[Note: This article is part 2 of a 3-part series intended to help bring together marketers and financial leaders to tackle challenges associated with modernizing marketing organizations for the AI-Era. Read Part 1: Marketing in the AI Era]
Marketers have often placed marketing activities on a spectrum. At one end is brand marketing, or the activities designed to promote awareness and solidify customer relationships. At the other end is growth marketing, or the laser focus on finding new prospects and generating leads. In actuality, brand marketing and growth marketing—and everything in between— have to work as a system (see image below). It’s hard to have one without the other.
In the age of AI tools, the interdependence of brand and growth marketing is becoming more critical than ever and is requiring marketers to shift how they think about brand marketing. To understand why, let’s start by taking a look at standard definitions of brand and growth marketing.
Brand marketing aims to build a positive perception of a company or product and promote a long-lasting relationship with a customer. Through brand marketing, a company can develop an emotional connection with a customer, ideally to create loyalty to a product or service. At its core, brand marketing leverages storytelling–promoting stories about the feelings or emotions a product can evoke. The tactics to promote those stories have historically been advertising-based and encompass other promotional or awareness activities. Brand marketing success used to be measured by brand surveys or questionnaires, but measurement is now largely online and in many cases automated. In the past, brand marketing outcomes were difficult to tie causally to pipeline or revenue, though marketing teams could point to correlations. That’s changed with the introduction of new brand assessment tools.
Growth marketing, by contrast, is a data-driven approach in which marketing teams get leads and convert them quickly into a sales pipeline. Growth marketing is typically focused on digital activities such as search, content marketing, intent-based marketing, social marketing, and other types of performance marketing in which digital campaigns are reviewed frequently for their effectiveness and efficiency. It can also include product-led growth, in which product trials and product use serve as a marketing engine. The primary objective of growth marketing is to turn all of these activities into leads–fast–and then optimize their conversion rates using tactics like A/B testing, SEO optimization, and dynamic content. The success of growth marketing can be measured by Customer Acquisition Cost (CAC), Lifetime Value (LTV), and monthly active users, among other metrics.
How Brand Marketing Will Change in the AI Era
Each time a new digital technology arrives, companies adjust their marketing accordingly to take advantage of the new channel. For example, when mobile technologies launched, companies revised their strategies to include mobile apps and targeted advertising. When social media arrived, companies developed social engagement and advertising plans, and stretching way back to the early era of the internet, companies adapted their marketing to manage their online reputation, build websites, and launch online marketing. Each new digital technology placed new demands on brand marketing. In social marketing, for example, companies had to figure out how to engage with customers in a new way and respond to real-time feedback.
The same is true for AI but with its own twist. AI isn’t simply a new channel for which companies will adapt existing content or strategies. Because AI has the potential to create, manage, and optimize - brand marketing and guidelines will have to flex and predict the many ways that AI tools might choose to represent the brand.
Perhaps more importantly, as more of your marketing becomes automated, creating an emotional connection with your customers through stories that resonate with them–will become even more critical.
Let’s step through areas of change that you’ll have to navigate.
1 - Hyper-personalized engagement
As AI tools get better and faster, you and your team will be able to deliver highly personalized content at scale, and you’ll be able to analyze responses and engagement around that content in real time, giving you even more insights into prospects and customers. While this sort of engagement is usually considered “growth marketing”, the personalized nature will need to reflect your brand and not be generic. You’ll need to ensure that your brand guidelines are up to the task of rapidly producing content engines. You may even need to prepare for backlash against AI systems. Gartner notes that by 2027, 20% of brands will position and differentiate themselves as “AI-free” in their business and products based on consumer demand.
2 - Reputation management
Smart marketing leaders have already been spending time cataloging what “the bots” are saying about their brands. If you haven’t asked a generative AI tool questions about your company’s brand, do it now! Gartner notes that by 2026, 60% of CMOs will adopt specific technologies to protect their brands from GenAI-driven deception. Consider this scenario: when a user asks AI about your brand, that system first retrieves relevant knowledge from its database. That response is often “enriched” with additional external data from outside the database in a process called “retrieval-augmented generation”, or RAG. It’s critical in brand management that your team ensures marketing materials and public responses contain accurate, up-to-date information and that you’re staying ahead of what’s being published about your brand.
3 - Brand Trust
With the rise of AI-generated content, consumers might become more skeptical of overly polished messaging and seek authenticity instead. Companies must be transparent about using AI to personalize interactions and content.
4 - Avoiding homogeneity
As brands increasingly use AI tools to create and manage their marketing efforts, there's a risk of messaging becoming standardized. Marketers must find innovative ways to use AI creatively to differentiate their brands. This leads to the final topic: storytelling.
5 - Storytelling
Telling meaningful, relevant, and emotional stories is critical to brand marketing. Good stories aren’t about you or your products. They’re about your customer’s experiences with your products–experiences that carry emotional significance and create a bond. As AI becomes more prevalent in marketing and provides hyper-personalized, perfectly timed, and efficient, storytelling will become a more indispensable human element of your marketing. AI might be able to target a campaign and build personalized assets, but it can’t create true, emotional stories about your brand. Yet. Today, those stories are created by you. And they’ll continue to serve as the emotional anchor for building customer loyalty.
Where do we go from here?
As AI technologies reshape the marketing landscape, integrating the agility of growth marketing with the depth of brand marketing will be critical to ensure long-term brand equity and loyalty. For CMOs, steering their brands with a balanced approach in these two areas is more crucial than ever and underscores the role of brand distinction as a key competitive advantage. And, it’s critical to understand where AI is best used and which elements, such as storytelling, have no human alternative.