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Booking.com showcases its ‘Connected Trip’ vision with Sonakshi Sinha and Zaheer Iqbal

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Mumbai: Booking.com, an online travel company, along with actor couple Sonakshi Sinha and Zaheer Iqbal teamed up with Booking.com’s country manager for India, Sri Lanka, Maldives and Indonesia – Santosh Kumar to enjoy a guided cooking experience, highlighting one of many exciting experiences and attractions available on Booking.com.

Planning a dream vacation can quickly turn into a logistical nightmare. A recent Booking.com survey reveals that nearly half (42 per cent) of Indians find trip planning stressful, including juggling flights, accommodations, car rentals, activities and the overall logistics. Booking.com, one of the world’s leading online travel companies, is addressing this need by orchestrating the best traveller experience and aiming to make every trip a connected trip.

Booking.com empowers Indian travellers to seamlessly plan and book all key aspects of their journey on the Booking.com platform, eliminating the need to navigate multiple websites and apps. From finding the right flight to booking the perfect stay, travellers can craft their ideal itinerary with ease. Additionally, options for car rentals, private airport transfers and a vast selection of exciting local activities are all  readily available in one place, to create a frictionless travel experience.

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With nearly half (48 per cent) of the Indian travellers choosing a destination to indulge in local cuisines, the event was a perfect blend of travel, food and memorable experiences. At the ‘The Connected Trip: A Culinary Experience’ event on 12 September 2024, Sonakshi Sinha and Zaheer Iqbal shared their food inspired travel stories while learning to prepare their favourite avocado and cucumber sushi and sattu ka paratha with eggplant and tomato chutney, a delicacy from Bihar reflecting on their local and global adventures and childhood memories. The event illustrated how Booking.com connects travellers with diverse, authentic and immersive experiences based on their needs and preferences.

Actor Sonakshi Sinha commented, “Travel is my passion. I love immersing myself in the destination’s culture,  exploring the local markets and of course relishing the local cuisine. But planning is a bit of a headache. Juggling flights, accommodations and activities can be overwhelming. Thankfully, Booking.com has simplified this and travellers can now book various elements of their trip on one platform and enjoy a stress free holiday.”

Adding to this, actor Zaheer Iqbal said, “Food is integral to India’s culture. It has the power to unite people from all over the world. As someone who loves exploring local cuisines whenever I travel, I’m excited to be a part of this event showcasing Booking.com immersive experiences for Indian travellers. Travellers can easily book attractions like sushi making class in Japan or exploring Kolkata’s street food scene – everything in the palm of their hand.”

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Booking.com leverages smart, data-powered predictive technologies, like machine learning and AI, to enhance the traveller experience further. By analysing past choices and preferences, Booking.com can suggest other useful services for their trip, such as car rental, dining reservations, tickets to attractions, and shuttle services, ultimately creating a personalised, AI-enhanced and truly connected booking experience.

“Today travellers are looking for seamless trip planning and travel experiences where they can search, book and manage different aspects of their trip on one platform,” said Booking.com’s country manager, India, Sri Lanka, Maldives and Indonesia – Santosh Kumar. “At Booking.com, we are dedicated to eliminating friction in travel by continuously innovating to address their evolving needs. Our ‘Connected Trip’ vision embodies this commitment by offering multiple elements of the travel experience in one place and providing seamless, end-to-end support throughout the entire journey. Today, we’re excited to see real progress with our vision for a ‘connected trip’. Today we are seeing real progress in our vision. According to our Booking Holdings Q2 2024 earnings, our connected transactions increased by 45 per cent y-o-y and continue to represent a high single digit percentage of Booking.com’s total transactions.”

He further added, “We are excited to have partnered with Sonakshi Sinha and Zaheer Iqbal to showcase how travellers can easily book just about every element of their trip on Booking.com – whether it’s renting a car, enrolling for a cooking class or booking an airport taxi – and easily create a travel experience.”

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Digital

GUEST COLUMN: How AI is restructuring distributor and retailer motivation models

From incentives to intelligence, AI is redefining how brands engage channel partners

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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

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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.

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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.

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