MAM
Tamil Nadu’s retail brands weigh in on television as a marketing medium
MUMBAI: Tamil GECs should include subtitles in their shows to increase stickiness and drive more brands to advertise on them, was the conclusion of the very insightful ‘Retail Therapy’ session at the recently concluded Tele-Wise Tamil conclave by Indiantelevision.com. The panel was discussing the role of retail advertisers in the Tamil market and how broadcasters can get them to advertise more on television.
Part of the panel were SRM University head of marketing & media Chaitanya Gurijala, Challenge Advertising founder and CEO R. Sakthivel, Kalimark Group joint managing director J. Ramesh, Viveks vice-president marketing B.S. Vishal, and Jaya TV Network business head Viswanathan Devaraj. The session was moderated by Win News executive director, Cornerstone founder president, and Puthiyathalaimurai Group former CEO R.B.U. Shyam Kumar.
The two broadcasters on dais, Devaraj and Kumar, discussed how important subtitling can be in not only driving more viewers to regional channels but also greater advertising revenues. However, they insisted that it has to be evaluated on a cost-benefit model before implementation.
Kumar noted, “I am sure moving hyperlocal, particularly in the GEC segment, will drive a lot of brands because coming from a news channel, I have seen those 4-5 aston bands that we run get a lot of stickiness to our programmes. Even GEC segment can try subtitles as an option to break the ongoing rules and get more traction. Forget about advertising, first of all, it will increase the viewer base to a great extent.”
Devaraj said, “I agree that stickiness to a content increases when there are subtitles on it. In Singapore, if they have a Tamil movie playing, they post subtitles in four different languages, including Tamil language. But when we look at, say Vijay TV, that goes on air in Singapore doesn’t have subtitles in all languages because it is a costly affair.”
To this, Indiantelevision.com founder, CEO, and editor-in-chief Anil Wanvari added that it takes approximately between 12-15 thousand rupees to add subtitles in a half hour episode.
Kumar claimed that if GECs can monetise that additional cost to the production of an episode of a TV show, which he assumed to be close to Rs 1.50 lakh for an half hour run, broadcasters will be equally interested in drawing new audiences.
Devaraj added that this will require a deep analysis based on the cost effectiveness.
The panel also discussed a lot of other interesting topics related to retail advertising in Tamil Nadu market. While Gurijala and Vishal reinstated the fact that print advertising is working for them to a great extent, Sakthivel and Ramesh vouched for the need advertise on TV to increase the user base.
Gurijala said, “I am huge fan of television but for education as a medium, print gives us an edge that we need to survive. There is a belief that parents are looking for education institutes that are more subtle. And subtlety has been the mantra that some of the biggest universities across the globe have followed and are following to build their ads.”
He acknowledged that a few universities like Amity and Lovely Professional are turning the narrative to the other side and investing big in TV but he insisted that advertising on television is only good for getting a sudden spike in the visibility.
Vishal shared that Viveks have been investing in print since the day they started in 1965.
“Back then, the competition was very less and everything that started was on print. Also, I would say that word-of-mouth was a strong medium. I would say, till date, we are known by the trust (that people have in us), and that has given us a strong foothold. I am spending close to 80-85 per cent of my budget on print”
He added, “TVCs are only for a brand recall purpose. But there are national players like Reliance and Croma, who are now spread across Tamil Nadu. For them, I believe, TV TVCs get more leverage than they do for players like us.”
Ramesh shared that television helped his Kalimark Group to a great extent. “When we started in 1916, for the initial few years, we used only paintings to promote our drinks. Later, I am very proud to say, TV helped us greatly in our brand journey. People in Tamil Nadu are very sensitive and they believe what they see. So, TVCs help us in getting their attention. I am spending 75 per cent of my budgets on TV.”
He also shared that the brand initially had a rule that it will not engage with any celebrity to promote its products, but they revoked it with changing times.
Sakthivel also mentioned that TV is the dominating medium in Tamil Nadu. He said, “As an advertising agency that handles a lot of retail clients, I believe that Tamil Nadu is still a television market. To give you an example, 18 years back, my first client was a computer institute who was advertising just on print, spending somewhere around Rs 4-5 lakh rupees for a month-long campaign. We helped him go to television with the same budget, did a TVC with a popular TV star of that time and placed it on 3 GECs. Within 3-4 years, the institute grew from 10 centres to 350 centres.”
He added that while digital is soon catching up with television, advertisers can focus on creating a mix for both the media but only digital will not be able to drive growth.
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.
