With the markets gradually limping back to life again, businesses are realizing that a lot has changed. Customer expectations, buying behavior, and sentiments are quite different now and this change calls for a recalibration of marketing strategies and efforts. We have been conversing with marketing leaders from across verticals and brands to get their perspective.
In this interview, Avnish Anand, the Co-Founder and Online Head at CaratLane, talks about his journey being the owner of digital product management in CaratLane and how his team strives to create seamless and integrated customer experience across traditional and digital channels through the usage of data science and ML-powered marketing tools. CaratLane is one of the leading online and physical jewelry retailers in India.
This conversation is a part of our exclusive interview series with top marketing leaders, conducted in collaboration with ResearchNxt, a leading marketing research company that does in-depth research on trending enterprise technologies.
Key takeaways from this interview are:
- How machine learning-powered marketing approaches identify escalation prevention mechanisms through sentiment studies for CaratLane customers
- Why personalization needs to become even more critical now post the Covid-19 business era and how CaratLane already has the first-mover advantage
- How data science is being used by CaratLane in maintaining a lean inventory model and to understand customer’s preferences and start building back the inventory at different stores accordingly
Here are some extracts from the insightful conversation we had with Avnish.
Netcore: Could you tell us a little about your background and how you came to be the Co-Founder at CaratLane and your role as the leader of digital product management in CaratLane?
Avnish: I became a part of this company in its initial stages way back in 2007 when the business was formed by just the two founders Gopal and Mithun. The company was started based on the idea that we could sell solitaires and then diamond jewelry online. I came on board without any background in digital business. We built the company slowly and put all the other things in place and took up various roles as required. I was there for 3.5 years and then left to join Times Internet. However, in 2016, I came back here, and we started expanding into new things. I started managing more core functions like product management, digital marketing, sales, and so on. While these responsibilities have been kind of organically added, I truly enjoyed every bit of it.
Unlike other industries, the customer journey and the conversion time in the jewelry business is long and complicated. Hence, data science plays a vital role here.
Netcore: From 13 stores in 2016 to 92 now, this is an excellent progression to being India’s leading omnichannel jewelry brand. How does CaratLane create seamless and integrated customer experience across traditional and digital channels?
Avnish: For us, omnichannel is not the end goal. It is a way of life at CaratLane. What we care about strongly is how we solve our customer problems in a better way. Our overall business funnel has two critical aspects; the first part is demand generation, which is getting people to the website and leading them into the buying journey. The next part is the buying journey itself which includes browsing, discovering, and selecting products, until it becomes a conversion. So, over the years, from these customer journeys, we identified triggers for purchases and the issues in the buying process. The learnings led us to start the physical stores as well, which instilled more trust and credibility in our online marketplace. The stores were introduced as a destination for “Try and Buy” convenience. Moreover, the stores also cater to a lot of other operational and service delivery requirements. So, whatever solutions or channels get built is always done by keeping the customer as the focus.
Additionally, at CaratLane, we look at customer segments in slightly different ways. A critical section for us is that is it for self-purchase or is it for someone else. Secondly, there are patterns around cities when it comes to try and buy jewelry. Thirdly, very obviously, we have the genders as a segment. We also segment customers based on the frequency of purchase and even occasion-based buying. To sum it up, our customer segments are created based on the various attributes and use cases of the buyers.
However, to ensure that the customer experience is seamless and very personalized for each customer, we need to find and collect the buyer signals from as many sources as possible. And this is where technology comes into play. I believe complete personalization is still a hopeful dream mainly because standard solutions available in the market don’t work well for us. Secondly, unlike world leaders like Amazon, we don’t have massive data where just correlation itself can be excellent insights. So, I think we are on this journey we will soon be using AI-led personalization once we are at a strong position with the data collecting process and then building the right technology and experiences to create it at scale.
Netcore: Online jewelry business primarily runs on a very lean inventory model to ensure the price advantage. Do you use any AI-led data mining for making smarter decisions around pricing and promotions across channels, and even supply chain and inventory management?
Avnish: Absolutely. With the right approach and the right kind of data, we have been able to do inventory planning and saw a lift in business. Even in terms of supply chain and category management, we start by understanding the customer’s preferences and start building back the inventory at different stores accordingly.
Post the Covid-19 phase, the planning and execution of personalization needs to happen in a much better manner as it becomes even more important now.
Netcore: The role of Artificial Intelligence (AI) is and will be crucial for the personalization of services, making smarter decisions around dynamic pricing and offers. Are you leveraging AI-led decision making to deliver omnichannel experiences for your shoppers?
Avnish: Yes, one of the use cases where we have already implemented Machine Learning (ML) tools is performance marketing. All marketing campaigns along with dynamic pricing based on customer attributes, and then the whole remarketing part is being carried out by tools equipped with ML. Another use case is that we try to understand the customer journey with various data points like intent types, and then we accordingly serve the customer with relevant offers.
However, unlike other industries, the customer journey and the conversion time in the jewelry business is long and complicated. Hence, data science plays a vital role here. Moreover, we also have some other use cases, which are in our post-order scenario, like we are working with a new chatbot involving ML technology. We are already using the chatbot conversations to identify escalation prevention mechanism through sentiment studies. So, there are many use cases that we have seen in the data science front, but going forward, we will see more use cases as the amount of data being collected increases in size.
Netcore: What is CaratLane’s strategy to overcome the challenges this year, and what kind of government intervention would help the Indian jewelry industry in times of this COVID-19 crisis?
Avnish: Jewelry industry has one of the lowest digital penetration in the country and is primarily into physical retail. So, I can already see many changes happening in this front as everybody is trying to get on to a digital platform. In that sense, I feel that we are, kind of more prepared for this change, which is going to happen. So, in this scenario, the execution of this personalization that we were discussing needs to happen in a much better manner as it becomes even more important now. That means we need to work even harder now, making sure that we stay ahead of the curve. Secondly, there is a lot of concern in the industry about jewelry being a luxury category, and will it be the worst affected, etc. However, I feel that jewelry being in the luxury category doesn’t necessarily have to be in the non-essential category as it is, particularly in India, very much connected to the emotional and psychological well-being of the individuals who are consuming it as a possession. And I do not think people will completely change the way they live their lives and the way they seek joy in this world. I think that is the most positive thing to happen. So, our connections and communications with the people have to adapt accordingly to the changing situation.
Now the last part about the government, I think that the government needs to allow things like a store opening or e-commerce deliveries. And I am sure that they have the reasons why they have been extending it. In terms of support, I think that there is more work that is required because there are lots of small SMEs and vendors in this industry, small exporters, etc., and because the business has completely stopped for them. Moreover, this industry is vital to the country as we do many exports. So, the policymakers should not write us off as a luxury category; we are still businesses that employ so many people. And I think the government would look at it in that light and not say it’s not essential.
We believe this conversation helps you understand the shifts happening in your business vertical, and how can AI and ML-based tools aid you in overcoming the present challenges posed by the COVID crisis. To learn more about how an AI-powered platform like Smartech can be your partner in this journey, get in touch with us.