86% of customers say that personalization impacts what they purchase, and one quarter admit personalization ‘significantly influences’ their buying decisions.
Personalization is something that has become critical to a brand’s success, regardless of the industry. Customers expect a personalized experience across all touchpoints including web, mobile, in-store, email and many more. To succeed in your marketing efforts, you need to understand how customers interact with your brand, and then customise their experiences across the journey.
To better understand the role of personalization in the e-commerce sector, we had a discussion with Mr. Shashank Misra – Senior Product Manager at Ferns N Petals (FNP). Read on to know more about how companies like FNP have successfully grown over the years by leveraging the power of personalization and recommendation engines.
PH: To begin with, could you tell us a little bit about Ferns N Petals and its genesis? What has made it such a dominant player in the market today?
SM: We started in 1994 with one store in Delhi. Today we more than 350 stores across India. It is one of the world’s leading florists and online gifting platform with great retail exposure and high online visibility. With time, we look forward to exploiting more opportunities as they come our way, by leveraging the increasing applicability of AI/ML in businesses across all industries. Starting with flowers, we have now expanded into cakes and personalized gifts and give our customers more than 2 lakh products to choose from.
Today we stand as an omnichannel retail platform, serving both offline and online customers.
PH: It is remarkable how FNP has grown over the years. I would want to know about your thoughts on the challenges you face as an online retailer or e-commerce platform when it comes to customer acquisition, engagement, and monetization?
SM: For any e-commerce business, any user that visits their site, is an asset for them and the centralized traffic on their website is the company’s customers. At the end you want to engage this set of customers and retain them. Now, the biggest fundamental challenge we face is that our customers are coming to buy products, not for themselves, but for someone else. Whereas in Myntra or Flipkart, customers are mostly shopping for themselves and they spend a good amount of time on these platforms. Let’s say you are to shop with FNP, then you are more likely to visit us a day before an occasion. Having said that, the customers on our platform always come with the intent of purchasing. But again the challenge here is that the customer also has to take into consideration whether person for whom the gift is, will like it or not. There is a budget constraint as well.
The bottom line is that my customer is not the consumer. We will never know about the experience of the customer and we miss out on feedback in terms of product quality. But again, there is a positive side to this as I get the opportunity to connect to the customer’s friend also. One order helps me reach to two customers. The second challenge is that you could face is that you are unable to determine when your customers will be back. You have to come up with ideas that would make people at least just browse through your site. I think the increasing dependence on AI/ML could help us resolve some of these challenges we face.
PH: You spoke about the challenges you face and you mentioned that AI/ML could help resolve these challenges. I want to know how AI/ML can help with setting up a powerful recommendation engine that would give the users what they are looking for.
SM: This is a very interesting question. Let’s assume you are a customer who is looking to gift something to your mother on the occasion of Mother’s Day. That itself gives me a lot of information in terms of your mother’s gender, age, etc. Now, if you are an existing customer and suppose you bought a cake last year, then with the help of AI/ML I will give you only those recommendations that are relevant to that particular occasion similar to your purchase last year. The recommendation engine helps us upsell and cross-sell more. AI/ML helps us give suggestions to customers. The aim is to make the customer buy more and that’s where AI/ML makes the job easier by providing relevant recommendations to the users.
PH: Moving forward, can you shed some light on the customer journey?
SM: Today, I can communicate with customers through 4-5 channels like email, push, SMS, call, in-app notifications, and browser notifications. At FNP, we have a call back feature wherein if you’ve visited us and added something in our cart, then within 5 minutes you will get a call and SMS because we know you have a clear intent of buying something but due to some reason or the other you are unable to do so. I have also observed three kinds of behaviours in customers or rather 3 segments of customers. One is the loyal customer, who knows what to buy and does not need any assistance as such, the second set of customers is fresh customers for whom we would want to create an experience that would turn them into loyal customers. Third are those customers who engage with us because they received a gift from us through an existing customer. They have a 50 % intent of buying something and this is where we use AI/ML to show the customers what his/her friend would have bought and helped them begin their journey with us.
Most of the information you want lies in the first click of the customer. Data Analytics helps you analyse this information further to create a more personalized journey for your users. And thanks to NetCore we have been able to improvise on our personalization journey.
This gets us to the point that it is important to understand that the behaviour of customers varies individually and personalization has to be revised accordingly.
PH: Very rightly said. Everything boils down to creating a different experience for every customer. This brings me to my last question. What are your thoughts on the future of digital or mobile marketing and how according to you will the application of AI/ML change the e-commerce ecosystem?
SM: If I think out loud, then looking at the rate at which AI/ML is changing the face of marketing, I think it is safe to conclude that there will come a time when there will be a device that would have all relevant information on the customer and it will be able to capture the users’ emotions just by his/her voice. There will be a voice that will be telling you what product is relevant to you and that you can get it just by looking at it. This may sound rather difficult but with the way AI/ML is advancing, anything seems possible.
With this, we come to the end of the second episode. There were indeed a lot of interesting insights brought to the table. It is true that while omnichannel may sound like a corporate buzzword but the concept is pervading. You need to leverage the power of personalisation if you wish to succeed in the business world. With the advent of AI/ML, it has become a lot easier for businesses to gain insights on the data available to them. Your focus should be on delivering seamless and consistent customer experience across all channels, and build the path for the customer journey. Then, you reap the rewards.
This blog post has been repurposed from our podcast series ‘The MarTechno Beat, titled Scaling E-Commerce Growth Like Ferns N Petals with Omnichannel Personalization. This post includes key insights shared in the podcast along with some additional information.