Digital
Kraftshala’s 2024 digital marketing hiring trends: skilled entry level jobs in demand
MUMBAI: It’s back to offices for most digital marketing companies, remote working is passe at the entry level – maybe hybrid working is ok – according to a trends report released by edtech platform for marketing jobs Kraftshala.
Entitled the Digital Marketing Trends Report 2024, it highlighted the surging demand for skilled entry-level digital marketers despite news of hiring slowdowns across the year in other sectors. The report provides a detailed analysis of 765 roles floated during Kraftshala’s placement processes for three programs: marketing launchpad, marketing launchpad (emerging talent – hinglish), and content and social media launchpad.
Key findings revealed a steady increase in entry-level hiring in 2024, driven by agencies and large brands actively seeking skilled professionals. Agencies accounted for 60 per cent of these roles, underscoring their reliance on fresh talent for growth. Bangalore, Mumbai, and Delhi-NCR emerged as dominant hiring hubs, contributing to 67 per cent of the roles. Interestingly, cities like Pune, Hyderabad, Jaipur, Chennai, Kolkata are also growing in prominence in India’s digital marketing landscape.
Bangalore remains the top choice for competitive compensation, with 28 per cent of roles in the city offering higher cost to company (CTCs). Interestingly, cities like Chennai and Noida, despite their smaller market size, are also offering premium compensation for niche skills, demonstrating the growing importance of regional hubs in the hiring landscape.
The workplace trends revealed by the report are equally compelling. 93 per cent of the roles floated in 2024 were either in-office or hybrid, and only 7 per cent were fully remote. Employers emphasised collaboration and on-the-ground problem-solving, which explains the limited adoption of fully remote positions. For candidates, this shift underscores the need to be adaptable to workplace expectations while demonstrating the ability to thrive in team environments.
Fluency in English remains a key factor for success, with over 80 per cent of marketing roles requiring understanding and a certain level of fluency in the language. While this does not preclude candidates with lesser fluency from securing opportunities, it does emphasize the advantage of strong communication skills during early hiring stages.
The perennial debate of skills versus degrees is also uncovered in this report where it’s clear that more and more recruiters are now open to non-linear career trajectories, valuing practical skills over conventional resumes. Examples of hires with non-traditional backgrounds, including those with career gaps or unrelated degrees or in fact no graduation degrees, illustrate the industry’s openness to diverse talent profiles.
Said Kraftshala founder & CEO Varun Satia: “The digital marketing industry is at a fascinating crossroads, with immense opportunities for those willing to upskill and adapt to the changing landscape. Recruiters are not just looking for candidates with certificates but those who can bring real value through their problem-solving abilities and technical knowledge. This report underscores the importance of building practical, hands-on expertise to stand out in today’s competitive job market.”
“What we’re seeing now is a clear departure from traditional hiring practices. Employers are willing to pay premium salaries even for entry-level roles, provided the candidates can demonstrate their ability to think critically and adapt to emerging technologies. This is a wake-up call for students to not just focus on collecting certificates but actually focus on skill building.”
Recruiters are shifting their focus away from traditional hiring processes like aptitude and psychometric tests, instead prioritizing tasks that gauge problem-solving abilities and encourage candidates to apply themselves. This change aligns with the decline of basic roles, which are increasingly being automated or redefined. In parallel, recruiters are demonstrating a willingness to pay higher salaries for skilled candidates, even if it means extending the hiring timeline to secure the right talent. “
The report also underscores the challenge of ensuring quality among a growing pool of applicants. An example in the report notes how an emerging company sifted through 7,000 applications over five months to fill a single digital marketing role, highlighting the critical importance of demonstrated skills over superficial qualifications.
Kraftshala’s findings also shed light on the growing importance of technical specialisations. Roles in programmatic advertising and e-commerce are experiencing rapid growth, reflecting the industry’s adoption of cutting-edge technologies and emerging trends.
(The main picture of this story was generated using Microsoft Image generator. No copyright infringement is intended.)
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.
