Brand consistency is already important, but in an AI-saturated world it will become even more important.
The generative AI wave is bringing tools to marketing departments that will level the playing field. Small companies will soon be able to compete with larger ones because machines will be doing so much of the work. And as AI permeates marketing organizations, competing on marketing execution will become difficult because everyone will be better at marketing.
In such an environment, brand matters more than ever. When great marketing execution is par for the course, your brand values, brand promises, and relationship to your customers will be major differentiators.
So, in this new world, how do you master brand consistency?
This article will cover three ideas that can help marketers increase brand consistency in an AI world.
But first let's step back and understand why the problem exists.
Over the past decade, as companies' workforces have come to consist of more contract employees, marketing content cycle times have demanded faster responses, and the channels used to reach customers have become more fragmented, it has become increasingly difficult to monitor everything. Although it's reasonable to have every press release or website change reviewed up and down the chain of command, can you do that for tweets and other social media and still move quickly?
Many creative processes are also fragmented. Do you have agencies and contractors creating brand assets that take time to review and often need revisions to align more accurately with brand guidelines?
This problem of brand consistency exists today because of the speed at which marketing moves and the number of people involved in creating branded assets and content. Now, as generative AI has unlocked the ability to create thousands of unique and personalized marketing programs, it is exacerbating the brand consistency problem by giving you more to review on shorter timelines.
Generative AI is powerful, but AI models, such as ChatGPT and Midjourney, inherently don't understand your brand. When you ask them to generate emails, social media posts, landing pages, or ad content, AI tools pull from their knowledge of the general Web, not the knowledge of your company.
Here are three ideas for harnessing the power of generative AI and maintaining brand consistency.
1. Build a more exhaustive style guide
Style guides are often started with good intentions but they tend to end up unfinished. Adding a broad set of rules and samples of good and bad content makes it easier to more thoroughly define and understand your brand. Brand consistency is easier when there is a clear definition of what it means for something to be on brand.
The best way to do that is to look at some of the public company style guides available online. Companies that have large budgets, large teams, and deep brand expertise have to be thoughtful about what goes into defining a brand. So use those guides as a road map for your own best-practices and take the time to complete your style guide and brand guidelines.
2. Create a prompt library
Generative AI tools work with prompts. Prompts are inputs you pass into ChatGPT or Stable Diffusion or similar tool to get the output you want. Prompting is an art, and slight variations in your prompt can have large variations in the output you get.
Consider these two prompts:
- Write a promotional email of 150-250 words for my new red wine.
- Write a promotional email of 150-250 words for my new red wine that targets young urban professionals who care about sustainability and are price sensitive.
Those will generate emails that are very different from each other.
As your team goes through its workday and writes prompts for generative AI, set up a library of the best prompts, and include tips and tricks that work for your brand. That allows everyone to learn faster and get more on-brand output from the generative AI tools they use.
3. Consider a brand governance platform
A brand governance platform is a new category of software that uses AI to monitor brand consistency. It's an emerging field, and BrandGuard happens to be the market leader.
BrandGuard ingests data from your style guide and samples of previously approved content and uses it to train dozens of AI models that monitor your brand for consistency.
Brand governance platforms are different from brand safety. They don't analyze the webpages where your content appears; instead, they analyze the content created by your teams—whether employees or contractors or generative AI tools—and they ensure that everything produced adheres to your brand guidelines.
Consider a use case: If you use OpenAI to draft 1,000 personalized emails to your email list, BrandGuard can auto-approve the ones that are high-quality and on-brand, and it can trigger a human review or rewrite of the ones that aren't.
As you scale with generative AI, no human can review everything you put out. BrandGuard is trained by your team to be that automated review platform.
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In summary, brand consistency is hard, and generative AI is making it harder. But, at the same time, in an AI world, brand will become more important than ever. You can thrive in this new world using the three tactics mentioned in this article, but it takes time to implement them and reap the benefits.
AI is developing fast, so your best path is to embrace it early and learn how to use it to your advantage.
