Will you have fries with that?

Time of India

2 days ago

Will you have fries with that? This classic line is one of the most memorable examples of cross-selling, reportedly contributing up to 40% of revenues for the global fast-food giant McDonald's. A powerful sales lever, cross-selling has become table stakes across industries such as banking and finance, insurance, retail, travel, automotive, hospitality and subscription businesses. With the emergence of digital media, marketers adapted upsell and cross-sell strategies for mass campaigns via digital channels.
In the Internet age, digital cross-sell strategies took shape. E-commerce players such as Amazon introduced nudges like 'Customers who bought this also bought…', while OTAs (online travel agents) sold everything from hotels and rental cars to insurance based on a customer's travel plans. These strategies leveraged psychological insights and adapted website or app design to help consumers navigate the digital world.
The evolution of cross-selling accelerated as marketers harnessed data analytics to better understand complex consumer journeys and build campaigns that struck at the moment of consumer truth. A famous example is retailer Target, which used data analytics to identify which trimester pregnant female customers were in, allowing the brand to target them with relevant product offers.
This level of granular understanding of consumer journeys through data opened up a brave new world of cross-selling strategies that continues to evolve. The expanding suite of marketing technology (
martech
) solutions today can not only execute highly sophisticated cross-sell strategies but also scale them effectively.
Anand Bhatia
, chief data and analytics officer, HDB Financial Services, observed, 'Martech makes it possible to manage cross-sell and upsell at scale, in real time, and importantly unearth aspects you were blind to earlier. For example, the impact of the make of the phone as a loose surrogate for income, and using it as a targeting variable. So, it gives the marketer the ability to manage more. And decision-making needs data. With the right tool, the data is real time and so is the response. The customer too feels the impact of faster access to deals and services from the brand. It makes the brand look (and behave) responsive! It also helps that these tools help visualise data/output far better, and that is a big positive.'
The biggest unlock that modern cross-selling strategies have brought, this author believes, is in the
BFSI
sector, where complexity is enormous and consumer behaviour and journeys vary widely. Historically, the guidance of a financial expert (agent, broker, relationship manager etc.) was required to move a consumer towards any kind of decision. These decisions carried high stakes, potentially affecting a customer for the rest of their life, so they were made with great care. Add to this the considerable regulatory scrutiny applied to any form of financial advice or influence.
Sumit Aggarwal
, SVP – group customer data and cross-sell,
Motilal Oswal
, explained, 'In the investment world, timing and relevance are everything. The same principles that guide a well-timed equity trade also define effective upselling and cross-selling. Offer a product too soon, and the customer isn't ready. Too late, and the opportunity has passed.'
He added, 'Earlier, our industry relied on relationship managers to read these cues through conversations, portfolio reviews and market updates. It worked, but it was personal, not scalable.'
Today, customer interactions have shifted from the broker or financial adviser to mobile apps and websites. But in many cases trust and authority still rest largely with the adviser.
Aggarwal elaborated, 'Customers expect the right product recommendation, in the right channel, at the right moment, whether it's a PMS (portfolio management services) pitch after a strong equities run, or a bond ladder suggestion when volatility rises.'
In the early days of martech adoption, brands began delivering relevant offers and transactional messages in real time across multiple channels including apps, email and push notifications. Data dashboards democratised insights and equipped customer-facing staff such as advisers with context-rich information before every customer interaction. In an omnichannel environment, the biggest breakthrough was synchronising online and offline conversations so customers experienced a seamless journey.
The next generational shift saw brands move away from obvious product pushes towards hyper-personalised, timely recommendations informed by a customer's portfolio, behaviour and life stage. This is considered the holy grail of marketing because it is invisible to the customer, creating the impression that the brand genuinely cares.
Bhatia remarked, 'Martech tools offering automation of the process of cross-sell have been the biggest unlock, from delivery of the communication, message or nudge, to instantly identifying "whom" to target. This has meant a whole new way of working emerged, try fast, try small, get a quick sense of what is working, and scale up if it works. This speed is a great power to have. It is a combination of technology, process and people. People play a key role, as the machine is an enabler, you need someone willing to run rapid campaigns and fail so that the successes are big!'
With campaign automation tools making message delivery easier than ever, the onus has shifted back to data, activating campaigns based on complex consumer insights. Marketers now use multiple data modelling techniques, including propensity models that estimate the likelihood of a customer purchasing a product, and LTV (lifetime value) segmentation to focus on high-value customers. The complex logic driving these campaigns is only increasing as marketers strive to avoid predictable, one-dimensional approaches.
Aggarwal stated, 'We combine propensity models,
RFM
(recency, frequency, monetary) scoring, LTV (lifetime value) segmentation and behavioural triggers to find the perfect engagement moment. Idle cash in a portfolio might trigger an FD or liquid fund message, a maturing SIP could prompt a PMS discussion. This isn't just good for business, it delivers a better, more relevant customer experience, increasing trust and long-term value.'
Anand explained, 'Brands will use all these data models in campaigns. Each approach has merits, and possibly demerits. What is important is understanding how these work. It's very interesting you speak of RFM in a world dominated by complex logic. RFM is a great tool, especially in retail, e-commerce or payments businesses, to segment customers. In martech, retail, e-com or payments environments, it's one of the go-to tools, quick, effective, and totally in sync with buying behaviour.'
The increasing complexity in data modelling can sometimes throw marketers off. Segmenting customers as first-time buyers, repeat buyers or high-value buyers, or grouping them solely by interests, risks creating one-dimensional profiles that may limit broader upsell and cross-sell opportunities.
Marketers therefore need to look at data not only from marketing campaigns and consumer outreach programmes but across departments and channels to gain a more holistic view of the customer journey.
Aggarwal noted, 'Today, key challenges that remain in cross-selling and up-selling are data unification, quality gaps and channel orchestration. But centralising intelligence in the
CDP
(customer data platform), standardising taxonomy and creating always-on journeys have been breakthroughs.'
As Aggarwal highlighted, for many brands, cross-selling opportunities represent not just a way to drive more sales but also a route to improving customer experience, building loyalty and creating long-term brand value.
Until recently, data analytics remained firmly in the grasp of marketing, product, digital and analytics teams. But with the emergence of intelligent AI models, even this aspect of up-selling and cross-selling may increasingly be handled by machines.
'The next leap will come from AI, which is already helping us predict exits, spot portfolio gaps and generate personalised, compliance-ready narratives. This will move us from reactive selling to proactive, predictive engagement, ensuring every customer interaction adds value and strengthens the relationship,' concluded Aggarwal.