How Do You Use Generative AI in Marketing To Build Customer Trust?

What’s the value of trust? Certainly, a breach is very serious. Hence why international legal frameworks, such as the GDPR for personal data, have been designed to protect customer trust. And why almost all IT leaders are focused on data trust.

Think of your own job in marketing. It’s far easier if your customers trust what your brand’s saying. Loss of that trust can have a significant financial impact.
 The high stakes involved can make it seem like it’s a risk to adopt disruptive new technologies. In fact, trust is cited as one of the main concerns for organisations looking to adopt generative AI according to Forrester research. But the bigger risk might be not adopting it. So, reframe the question: Rather than wondering how to maintain trust while adopting AI, ask how AI can help build customer trust.

Prioritising customer trust in the age of generative AI marketing

The true value of customer trust is incalculably high. You trust brands to provide a product or service, and also to protect any data they collect, including your personal information and bank details. Trust is the foundation for a good reputation, customer loyalty, and repeat business. The damage done when trust is broken can be fatal for a business, if not hugely expensive.

Maintaining the trust you’ve earned is obviously important when adopting new technology, but it doesn’t mean you don’t do it — customers also trust that companies will use the tools at their disposal to provide the best service possible. 

Today, that means using AI. Companies that use generative AI in marketing have shown an increase in their productivity. For example, AI can help you with:

• Segmentation — analysing leads at speed and scale to put them into the right segment to receive relevant marketing comms.
• Personalisation — analysing data instantly to personalise touchpoints in real time. For example, Einstein Content Selection is a no-code tool that optimises campaigns by evaluating which images generate the highest engagement. This makes personalising the browsing experience effortless.
• Real-time offers — combining AI with data such as geolocation data means offers can be tailored and updated in real time.
• Deep insight — Einstein Messaging Insights monitors changes in performance to identify anomalies and generate insights.
• Optimisation — Einstein can analyse your copy and subject lines for better content, and analyse engagement to identify good candidates for account-based marketing (ABM).

These benefits are driving adoption. The Salesforce State of Marketing 2023 report shows that 62% of respondents, globally, already use AI. But to really get your customers on your side, you should look beyond how AI can help you and see how it can help your customers.

Overcoming challenges and building customer trust with AI

Before jumping to the advantages, there are some key challenges around AI and customer trust that must be considered. According to the State of the Connected Customer 2023 report, almost half of customers globally don’t trust companies to use AI ethically. Customers will be wondering how their data is being used by AI. Where’s it stored and how’s it secured? Your business must have the answers.

When it comes to AI ethics, there are issues that need to be addressed around bias, transparency, accessibility, algorithms, datasets, and the level of human involvement. If biases present in human-generated data aren’t addressed, the AI tends to learn and perpetuate those biases. This is something Salesforce has been concerned with for many years, and to promote transparency on this issue, Salesforce audits and publishes its model cards so customers and prospects can learn how the models were trained to make predictions.

Being mindful of these challenges is critical to maintaining trust. But how can AI help build customer trust? 

• Personalised recommendations: By offering relevant suggestions based on past purchases or browsing history, you demonstrate an understanding of your customers’ needs and preferences.
• Predictive analytics: Generative AI-powered data analytics can anticipate customer challenges and write the answers, allowing you to proactively and swiftly provide assistance before issues arise. Our Einstein 1 Platform helps you create a 360 view of your customers while generating more than 200 billion AI-powered predictions per day.
• Chatbots and virtual assistants: AI-driven chatbots can enhance customer service by providing round-the-clock support on your website and social media platforms, fostering trust in your brand’s dependability and availability.
• Fraud detection and security: By analysing patterns and anomalies in customer behaviour, AI algorithms can help detect and prevent fraudulent activities, such as unauthorised transactions or data theft.
• Transparency and accountability: AI can provide transparency into your business practices and decision-making processes. For example, AI algorithms can explain the rationale behind pricing strategies or recommendations.

Recipe for a trusted AI strategy: principles and integrations

If your business is going to integrate AI into marketing, what can you do to reassure customers? You need a defined AI strategy that does two things. First, it establishes data security protocols and trusted AI principles so that your organisation is genuinely ahead of the challenge and isn’t trust-washing. Second, it communicates the first part to the wider world — to build trust, you mustn’t only do but say. 

Every business is unique, and your AI guardrails need to be considered according to your own customers’ needs, but it may help you to review the five principles we’ve designed at Salesforce:

• Accuracy: We need to deliver verifiable results that balance accuracy, precision, and recall in the models by enabling customers to train models on their own data.
• Safety: We must protect the privacy of any personally identifying information (PII) present in the data used for training and create guardrails (For example, force publishing code to a sandbox rather than automatically pushing it to production).
• Honesty: When collecting data to train and evaluate our models, we need to respect data provenance and ensure that we’ve customer consent to use it.
• Empowerment: There are some cases where it’s best to fully automate processes, but there are other cases where AI should play a supporting role to the human.
• Sustainability: As we strive to create more accurate models, we should develop right-sized models where possible to reduce our carbon footprint.

Trusted future for AI: best practices and opportunities

The State of IT 2023 report shows that 86% of IT leaders globally believe generative AI will play a big role in their organisations in the near future. So, it looks like tomorrow’s marketing will be AI-powered. But the cornerstone of marketing will continue to be — as it always has been — trust. Trust will still be at the centre of any B2C or B2B relationship.

Regulations are quickly being introduced to ensure businesses act ethically. India, China, and the EU all published guidance or draft regulations for responsible AI in 2022. On March 13th, the EU endorsed, by an overwhelming majority, the European Union’s Artificial Intelligence Act (EU AI Act). The EU AI Act is expected to be officially endorsed by Member States and published in the Official Journal of the EU shortly after the vote and will start to apply 20 days later. Prior to this, since 2019, at least 17 US states have proposed bills or resolutions to regulate AI applications. 

Building AI that strengthens trust requires that you stay ahead of regulations — to keep your reputation intact and avoid fines.

So, you’re ready to include AI in your marketing operations to build trust and drive sales. What’s the plan to ensure long-term success? Here are five best practices:

1. Set clear goals and objectives for your AI marketing initiatives: Well-defined objectives will help you stay on track.
2. Run a pilot: Pick one area or campaign to enhance using AI and monitor its impact closely.
3. Choose the right AI tools and platform: Select solutions based on your specific needs, rather than the capabilities of the technology. Focus on the problem first, and technology second.
4. Connect your existing marketing systems and processes to your AI tools: Give your marketing team comprehensive insights and recommendations.
5. Train your marketing team on how to use AI effectively: Give them the skills and knowledge to use the tools you’ve implemented and to interpret data.

Rushing into AI adoption is a mistake. Carefully considering the challenges is the responsible thing to do. However, it also makes sense to look for opportunities. Identify the areas where using AI in your marketing can help build trust.

To learn more about how Salesforce is tackling the issues around customer trust and AI, read our commitment to Trusted AI.