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Chief marketing officers (CMOs) are increasingly considering leveraging Artificial Intelligence (AI) to manage their marketing budgets. Marketing spends on digital channels have increased by 20 percent per annum as per industry estimates. Digital marketing itself has incorporated AI by skipping a generation of intermediate system development. Modern marketing automation platforms already include chatbots for customer interaction, voice recognition/translation in their websites and semantic search in their product catalogues.
However, the shift from traditional marketing to digital marketing was driven by the very fact that one could drive more personalised and segmented messaging to customers to drive up conversion rates. AI driven initiatives increasingly are used by marketing teams to deliver razor-sharp messaging to prospective customers and as it enables them to monitor and track the impact in real-time.
Programmatic advertising helps not only cut the time required to launch campaigns but helps advertisers keep a close tab on budgets and monitor return on media investments (ROMI). While these platforms are run primarily on AI engines, they do not provide CMOs with the flexibility to customise the solution as per their needs. Smaller modules of machine learning algorithms are now helping CMOs pick and choose their
AI interventions to suit the marketing needs of their brands CMOs are now looking at mixing and matching a brand’s marketing needs with a variety of AI initiatives. This provides them greater flexibility to customise and allocate scarce marketing budgets to achieve better ROIs. One way of planning AI investments is to look at a typical journey of a customer from awareness to post-purchase interaction. While different brands may have different customer journeys, an illustrative one will typically consist of five stages. Based on the marketing strategy for the particular brand various AI algorithms maybe implemented. A sample is provided below:
Of course, needs may change over a period of time and brands may have multiple customer journeys. But a prudent analysis of costs to benefits of individual AI modules will help design the customer journeys to yield the best result. With a plethora of AI algorithms or “use cases”, it becomes important to question the end outcome required and redesign the customer journey by introducing a series of AI Lego Blocks to complete the journey with the desired outcome. By aligning the correct interlocking Lego Blocks of AI, one should be able to transform a customer’s experience in interacting with the brand. This alone should be significant incentive for CMOs to invest in Lego blocks.
By Shyam Rao, Senior Director, Digital Business Services, Infosys BPM