:15 They have marketing that, that that goes out to customers marketing messaging, how this communication channels, how can this be unified across, let’s say online offline?

15:25 And how can this data be used to send offline data for an online customer and vice versa as an example.

15:31 So this is evolution of technology evolution of product and then we have the world in front which is basically doing things like chat GP T S Blockchain, et cetera.

15:41 So it is evolving into an interesting circus.

15:48 And it is very difficult, I think it’s, it’s almost endless that it’s limitless, the possibilities, the possibilities that retail can reach as a space.

15:59 I think it is also turning out to be endless.

16:01 Now there used to be limitations.

16:02 OK.

16:02 Stores can sell so and so items online can sell so and so items now there is no boundaries between it’s it ceased to exist post COVID.

16:12 It’s almost right, you know, like everything is even with augmented reality.

16:16 So like even I can almost have a life size refrigerator without the refrigerator be there.

16:20 So it’s not really about online online anymore.

16:23 It’s about evolving technologies, evolving products and the world evolving around it.

16:30 And I think the possibilities are endless, to be very honest.

16:33 From December.

16:36 True, true.

16:36 I really like that interesting circus part.

16:39 I mean, like all of us are super excited about what comes next.

16:43 You did touch upon the emotional part invading the privacy part and being ethical.

16:50 So how important in your opinion is sustainability in retail and sustainability in consumer electronics, retail specifically?

17:00 So, yeah, again, a a as I said, right?

17:06 Beyond the point.

17:09 OK, I, I know that probably I’m looking for mobile phones as an example.

17:16 And I don’t want to probably disclose the fact that I’m looking for a mobile phone for my wife as an exam, right?

17:22 In this case, I’m just looking for a mobile phone and I’m, I’m looking at various options.

17:27 So I’ve been looking for quite some time.

17:30 So to personalize me and tell me that you’ll be looking at these, let’s say brand these models for some time.

17:36 And I think this would be a better option for you as a recommendation or, or as a marketing communication.

17:43 But somehow at some point of time figuring out that this is for my wife and basically coming back to me, even without me actually telling you as a website that oh, I’m looking at this for my wife as an example.

17:55 You still come back to me and say that, oh, this would be better for your wife either based on data to say that probably I’m looking at pink iphones, me as a male.

18:04 I again, I’m not, I’m just giving an example.

18:07 So I hope people don’t take it in the wrong sense to say that I’m you know, discriminate against the color or race, etcetera.

18:14 So I, again, this is, this is what we don’t want to make as assumptions right to say that I’m I’ve been looking at pink iphones or, or pink smartphones for quite some time.

18:23 And without me even telling you that I’m actually looking at this, these smartphones for my wife.

18:29 I don’t want you to come back and tell me as a marketing strategy to say that, oh, we think that this would be better for your wife.

18:37 Now, this is invasion of my privacy because I, I’ve not told you that I’m looking at smartphones that’s fine.

18:42 And I, I acknowledge the fact that, you know, that I’m looking at smartphones, but you can’t make a decision on my behalf to say that I’ve been looking at this for my wife, whether it’s for my mother, whether it’s for myself.

18:54 I’m, I’m, I’m in drink by the color of pink and, and I do it for myself.

18:57 So this is where I think data should not or we should not enable data to take a decision based on data itself.

19:07 or OK, probably I’m not saying this the right way, we should not allow data to dictate the elements that are not determined by facts, right?

19:18 So there are, there are hard core facts to say that this is, this is the fact or this is the data for the customer.

19:23 Now, I don’t want based on the data, I want to assume further, I don’t want technologies to assume further on top of that data and say that, oh, we assume that this is probably what you try to do based on the data that you’ve given.

19:36 And so here are three recommendations.

19:38 This becomes, this becomes a for me and I’m either thinking or either somehow you’re figuring out you’re looking at, oh, you’re basically been figuring out that I’m I’ve been chatting with my wife and I’ve been sending these recommendations to my wife asking her if she likes it.

19:53 You have been figuring this out without me even telling you that I’m looking at this for my wife as an example.

19:57 So this is where I think it becomes critical that because usually it wouldn’t be the way that there is an I A I robot telling the website, oh, this, this guy is basically chatting with his wife on the site and he’s asking that or he’s giving a recommendation.

20:10 Usually what would happen is there are assumptions that are being made on the data that is you know, presented.

20:16 So instead of taking action on the data, people end up taking action on the assumption which becomes slightly personal.

20:24 So either you’re judging me in a way which is pure invasion of privacy, which I’m not interested.

20:30 And then I I it’s a time that I would basically move in and go to this choice, right?

20:35 This is not basically giving me either it’s, it’s not SAT to my IQ or my I Q in, in, in one way or the other.

20:42 So I don’t want you as a website, I have choice in front of me.

20:46 So, so I think that is where it becomes very important, how decisions are based on data as much as possible.

20:53 And the important thing that we do in this case is to gather as much data as possible.

20:57 Now, in this scenario, you can ask him, I mean, hey, hey, you’ve been looking at this smartphones for quite some time.

21:05 Are you looking for, for products for somebody?

21:08 So you know, that is where you gather data rather than making an assumption already to say that, oh, you buy something for my wife, probably this is a better fit, right?

21:16 So it’s, it’s better to gather data and, and, and, and end up your game on that front rather than basically assume something on behalf of somebody.

21:25 And then basically screw with this entire motive of looking at something or, you know, or, or figuring out that data for you from yourself.

21:37 True.

21:37 So true.

21:39 I, I can imagine of an example like I had such a situation on my daughter’s birthday, I received a gift from a toy store both online online.

21:49 I’ve been visiting with her name, her the age like how many years she is old and her school name, that was a red flag, the red flag.

22:01 And I was like, I never shared that.

22:03 So yes, that’s like, you know, that is where the retailers have to draw a line.

22:09 I mean, that is the, the, the sensible, the sensible thing they would have been for them to ask her, what’s I mean, are you interested in sharing your daughter’s birthday then we can send over, right?

22:21 That would have been the case and it would have said how great they did, they did they, they, they’re doing personalization.

22:25 They, they are really considering me as a person.

22:27 Now, this is basically being a stalker who’s basically figured out this, this is this person who lives here who has a daughter.

22:34 maybe I should send them.

22:35 So yeah, that is really super creepy.

22:37 I agree.

22:38 Right.

22:39 Let me go back to that retailer as a retailer.

22:44 some example around the, you know, best recommendation strategy or best you know, situation with like you’ve had maybe it was a challenge and then you were able to using recommendations or strategies get the best.

23:00 Our, our biggest I wouldn’t say issue was cross selling was, was always our pain area with respect to how do up selling is, is still OK, because I is an issue as well, but our biggest issue was primarily, you know, cross selling.

23:18 So I, but, you know, I have a laptop and then how could I cross sell basically a mouse, a keyboard or a whole accessory, the laptop as an example.

23:27 So this is where we implemented.

23:31 I mean, I got along with everything else.

23:34 Probably one of our success around the time that we implemented our economy was us basically implementing the actual actual right cross strategy around the.

23:46 So from a, from an offline perspective at the, at the, at the till or at the customer till.

23:51 So this is this is our right to basket journey.

23:54 This is almost where the customer is almost ready to be, right?

23:58 And this is where we ideally would offer from a store perspective.

24:02 the different let’s say elements to the customer.

24:05 So this from our perspective, and this was from a click through perspective, from a conversion perspective.

24:12 This was the most successful, let’s say placement that we had on the website.

24:17 So, so I, I think this is one big example of and, and again, so there could have been a let’s say a normal generic rule running on this particular placement of this experience, this part of the experience of the website.

24:30 But we got a lot of recommendations from an economy to say what is the best practice to basically do at this point of time as an implementation.

24:37 And that is where we went ahead with that implementation.

24:39 And, and, and a while you just like what he said, that was our highest converting placement on the website.

24:46 some time back now, we’ve changed the user experience, et cetera, but they’re probably talking about the initial experience that we had with the awesome, awesome, this is really interesting, this you know, episode so far has been very, very interesting, very, I would say intriguing a lot of points I have noted down and I’m ready to start searching them.

25:10 Thank you.

25:11 Thank you so much for your insights and everything around specifically consumer electronics and retail and a lot of things that are coming ahead for us.

25:21 And how we could draw a line between personalizing and over personalizing.

25:27 Thank you.

25:28 And basically, and basically how we rather than getting ahead of technology, get at least 2 to 2 with technology.

25:35 Yes, one noted.

25:37 So, thank you so much and have a great, great you know, association with Algona, a lot of other strategies and discussions coming up.

25:46 I’m eagerly looking forward to them.

25:49 Awesome.

25:49 Thank you.

25:50 Thank you to again as it been a pleasure and thank you very much for having me.

25:53 Thank you.

25:54 Thank you.

25:55 Thank you to our wonderful audience as well.

25:57 Thank you for tuning in today and thank you for supporting us.

26:04 I hope you enjoyed this episode as well and don’t forget to subscribe to the retail story.

26:09 The show that is available on all major platforms including Spotify and Apple podcast.

26:15 Stay tuned for the next episode for more insights and perspectives from the world of retail until then take care.

26:22 Have a good day.

0:00 Hello, everyone.

0:01 Welcome to yet another episode from the retail story, a podcast series that explores how technology is transforming retail, both from the business and consumer perspectives.

0:13 For everyone.

0:14 Joining for the first time here, each of our episodes features conversations with technology leaders and domain experts who talk about everything in and around the challenges retailers face the ways to address them new and emerging trends in industry and digital strategies that retailers are implementing today to win customer love and stay ahead of the game.

0:37 I’m your host, Minu Manisha Babel and today I have with me yet another industry expert Shahin Riaz, who is currently the head of product management e-commerce at extra dot com.

0:51 One of the leading consumer electronics and home appliances retail giants today extra dot com is the most popular destination and has more than 12 million shoppers with 45 branches across the Kingdom of Saudi Arabia, Bahrain and Oman Shahin has over 15 years of experience with Fortune 500 retailers including Walmart A S D A, Argos TJ Maxx Phillips and he has been with extra for the past seven plus years.

1:23 Welcome to the show Shahin.

1:25 Thank you.

1:26 For joining us and it’s a pleasure to host you.

1:29 Hey, hey, thank you.

1:30 Thank you, manu.

1:31 Thank you very much for that hefty introduction.

1:34 And yeah, really looking forward to the podcast and a pleasure to be joining you guys today.

1:40 Thank you so much.

1:41 Let us just start with your background, your experiences and something.

1:47 Why retail?

1:48 How did you start like your journey in retail?

1:52 Yeah.

1:51 So I’m 15 years into the industry now and then let’s say, different capacities, different roles.

2:01 I started off as a technology person 15 years back on, on retail space, but mostly on, on, on technology side, I used to be an A T G developer back then even without having any background coding, et cetera.

2:13 So it was like a, a completely different career switch after studies, et cetera.

2:18 So I, I used to work with the pro previously before and yeah, as I said, I started off as an A T G developer.

2:28 Then eventually I figured that coding probably was not my forte and I wanted to move into a more dynamic, let’s say space which, which was you know, business functional side for me from a retail standpoint.

2:44 And that is where I switched to moving, you know, into another multiple other projects where I was, I got to a functional e-commerce, let’s say business analyst space.

2:54 And I’ve gone probably from various breadth of industries even.

3:04 this is even, let’s say tech.

3:07 I think it’s, it covers a breadth of technology and industries as well.

3:12 So I’ve worked in, let’s say retail space.

3:14 E-commerce, I worked in government space.

3:17 I’ve worked in healthcare to an extent.

3:19 I’ve worked in fashion over for a brief, brief amount of time.

3:25 But e-commerce retail has been my, you know, let’s say pet peeve for quite some time.

3:32 And this is where my expert is as well.

3:34 And so after almost a year and a half years with you know, massive like as Walmart Phillips, that is where I decided to make my jump from on to the Middle East and basically moved to Saudi Arabia around seven years back.

3:56 And I’ve been with extra for leading their let’s say, e-commerce product journey.

4:03 So again, I probably started off when we were almost very negligent from a, a store versus e-commerce split.

4:13 I mean, this was, this was where probably extra was almost moving, not moving away, but moving into more of a digital transformation space.

4:23 And we’ve come a long way in this last seven years.

4:25 So we’ve now ma, you know, major chunk or major share with respect to the split in business between online and, and stores.

4:34 So yeah, that is where that’s been the journey up to now from, let’s say 15 years back now.

4:40 Touch.

4:42 Awesome.

4:42 You’ve covered all the industries and probably all the sectors I could dream of and digital, not just digital, I would say like marketing also.

4:52 Yeah, that, that, that I think that’s one of the perks that comes up with working in a company like because you can keep switching.

4:58 unlike where I basically represent business when I used to work with, it was mostly with different projects.

5:04 So a project and then you basically get bored of that project, you move on, you move on to another technology and another industry.

5:13 and it’s a completely different volume.

5:14 So it’s, it’s, it’s a lot of experience, a lot of good experiences as I see.

5:20 Perfect.

5:21 So let’s come to the digital com customer experience space.

5:28 How do you feel that people are more likely to purchase from brands which personalize and what are some of the major steps that you have taken to personalize the online shopping experience for extra dot com?

5:45 So it’s, it’s an, it’s a very interesting question.

5:49 So again, as I said, right from, from the onset of our journey, our digital transformation for extra dot com when I started off here, our basic intent or extra basic internet at that point of time, was to make sure we get a full fledged website out to customers right from, from an online perspective.

6:04 So stores are doing really well, are still doing really well actually.

6:10 but our online space was mostly very, it was mostly a digital catalog where so some customers would buy.

6:16 But it was not like, you know, it wasn’t really tailored suited for even online shopping at that point of time.

6:23 So that journey itself from, from the last seven years to move from, let’s say, just building a website and sending out communications, sending out mass communications per se mass blasts without giving a heat to what customer really you know, wants to buy et cetera from that position to come to a place where we are using a lot of technologies including al economy at this point of time where we are tailoring our customer experience and journey to be more personalized.

6:55 More importantly, our communications tailoring them to be more personalized.

7:01 So we are sending the customer information, advertisement marketing based on what is he looking for at this point of time.

7:10 So again, it’s very difficult to say that, you know, we’ll reach a saturation point over there.

7:16 But because everyday technology is changing, everyday customers expectations and needs are changing.

7:23 But then the evolution for us over the last seven years has basically seen the difference in the buying patterns as well.

7:31 So as opposed to me sending a mass blast of, let’s say the new iphone is here.

7:35 I’m gonna send it out to, you know, all of the six million customers or the, all of the, all of the, let’s say public in in the region and to see the dropout versus me, figuring out somebody who’s interested in smartphones, in particular, somebody who’s really interested in, let’s say iphones and, and sending them out a very personalized, customized and yet very relevant message.

8:00 It’s very evident to see the dropout or let’s say the the difference in click through of, let’s say these kind of communications at this point of time, even let’s say the recommendations that we show to customers.

8:11 So there are certain scenarios where we have to show generic recommendations to customers.

8:15 And there are other scenarios where we, we basically show personalized because we know this is a customer at this point of churn and the let’s say even the click through or the conversion of these different blocks is very evident even for brands, even for established brands.

8:31 For a matter of fact to say that personalization is not the way forward.

8:37 I think it is something that is already should have been achieved in the past and we are already almost way behind time with respect to getting to that saturation limit where we know that, OK, Shahan needs this item now.

8:52 So that is the important of personalization.

8:54 And I think it and that is how I think I see it from a brand perspective as well.

8:57 It doesn’t matter really whoever you are as a brand because there’s, there’s enough competition, there’s enough choice at this point of time.

9:04 Unless the right communications, the right customer experience is provided to you know, and, and profile that customer as him rather than them.

9:17 This is the most important.

9:19 So true, so true.

9:21 Yes, I do agree.

9:22 I can’t agree more that we should have done personalization long, long back.

9:27 But nevertheless, you mentioned about using Algo too late, we cover up.

9:34 You mentioned about Algonomy as the tool that you are using to personalize for your customers.

9:41 What were the let’s say the points or features or comparisons that led for you to opt for Algonomy and how have they been able to come so far?

9:58 Covering the pain points?

10:00 Yeah, so the good thing with the economy has again, it’s see, every, every, for me, every marketing, let’s say a marketing tool or every personalization tool, every recommendation engine comes with its own positives and negatives, no system is completely full, no system that is aided by an I T, let’s say software is not, is, is never 100% foolproof or is never sorry, 100% satisfactory from a business standpoint, right?

10:32 Having said that the one good thing that I’ve noticed with the economy and probably this is maybe because I’ve interacted with that.

10:39 One person is the expertise that comes with the solution itself, right?

10:45 So there are a lot of other recommendations in Engine as well.

10:49 I have worked with personally a few others as well.

10:53 But the stark difference that I saw with the respect to because I was and very interestingly, Algo, although it was called before, this was my, let’s say first implementation months, I joined as a major project per se, right?

11:10 So it’s quite close to my heart as well.

11:12 And from that perspective and the luckiest thing was I got to deal with somebody an expert on, on Algonomy original site fair.

11:22 The person was usually when, when you, when we go with partners, they’re more inclined on the implementation level, right?

11:29 To say that, OK, how can we get this quickly implemented, quick to market?

11:33 What is the best implementation techniques?

11:34 Let’s get more technical, technological, et cetera.

11:37 But the person or the support that I got from Algo was before we got into even, let’s say technicalities, we were talking function.

11:45 We were like shine.

11:48 You tell me as business at this juncture of your customer experience, you know, what do you expect your recommendations to basically to what kind of recommendations do you wanna show to your customers?

12:02 So, so I’m already bringing in a lot of customer insights, right?

12:05 And, and then there’s I think Algonomy algorithm, I think, or the number of strategies that I’ve seen with respect to what I can push as data to customers is, is quite a lot as opposed to other to, I’ve not seen a lot of other tools from a recommendation standpoint as a back end, I’m purely talking about the, the, the engine in the back end.

12:29 But I and I have closely worked with Algo back and the amount of strategies that, that not I and I think this comes with a learning from, from both perspectives.

12:40 One is the, let’s say industry best standards, the expertise that comes with the person who’s working on it and also getting inputs from customers.

12:49 When I say customers, customers here are not actual end user customers, but business, right?

12:55 So having incorporated all of these things into your set up, I think the implementation was really smooth.

13:06 Although technologically, you’ll always have issues which is mostly to do with integrations and stuff.

13:11 But from a business integration perspective, Algonomy was amazingly smooth even with let’s say a merchandizing team, who’s, who’s really not fully equipped to work with systems, right?

13:25 They, they, they mostly function from a business standpoint.

13:27 They’re not really fully equipped to deal with I T systems as much.

13:32 I call it I T system, but it’s the systems per se.

13:36 So Algonomy was even slightly easier for them to, you know, get into.

13:41 And I think that, yeah, that, that probably was a beautiful differentiation for me from an Algo standpoint.

13:48 And of course, the other thing was also post implementation.

13:53 It’s not like OK, most of the vendors, what they do is OK, once you’ve done the implementation, then I have a contact with you for three years.

13:59 I don’t care.

14:00 I might give you support, et cetera, et cetera.

14:02 But Algo, especially the people that I worked with on Algo side.

14:06 I work with and a few others and, and a few others as well.

14:12 Now these guys come back with recommendations from their side in terms of how, how, OK, I mean, this is how you’re utilizing us at this point of time and probably utilizing only 10 or 20 or 50% of our available resources from our side.

14:29 Why can’t you maximize the rest of the 50% to basically bring in that extra bit of sales or that extra bit of customer experience?

14:37 So that is another, let’s say, important differentiator that I see from on, on, on Algo side as opposed to some of the other you know, partners or, you know, strategy partners that I worked with.

14:51 True, true, very true.

14:54 I can’t agree more.

14:57 what according to you.

15:01 was the challenge like the biggest challenge we are talking about is when people were not understanding personalization and when you started your journey internally, what were the biggest challenges and during implementation or you know, selection of strategy and how were you able to overcome them?

15:20 Yeah, it’s, it’s an interesting question just like any, any digital transformation or, or even basically, you know, whenever we wanted to, we used to have the old age or the age old waterfall methodology of implementation.

15:33 And then a child came into picture and then what we probably a child, people did not figure out was you just don’t put a child or implement a child in a team, you basically do it, you know, top down as an organization similar to that personalization as a concept.

15:47 Although it’s very easy to you know, lay down to say that, yeah, it’s just identifying me as a person, what are the different elements?

15:58 And, and again, so there is always a thin line with respect to identifying shine as a customer and not to invade into shine’s privacy, right?

16:07 So there’s always let’s say that thin line that this, which is, which is very important as well.

16:15 So as an example, if, if we were to launch the new iphone, right?

16:21 Although the mind is saying that fine we need to and this is let’s say from an organization perspective or from a people thinking perspective.

16:30 Although the mind would be saying that and we should personalize and send the communication for this new iphone only to the customers who are really interested.

16:39 But then there are also other tricks, other parameters playing in my head to say that I need to back to my sales, right?

16:45 This is one of the objectives any retailer would have as an example, I need to bring acquired new customers.

16:50 I need to basically convert other customers.

16:53 Not.

16:54 And that conversion is a very interesting fact because it’s not to say that me as a retailer, I’m really interested in you converting from, let’s say a brand to another brand.

17:03 But for me at this point of time, most important priority is to sell this brand.

17:07 So I need to probably make sure that I know I somehow change your mind and then you know, migrate you from this place, this brand to another brand.

17:15 So I think all of these are, let’s say internal conflicts that that are major roadblocks for actual personalization where customers, although we want to send out proper measured noninvasive messaging marketing or even let’s say personalized recommendations to customer, there’s always the devil that’s playing around in our heads, which is, but there is a bigger objective that needs to be met.

17:45 So how do we figure out the optimal and both of them are important and not to, let’s say, trivialize one or the other because both of the objectives are right.

17:55 There’s, there’s no, there’s no actual right or wrong in either of the thinking.

17:59 It’s about finding that middle ground of how do I personalize yet?

18:04 How do I basically make sure that I also get the other parameters that are required from my K P A perspective from my company K P S perspective.

18:13 And for, for me as a brand as well.

18:15 So, so I think these are, let’s say few challenges from a from a retailer standpoint from business wise integration again in integration is all about data.

18:24 I am of the world again where we, where I keep saying that we are far behind with respect to utilization of data, we have so much data and I think probably we are late adopters.

18:37 Let’s say we are as a region, probably we are slightly late adopters with respect to data.

18:42 I think data mining data selling data as a business has been already, it’s been quite some time, right?

18:49 But the amount the importance of data is being realized is slightly already being realized.

18:56 I think at the event from the event of COVID, this is when people are slightly moving away from, not of course COVID, people had to move away from brick and mortar to come online.

19:07 And then when you come online, it’s all about then I don’t know me as a person.

19:11 again, not putting anything against your name, but sometimes it’s for, for certain country people, they wouldn’t know even if was a male or a female or he was a male or female, if they walked into a brick and mortar, I would know is a lady is a guy.

19:27 But online again, this is data.

19:29 This is the power of data and, and recognizing, identifying, collecting and mining this data to basically push the right objectives for us.

19:39 This is the most important thing from a technical integration of how we get the right data and how we mine the right data and how we use it again in such a way that this does not really invade my privacy.

19:55 At the same time, it’s identifying me as shine rather than Hello mystery.

20:01 True, true.

20:02 We’ve touched upon a very, very interesting and very important aspect I would say here, data, like we moved from data silos to organizing classifying data, grouping data.

20:13 Then now we are at a place where we are stitching online and offline like brick and mortar data has to come in handy for the online experience as well and vice versa, and vice versa.

20:24 Right.

20:25 Right.

20:25 So in this age of digital disruption, what can be like let’s say for the retailers who are starting what can be done by these retailers to unify that online and offline experience without entering that, you know, exceptionally personal stage without invading their privacy.

20:47 So, I think again, see data collection is, is always very contentious, especially online, even offline for that matter.

20:58 You can’t make a lot of these things mandatory, right?

21:00 If you, if you, if you ask a customer, and again, it also depends on, especially stores online is, again, it’s, it’s two slightly different discussions per se in stores.

21:11 It depends on the person who’s basically at the cash.

21:14 What is his interest to basically understand you as a customer?

21:18 And I’ve noticed this, let’s say in even in a lot of supermarkets, groceries as an example to the same, let’s say to the same store that I go, this can be any store by the way.

21:30 And I’m a repeat customer by the way.

21:32 So probably there are five salesmen in that store and I’ve encountered each of these five salesmen.

21:38 Probably not.

21:39 All five salesmen are gonna ask me if I have loyalty, right?

21:43 Some of them would just basically scan the item and say go ahead, just pay and the three others who are probably really interested, they would say, oh, do you have a loyalty?

21:50 And then can you give me your mobile number?

21:52 If not do if not, do you want to be a loyalty member?

21:55 Can you share your details?

21:57 So store is a very is a it’s a very personal experience.

22:04 It depends on the personality of who’s basically, you know, collecting this information from the store and also how the customer reacts it.

22:11 It also differs region to region.

22:14 Of course, every region has their kind of customers per se.

22:18 Now, online is again, another slightly different game online is about every registration, every registration that we take in ideally is an opportunity for us at the same time.

22:33 So, so how we basically there are there are multiple things that you know, you can incentivize customers to basically say that over register up with us and then get a 15% voucher code on your next purchase or whatever that is.

22:46 So there’s a subtle way of how you take the initial registration and then take the rest of the information at a later stage rather than pressurizing the customer to basically start filling up a form of 100 and 50 fields and basically look into your registration.

23:00 Nobody does that.

23:01 I mean that, that, that used to be the case previously on even on e-commerce or digital website.

23:06 There used to be forms of, you know, like let’s say 50 fields, your salary, all of your details, all of the details which you don’t want to even give somebody.

23:15 This kind of information is asked.

23:17 And I think over a period of time, e-commerce digital space have realized that this is a lot of this is actually intruding into somebody’s private space.

23:25 I don’t want to basically define what is my gender or, or, or what’s my pay scale or, or where do I work at this point of time?

23:32 It’s not about, I don’t want you to know my birthday as an example or my age.

23:36 I’m very sensitive about my age as an example.

23:38 So it’s about subtly first, you know, helping customers realize probably them registering with us is for a different purpose.

23:48 It is probably to better track your orders.

23:51 It’s probably to marry your data between online versus offline because offline, we are capturing the data, et cetera.

23:56 And then subtly at various points of the customer journey, try to gather information in a non mandatory fashion again, either by incentivizing them or telling them.

24:08 And if you do this, we can, we can give you this right.

24:11 If you give me this information, then I can tell you when the or if you as an example, if you tell me what is your interest with respect to?

24:17 Are you interested in smartphones?

24:18 I can tell you when the next smartphone is coming rather than me, basically sending you smartphones, refrigerators, washing machines, ovens and all kinds of products as in marketing.

24:27 So it’s a way of how again, it depends on your tone of voice.

24:32 It depends on how you gather this information.

24:34 So that the two, the collection of data from both these points are completely different and it’s true.

24:40 Especially in stores online.

24:42 Again, you can always devise journeys because you, you’ll get a lot of reference in stores.

24:48 There is nothing that you can do.

24:49 It’s completely dependent on your store personal.

24:52 It depends on your cashier or whoever is getting that information.

24:55 If he’s good, if he has all of the information, if he knows how to deal with customers, then you’ll get the information as you will not get the information.

25:02 And once you have this information, it’s important to unify.

25:06 I think from a technical perspective, what happens usually as an issue is sometimes the parameter that we use to identify a customer, it can be mobile number, email address or a customer ID, whatever that is, is not really the same between your stores versus online.

25:23 And because of that, there usually is a duplicate in terms of how do I identify the customers.

25:29 But if we, and, and you, you ask, you ask for somebody who’s gonna start, right?

25:34 If they can already define that parameter, this is gonna be my identifier for a customer.

25:40 It’s a mobile number or an email address, then things will become very easy because that becomes your primary key and then there’s no duplication of that value.

25:47 So then once you have the data across both, you’re already marrying both those data.

25:50 So I think that that probably would again, easier said than done.

25:54 It’s I’ve, I’ve had all kinds of experiences with different kinds of clients.

25:58 So easier said than done.

26:00 This concludes the first part of my conversation with Shahin.

26:05 Stay tuned for part two, where we dive deeper into personalization, the role of A I machine learning and so much more till then, take care and stay safe.

26:16 Thank you.

0:00 The average consumer now carries out at least two transactions online each day.

0:06 Amazed.

0:06 Well, we have some more such fascinating facts coming up.

0:10 Hello, everyone.

0:12 Welcome to the retail story, a podcast series that explores how technology is transforming retail from both the business and consumer perspectives.

0:23 Each episode in this series will feature conversations with technology leaders and domain experts who would talk about challenges retailers face and ways to address them some new and emerging trends in the industry and the digital strategies that retailers are implementing today to win customers and stay ahead of the game.

0:46 I am your host, Minu Manisha Babel and today I have with me Mr Omar Ali from Middle East.

0:54 Omar is a seasoned product management professional.

0:57 He has over 16 years of work experience in creating digital consumer experiences that translate to higher engagement, loyalty and revenue.

1:08 He’s an expert at developing web mobile platform and I O T.

1:13 Thank you so much Mr Romer and welcome to the podcast.

1:17 It is great to have you and looking forward to an insightful conversation today.

1:22 Thank you so much for having me, Minu.

1:24 It’s a pleasure to be a part of the podcast.

1:26 Awesome.

1:27 Thanks to begin our conversation.

1:30 I’d like to ask.

1:31 could you please tell me a bit more about your background experiences and what excites you the most about retail and the digital customer experience space?

1:43 Yeah, sure.

1:45 so I’ve been working in the digital space for over a decade now.

1:50 I started my career being a customer service agent.

1:54 then e-commerce was, was always a point of interest to me.

2:00 And from there, I naturally evolved into being a product manager because I wanted to own things, the ones that I was working on.

2:11 So, and now I’m actually a full time product manager running e-commerce products.

2:18 I’ve been working in various industries including B to B, Ecommerce, travel, automotive, classified E government.

2:26 And now I’m in, in retail.

2:29 the thing that excites me the most is like this space where I work.

2:35 It’s, it’s just like it’s, it’s constantly getting innovations.

2:41 There is an evolution of technology with, with evolution, it comes with, with new opportunities, new opportunities to meet customer needs and exceed their expectations.

2:54 And what interests me the most is the intersection of data with technology and C X in general and how we as you know, organizations or, or product people can leverage that data to drive growth and customer loyalty.

3:16 Awesome, awesome.

3:19 just discussing about like a current state we just entered a new financial year.

3:24 So what how according to you, you know, is the state of retail specifically in 2023?

3:34 Yeah.

3:34 So retail this time around like it, it, it has multiple challenges like given all the geopolitical scenarios that are happening.

3:45 but it also comes up with, with, with so many opportunities that, you know, that were not offered earlier.

3:52 digitally.

3:54 we feel that you know, more retail companies are now opting for personalization experiences.

4:06 They are now, you know, the customers of o of all such products are expecting personalized experiences across all touch points from the discovery to purchase and beyond.

4:20 Just to summarize this customers now have multiple options.

4:25 And what they’re looking for is a simpler solution that can fulfill their needs.

4:34 like it, it’s like it, it can come down to any, any shopping app that you see out there.

4:41 And, and I, I feel like the companies who are, who are unable to prioritize personalization, they are like on, on the risk of losing customers to competitors who are, you know, providing more tailored experiences.

4:58 So, yeah, I feel personalization is, is where, you know, I feel most of the of, of the retail digital organizations are moving to in 2023 that’s where the focus is going to be very true.

5:14 I I do agree, like from discovery to purchase and beyond, it’s a very competitive market and yes, the customers are spoiled for choice.

5:24 So what does it take to acquire and retain customers today?

5:29 And how can the retailers grow their customer base in this intensively competitive market?

5:37 Yes, you’re right.

5:38 So like, as you earlier said, like these days, like retail market is intensely competitive.

5:48 and in order to acquire customers and retain customers, we have to present them with personalized experiences.

5:59 And it’s, it’s, it’s getting increasingly important now by personal experiences.

6:04 I mean, we need to, you know, like companies need to enable the teams to leverage customer data.

6:14 look at advanced analytics.

6:17 see how can you know, the personalized experiences that you’re creating are meeting customer needs or even ex exceeding those needs at times.

6:28 I can, I can call an example here, like for example, recommending a product based on customer past purchases seems to be quite simple.

6:36 But understanding based on the frequency of a certain product that a customer has bought and then recommending that might add another value and that would exceed customers expectation when they are, you know, coming back to the platform to buy the same product.

6:52 So, so just by accumulating customers past purchase data, looking at their browsing history, we can increase the chances of you know, improving customer satisfaction which would directly impact to the overall N P s.

7:09 And you know, the these recommendations would also help retailers to stand out in a, in a, in a very crowded and competitive market out there because at the end of the day, you are looking to build some sort of a brand loyalty, right?

7:25 And any, any, any retailer, any, any, any such company that is prioritizing personalization would be better positioned to succeed in acquiring and retaining customers in the long run.

7:37 Very true, very true.

7:38 So like you mentioned about leveraging customer data and you know, the advanced analytics and how we move from data silos to organized and classified data to maybe stitched across, you know, platforms.

7:52 And so much more like when we talk about data.

7:54 So what types of data do you think are essential to personalize commerce experiences?

8:01 And what is the role of A I machine learning in enabling that kind of personalization?

8:09 Yes, I I guess there are multiple touch points.

8:12 I guess retailers must collect and analyze data of customers including their demographics such as their age, their gender location along with, with past purchases through browsing and preferences wherever those are collected.

8:31 It is only by analyzing such data.

8:35 and you can only by analyzing such data, you can you know pre detailed customer profiles which would then help the business better understand their customers and anticipate their needs.

8:47 And to just do all of this, I guess A I is, is, is the way forward.

8:54 So A I N M L machine learning technologies are critical to such analysis and, and processing of, of such vast amount of customer data.

9:03 And, and, and there are, there are multiple algorithms that you know, that can help you come up with, with certain analysis on how to make use of that data in, in, in the right way.

9:16 Right.

9:16 Right.

9:18 Very true.

9:19 Coming back to like different stages of a customer journey.

9:24 how can retailers deliver personalization at you know, the exploration stage, decision stage, purchase stage or even beyond like loyalty and all and how can A I M L power this like even further?

9:42 So I, I would say retailers you know, can so it comes down to the customer data again.

9:48 If, if, if we begin with the exploration stage over there, I I guess retailers can start by, by recommending certain content based on customers previous history or, or the demographics as we spoke earlier.

10:03 because this stage the customer is just exploring the products and, and the services offered by the retailer that they’re just exploding and not, not performing a things just do start to get a little interesting when they are in the decision stage, that’s where customers are kind of expecting more, more relevant product recommendations or, or personalization algorithms to chip in.

10:30 and even then even on the decision stage, there are times when, when we feel that the customers are a bit in indecisive at this stage.

10:39 So, and when we know that, you know that they’re, they’re falling, that they’re actually following a certain path on, on the funnel.

10:47 We, at that point of time, certain product recommendation of certain content actually boosts their decision making capability and in, you know, make them a paying customer or help them purchase a certain item or just, you know, increase the chances of a purchase.

11:08 that, that’s, I, I guess, is, is, is important in, in the decision stage.

11:13 If you look at the purchase stage, I think that’s, that’s one of the very crucial part of the funnel.

11:18 It’s, it’s where, you know, as, as a customer, I have all the items that I wanted from, from a certain section of, of the app or from, from a certain category.

11:30 But here, what I might also be looking for is something that might go well with, with the product that I’ve, I’ve already added to my card, something that can be fed or, you know, some things that, you know, people who bought an item that I was looking at or that I’m buying right now and they actually coupled it with, with, with, with another product.

11:52 So, I, I feel, I feel, and, and this is where like you’ve been experiencing as well, like right at the card or at the point of where you’re checking out, we do give them a final nudge saying that, hey, you know, you, since you’ve bought certain items, would you like to buy again an item that you might have missed right down the card, but you have bought earlier and people do get to add that item in, into their cards.

12:19 So it’s just to summarize this by, by like if you suggest relevant products or services during the purchase process, you can increase the average order value and improve customer section customer satisfaction.

12:35 And finally, yeah, and finally just the, the, the loyalty stage, right?

12:39 Which is I think the the final stage.

12:43 it it’s where we, we have to like retailers in general can personalize the customer experience by providing exclusive offers and personalized messaging and content to encourage repeat business from a certain customer and you know, enhance the brand loyalty that the customer has towards them.

13:05 At this stage, we would already know that the customer is already loyal customer, right?

13:11 For, for that certain product.

13:13 And now we like the product is in like the retailers are in, in a, in a certain position where they are leveraging that relationship with the customer to provide certain exclusive offers and, and you know, just bring more stickiness to, to, to that brand loyalty that the customer has.

13:35 So yeah, I would say these, these are, are the few points that I would see are like how retailers can kind of, you know, personalize throughout the different stages of the customer journey.

13:48 Right.

13:49 So true.

13:50 And coming back to the metrics that you shared that yes, we do have a Forester Report which says that 53% of digital experience delivery professional said they lack the right technology for personalizing experiences.

14:08 So how can retailers make an informed buying decision?

14:13 How can you know the commerce teams build a business case so that investments in such personalization technologies is increased eventually to, you know, increase the average order value, the experience of the customer the revenues left.

14:33 Yeah.

14:34 Yeah.

14:34 No, you’re right.

14:35 I think with, with so many personalization vendors in the market, I think retailers can make a very informed buying decision by conducting a a thorough research, market research and evaluate vendors based on the technology, the infrastructure, the data capabilities.

14:56 And most importantly, the track record of this platform’s success, I think as, as a retailer like it should also be considered the like the vendor’s ability to integrate with their existing technology stack.

15:12 Whether the vendor provides an ongoing support and training, I think that’s, that’s quite important.

15:18 And only after conducting such an evaluation, I guess retailers can, can select the vendor and you know, understand the meet the needs that it it meets for, for their digital aspirations and and personalization in general, I think just to, just to build a business use case for you just to onboard a personalization stack, I think before even investing in, in, in personalization platforms, I think the e-commerce teams should first understand the benefits that they’re looking to reap out of personalization in general and those have to be linked to certain key metrics.

16:05 It can like we can debate on, on what those metrics can be but just on the, on in the top of my head, I guess in like increasing customer loyalty is one higher A O V is one improved customer satisfaction or N P S scoring is, is another indication that, you know, you might want to go and you can leverage personalization through that.

16:32 And on top of that, I think e-commerce team should, should also conduct a cost benefit analysis to evaluate the R Y of, of, of personalization tech.

16:42 And you know, demonstrate the financial benefits of investing in personalization platforms in general.

16:49 And I think these inputs would obviously create a strong business case.

16:55 And I, I guess that would, you know, help any, any, any team get a buy in from, from their leadership to, to start implementing personalization, I would say, and then there can be you know, multiple approaches to it.

17:14 But I, I feel just embarking on, on, on, you know, such a journey where you are integrating personalization for the first time.

17:25 I think these are the most important points that you would need to consider in your business case, contact.

17:33 Like you did mention about the loyalty satisfaction and P S, these are the quality parameters, not many retailers would be emphasizing that.

17:43 And when we talk about personalization, it is kind of an iceberg 20% is the A O V or the revenue uplift 80 85% is just below which is not seen, which is these indirect impact that it would have on the brand, on the customer loyalty satisfaction and long term association.

18:08 even when you talked about like the experiences enriched further.

18:12 So it is kind of a guided you know, interface for a customer, be it cross sell, be it bundling.

18:21 So how can retailers and maybe you can give an example or any situation that you might have had where you know, you were able to prioritize these commerce touch points and how like from beginning your personalization journey for your company and how have you progressed in terms of majority curve?

18:46 Yeah.

18:47 So we prioritized the personalization based on four factors, right?

18:52 So the the main factor was like the main driving force were, was the business goals that we had.

19:00 we were also looking at the technical feasibility, but in parallel, we were also, you know, focusing on the impact on the C X and just looking at ways on how to enhance customers, customers experience on our platform by just showing them the product that they preferred and you know, just somehow understand their behavior and, and you know, help them go through their journey on the product much seamlessly.

19:35 So we were looking at obviously the technical feasibility first.

19:40 So we wanted to understand where all it the the personalization platform is going to integrate and what all the touch points would be.

19:50 some touch points may be easier to personalize than others.

19:53 Like retailers can prioritize those that are feasible and, and you know, easily implement and cost effective.

20:04 But there are others like, for example, when we say content personalization, it requires a lot of investment from multiple stakeholders, right?

20:14 So those can be paradise in a different way.

20:17 But if you look at And in terms of the business goals that we were trying to set, we were like, our goal was to just increase online sales.

20:27 And we, we were like analyzing the whole journey and we were coming up with as many touch points as possible for our customers to just help them ease through the shopping process so that they don’t have to search for the items that, you know, we know that they’re going to buy, like it should just pop in front of them and they should be just able to add those items seamlessly.

20:57 What we wanted to do when we say that we wanted to have an impact on our customer experience.

21:02 We wanted to reduce the friction that our customers might have when they were using our apps.

21:09 So like if, if I know if I’m a grocery retailer, I and, and if I’m a repeat customer of, of such an app, I wouldn’t want to go and search for the same item that I continue to buy every other week.

21:26 I want the platform to know what I’ve been buying and then focusing that right in front of me so that, you know, I would just have to do a single tap and with another tab, I can just go and quickly check out this is what we focused on and it has given us great outcomes.

21:43 For example, we personalize the whole buy experience for our customers.

21:51 So we are an omni channel organization.

21:54 So if you go and buy offline or online, we, we merge your buying history to, to in, in, in your buy game section, which is powered through product recommendations.

22:09 So what we do is we just showcase those items that right on the home page very prominently to our returning customers and it has given us great results.

22:21 We have gained good CPR out of that section and the revenues from just this one are, are really promising.

22:30 So we understood that you know, if I’m there to buy a pack of milk, I don’t have to go and search for a pack of milk.

22:39 The platform should know what pack of milk have I bought last time.

22:43 What brand is my preference and build propensity around the product and the category and show me that right, right there so that I can just quickly buy that.

22:53 And something that we are experimenting now is since we know the kind of products that you as a customer is, is buying from our platform, we are now also focusing on creating some sort of a category level propensity where we understand that you, whenever you land, you buy from these 22 or three or four categories most of the times, right?

23:21 So if, if I have some offers that you might be interested in.

23:24 I would like to showcase you those offers right in front of you so that there are greater chances of you getting the getting converted into a paying customer.

23:34 I think retailers must understand their business objectives and their technical feasibility to come up with certain C X initiatives.

23:43 And then I think like factoring all these points together, we can have a good personalization journey.

23:51 So true.

23:53 So true.

23:53 I do like being a customer myself and into the retail industry.

23:59 I do understand like, you know, having that sync of online offline or omni channel presence is so important if today I have some bought something, definitely, I would want the app or the website to record it.

24:16 So again, we come back to data and then the disruptions like the level of personalization that currently you are into it.

24:23 So exciting to you know, think about the road map, like the category level or maybe using even deep dive affinities of a user.

24:32 So just around that, what are some of the emerging commerce and you know, consumer behavior trends from customer point of view and how retailers should be preparing themselves for the coming years.

24:54 Yeah.

24:55 So as a product manager specializing in in personalization, I would recommend retailers to, you know, prepare for hyper personalization for personalization using augmented reality for personalization using social proofing.

25:19 and also while doing all these key points, also focusing on the sustainable and ethical shopping factor, right?

25:27 Because we don’t want customers to feel as if we are over selling them.

25:33 We want to maintain that line or, or the retailers might want to maintain that line where you know the options that they see are the ones that they’re looking for.

25:43 And while they are searching for it, we continue to nudge the customers with certain value added products or maybe cross sell them with, with certain other products that they might want to buy.

25:56 So I would say hyper personalization is where the focus should be.

26:07 it is to, you know, it, it it all comes down to the customers.

26:12 The customers these days are increasingly expecting personalized experiences across all touch points from product recommendations to marketing messages, right?

26:25 So I would suggest retailers should leverage A I and, and machine learning technologies to, you know, that offer hyper personalized experiences to meet individual customer needs and preferences.

26:38 Like for example, we’ve implemented a use case where now we understand the gender and the age of the customer who, who’s logged in and who’s browsing right now.

26:50 So for, for, for a lady who’s searching on like who’s who has landed on her home page, we would not show her any, any, any product that might not be related to her.

27:01 But for, for, for a guy who comes to, to our, to our homepage, we might show the, the, the couple of a few banners that you see on the top, those might be related to categories that are more linked to men as, as compared to women.

27:16 So that’s, that’s how we are, you know, kind of leveraging.

27:22 I, I, I won’t call it hyper personalization.

27:24 It’s just very, very basic aspect of personalization, but we are deep diving into, you know, starting to leverage the age group of the customer because there are certain products that I might not be interested in because I’m, I’m not that old, but there are certain customers who might not want to see sunglasses popping up every time because they don’t want them, right?

27:50 So leveraging their age data or the, the age group I would say is important.

27:57 And also in our scenario with, with growth, retail, we are also focusing on nationalities.

28:03 So we, we, we do take this input from, from the customers.

28:07 So for example, for a customer who’s a French, customer might be searching for certain French product.

28:16 There is no point of, you know, sharing with them Italian products, for example, right?

28:24 So, so we would need, so if, if I’m there and also we’ve kind of realized that such customers might not even know how to search their ethnic products, ethnic grocery products.

28:38 So, we’ve built product recommendations around their ethnicity as well so that, you know, they can just have a quick start.

28:46 So this is like, I guess where hyper personalization is leading us to, I would say with, with everything that’s happening in meows now, a r augmented reality based shopping experiences are now, you know, coming into, into picture as well.

29:04 But I guess it would just allow customers to visualize the products much better before making a purchase.

29:09 And I guess that can be another thing that retailers can, can, can choose to implement.

29:15 and then social proofing, I think it, it has been there for, for, for some time.

29:20 But I think this would continue to be there.

29:25 And I guess retailers should be focusing on, on social proofing because at times when as customers, you’ve seen that, you know, you, you, you’re buying something but you are influenced by what other people have bought and what other people have thought about that product, right?

29:42 And that kind of influences your decision as well to, you know, make, make a, a shopping decision.

29:47 So with such with such inputs, you validate customers opinion, you, you validate their, their, their decisions.

30:00 I think social proofing is going to be quite important with any, any retail e-commerce platform in the future and it still is.

30:09 And I think at the end when it comes to sustainable and ethical shoppings, I think customers are, are, are, are becoming more conscious about, about the impact of their purchasing decision on the environment and society.

30:24 I think what retailers should also prioritize is sustainable and ethical practices with their products and marketing, you know, just to meet the personal expectations.

30:35 Like, for example, we’ve recently stopped using any plastic bags as part of a policy.

30:42 So we, we mentioned that clearly that it’s not there because it’s impacting the environment.

30:46 So it, it’s not there.

30:49 I think these are the few emerging trends and I, I I kind of feel confident that if retailers can, you know, adapt to these, I think that they can stay ahead of the competition and, you know, pro provide more personalized, engaging and sustainable shopping experience for their customers.

31:07 So true.

31:08 So true.

31:09 I’m like, you know, really glad that you brought in sustainability and being ethical, not over personalizing.

31:17 So there’s a very thin line between, you know, personalizing and overwhelming customer with you know, things which might not be relevant things which are not sustainable.

31:28 So this is something like, you know, we should be brainstorming, maybe we should be adopting as a culture and moving forward with the trend.

31:39 very, very nicely beautiful in, you know, put forward by you.

31:44 one last question before we, you know, end this conversation.

31:49 Very interesting conversation.

31:50 Let me tell you, what was the, you know, aha moment for you in the history of retail, maybe from when you began your career until now.

32:02 And how do you see that, you know, the aha moment to be, let’s say, three years down the line.

32:11 So I can, I can recall one experience that I just had and I, I, I call that aha experience.

32:18 So what we did was so we like in grocery retail, when a customer is on a on a buying spree, you have to make sure that what the customer is searching for is what the customer is seeing at that point of time.

32:34 If you don’t show the customer the right product with the right quantity available, the customer is going to churn and you know, just find another other platform to buy that same product.

32:47 So what we wanted to do was in the whole buy gain experience that we created.

32:55 We understood that there are certain items where, you know, you might have bought them either online or offline, but when you come and you know, try to buy them again, they might be out of stock because of your location because of where you want them delivered.

33:12 Because of the timing, et cetera, et cetera.

33:15 What we did was we initially, we thought, let’s maybe not tell that this is out of stock or maybe just let’s hide the product altogether.

33:24 But what we ended up with was we wanted to be very transparent with our customers and tell them that we respect your decision to go with the brand with a certain product with a certain quantity.

33:36 But we regret to inform you that this is out of stock, but we didn’t want it to stop there.

33:41 We wanted the, the journey to continue.

33:43 So what we did was we came up with a replacement flow that was powered by personalization again.

33:51 So we knew that a certain pack of milk is out of stock, but the same brand with a certain different I wouldn’t say the size of, of, of, of the packaging is different, but there are certain other, other option that you can go and, and, and you know, opt for.

34:11 So we did this experiment and it has been a like I would say, it, it has been a success.

34:20 We’ve seen a CPR of over 60% where customers have opted to the substitution model that we came up with using recommendations.

34:33 60% of the customers actually opted for those products which validates the, the recommendations that we were giving them.

34:41 So this actually, you know, made the whole shopping experience.

34:47 or, or, or the journey of the customers really flawless and it was seamless for them.

34:53 So if, if they, they, they were there for some milk and it was out of stock, we said we are sorry, it’s out of stock.

34:59 But here are some other milk that you might want to see and have a look.

35:02 They are of the same price point.

35:04 We’re not, you know, we’re not trying to get more from you.

35:08 We understand that you bought something for, for $5 for example.

35:12 So what we’ve done is in the recommendations, we’ve also put a check, a price check and a brand check and a category check so that I don’t recommend you stuff from multiple sections.

35:23 And this has been a huge success and the customers are engaging with that platform really well.

35:30 And even like I’ve really spoken to certain customers who’ve said that we only come to your app or to use, just use the Buy game section because that’s what we want.

35:39 We don’t search for anything.

35:40 It’s, it’s all there.

35:42 So that, that for me and the team that I worked with this was an aha moment for us and we really cherish this, this this success.

35:54 Awesome.

35:54 Awesome Omar.

35:56 I come to you know, share a very small but very meaningful quote by my manager.

36:02 small is big like these are the small things which make huge impact and like be it the customer, be it the retailer beginning small and then you know, integrating them together to make that huge impact, awesome, awesome, awesome conversation.

36:19 And thank you so much Omar for these valuable insights and I’m so enthused and you know, excited about what is ahead of us, not just as a retailer, but as a customer as well.

36:32 And yeah, thank you so much for your time, Omar.

36:36 Thank you so much for having me.

36:37 It was a lovely conversation.

36:40 Awesome.

36:41 And thank you to our wonderful, wonderful audience.

36:44 Thanks for tuning in today and thanks for listening to the one of many, many podcast series coming up ahead.

36:51 I hope you enjoyed this episode as much as I did.

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37:03 Stay tuned for next episodes for more insights and perspectives from the world of retail.

37:09 Until then take care, stay safe and stay healthy.

37:16 Good.