AI Branding Strategies for Modern Businesses

On slow market days, this was done. Today, consumer trends can shift within hours because of viral content and fast-moving online conversations. Rigid brand playbooks are not the only inefficient thing. They're a liability.

Rather than giving up on consistency, businesses that are scoring in branding these days are making it smarter. They're not using AI to do what they can't do without it - they're using it to deliver what they can do with it.

Let us examine what this means in reality.

Think about a retail brand hosting a flash sale on six channels: Instagram, email, website, digital billboard, Google Ads, SMS. This is often a design team that is running up and down shifting the same creative concepts from channel to channel or writing new specifications. In other words, a design team that has to overhaul their creatives to be resized, reformatted and tweaked for each channel or write new specifications. It takes time and money, and it is not reliable.

AI tools can be used to change that. Coca-Cola and Zara are deploying AI systems that are able to generate hundreds of variations of correct formats in the same time it would take for one to be created ‘the old-fashioned way’. All of these elements are based on an internal brand visual identity, including logo guidelines, colors and typography.

For example, when a sportswear company is releasing a limited-edition shoe, it can send a brief to the system and get all the assets it needs, tailored for each platform and localized for each region, in a matter of hours. The speed is not only convenient; it is a huge time-to-market reduction without stepping out of the brand identity.

The term “Hi [First Name]” has long ceased to be a personal greeting. Today's consumers are able to sense when they are being treated as a number, not a person, and can easily recognize generic marketing.

If a customer is always returning to the site and purchasing running equipment, they should not be greeted with the same homepage as one who has just found the site and is surfing around. By employing AI, the layout, featured products, and even the brand's messaging can change in real-time depending on the knowledge that the AI has about the visitor.

This also applies to B2B. When it comes to content, a CFO wants data, ROI projections, and business cases to justify the investment. A marketing manager from the same company desires ideas, trends, and creative ideas. Previously, a brand's marketing efforts required it to craft two sets of content messages and deliver them in two distinct styles and structures; however, with AI systems, this is no longer necessary.

Old-school market research was just as frustrating as watching your favorite TV show and then having to wait long hours to hear the results of the survey; by the time you had the focus groups, put together the feedback, and written the report, the market had moved on.

Brands such as Adidas and Glossier are now on the lookout for social media, customer reviews, search activity, and real-time cultural discussions. It is not the final step to understand what your customers care about. When a food company hears a lot of people talking about “gut health,” it can begin to integrate gut health into its messaging weeks before the next quarterly review occurs.

This is where many businesses go wrong: they completely rely on AI to create content and then complain that it is dull and generic.

Fully automated content. While accurate, it lacks the reality that comes from someone who has been in the industry and has seen real usage, such as a customer story, an honest opinion, or the kind of observation that only someone who has actually been in the industry can have. They pick up ears, and when they hear, they lose faith.

Salesforce, for example, has an AI-powered content team that creates technical explainers and product announcements, but its most popular thought leadership content is still written by humans who have a solid understanding of the industry and can provide something really interesting. The AI saves time. It is definitely worth reading; humans make it worth it.

As more and more AI-generated content is churned out on the Internet, users are becoming increasingly suspicious. People are now skeptical of what they read and watch on the Internet, with deep fakes, bot-written reviews, and fake news. This can pose a risk or create opportunities for brands.

The danger is that any content that seems artificial or any AI behind content that feels like exploitation - particularly with customer data - will not gain credibility quickly.

Brands that are transparent about their use of AI and show that they are seeking to manage their customer data responsibly are standing out.

Trust has been built in Patagonia for a long time by being open and honest, even when it hurts. The same is true for AI. Stating that you use AI to be more responsive and to tailor your experience for you is not a liability. The fact that you use AI to be quicker to respond and to customize your experience for you is not a disadvantage. It's a differentiator.

Here are some helpful guidelines for incorporating AI into your brand strategy:

• Be transparent about using AI - Particularly in content and customer communications.

• Secure your customers’ data - Customization should only be done when the customer can trust you with their data.

• Always verify facts - AI can get it wrong. An editorial review process is not an option; it is essential for brand protection.

AI will not replace the people who create great brands. It will never take the place of the strategist who knows what a business is about, the writer who can create a story that resonates with people, or the creative director who knows that it just does not feel right.

If used well, it will eliminate the drag of business thinking from great brands. All formatting, drafting, research, and resizing can be completed more quickly. This translates to the fact that the people who can do the human stuff more effectively will be able to do more of it.

Brands that succeed are not the ones that automate the most. They understand what should be done with AI and what should not be delegated to an AI.