Generative AI is being widely used in marketing. According to a Salesforce survey of 2023, 1,000 marketers found that more than half are currently using generative AI and another 22% plan to implement generative AI in 2024.
According to a BCG Generative AI survey in 2023, CMOs are focusing on following different kinds of use cases in marketing.
Personalization, Content creation are major use cases of Generative AI in Marketing. Customers are quite wary about the usage of their personal data. It is imperative to take certain steps as Adobe uncovered this in a report after interviewing several external clients and subject matter experts that with the early adopters of Gen AI in marketing are facing some challenges. For examples, 80% of customers prioritize knowing when they are talking to a human being or a bot.
To differentiate your brand and build trust among your customers, following several steps at the start of implementing this technology can have favorable impacts.
Be Transparent while building your first party data:
User data should only be collected with consent. It must be cookie-free and not rely on third-party data. Customer trust should be built by clearly informing them whether they are interacting with a human or AI-generated voice. Companies should act in the best interest of customers without waiting for regulations. The Business Value mindset is okay but several times it is important to weigh a use case through customer satisfaction ratings and their preferences. For examples, the bot that you deployed to interact with the customer, what percentage of time are customers switching to an actual human from being talking to a bot. What percentage of solutions are being directly solved by the bot?
First movers retain a human in the loop to ensure consistent brand messaging, imagery, and tone, guaranteeing meaningful customer experiences every time. It is better to custom train your model with your own data so that it keeps the brands unique traits.
Demonstrate Generative AI as a career building opportunity for your employees.
The organizations should be transparent with the employees to address management overconfidence and employee’s trepidation about the technology. The management should be part of change management initiatives to ensure adherence to policy, set expectations, alleviate mistrust, and engender a mindset shift. Employees should be included in the piloting of generative AI use cases so as they are able to understand what’s in it for me/Strategic expectations in roles. Other than upskilling the employees, hold “promptathons,” a series of prompting sessions to upskill the team in the “art of the prompt.” While in the pilot sessions, use following short-term comparison metrics before and after progress.
- Workplace satisfaction
- Time saved
- Volume of content created
- People required
- Cost per asset
- Speed to launch
Ensure Accountability and Responsibility
Early adopters are establishing the Center of Excellence as a single point of control for all Gen AI related stuff across all the departments. Some companies are even setting up geography-oriented Business Units to drive Gen AI initiatives according to the various geographies. Such initiatives are giving a fruitful result in driving these changing technologies from a single focal point and can be adopted by newer organizations. It is important to map and mitigate all Gen AI related risks such as fairness, Biases, Transparency and Security. It is good practice to organize goals in the right sequence. For example, A company should aim to prove the concepts and cultivate skill and insights within the team before taking on more complex cases. The team should be clear on how Vendors and strategic partners should map to the needs of the organization. It is imperative to have the mid to long term data transformation plan sorted.
Source:
1. Leading generative AI deployment for marketing by Adobe and EY
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2. Salesforce
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