Sixteen years ago, LinkedIn entered India with a clear purpose—connecting professionals. Back then, it was a digital resume board, a place where job seekers polished profiles and recruiters hunted for talent. But networks, much like economies, evolve. What began as a career marketplace has transformed into an ecosystem where professionals don’t just seek opportunities—they shape conversations. Today, companies share earnings reports, ESG initiatives, and industry insights, while thought leaders debate innovations, market shifts, and business strategies. In this shift, LinkedIn has not only become a knowledge-sharing hub but also a key player in B2B marketing, leveraging AI-driven solutions to redefine how brands engage with their audience. “Unlike social media platforms that cater to a broad range of content, LinkedIn remains focused on professional knowledge and industry discussions. Users engage with valuable, career-oriented content, reinforcing LinkedIn’s positioning as a platform for professional growth rather than casual social interaction,” Sachin Sharma, Director- marketing solutions, Linkedin, told Shailja Tiwari.
B2B blues!
There has been growing scrutiny on marketing ROI, particularly post-Covid and after the zero-interest-rate (ZIRP) era. CEOs, CFOs, and investment firms are closely evaluating every marketing dollar spent, looking for clear value and measurable impact. It is believed that one of the biggest challenges in the B2B tech world is the lack of standardised industry benchmarks for ROI. Different SaaS companies track different metrics, making it difficult to establish a common framework for measuring marketing effectiveness. The second challenge is the integration of systems. Many companies use multiple tools like CDPs, CRMs, and connectors, but the data flow between these systems is often fragmented, leading to inefficiencies. The third challenge is balancing short-term and long-term marketing goals. While there is increasing pressure to show immediate returns, businesses also recognise the need to invest in brand building over time. This dilemma is particularly evident in India’s tech sector.
According to LinkedIn’s research, nine out of ten marketers struggle with these challenges. To address this, leveraging first-party data becomes critical. With access to decision-makers and their data, the focus is on helping CMOs prove attribution, demonstrate impact, and justify marketing spends internally. “One of the solutions introduced is the Conversion API, which allows marketers to link their CRM with LinkedIn. By integrating first-party data, the system can auto-optimise campaigns in real time, ensuring better lead quality and more efficient spending,” Sharma said.
He further gave an example- SaaS companies typically classify leads into marketing-qualified (MQL) and sales-qualified (SQL), with further categorisation into specific types. By feeding CRM data into LinkedIn’s system, campaigns can be optimised to prioritise high-value leads. This also enables marketers to control their budgets more effectively, ensuring they acquire the right type of leads at an optimised cost. The key advantage of this API is that it is free for anyone to use.
Another tool introduced is Revenue Attribution Reporting (RAR), which tracks both online and offline conversions and connects them back to marketing campaigns on LinkedIn. This allows businesses to measure the real impact of their LinkedIn marketing efforts, justify investments with clear data, and gain deeper insights into how marketing activities influence revenue. “By addressing these challenges, the goal is to provide marketers with better tools to navigate the increasing scrutiny on ROI while still enabling long-term brand building,” Sharma said.
Long-term impact!
Measuring the long-term impact of a B2B marketing campaign is challenging, especially as buying cycles have become longer. Sharma highlighted that the average B2B buying cycle today exceeds 190 days, up from 129 days. This extended timeline makes it harder to close deals and align multiple stakeholders within the buyer group.
“At LinkedIn, we offer tools to help businesses track long-term brand impact. One option is a brand lift study, which allows companies to measure shifts in brand perception over time. However, in a B2B scenario, even lead generation and revenue attribution operate on long-term cycles. For instance, a company may recognise only 10% of revenue from a deal within 30 days, while the remainder, especially in SaaS environments, accrues over the next 90 days. It often takes two years to fully measure the total revenue impact,” Sharma added.
Sharma explained that their systems track customer lifetime value (CLV) to help businesses understand the long-term impact of marketing investments. In a typical SaaS CRM setup, he noted, customer lifetimes range from two and a half to three years. By linking marketing spend to long-term revenue generation, the system demonstrates how an initial $1 investment contributes to revenue over the entire customer lifecycle. This approach, Sharma emphasised, not only justifies long-term brand-building efforts but also ensures accountability for marketing expenditures.
Lack of Standardisation!
There is no standardised format for measuring the ROI of marketing campaigns, as the industry remains fragmented. Different organisations prioritise different metrics, creating challenges for CMOs who face pressure from CEOs demanding frequent performance updates. Many focus on short-term metrics like the cost of acquisition, but without high-quality leads, ROI remains limited since revenue is the ultimate measure of success. LinkedIn has developed a playbook that outlines how to measure both short-term and long-term impact. “The challenge is not the lack of a framework but rather the industry’s inconsistent approach to measurement. To address this, LinkedIn is working to educate marketers and provide systems that help track relevant metrics over different time frames,” Sharma addressed.
For long-term measurement, brand lift studies remain one of the most effective tools. Large tech brands, for instance, track unaided and aided recall to determine whether consumers consider them in purchase decisions. Establishing these connections between short-term performance and long-term brand impact helps marketers align their strategies with business objectives and effectively communicate results to leadership.
AI in marketing
India has seen significant adoption of AI in B2B marketing, with research indicating that 60% of Indian marketers are already using some form of AI solution. The primary use cases include campaign optimisation, ad effectiveness measurement, and content creation.
Compared to the US, UK, and France, India’s AI adoption is driven by cost efficiency and scalability, allowing businesses to optimise marketing spend in a competitive and price-sensitive market. While Western markets have been using AI for a longer period and focus on advanced personalisation, predictive analytics, and automation, Indian marketers prioritise efficiency-driven applications.
India’s diverse linguistic and regional landscape also presents unique challenges, which AI helps address through language localisation and automated content adaptation. With rapid digitalisation and a growing emphasis on data-driven decision-making, AI integration in Indian B2B marketing is expanding, though still evolving compared to more mature Western markets.
AI is deeply integrated into marketing tools, often operating in the background to optimise campaigns and improve effectiveness. Many of these AI-driven features have been in use for years, even before AI became a major buzzword. “On LinkedIn, AI-powered tools include Predictive Audiences, which analyse engagement likelihood, and Matched Audiences, which help refine targeting. Recently, LinkedIn introduced Accelerate, which allows marketers to launch AI-generated campaigns with minimal input—by analysing webpage content, generating ad copy, and suggesting creatives,” Sharma highlighted.
Beyond these, AI plays a crucial role in campaign optimisation, remarketing, and audience targeting. Features like recommendation engines and knowledge graphs enhance ad performance by continuously refining targeting and engagement strategies. AI’s real value lies in improving efficiency, reducing manual effort, and delivering better results through data-driven decision-making.
Viral content scrutiny!
Recently, Samay Raina and Ranveer Allahbadia came under scrutiny for their comments on the show IGL, which gained significant traction online. The show’s format and discussions, which amassed millions of views on YouTube and went viral on Instagram, have sparked debate over how digital platforms amplify content purely based on engagement, regardless of its nature. “On LinkedIn, any content that would obviously go viral is actually disincentivised. We don’t want people to just look at content for the sake of looking forward; we want people to engage with content and see content in the feed that is actually valuable to them,” Sharma pointed.
Sharma said that in fact, our CEO was here last year, and he talked about this, saying, “We look at it differently. We don’t want you to post something and have it become viral because then, over a period of time, you’re incentivised to only do that. We try and make sure things don’t go viral but go to the right audience, are in the right feed, and we actually publish that.”