Generative AI has taken up holding in sales and marketing functions, where personalization and text-based communications are driving forces at scale. Gen-AI-empowered technologies can generate personalized messages tailored to specific customer preferences, interests, and behaviors. Also, capable of doing tasks like creating first drafts of brand advertising, slogans, social media posts, headlines, and product or service descriptions.
Personalizing Marketing with Generative AI
Presenting generative AI in marketing operations requires careful consideration. One consideration could be, that mathematical models trained on publicly available data without safeguards against copyright, branding recognition, and plagiarism risks contravene intellectual property rights. A virtual attempt made on applications can produce biased representations of specific demographics because of limited trained data. So, remarkable human oversight is required for strategic thinking and specific to a specific company's needs.
Some potential benefits of using generative AI for marketing include the following:
Effective and efficient content creation - Gen-AI could significantly minimize the time required for ideation and content creation, saving resources and effort. It can also ease consistency across different content, ensuring uniformity in brand positioning, writing style, and format. With generative AI, team members can collaborate to integrate their ideas into a single cohesive piece. This lets team members improve personalization in messaging targeted at different customer segments, demographics, and geographics. Email campaigns are translated into many vernacular languages with specific imagery and messaging based on the target audience. The ability to create content with varying specifications can increase customer attraction, value, and retention at a scale beyond what is possible through traditional strategies.
Enhanced use of data - Generative AI can help overcome the challenges of inconsistent, unstructured, and disconnected data. For example, from various databases - by interpreting data sources like images, text, and varying structures. Marketers can better use data to understand customer behavior, arrange customer feedback, and territory performance to create data-oriented marketing strategies like channel recommendations and targeted customer profiles. Such marketing tools can identify trends, and market opportunities from unstructured data such as news, social media, customer feedback, and academic research.
SEO optimization - Generative AI can help marketers achieve a higher conversion rate and lower marketing costs through SEO for promoting technical components such as image tags, page titles, and URLs. It can integrate key SEO tokens, distribute targeted content to customers, and support experts in SEO content creation.
Product discovery and search personalization - With Gen-AI, product search can be personalized with inputs from images, texts, and speech, and a better understanding of customer profiles. For instance, technology can collect individual behavior, preferences, and purchase history to let customers discover the relevant product and create personalized product descriptions. This would allow companies from the travel, CPG, and retail sectors to upgrade their e-commerce sales by achieving website traffic.
Estimate says generative AI can increase the productivity of marketing operations by up to 5 to 15% of total marketing spending.
Our analysis of the potential use of generative AI in marketing does not take into account any consequences beyond the direct effects on productivity. Gen-AI-enabled technology can provide data insights, which give new ideas for marketing campaigns and better customer segmentation. Marketing operations can carry resources for producing higher-quality content for owned channels, reducing expenses on external agencies and channels.
Sales Productivity with Generative AI
Generative AI also brings empowerment to both B2B and B2C companies and changes the way companies approach sales. Below are use cases of Gen-AI for sales.
Increase sales probability - Generative AI can prioritize sales leads by designing customer profiles from structured & unstructured data. Also, suggesting actions to human agents to improve client engagement at every point of interaction. For example, it can provide better insights into customer interests, leading to an improved deal close rate.
Improve lead generation - Sales representatives can leverage generative AI to nurture leads by blending product sales information and consumer profiles. Gen-AI can create discussion scripts to carry out customer conversation, including up and cross-selling talking points. It can also automate sales follow-ups to nurture leads until the customer agrees to direct interaction with the sales agent.
Our investigation suggests that generative AI has the potential to increase sales productivity by 3 to 5% of total global sales expenditure.
This estimation does not account for additional revenue that Gen-AI could bring to sales operations. For example, generative AI's capability to unify leads and follow up can bring new leads and facilitate more effective connectivity that would bring more revenue. Also, sales representatives who save time with Gen-AI's abilities can invest in higher-quality client interactions, leading to sales success.
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