Shivani Narang is Specialized in Integrated Marketing Strategy from IIM Lucknow, and specialization in Digital Transformation from ISB Hyderabad, she is adept to work towards revenue growth through combining Marketing & Sales led functional experience with expertise in Digital Automation, People First Digital Strategy, SEM, Paid Channels, Value Consulting, and Digital Marketing Operations & Analytics.
In the conversation with Women entrepreneur Magazine. Shivani shares her views on challenges or risks anticipated with the increased use of AI and automation in marketing.
According to you, what are the main benefits of incorporating AI and automation into marketing strategies?
Marketing is one of the most essential business functions where AI & automation will drive enormous change in operations while making a financial impact. Marketers do recognize the transformation and impact AI will bring to the marketing industry. In the current scenario, where marketing and technology go hand in hand, this handshake has started developing an organization's data-and-AI-literate culture. Marketers are adopting AI and Automation tools for building a tailored strategy using predictive analysis, and customer data insights, based on changing needs of customer landscape and behaviour. To create that X factor, smart businesses have pivoted their focus on data insights for personalized experience delivery. Be it the B2B or B2C sector, this has helped marketers in orchestrating contextual content in the right channels & timings, directly enhancing the customer experience from inception to delivery, and then advocacy.
Going into the Covid and post Covid time, organizations that have had early adoption of AI-based tools and Marketing Automation Platforms, have managed to empower marketers in building more focused marketing strategies that are less dependent on assumptions, faith, and experience. They are now driven using data insights of the existing customer ecosystem, competitive landscape, customer preferences and behaviours& predictive analysis of the industry trends and demand. Therefore, with the adoption of AI and automation, it is estimated that there will be an increase in productivity of the marketing function between the value of 5 to 15 percent of the total marketing spend and 10%-15% of the global functional spending will be specifically for AI & Automation Tools.
What challenges or risks are anticipated with the increased use of AI and automation in marketing?
As the adoption of AI is an ongoing process, which will develop a more AI-literate culture, the change definitely has hindsight where there is lack of confidence due to multiple reasons. One of the biggest reasons is the availability of use cases and proven capabilities to marketers and businesses before investing in AI implementation. This would include having people who are skilled and formally trained in adopting this big change.
Secondly, people who are up skilled & educated need to simultaneously identify the risks where human intelligence shall play a crucial role. E.g. - With AI-based Marketing automation tools that help to deliver personalized experiences to customers such as in retail, banking, or healthcare, these platforms are heavily based on predictive analytics, using and consuming customer data. Therefore, challenges such as Data Privacy and Security are of utmost importance. Consumer and customer information must be secured using advanced cyber security firewalls and frameworks, and entire data must have a regulatory body administering the use of this data. Effectively, regulatory and robust security measures should be in place to protect sensitive information from any breach.
Thirdly, with AI driven insights and analytics determining marketing decisions and with a minimal human interface, there are risks and chance of building negative brand perceptions and a low brand trust basis impersonal interactions.
Subsequently, depending on the size of the organization or its customer base, the integrations could be complex, costly, and time-consuming, and a few incorrect or biased data feeds can lead to inappropriate and unfair marketing decisions.
Last but not the least, overreliance on AI without human oversight can lead to errors and misinterpretations. It is essential for marketers to be up skilled, trained, and adept with the pros and cons of technology and automation to augment human-led decisions rather than completely relying on AI.
How can AI be applied in content marketing to create more relevant and engaging content for target audiences?
Adoption of AI for digital marketers or content marketers has started playing a significant role by not just reducing time and costs, but by also building a uniform, brand-friendly content that would resonate with each type of customer segment and persona in a most personalized way. With AI-enabled automation tools, marketers are fetching better campaign ideas, smarter and quicker content drafts that could help in fuelling the change needed in the narrative or need gaps through sentiment analysis.
Not only this, with the capability of generative AI, dependency on agencies and larger teams for repeated SEO tasks, keyword extraction or content gaps analysis is reduced which becomes life support for content writers while generating and meeting the ongoing demand for SE-friendly content for the organization or its business verticals. This content is then utilized for pushing engaging social posts, advertising copies, SEO meta tags, personalized product or service descriptions, blogs, and industry-relevant articles. All in all, generative AI will gradually become a catalyst for building and marketing content that will provide a superior experience to the writer and the reader!
What metrics and KPIs would be needed to measure the success of an AI-powered marketing campaign?
The inclusion of AI and automation in any marketing campaign offer several compelling reasons like an ability to personalize at scale using real-time customer insights. Based on this a tailored approach can be created based on customer preferences and choices. E.g. Fashion Industry is providing immersive experiences to customers based on their fashion choices, body types, purchasing power etc. Then, companies like Apple, Meta, Adobe, Salesforce, and other Martech leaders are heavily investing in AI investments and solutions for the last decade or more.
With platforms like these, marketers can do real-time campaign optimization through AI-led insights and alerts, or tweaking workflows in a spin of seconds, which leads to better marketing outcomes, customer experience, and time to market. With these technology enhancements, the success of an AI-led marketing campaign can be measured through a mix of traditional marketing metrics and specific AI-related key performance indicators (KPIs) such as:
- Reach & customer engagement like time spent on site, pages per visit, and bounce rate to understand how engaged users are with the content delivered through AI-powered personalization.
- With an option to do A/B tests to compare the performance of AI-generated content against non-AI content variations. Monitor metrics like CTR, conversion rate, and engagement to identify the most effective content.
- Then costs saving and change in time to market with effective implementation of AI & automation tools.
- AI-specific performance indicators like accuracy, precision, and recall for recommendation systems to ensure the AI model delivers relevant and accurate results
- To top it all No. of Lead Generations, Conversions, Time to Conversion, and Customer Lifetime Value (CLV)
- And finally calculating the ROI and profitability by analysing the cost of AI tool implementation plus the marketing campaign cost against the revenue generated.
