As potent as branding is, it loses its mojo when the cankerworm known as blanding infests it. If it were just a matter of logos, colour palette and other visual markers, it would be tolerable. Blanding delves beneath the surface to create a sea of the same.
That blanding is a neutral industry trend towards minimalism and safe design choices doesn’t change the fact that it chips away at brand health and equity. Nothing else makes the case for branding more than instances of blanding, even though the former is meant to avert the latter. Quintessential branding sets a product apart from its rivals but brands without unique personality breach this boundary by conveniently adopting minimalist, hyper-safe, and nearly identical visual identities.
Driven by the idea that simplicity is more versatile and globally recognisable, blanding is the mass homogenisation of corporate identities. According to Karen Maxwell of Fluxbranding, blanding typically borders on characteristics such as sans-serif typography, clean lines, geometric shapes, a limited colour palette, and the overall simplification of logo
Early adopters of blanding include luxury fashion collections like Balmain, Yves Saint Laurent, and Burberry, streamlining their logos to exude a minimalist, contemporary feel. Tech companies like Google, Uber, and PayPal soon followed suit, coming up with identically clean, versatile designs that align with today’s digital-first world.
If it sounds bland, then it’s blanding
When a copy or collateral lacks freshness and hits as jejune, expect it to feed into or culminate in blanding. It is for the same reason the broad way is crowded while the narrow path is almost deserted. With most people ill-disposed to heavy lifting and would rather take the easy way out, blanding is far removed from the few who diligently deliver a nuanced brand voice.
Ordinarily, branding should make a product mean something to someone but blanding robs it of that. Since most brands aren’t introspective enough to uncover and run with what makes them tick, they are susceptible to sounding like everyone else who is equally interested in matching efforts to industry. It takes ingenuity and curiosity for an organisation to stand out.
Blanding takes centre stage when brand custodians replace curiosity with assumptions. We assume we know what works for each audience segment. We assume certain colors communicate trust. We assume every brand needs to sound conversational, participate in cultural moments, or adopt the latest creative format. These assumptions, which may sometimes be correct, often go uninterrogated. Before you know it, they get hackneyed due to overuse. Curiosity is therefore needed to help marketers understand what’s worth creating in the first place, so that it won’t be a bandwagon thing.
In this content-first era, there are extraordinary artificial assistants smart enough to create and distribute content. AI can accelerate production, help explore ideas, and make creative work more accessible. However, faster answers won’t necessarily make brands more distinctive if everyone begins with the same questions. Technology can expand what we create. Channels change. Technology evolves. Human behaviour gets cultivated overtime. Remember one thing: the buyer and the seller are both human. And humans don’t just buy products. They remember how brands make them feel.
Branding builds, blanding hacks
As branding builds connections and memory with stakeholders, lazy competitors lean on blanding to hack the emotional attachment consumers have with brands they trust, identify with, and believe in. Branding builds by creating the meaning, trust and preference that makes one option feel more right than the others.
Blanding overlooks the power of community-driven content. Genuine user-generated insights often hold more weight with AI than polished PR pieces. Building trust through conversations can be the game changer. Bereft of the ability to build meaning, trust, preference, and experiences that turn visibility into long-term value, blanding resorts to hacking these from branding. Yet, winning brands are etched in memory, not just in the market. They are built, not hacked!
Automation and artificialness advance homogeneity
In today’s digital-first ecosystem where standard Retrieval-Augmented Generation (RAG), trendjacking and obsessions with SEO and keywords make everything virtually indistinguishable, branding has never been more expedient. As artificial intelligence models train on existing design trends, the ease of generating instant logos, website layouts, and copy is accelerating visual sameness
Businesses can’t help but adopt identical user interfaces, generic prompts and visual assets for global consistency, perceived modernity, and cost efficiency. The necessity for them to speak the love language of agentic AI like ChatGPT, Muse, Dot, and Grokbot for discoverability’s sake and to end up in the shopping cart also forces brands to sound alike. Branding therefore remains the panacea to the ensuing blanding problem.
Apart from the saturation of AI-generated minimalism, algorithms and large language models (LLMs) are programmed to favor data-driven and high-converting templates. By their training on existing web data and capabilities for infinite manipulation, these machines inherently output the “average” of what already exists for brands that rely heavily on their content generation capabilities.
As LLMs grant everyone equal access to create mid- or even high-quality assets and agentic eCommerce assumes the role of an umpire, information on customer preferences has become a commodity, and functionality common sense. The differentiating factors are therefore meaning, reputation and resonance. Even with AI, brands that don’t meet these criteria can easily be filtered out.
Used intentionally, AI can sharpen original thinking as the Muse not the Artist. Used indiscriminately, it can flatten a Thought Leader into the Average, or turn the Average into the Mediocre Thoughtless Leader. With intention, the outcome is AI-assisted content, but when the prompt is left entirely in charge, what results is AI-abandoned content.
Before AI slop, there was passing off, Isomorphism
It is not only the preponderance of generative AI outputs that makes for blanding. Before the ascendancy of artificial intelligence and the demands of digital scalability through SEO, fringe companies have been mimicking market leaders or major competitors until every company in the industry started sounding similar.
It got malicious with “passing off,” which is the illegal or unethical practice of misrepresenting goods or services to look like those of another established brand. Passing off is a concept under the common law where one party parades their goods or services as those of another, damaging the authentic brand’s established goodwill.
Although it deliberately makes consumers think someone else’s goods and services are connected or the same as the original, passing off is too extreme to be a synonym of blanding. A more agreeable synonym is the sociological term Isomorphism where tech firms and startups design themselves to look like each other to gain legitimacy. Blanding is a typical bandwagon or me-too marketing that sees companies jumping on a popular stylistic trend just because everyone else is doing it.
Some brands are so unambitious nd unimaginative that they don’t mind playing second fiddle or impersonating just to get a slice of the dominant player’s market share. In a manner of speaking, blanding can be likened to a brand shooting itself in the foot for aesthetics; while passing off is someone else stealing your foot. Blanding’s minimalist aesthetic is appealing in its ease and recognisability, but this comes at the cost of personality and uniqueness.
What gets brands into AI shortlist can actually solve blanding
How ironic that the same AI that fertilises blanding through standard content generation (GEO) does the exact opposite when it comes to citations (AEO). This is because AI visibility depends mostly on how clearly a brand is represented across sources it doesn’t control (earned media and third-party validation).
Brands and businesses won’t yield to blanding if they satisfy what makes for AI discoverability. According to LinkedIn’s VP of Product, Laura Lorenzetti, when AI is overused, especially at scale and in an automated manner, it can dilute the valuable insights real human conversations can spark. While noting that “it’s okay to use AI to help you write,” she posits that posts and comments must reflect the author’s voice and perspectives.
The answers to the folLowing algorithm-aligned queries will be the brand’s moat for blanding:
— Does our brand consistently attract the same narrative whenever it shows up?
—- Do people organically engage with our LinkedIn posts?
— Are our leaders featuring in popular podcasts and YouTube shows?
— Are we getting mentions from people we don’t pay?
—How rave is the reviews we are getting from customers?
—Is our brand getting adequate press coverage?
—Are we getting expert quotes in articles?
—What rare evidence can we bring to ongoing topical conversations?
AI search visibility is predicated on credibility, not just ad spend. Consistent messaging, genuine customer reviews, and trusted third-party mentions are increasingly playing a significant role in how AI discovers and recommends brands. While branding guarantees this, blanding doesn’t!
Ugochukwu, the Communications Manager at Rhiagano, can be reached via ugo.ugwuanyi@rhiagano.com
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