MAM
Weekend Unwind with Gargee Designer’s Ravi Gupta
Mumbai: With another weekend upon us, it is time to unwind with the latest Q&A edition of Indiantelevision.com’s Weekend Unwind—a series of informal chats that peek into the minds of business executives through a fun lens in an attempt to get to know the person behind the title a little better.
In this week’s session, we have Gargee Designer’s creative director Ravi Gupta.
Gupta is a fashion designer and the creative director of Gargee Designers. He honed his skills by completing his B.A. in Design & Technology, during which he actively participated in renowned competitions worldwide, including “WOW” in New Zealand, “The Debut” by Wills Lifestyle in Delhi, “Haining Warp Knitting Fashion Design Competition” in China, and “Swatch Alternative Fashion Week London.” These experiences served as a stepping stone for his journey into the world of fashion.
So without further ado here it goes…
1.Your mantra for life
Ans: My mantra in life is to Don’t tell what you cannot show. This is what pushes me forward in life.
2. A book you are currently reading or plan to read
Ans: One book that I am currently reading is The 12-Week Year. It’s reshaping my approach to productivity and goal-setting, emphasizing the power of consistent action and strategic execution.
3. Your fitness mantra, especially during the pandemic
Ans: My fitness mantra has always been to wake up early in the morning meditate and do yoga and even during the pandemic this was the fitness mantra I solely followed.
4. Your comfort food
Ans: When it comes to finding solace in food, nothing compares to the comforting embrace of a warm, flaky paratha generously slathered with creamy butter and paired with tangy pickles.
5. A quote or philosophy that keeps you going when the chips are down
Ans: “Reflect upon your present blessings of which every man has plenty; not on your past misfortunes of which all men have some.” Thankful for whatever we have rather than focusing on misfortunes.
6. Your guilty pleasure
Ans: Indulging in Big Chill’s desserts is my ultimate guilty pleasure whenever I crave something sweet. From their decadent cakes to their creamy ice creams, each bite is a delightful treat for my taste buds, satisfying my cravings like no other.
7. The last time you tried something new
Ans: A very recent thing that I tried is Chat gpt4, as the world is getting technologically advanced chat gpt has become one handy tool which has become a necessity in today’s time.
8. A life lesson you learned the hard way
Ans: “The greatest wealth is health” highlights the value of good health. Effective communication and transparency build trust, collaboration, and goal alignment. Active listening, clear expression, and feedback are key. I aim to foster open dialogue and problem-solving.
9. What gets you excited about life?
Ans: What excites me about life is the daily opportunities to meet new people, and engage in novel experiences, particularly those involving creativity, which ignites a spark
10. What’s on top of your bucket list?
Ans: At the top of my bucket list is to visit Japan. The place is known for its traditional clothing, especially the kimono.
11. If you could give one piece of advice to your younger self, what would it be?
Ans: Embrace learning and growth, trust your abilities, and persevere through challenges. Stay passionate, and resilient, and cherish the journey ahead.
12. One thing you would most like to change about the world
Ans: One change I aim for in the world is to advance sustainable practices across all industries. Our planet confronts various environmental issues such as climate change, pollution, and habitat destruction. To enact meaningful change, global systemic shifts are imperative.
13. An activity that keeps you motivated and charged during tough times
Ans: Dedicating time to read motivational literature, and engage in conversations with supportive individuals who uplift, inspire and create a positive mindset amidst challenging circumstances.
14. What lifts your spirits when life gets you down?
Ans: Learning from past experiences and understanding life’s inevitable ups and downs is what lifts my spirits, it helps break the monotony, fostering peace and rejuvenation.
15. Your go-to stress buster
Ans: My go-to stress buster is spending time at the club, where I can unwind, socialize, and enjoy music and dancing.
Digital
GUEST COLUMN: How AI is restructuring distributor and retailer motivation models
From incentives to intelligence, AI is redefining how brands engage channel partners
MUMBAI: Artificial intelligence is rapidly transforming how brands engage with their most critical yet often overlooked stakeholders: distributors, retailers, and last-mile influencers. For Abhinav Jain, co-founder and CEO of Almonds Ai, this shift marks a fundamental departure from traditional, transaction-led incentive models toward behaviour-driven, data-intelligent ecosystems. In this piece, Jain examines how AI is enabling brands to decode partner motivations, predict engagement patterns, and deliver personalised, scalable experiences—ultimately redefining channel relationships from transactional exchanges to long-term growth partnerships.
Across many sectors, there is increasing recognition that motivating those who bring products to market (distributors, retailers, last-mile influencers) poses a growing challenge.
Brands continue to invest significant marketing and digital resources to consumers, yet in many countries and the vast majority of emerging economies, these types of consumer-focused investment areas have had little impact on ultimate product delivery. Rather, it is still the case that traditional retail continues to make up most products sold.
So why is it that the systems built around motivating these channels have yet to evolve?
For decades, distributor and retailer engagement revolved around static schemes – quarterly targets, volume-based rewards, and occasional trade promotions. These programs were designed around transactions, not behaviour. The assumption was simple: if incentives increase, performance will follow.
Now, with the advent of artificial intelligence, the definition of performance is being challenged.
With the development of artificial intelligence, businesses can move beyond simply creating loyalty based on transactional-based models and toward models built on behaviours, the behaviours of channel partners that are intrinsic to their motivations in engaging with particular brands. As a result, the means by which businesses develop relationships within their distribution network are starting to evolve; thus, ultimately changing how brands interact with those within their distribution network.
Assessing engagement: Transitioning from transactional- to behavioural intelligence
Traditional loyalty systems refer to transactional activity (sales data). Although this data is valuable and important, it only provides a partial view of engagement across the channel partner.
For example, a retailer may have a high frequency of sales of a product, but their lack of engagement with the manufacturer would not reflect that they have true loyalty toward that brand. Conversely, a retailer who actively participates in training programmes, acts as brand advocates, and is engaged in learning with the supplier would exhibit more profound levels of loyalty but would have been invisible based on historical incentive programmes.
Artificial intelligence allows for the identification of behaviours that help to address this gap. Brands are able to use a variety of engagement data points, participate in learning programs, respond to communications, redeem behaviour and track platform use behaviour in order to identify motivation through behaviour.
McKinsey has stated that companies that leverage advanced analytics for their sales and distribution functions can achieve as much as a 15-20 per cent increase in productivity due to increased awareness of their behavioural trends throughout their networks.
This visibility of behavioural patterns within channel ecosystems can be transformational to brands as they can now view how partners engage on their path to purchasing products, instead of just measuring the sales revenue generated by those purchases.
Predicting motivations, not just measuring performance
Possibly, the largest contribution of Artificial Intelligence (AI) to helping brands engage with partners via channel ecosystems is its ability to predict future engagement versus simply measuring past performance.
Traditionally, brands only realised that a partner was disengaged (not likely to purchase products) once their sales performance had already declined. By then, the brand would have to use significant amounts of incentives or aggressive promotional activities to recovery their partner’s engagement level.
AI models can help organisations to detect early signs that a partner is becoming disengaged, such as declining participation in learning modules, declining interaction via the platform, or slower reward redemption rates. These indicators can help organisations to proactively engage with their partners before their sales performance begins to decline.
The practical application of AI and predictive analytics gives brands the ability to re-engage with their partners prior to their sales performance declines. For example, instead of developing and implementing broad-reaching incentive programs that provide a “one size fits all” incentive to all partners in an ecosystem, brands are able to develop targeted, engaging re-engagement programmes. This is how personalisation can be done on a large scale, such as across global distribution and retail networks.
The vast majority of distributor and retailer channels have thousands, if not millions, of individual channel partners. Historically, providing personalisation to such a large number of businesses has not been feasible.
However, with the advent of AI, personalisation at scale is becoming a reality.
Brands can now create tailored engagement journeys for all their partners, based on their partner profiles, through some combination of machine learning models and behavioural segmentation. For example, high-performing distributors might receive higher levels of leadership-based recognition and greater incentives to continue to grow. Emerging retailers, on the other hand, might be supported with training, onboarding rewards, and measurable performance milestones.
The shift towards personalisation of partner engagement echoes the direction that consumer marketing is already moving towards.
According to Salesforce’s report, over 70 per cent of customers expect personalisation in the way that brands engage with them. As such, there is a growing expectation for B2B ecosystems to have these same types of expectations from their channel partners.
Gamification and continuous engagement
AI is also radically changing how brands will engage with their channel partners through the use of gamification.
Many traditional incentive-based contests and leaderboards would spark temporary engagement among their participants, but they struggled to sustain engagement over time. With the use of AI, gamification mechanics are evolving dynamically based on historical and evolving participation patterns by their channel partners.
Challenges, rewards, and recognition structures can be modified continuously in order to sustain engagement with all of a brand’s partner segments. This will provide a greater opportunity to move away from episodic campaigns towards ongoing, continuous engagement experiences.
When channel partners receive motivation as part of their daily business activities through recognition, learning, and tracking their performance, long-term loyalty will be achieved.
Aligning motivation to broader impact
There is a growing trend within the channel ecosystem to integrate sustainability and socially responsible behaviours into the channel partner programmes of brands.
Increasingly, brands are motivating their partners to use sustainable practices in their operations, participate in sustainable practices like sustainability-related knowledge programmes, or promote products that are in line with their sustainability objectives.
Brands can use AI to monitor and measure these types of behaviours and incorporate them into their incentive frameworks so that brands can align their commercial objectives with broader social and environmental outcomes.
A shift in the way brands view their channel partners
AI is having the most significant impact on the way that brands are now viewing their channel partners, as it relates to the underlying philosophy of those fundamental relationships.
For the past several decades, many brands have viewed their channel partners as intermediaries in the supply chain. More and more brands are now beginning to view their channel partners as key ‘partners-in-growth,’ and their actions can have a direct impact on market performance.
In fact, all the channel ecosystems are using behavioural engagement platforms to design new models that reward not just transactional behaviour, but also create continuous engagement journeys for their partners, where their partners can receive recognition for their participation, learning, and continued engagement, thereby reinforcing long-term loyalty to the brand.
The future: Intelligent channel ecosystems
As we consider what the next phase of channel engagement may look like, many believe that it will be based on intelligent ecosystems, using AI to continuously monitor and adjust the engagement strategies used to engage their channel partners, in real time and based on the behaviours of those partners.
For brands operating in complex distribution networks, the ability to perform well will be determined both by whether products are available to their customers, as well as by the enthusiasm, expertise, and loyalty shown from each channel partner that represents the brand each and every day that they are working on behalf of the brand.
While AI clearly does not eliminate the human aspect of a brand’s relationship with its channel partners, it does allow brands to better understand and nurture that relationship.
In markets where the last mile will determine whether a sale is made, how one leverages the intelligence gained by using AI will ultimately be the difference between gaining a new, sustainable competitive advantage versus losing one.
