MAM
Local paint industry looking at bright future: Kamdhenu Paint’s Saurabh Agarwal
NEW DELHI: The Indian paint idustry, pegged at Rs 50,000 crore in total value, is coping with tough times these days, consequent to the extended lockdown condition and interrupted economic activities in the country. According to Kamdhenu Paints director Saurabh Agarwal, the prospect for the industry is not going to be good for the current year.
“The pandemic and lockdown conditions enforced throughout the country has caused significant problems to local businesses having to maintain their fixed expense such as salary payments to their staffs, rental obligations of shops or offices etc. Further, local business is also looking at a massive shortage in the availability of labour in the markets as migrant workers have left the cities and head to their home towns,” he told Indiantelevision.com.
However, Agarwal believes that the industry is looking at a bright future ahead as there will be tremendous growth prospect for all Indian paint companies, courtesy the ‘Vocal for Local’ campaign, initiated by the Indian government.
He told Indiantelevision.com that the paint industry is greatly dominated by Indian players. “Domestic brands have a market share of about 75 per cent to 80 per cent of the paints industry while the rest is made up by international companies operating in the country. The promotion of the ‘Vocal for Local’ campaign will have a positive impact on Indian paint companies as branded customers will now be focusing on domestic companies rather than going for products of international players.”
The brand has taken extensively to raise the support and awareness towards the motto of popularising local brands in India. It also launched a new social media campaign to amplify the message of buying local and self-reliance.
Agarwal shared, “The main idea behind the various social media campaigns that we undertake is to support the call made by our PM. It is a good opportunity for all Indian industry to come forward and support this campaign. It is also our moral duty to encourage our fellow countrymen to buy only 'Made in India' products.”
He showed confidence in the fact that with such campaigns, Kamdhenu Paints will be able to add new consumers to its portfolio.
Elaborating more on the consumer behaviour towards the local brands, Agarwal quipped, “Consumer buying behaviour can be broadly categorised into two. One category is the brand-conscious buyer that will only buy brand names and the other is the price-conscious buyer who will buy products that give him the biggest bang for the buck. By adopting better standards in the manufacturing process local brands can produce competitive products with quality that are at par with the best. Improving quality in production by local brands can attract both the brand-conscious buyer and the price-conscious buyer as high-quality local brands will be available to consumers at very economical prices which suits their pocket.”
Agarwal also praised the government support, which has been extended in the past few weeks. “The government has announced a very good package for the economy. I am sure it will have a positive impact on economic recovery as we come out of the lockdown restrictions. The result may however not be visible instantly as the impact of the initiative will take some time to percolate through.”
However, he also feels that as we emerge from the shadows of the lockdown and the economy slowly begins to pick up, the government needs to do more as this is not a one-shot cure and more needs to be done to prop up the economy.
He concluded, “The government can look at giving some relaxations in tax slab that can help cushion everyone from the impact of the pandemic. They might consider giving some relaxation in tax slab for all individual, an interest waiver for full-year on EMI of all types of loans, direct benefit transfer of some amount directly to low salary workers in both organised and unorganised sector, compensation of rent for all low-class employee or migrant labourers and arrangement of shelter homes for all migrant workers with provision for food and stay facilities.”
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.
