Unveiling Next-gen Marketing: AI's Evolution In Marketing Suite

In the world of sales and marketing, an Artificial Intelligence-led revolution is brewing, changing the way companies promote products and services and adding immense value to their business and customers. For instance, generative AI is expected to create US$ 2.6 trillion to US$ 4.4 trillion in value annually, 75 per cent of it in four areas of which sales and marketing is one. Here are the top three impacts of AI in this space: 

Higher Marketing Efficiency 
AI is rapidly automating sales and marketing operations, increasingly driving efficiencies by handling tasks like research, communication, content creation, and analytics. By next year, large companies will generate 30 per cent of their marketing messages using AI. Grunt work aside, generative AI creates marketing collateral aligned with prescribed brand guidelines. Users report saving an average of 11.4 hours per week with AI, enabling them to focus on higher-value or more strategic tasks. AI also analyses performance data, offering improvement suggestions. For instance, brand marketers who spend substantial resources on market studies to identify trends and opportunities can employ AI solutions to gather and process huge quantities of structured and unstructured information into granular insights to help refine communications, personalise offerings for a segment of one, or engage customers better at a fraction of the time and cost of traditional research.  

Personalised Engagement & Memorable Brand Experiences 
Advances in AI are now enabling marketers to personalise engagement like never before. The latest AI models are using their growing analytical and natural language abilities to refine customer understanding and conversing with customers just like human agents, resolve problems or make relevant recommendations to create highly personalised experiences on every channel. A good example here is a Swedish payment processing firm that along with some e-commerce platforms has integrated a chatbot and virtual assistant in their solutions to offer online shoppers curated product recommendations, targeted advice, and a product search and comparison tool through which they can also make purchases.  

Marketers are also able to take better and timely decisions thanks to real-time visibility into marketing operations; by seeing what’s working or not in a particular campaign they can make changes (while the campaign is still on) to improve effectiveness. Other benefits of AI to marketers include better ad targeting, optimised email send-times, and conversion probability estimation.  

Faster Business Growth 
For sales teams, AI’s customer insights translate to better demand capture and lead generation, higher channel conversion, and cross-selling/ upselling opportunities to improve repeat buys and revenue per customer. Armed with early information on market trends and competitors’ moves, the sales force can direct pricing strategy, design market-leading loyalty programs, and initiate various efforts to grow the business faster. Also, instead of spending months in the field to discover new opportunities, sales teams can now tap generative AI for an instant summary of customer conversations and take appropriate actions to meet their needs.    

Users of advanced AI-amplified marketing suites stand to improve brand relevance and increase the number of repeat buyers by as much as 50 per cent, among other things. For example, by using AI to refine segmentation based on 5,000 customer attributes, a global sporting goods retailer succeeded in hyper-personalising marketing and enhancing engagement to boost customer purchases by 35 per cent.  

Data-readiness Imperative For AI-powered Marketing 
AI is paving the road to next-generation marketing, but it comes with challenges. Most of these stem from data. To ensure AI models perform effectively in marketing, establishing a solid data foundation is crucial. Of course, the data must be clean, accurate, and unbiased, but for the best outcomes, it should be hygienic and ready for AI integration. Adding layers of context goes a long way in producing first-time right outcomes. To avoid a situation where disparate AI solutions working in silos with independent datasets create chaos and contradiction, marketers should implement an enterprise data fabric and unified AI solution suite to aid AI integration. Most importantly, they need to use data and AI responsibly to protect everyone’s interests. Data privacy, security, and confidentiality apart, organisations should ensure ethical use – disclosing when content is AI-generated, using customer data only with consent, and building transparent, explainable AI models trained on data that is accurate, complete, and free of bias.  

John Premkumar

Guest Author The author is the Vice President & Global Head of Digital Experience at Infosys