Digital
Our AI growth engine gives brands the ability to scale their marketing with full confidence: Amitek Sinha
Mumbai: We live in a digital era where everything is driven by data and analytics. With increasing competition, becoming visible to the intended customers has become very crucial for brands vying for the audience’s attention. In such a scenario, several digital marketing agencies are emerging on the scene. But the ones doing a commendable job at helping brands scale up their size and presence are far and few.
Incepted in the year 2013, Etml is headquartered in Saket, New Delhi. Its founder & CEO, Raghav Kansal, was in his third year of college when he started his first venture, Edulution Technologies, with a couple of friends intended to be an online portal solely catering to engineering students and aspirants. It was started in 2010 and was operated till mid-2013. The ride wasn’t very smooth for the team and the business was not picking steam despite the website getting a decent traction. Raghav still wasn’t disheartened and decided to give entrepreneurship another go. The good thing that came out of his maiden venture was that in the process of promoting his business online, Raghav took up an active interest in the digital marketing space.
Indiantelevision.com’s Rohin Ramesh caught up with Etml co-founder & COO Amitek Sinha where he discussed how data when coupled with a hyper growth attitude can radically transform the way companies acquire and grow with high value customers.
Edited excerpts
On some key factors that contributed to your success since the company’s inception in 2013
Our success at ETML, since we started in 2013, comes down to one simple truth: it’s in our DNA. The core of everything we do revolves around People, Process, and Data. Data, especially, is what drives us—it’s the backbone of our approach and the reason we’ve been able to build data models and testing frameworks that deliver exceptional advertising ROI for our clients.
The journey always starts with a solid data strategy and monitoring framework because, as we like to say, “what you can’t measure, you can’t improve.” It’s about digging deep into insights, studying customer behavior, and setting the right KPIs. Once we’ve laid that foundation, we focus on strategizing the best mix of audiences, channels, funnels, experiments, creatives, and messaging. And then comes the part where we bring it all to life with seamless execution—because without great execution, even the best plans fall flat.
But it’s not just about data. It’s also the people behind the scenes—our team includes brilliant minds from IITs and top-tier engineering schools. Their expertise enables us to identify gaps, design smart experiments, and prescribe solutions that help businesses grow. Our process is rooted in a deep understanding of what works, and our track record shows it—whether it’s boosting revenue, improving ROI, or scaling brands across verticals.
The businesses we work with have seen impressive results, from double- to triple-digit growth, and that’s what drives us to keep innovating. It’s a combination of building the right strategy, understanding the needs of the business, and executing flawlessly that has helped us become one of the fastest-growing digital agencies today.
On technologies helping your clients achieve sustainable growth
At ETML, we’ve built our success on innovation, and Adbytzz 2.0 is a perfect example of that. It’s our proprietary tool that brings together more than a decade of digital marketing experience, powered by both AI and human intelligence. Adbytzz 2.0 connects a brand’s data across all key marketing channels—campaigns, creatives, CRM systems, and more—into one central system. This allows us to deeply analyze and optimize every step of the customer journey, from the first click to the final purchase.
What really sets Adbytzz 2.0 apart is its ability to continually fine-tune everything—audiences, platforms, creatives, you name it. This constant optimization has helped our clients achieve real results, like a 20% boost in revenue for a financial conglomerate and a 1.6x increase in leads for India’s top real estate group.
Our AI growth engine gives brands the ability to predict and scale their marketing with full confidence. It’s not just about generating more traffic; it’s about growing smarter, optimizing budgets, and ensuring long-term success. In short, Adbytzz 2.0 allows us to take all the moving parts of digital marketing, streamline them, and deliver sustainable growth that our clients can rely on.
On partnerships helping you stay ahead in the competitive digital landscape
Being a Google Partner and Facebook Marketing Partner really helps us stay ahead of the game in the competitive digital landscape. These partnerships give us early access to new features, tools, and beta programs, which means we get to try out the latest innovations before they’re available to everyone else. This lets us offer our clients fresh strategies and cutting-edge solutions that keep them ahead of the curve.
What’s also great is the direct support we receive from both Google and Facebook. When we’re tackling complex strategies or need quick solutions, having dedicated experts on hand is a huge advantage. It ensures that we’re always optimizing our campaigns to the fullest.
Plus, these partnerships mean our team is constantly getting top-notch training, so we’re always up to date with the latest platform changes and best practices. All of this helps us deliver more effective, data-driven strategies that keep our clients ahead of their competition and drive real results.
On the future of Etml
We are targeting a very specific spot in the realm of digital marketing and we intend to grow in this niche. All our actions are planned and executed to progress one step at a time towards our goal.
Looking ahead, the next big step for Etml is international domination. We’ve already established a strong presence with offices in Dubai and Singapore, and we’re working with clients across the USA, Middle East, and beyond. But now, we’re aiming to really make our mark on a global scale. Our goal is to deepen our footprint in these regions, taking the success we’ve built and amplifying it across new markets. It’s not just about expanding geographically; it’s about bringing our unique blend of data-driven strategy, innovation, and flawless execution to a much bigger audience.
As for the future of digital marketing, AI is definitely going to play a massive role, and we’re already preparing for that shift. But it’s not just about relying on AI. The key will be how we, as marketers, manipulate AI to work in our favor. We believe that while AI can do incredible things, it’s going to take sharp minds—our people—to harness it effectively. This is where we’re focusing our efforts, blending the power of AI with human intelligence to ensure it’s beneficial for our clients.
At the same time, we know that data privacy and personalisation are two sides of the same coin. Consumers want more personalized experiences, but they also demand stronger privacy controls. Navigating this balance is going to be critical, and we’re already laying the groundwork by building systems and strategies that respect both. So, as we look to the future, we’re preparing to not just adapt but to lead the charge in this evolving landscape, ensuring that we stay at the forefront of innovation while continuing to deliver exceptional results for our clients.
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.
