MAM
Media planners blamed for shrinking DD advertiser base
MUMBAI: With its advertiser base declining steadily, public broadcaster Doordarshan has dropped its ‘unwritten’ clause requiring software producers to buy additional spot buys.
While this has lured back producers like BR Chopra, Sanjay Khan and Dheeraj Kumar back to the terrestrial channel, (particularly with reduced primetime telecast fees now costing Rs 3,50,000 for 30 minutes with 120 seconds of advertising time), “warped” perceptions of media planners and buyers are still keeping the advertiser away from DD, claims the pubcaster.
DD’s dwindling client base has forced it to rationalise and re-negotiate terms with producers. Earlier, many producers considered DD to be an unviable proposition as it insisted on additional spot buys at Rs 80,000 for every additional ten-second spot. Total advertising time during the DD hey-days in 2000-2001 had increased to 15 minutes for a one hour episode. DD had got used to higher telecast fees of Rs 4.2 million and producers used to make profits even on these higher telecast fees.
With DD back wooing producers, Dheeraj Kumar’s Creative Eye has bought slots on the DD afternoon band, while Sanjay Khan’s Numero Uno is back with two mega serials – Maharathi Karna and 1857 Kranti (which had been discontinued after four episodes in its earlier run in May 2001). BR TV is ruling the roost with Ravi Chopra’s Aap Beeti which featured in seven out of the Top 10 shows on DD in 2002. Shows like Om Namah Shivaya, Chitrahaar, Rangoli (all Creative Eye) and Zameer (Mukta Telearts) were pulled out of DD in February 2001when the telecast fees shot up.
However, DD producers also blame the media planners and buyers who they say have been responsible for DD’s dwindling base of 100 clients reducing to less than 50 in the last few years. “There is a clear mismatch, as the brands who should be on DD are shifting loyalties to C&S homes. The main culprits are ad agencies, planners and buyers who don’t have an understanding of the ground realities of semi-urban and rural areas; have never travelled to these areas; never interacted with the audiences in these areas and don’t have hard-core marketing experience,” says a producer on condition of anonymity.
Reach of DD channels as per IRS 2002 (All adults 12 yrs plus)
DD channels
C&S channels
All India
259.3m
(36.7 per cent)
165.8m
(23.4 per cent)
Urban
100.9m
(48.8 per cent)
104.5m
(50.5 per cent)
Rural
158.3m
(31.5 per cent)
61.2
(12.2 per cent)
“BR Chopra’s serial Aap Beeti had seven slots in the Top 10 list of DD’s programmes in week 1-46 of 2002. The high TRPs ranged between 13.38 and 12.42 for this period. An Aap Beeti episode reached out to 14,33 million viewers on 3 September 2002. Kahani Ghar Ghar Ki and Kyunki Saas bhi kabhi bahu thi could manage 7.04 million and 7.01 million viewers,” says Reasonable Advertising vice president marketing S A Khan who markets the BR TV’s serials Aap Beeti and Vishnupurana.
“The fact remains that the viewers in semi-urban areas and rural markets also have substantial purchasing power – especially true of pockets in the states of Punjab and Haryana,” adds Khan.
“If one travels beyond the metros to the smaller towns and district levels, DD continues to rule. In the Hindi belt, DD’s national network still remains popular,” adds Universal Communications’ MD Padmakar Nandekar, who claims his three programmes contribute 60 per cent to DD Mumbai’s revenues.
The programmes marketed by Nandekar include the feature films on Saturday and Sunday and the dubbed Laurel Hardy show on Sunday. Nandekar also has other programmes on DD-Thiruvananthapuran (four serials including three dailies and one weekly); DD-Chennai (one daily); DD-Bangalore (feature film on the premier Sunday afternoon slot).
The telecast fees for DD (Mumbai) Sahyadri channels are Rs 26,000 for 30-minute episodes with Rs 12,000 for additional 10-second spots.
Many producers are also investing in dubbed versions of the serials. Both the BR TV serials are being simultaneously dubbed into four languages – Hindi, Tamil, Telegu and Malayalam. Industry experts say that the dubbed versions result in a cost increase of anything between Rs 1,50,000 and 2,00,000 but the increased TVRs and the revenues from advertising compensates for the overruns.
Inspite of all these efforts and ratings, media planners and buyers are coaxing advertisers to choose the C&S platform, allege producers. Several categories like lower-end lubricants, two-wheelers and consumer durables are gradually increasing their spends on C&S and reducing spends on DD. FMCGs is one category which is still ruling on the DD scene. “Ad agency planners must take lessons from Hindustan Lever’s managers who believe in using DD to reach out to the interiors, semi-urban and rural areas. Many HLL managers know the ground realities and use media vehicles accordingly. Colgate Palmolive, on the other hand has reduced its spends on DD. Currently, HLL, Parle Beverages, Zandu, Dabur, All Out insecticides are advertising with us,” says Nandekar.
Khan adds: ” Our top advertisers include HLL, P&G, Godrej Soaps, Nirma, Zandu and Dabur. HLL has branded our offering as Wheel Vishnupurana. Life Insurance Corporation has regularly advertised with us. When brands like Saridon and Burnol were with the Reckitt Piramal combine, they used be heavy spenders on DD but are currently reducing spends. What is sad is the fact that several lubricants are shifting loyalties to C&S and reducing spends on DD,” he says.
“Earlier, Bajaj Auto used DD whereas it has increased spends in C&S channels. Media planners are recommending C&S for Mahindra and Mahindra’s family MUVs. All these brands ought to be on DD, ” says Khan, adding that he had earlier urged some white goods companies like Kalyani Sharp to advertise on DD and they had managed to get a good response.
When questioned about the better SEC A profile of C&S channels, DD loyalist producers claim that many of the buying decisions of the SEC A households are taken by their employees (drivers and servants). They also quote the IRS studies are a better indicator than the TAM ratings as it has a sample size of more than 2,00,000 individuals whereas TAM has recently increased the scope of its ratings to place the sample size at somewhere between 3,454-4,555 metres.
Some DD loyalists also point out that certain areas of Punjab, Haryana and Uttar Pradesh are not included in the TAM studies.
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.
