Digital
Driven by global momentum, PubMatic brings activate to APAC
Mumbai: PubMatic (Nasdaq: PUBM), an independent technology company delivering digital advertising’s supply chain of the future, has announced the availability of its newest offering, Activate, in the Asia-Pacific region. PubMatic’s new end-to-end supply path optimization (SPO) solution allows buyers to execute non-bidded direct deals on PubMatic’s programmatic platform, accessing premium video and CTV inventory at scale.
Since launching in the US and EMEA in May, Activate has gained traction across every region, with an active pipeline of more than 50 advertisers, agencies, and campaigns live through multiple global agency holding companies. Following this success, the solution is being launched in the Asia-Pacific region with partners including dentsu APAC, iQIYI, KINESSO India, Madison Digital, and Wishmedia.
Activate represents a new industry paradigm by creating a single layer of technology that directly connects buyers and sellers of digital media. Activate allows a smooth shift from conventional direct transactions to programmatic private marketplace (PMP) or programmatic guaranteed (PG) deals. The platform gives media buyers more control over their omnichannel video investments by facilitating transactions across PubMatic’s premium CTV and online video inventory within a unified platform.
“PubMatic’s launch of Activate in the Asia-Pacific region marks a significant milestone in our efforts to revolutionize the industry’s programmatic marketplace,” said PubMatic CEO & co-founder Rajeev Goel. “Activate is an extension of our successful SPO strategy that addresses advertiser demand for solutions that deliver a better return on video and CTV investments.”
“At dentsu, we prioritize adtech maturity, focusing on transparency and control in the programmatic supply chain for efficient, high-quality media delivery. Our partnership with PubMatic plays a pivotal role in our supply curation and SPO practices,” said dentsu APAC chief product officer Sunil Naryani, who supports the Carat, iProspect, and dentsu X agencies in the region. “With PubMatic’s Activate, we anticipate delivering enhanced value to our clients by bridging the gap between buyers and sellers and further streamlining the supply chain, unlocking opportunities to maximize working media for their video and CTV investments.”
“iQIYI is a long-time partner of PubMatic. Together we are committed to delivering innovation in the CTV ecosystem,” said iQIYI international business development & general manager of sales operation Andy Sun. “We’re excited to be a launch partner for PubMatic’s Activate solution and look forward to continuing to work closely together to drive effective programmatic CTV advertising.”
“PubMatic is a key player in the programmatic ecosystem, and we’re excited to explore how Activate can benefit our CTV clients,” said KINESSO India business head Paras Mehta.
“PubMatic is a valuable partner across India, helping us deliver transparent and effective solutions for advertisers,” said Madison Digital general manager & head of programmatic Suchi Jain. “We’re excited to see their continued innovation in streamlining video and CTV buying for our clients.”
“Wishmedia is dedicated to providing advertisers in Korea with best-in-class digital advertising solutions,” said Wishmedia COO Meejoo Na. “We’re thrilled to be a launch partner for PubMatic’s Activate and look forward to our clients benefiting from a more efficient digital supply chain, and greater ROI on their video and CTV spend.”
Non-programmatic insertion orders are expected to account for almost 60 per cent of CTV and 18 per cent of online video transactions by the end of 2023, according to industry estimates. Activate represents a nearly $65 billion expansion of PubMatic’s total addressable market.
Built leveraging technology from PubMatic’s 2022 acquisition of Martin, Activate is fully integrated into PubMatic’s growing software suite, including the PubMatic Sell-Side Platform and Connect.
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.
