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EP #2: Scaling E-Commerce Growth Like Ferns N Petals with Omnichannel Personalization

EP #2: Scaling E-Commerce Growth Like Ferns N Petals with Omnichannel Personalization

AWe discuss the impact of personalization and predictive recommendations across key industries, we spoke to Shashank Misra, Senior Product Manager at India’s largest flowers and gifts platform: Ferns N Petals (FNP).
About this Podcast

As part of our #PersonalizationThursdays series where we discuss the impact of personalization and predictive recommendations across key industries, we spoke to Shashank Misra, Senior Product Manager at India’s largest flowers and gifts platform: Ferns N Petals (FNP). An e-commerce expert, Shashank sheds light on the following:

  • The evolution of FNP in the Indian physical and digital retail space
  • Challenges involved in marrying customer data across both offline and online channels
  • Understanding customer behaviour to drive repeat usage online
  • Implementation of AI-led personalization at FNP to offer relevant product recommendations through Netcore Smartech
  • The need to deliver these recommendations across channels and at every stage of individual customer journeys

Tune in to learn how e-commerce websites and apps can uplift conversions and marketing ROI with the power of personalization!

Episode Transcripts

Pradyut Hande: All right ladies and gentlemen! Welcome to another episode of the Mar Techno Beat. Specially curated podcast powered by Netcore Smartech. And the next few episodes are all gonna be centered around the power of personalization and recommendation engines today. How they are extremely important to customers, the end customers as well as clients across different geographies and across industries. And today I am extremely pleased to introduce you to my guest, Mr. Shashank Misra, Senior Product Manager at Ferns N Petals, India’s number 1 florist and gifting platform. Welcome, Shashank!

Shashank Misra: Thank you Pradyut for introducing me to a, you know, prestigious platform like this where we can discuss the future of e-commerce. A very warm good afternoon to everyone who is listening to this and who – will listen to this, sorry, and I hope that we have a good session, both for me and for the listeners…so, yes Pradyut, how can we help each other now?

Pradyut Hande: Absolutely, so just before we begin, I’d just like to introduce Shashank, a little bit about Shashank. Uhh -Shashank’s been in the e-commerce industry for almost 10 years with a proven track record and solid specialization across diverse functions such as product management, customer experience, Conversion rate optimization, UI, and user experience and as well as mobile app growth and analytics. So a warm welcome to you Shashank once again and without further ado, let’s jump into the podcast at large.

So Shashank, to begin with, could you tell us a little bit about Ferns N Plants, its genesis, uhh, you know the growth story behind what has made Ferns N Petals such a dominant player in the market today?

Shashank Misra:  Sure So, just to help everyone, Ferns N Petals is also known as FNP, Okay? So just a, you know, small abbreviation for Ferns N Petals. So I’ve been with Ferns N Petals now for more than 2 years, okay? Before joining Ferns N Petals, for me, Ferns N Petals was a company that used to sell flowers only.

Pradyut Hande: Right.

Shashank Misra: In fact, when I joined Ferns N Petals when I scanned Ferns N Petals history and everything-

Pradyut Hande: Right.

Shashank Misra: I came to know that this is, you know, a company who can be seen by millennials, a company who can be seen by old age people, and a company that can be seen by a – person of 30-40 years in him also

Pradyut Hande: Correct.

Shashank Misra: So, the company was started in 1994-

Pradyut Hande: Right.

Shashank Misra: – with just one store in Delhi.

Pradyut Hande: Right.

Shashank Misra: Okay? And from there, we are more than 350 stores across India- 

Pradyut Misra: Right.

Shashank Misra: – and we have global experience, sorry, global exposure to close to 120 countries across the globe and you know we are proud to say that we are world’s biggest uhh, you know, a florist in online gifting which accepts large exposure of, you know, retail experience and online visibility also. Apart from this online visibility, we have recently opened our offices in Dubai, Singapore, and Qatar.

Pradyut Hande: Excellent.

Shashank Misra: Apart from- Ya, yes. So we can probably say we are — and yes, as the time will pass, there’ll be more opportunities next year across the globe. Coming back to Ferns N Petals, strength and promise, I would say that is started from flowers, but I’ve never seen, you know, looking back and they have now explored the categories like cakes, like gifts –

Pradyut Hande: Right.

Shashank Misra: -and now what else you can think of preparation; we are working on it. So close to we have more than 2,00,000 products on the site, as of now.

Pradyut Hande: Right.

Shashank Misra: And yes, we are the premium destination for any emotions, any sentiments, any kind of, you know, celebrations you want to have. We also believe incorporate this thing also, we also work with, we have a division called Senti-weddings, you know, where we help customers to you know, organize their weddings from end-to-end-

Pradyut Hande: Right.

Shashank Misra:-so FNP is a big umbrella, we have an FNP media section, we have an FNP wedding section, we have FNP Online, we have FNP retail. In retail, a lot of customers you know who buy something offline also. And that we have 350 stores across India.

Pradyut Hande: That’s a fantastic growth story, a fantastic growth story, given the fact that you know, FNP, to me, stands out as one of those brands that have successfully made the transition from offline to online and now it can, you know, comfortably say that it is an Omnichannel retail platform. You know, you can experience it in a physical store and you can also experience it digitally.

Shashank Misra: And also one very very imperative point I want to share here with everyone here today is that FNP is a zero-debt company.

Pradyut Hande: Right.

Shashank Misra: Unlike other E-commerce companies who have got money from investments, from other angel investors, etc, etc, we are profitable, and we are no debt company. Very very big, you know, a strong base for us. You know that we are, you can say, debt-free from any liabilities or any concerns you can see a lot of things there.

Pradyut Hande: No that makes a lot of sense, and also a matter of great pride for everybody based out of India to be associated with such a fascinating, you know, journey and entrepreneurship story such as that has been FNP’s since 1994.

Shashank Misra: Ya

Pradyut Hande: Alright, so that brings me to my next question, you know we spoke about how FNP has made the transition from just having physical stores to now having a very strong digital, online presence whether it is across websites or through mobile apps, just wanted your thoughts on, what are some of the key challenges that you face as an online retailer or an E-commerce platform, especially when it comes to customer acquisition, customer engagement, and monetization?

Shashank Misra: Ya, it is a good question Pradyut. See, for any E-commerce player, right, for him, any user who is using their site, is an asset, okay, whether you are a paying customer or an organic customer or it’s a word-to-word customer coming organically

Pradyut Hande: Right.

Shashank Misra: So, for an eCommerce firm, their traffic is their biggest strength. Once the traffic is capitalized, we call them customers.

Pradyut Hande: Correct

Shashank Misra: When they become our customers, we want to play with them, we want to help them, we want to retain them, that is called retention, and that is more and more customers, that is called acquisition, right?

Pradyut Hande: Right.

Shashank Misra: So now the biggest fundamental challenge, or you can say the behavior with FNP spaces is that on Ferns N Petals, mostly customers are coming to buy something not for themselves but for someone else.

Pradyut Hande: Correct. Absolutely.

Shashank Misra: Unlike Amazon, Flipkart, Myntra, you are shopping for yourself. So if you want a jeans or T-shirt, you’ll definitely spend more and more time, until and unless you find your choice of product.

Pradyut Hande: Correct.

Shashank Misra: But in Fern N Petals, you usually come a day before for your respective occasion-

Pradyut Hande: Correct.

Shashank Misra: – For example, your birthday or maybe father’s birthday is the day after tomorrow, so you will plan something, “okay, let’s see if there’s something on FNP or not”’

Pradyut Hande: Right.

Shashank Misra: So the intent is very very clear for our customer ki if any customer’s coming on FNP and has some intent, he is not coming for window shopping-

Pradyut Hande: Correct.

Shashank Misra: So, if you have opened the FNP site, that means there was something in your mind. Whether it is a marriage anniversary, whether it is a birthday, whether it is congratulations, whether it is valentine’s day, Rakhi, whatever…

Pradyut Hande: Correct.

Shashank Misra: So now let’s say your friend birthday is coming a day after tomorrow and you have browsed the (web)site, okay now you like the flower, for example, you personally like this flower, but you are not sure that if your friend will also like that flower or not.

Pradyut Hande: Correct.

Shashank Misra: Now you have a budget constraint also, but because then you buy for yourself, you will still have a, you know, a window of expanding your budget, but when you give someone, you are very very limited.

Shashank Misra: Okay, my budget is 1000, let’s not exceed this-

Pradyut Hande: Right.

Shashank Misra: So you will have the first level of filtration that I want to see the gifts, below 1000.

Pradyut Hande: Right.

Shashank Misra: Now, under 1000, there are a lot of products. There are flowers, there are cakes, they are personalized, so there you can choose whatever you want. So the point which I want to make here is the first challenge which we, you know, the face is that the consumer is not the cust-the waiter who is coming on the site is not the consumer. So basically I’ll never know what Pradyut has bought for his friend, and, how was the experience, because first Pradyut will never feel that experience which is gifting for his friends. 

Pradyut Hande: Right, Right.

Shashank Misra: Right, so this is one opportunity I can, or say, you know, a scope where I can connect to your friend also.

Pradyut Hande: Correct.

Shashank Mishra: Today I connected with Pradyut; Pradyut has already ordered something for his friend. Now…coming…if we talk about the future, maybe the way forward, maybe one or two li- one or three years from today, I would require, you know, a mechanism, amidst AI mm(?), that you know helps me to connect to that recipient also

Pradyut Hande: Oh, so basically you are not just reaching to that one customer at one time, you are also setting yourself up in the future to reach out to future customers, right.

Shashank Misra: Something called a return gift, you want to return something to Pradyut, so this helps me to you know, by one order, I can actually reach two customers.

Pradyut Hande: That-that makes a lot of sense, I think that’s an insight that you know, a lot of traditional e-commerce platforms would not be able to come up with.

Shashank Misra: Yes. So we are fortunate also, but we are a little bit unfortunate also because, you know, I really don’t know ki how was the taste of that cake which you have bought-

Pradyut Hande: Correct, correct.

Shashank Misra: – or what was the quality of that mug which you have bought. You can obviously ask your friend and then feedback, but that’s not really a scalable model because we try a lot of things and we end up having only service-related issues, sorry –  feedback. So even what maximum you can cheer – okay, delivery was awesome. It reached on time, but you actually don’t know how was the cake or how was the fairness of the flower, or how was the freshness of the flowers. So this is something you know, this is a bit of a challenge we face-

Pradyut Hande: I understand.

Shashank Misra: -and the second challenge that I face here, okay – Pradyut’s friend’s birthday has gone. Now, will he come back to me tomorrow again? I doubt.

Pradyut Hande: Yeah.

Shashank Misra: Maybe when his mother’s birthday will come, maybe his wife’s birthday, or girlfriend’s birthday, so there is a limited option to you know come on the site, unlike Amazon. So if I have to capitalize, so what should I do in FNP to help customers to browse daily…like today also we open Flipkart, Amazon but we don’t buy but we have a habit of buying something on Flipkart or Amazon because they have created a habit of opening that particular site

Pradyut Hande: Correct.

Shashank Misra: So this is something you know which I want to improve for FNP.

Pradyut Hande: Right, right…no, that makes a lot of sense…and I think your second challenge is, you know, equally pressing, given the fact that you know your advantage also becomes your weakness; you mentioned that you know, people who land on your website or mobile app have a clear cut intention to purchase-

Shashank Misra: Yes.

Pradyut Hande: – and – so the likelihood of them being just clearly being window shoppers, which is the case with almost 98% of the other E-commerce websites or mobile apps is not the case here. But because they have such a clear intention to make a purchase, you know, getting existing customers back to your platform can be a challenge in the future.

Shashank Misra: Yes. We wanted to do it but somehow, you know we had tried a lot of things but I can’t compel someone to, you know, buy something for the cakes because you buy cakes rarely for yourself. I don’t know- me personally, I am 31 years old, I have never bought a cake and then eaten it myself. So that’s something I want to create but technically I can’t create this intent for a customer.

Pradyut Hande: Right, right – no that makes sense.

Shashank Misra: This is the challenge for myself, whether I want AI/ML can help me or not.

Pradyut Hande: Actually that bring me to my next question; so while you mentioned that, you know, getting existing users to become, you know, regular customers on your platform can be a challenge, in that regard, how can the application of machine learning and artificial intelligence help you with probably setting up a powerful recommendation engine, that gives users exactly what they want as soon as possible?

Shashank Misra: Yes…so you asked a good question because you know in a way I have also-I can talk the entire day on this, okay? So, yes, so the question is, for example, if you are coming for an occasion called Mother’s day…okay, now, mother’s day itself has given me three answers.

Pradyut Hande: Correct.

Shashank Misra: That you are coming for your mother; then your wife’s mother, the recipient will always be female.

Pradyut Hande: Right.

Shashank Misra: And mother- assuming India as a country okay, if you are gifting for your mother, that means your mom is at least 35 years plus.

Pradyut Hande: Correct.

Shashank Misra: So these 3-4 answers are self-driven from this insight. Now using this data, and if you are a returning visitor, I know that you had bought a cake last year for mother’s day, okay?

Pradyut Hande: Right.

Shashank Misra: So now, AIML can help me in that sense that I will have only those recommendations which are mother’s day specific.

Pradyut Hande: Okay, Okay.

Shashank Misra: Sometimes my site also – sometimes shows incorrect recommendations to the calls. For example, if you are browsing mother’s day cake-

Pradyut Hande: Right.

Shashank Misra:– Recommendation might show a cake which is written with a Happy Birthday.

Pradyut Hande: Right.

Shashank Misra: Okay, because lot of, lot of cakes on my site-

Pradyut Hande: Correct, but those would be irrelevant recommendations.

Shashank Misra: Right. I’m not-you may also like, there might be a chance that I will show a couple kissing on a cake.  You know, I love you cake.

Pradyut Hande: Right.

Shashank Misra: Because the flavor was the same; you were searching for a chocolate cake, there are also occasion-related cakes there. So my accuracy should improve in that sense that I should only browse mothers’ day cake only. And relevant to your requirement and all.

Pradyut Hande: Correct.

Shashank Misra: So-and coming back to mobile phone site and apps, till my data is centralized, all the, you know, rendering and all the adjustments on the product, you know, will be similar on the mobile site also and the app also.

Pradyut Hande: Right. 

Shashank Misra: But, my data says that the propensity of opening the app on maybe, you can say, on the launch is more than on the mobile site.

Pradyut Hande: Okay, Okay.

Shashank Misra: So, my potential product for AIML adoption is App. App first, then mobile-first. And then the mobile site. So because the person who has my app installed is nearer to me compared to an m-Site user. 

Pradyut Hande: Right, Right, makes sense.

Shashank Misra: Right, so for abbreviation, I know the device idea, I know the app idea, I know who is he, how many times, where he is browsing on the app, so based on these data and clubbing AIML on it, I can at least, you know, I can help this guy to buy at least a cake or maybe something else for his mom.

Pradyut Hande: Right.

Shashank Misra: So this is something of an interesting area where you know, I want to explore the AI/ML concept.

Pradyut Hande: Right. So is it also fair to say that while providing the most relevant recommendations on the home page or your product display page is important; your recommendation engine is also important to help you up-sell and cross-sell.

Shashank Misra: Definitely, definitely. Because we are here to increase our business. So let’s say last year you bought a cake of 500 rupees, I will assume that you understand that I want to sell you something of more than 600.

Pradyut Hande: Right.

Shashank Misra: So why only cake? Why not a flower and a cake?

Pradyut Hande: Correct. Absolutely.

Shashank Misra: So this is upselling something which obviously AIML can have end number of uses and can help me end a number of ways.

Pradyut Hande: Correct. So again, fair to say that product bundles also become a major component in terms of your recommendation engine.

Shashank Misra: Right. And thanks to our vast catalog, you know, and our sourcing, strong sourcing team, you know, we try to cover all kinds of designs, range of products; we have personalized socks also, we have personalized clocks, watches, cushions and also we are about to bring electronic gadgets. For example, plop on speakers, if you have ever heard, we personalize it for you. You have a name embedded on your speakers.

Pradyut Hande: Oh nice!

Shashank Misra: This kind of – this kind of stuff we are also launching, and are very- our watch dial, you can have your name embedded in your watch. So this kind of stuff we are also exploring and then you know you will see a range of profiles of watches also.

Pradyut Hande: Right. Right. But that makes sense. So it’s safe to say that the personalization experience for every customer begins on the website or the mobile app and it is extended to the physical product as well; whether it’s a watch or a cake or etc.

Shashank Misra: Yes, but one thing you know, I want to ask really to everyone who is listening; I want feedback you know, how can I help my customer, you know, make him feel the quality of the product. So that means you are browsing a flower bouquet; apart from images and videos, what else can I do for him, to convince him that this is the best flower? Can he feel the most ultra-high resolution image? That’s a long thought. Or maybe you know, what else? It is an open question. I want to help my friends. What else can I show for that cake? Should I show him a cake-making video? Should I show how soft that cake is? The moment you see that cake; you feel like eating it. So this kind of experience, I want to give.

Pradyut Hande: That-that’s an interesting take actually and I am sure that we circulate this podcast to our listeners, we definitely ask them for recommendations and feedback on how they can also, you know, help you fix some of these issues.

Shashank Misra: Yeah because I am sure most of the listeners must have browsed something or the other on FNP. They must be having some good or bad experience. I will be happy to know you have that feedback also.

Pradyut Hande: Sure, sure. I am sure we can arrange that. Alright, moving forward, while we spoke about providing the most relevant and contextual recommendations on the website, the mobile app, could you also shed some light on the entire customer journey, so for example, your recommendations cannot be restricted to your website itself; you would also have to, you know, sort of craft those personalized multi-channel campaigns, right? It could be through emails or mobile phone notifications, so could you tell us a little bit about that?

Shashank Misra: Okay wow. So let’s say, today, I can communicate with customers via 5 to 6 channels.

Pradyut Hande: Right.

Shashank Misra: One is email. One is push. One is SMS. One is dial call. One is in-app notifications and one is browser notifications. So we have a very very strong, you know, call-back feature, where if you are coming on a flight, and if you have added something to your cart, within 5 minutes, you will get a call and an SMS.

Pradyut Hande: Okay, Okay.

Shashank Misra: Because we know that you have a clear intent, and you are trying to buy something, for some or the other reason, you are not able to buy. Our customer care team has a very very strong product there, where they can see who browses what and what has he added before in the cart, immediately, they trigger a call. So one is this. Second…so when I say I want to look at a cohort of these customers, and if there are physical behaviors of the customers which I want to observe today, maybe last two years, one kind of customer is your loyal customer. You know what you want to buy something and where to buy it, so he does not need much help, in terms of assistance. The 2nd type of customer are the ones which we call as fresh customers. So for them, I want to create an experience, you know, maybe in FD terms of testing or something; where I want to show the strength of FD first. So if you have landed on FNP, which is the best place you have come up with, and how we can help you.

Pradyut Hande: Okay.

Shashank Misra: For them, I want to know his gender; I want to know his name, I want to know his age, not lot of greedy things, you know, I want to know where he is located, where he wants to send his, you know, product. Until and unless he orders, I want to know a lot of things from him. And the third category is the customers you know who have listened to something from India and who want to give a return gift for the customer you have already bought for them. So these are the customers who know something-something about FNP but don’t know how to browse the site. So for that, they have a 50% intent. Yes, I want to buy something for them. There I can relate, yes, Pradyut has gifted me this particular product for me; these are the products that are similar to me as a return gift. So I have helped your friend in, you know, reducing the funnels and landing into the accurate products which we may buy. So these kinds of journeys, mini-journeys you can create and you know, looking at the data which he has provided of what kind of potential they have; we can break the products-sorry, customers in types of potential money, that this kind of customers buy for 500 to 1000 rupees, these are the customers who buy from 1000 to 2000 rupees, and so on.

Pradyut Hande: Right.

Shashank Misra: A very beautiful thing I like about user management and data analytics is the intent part of ideation, which I believe is the first click. Although users who are into floor management and want to be in data analytics, an experience which I want to share is that any customer who shows the first click, where he sees us first, is an intent. So capturing the first click of a customer can, you know, give you a lot of answers.

Pradyut Hande: Correct-Correct.

Shashank Misra: Sorry?

Pradyut Hande: I said very true.

Shashank Misra: Yes, yes. So these small-small things you know we have captured in society and collating that data and yes, thanks to Netcore and box, you know who has helped us in improvising, personalizing journey for a customer. And we are looking for a long term, you know, improvisation there also.

Pradyut Hande: Ya, thank you! Thank you for those kind words and you know, I’ll say, the entire personalization journey for every customer has to be, you know, revised over a period of time, because customer behavior varies on an individual basis and it’s so important to you know, respect how that behavior is changing. So while you can have a very solid customer data platform, or a 360-degree view of individual customers, which could have data points such as your demographic, geographic, device-related, or behavioral data, what’s important is to also keep reimagining how the experience can be personalized for individual customers.

Shashank Misra: I-i-I’ll share one interesting case, okay? There is something called O database for us, we call it ODB. So let’s say today you have bought something for your mom, next year, you will rebuy ODB. 

Pradyut Hande: Okay

Shashank Misra: And I will remind you last time you bought something for your mom, why not this time. Now, here comes the interesting story. Let’s say a boy is gifting for his girlfriend, something, on valentines, okay? Next year, our ODB call centre called this boy and asked, do you want to order something for your girlfriend, and you want to order something now? What if that customer has had a breakup with that girlfriend? Or you know, especially, or maybe he had a second girlfriend. And that customer care executive called that, saying that her name was Ankita, his first girlfriend, his second girlfriend’s name was Neha. And he was with Neha, and an email came out that you want to order something for Ankita? That is something you know, we haven’t done anything wrong, we haven’t done anything wrong; this is called personalization, this is called human analogy. So this is something, you know, very very interesting for FNP, is there something we can do about it, I don’t know.

Pradyut Hande: I’m sure…these are, I think, very use cases that the likes of FNP would have to address.

Shashank Misra: Exactly, because you know we are- see, FNP is based on occasions and sentiments. We are an occasion driven company. So as of now, tomorrow’s rose day. And today, my traffic is like mount Everest. In the back of this 30 minutes’ conversation, you know I could see a lot of orders and usable data, in the last thirty minutes, because rose day orders are coming today like anything. 

Pradyut Hande: Okay, Okay

Shashank Misra: Ya

Pradyut Hande: Alright, so a lot of fantastic insights were shared by Shashank. I would like to close by asking you one final question. So we spoke so much about, you know, data analytics and how it is important to gather the relevant data points, from individual customers, how it is very very critical to personalize the entire customer journey and different digital touchpoints, the importance of an AIML recommendation engine, I would just like (to know) your final thoughts on what you believe is the future of digital or mobile marketing, or the application- the further application of ML/AI and how you think this is going to shape the E-commerce ecosystem.

Shashank Misra: See, I like Robert Downey Junior a lot, five lance, okay? So I visualized, you know, Alexa is one part, okay? So if you think about AI and then- maybe I can just say something to someone and you know, he knows my correct mood also, if I am angry, or I am upset, or if I have a breakup; if I have just been left with a daughter or a son, maybe it is my second marriage, that data knows from me…and it’s just fraction of minutes, you know; if I buy something for my friend, she also knows how good my friendship is with Pradyut. And Pradyut has worked with me in so and so company, what is the age of Pradyut…so instead of browsing something, the AIML could simply say this is the best product for you today, just place an order in 2 seconds, and the order will be placed. This kind of delearning, I don’t know, if it’s possible or not, to capture the emotions of that customer. And you know, a device-today, a lot of devices are there for your needs, in a heartbeat. So I am just thinking aloud, you know; your mood, your current date of the month, where you are located, what’s your present scenario and we have said something only once, okay, ki I want to gift something for my wife and – if you are ordering for today, there is a birthday, anniversary, etc, etc, these kinds of, you know, hi-fi, you know – I am sound filmy, but I think this is possible with AIML.

Pradyut Hande: No, it makes a lot of sense, and a very interesting use case also that could be attributable to AIML in the future, and that brings us to the close of this particular episode of The MarTechno Beat. Thank you so much for joining us, Shashank, and sharing your extremely valuable and actionable insights.

Shashank Misra: Thank you so much Pradyut for your time and allowing me to speak.

Pradyut Hande: Alright, thank you so much, and for all those listening, we’ll be back with another podcast very very soon, where we are going to discuss the cutting-edge developments around personalization and recommendations.

 

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