For its first CTV campaign, Jennifer Aniston’s DTC haircare brand LolaVie had a few non-negotiables. The campaign had to be simple. It had to demonstrate measurable impact. And it had to be full-funnel.

LolaVie used Roku Ads Manager to test and optimize creatives — reaching millions of potential customers at all stages of their purchase journeys. Roku Ads Manager helped the brand convey LolaVie’s playful voice while helping drive omnichannel sales across both ecommerce and retail touchpoints.

The campaign included an Action Ad overlay that let viewers shop directly from their TVs by clicking OK on their Roku remote. This guided them to the website to buy LolaVie products.

Discover how Roku Ads Manager helped LolaVie drive big sales and customer growth with self-serve TV ads.

The DTC beauty category is crowded. To break through, Jennifer Aniston’s brand LolaVie, worked with Roku Ads Manager to easily set up, test, and optimize CTV ad creatives. The campaign helped drive a big lift in sales and customer growth, helping LolaVie break through in the crowded beauty category.

Learn more.

For years, startup websites have been designed around one assumption:

A human will discover the company, visit the site, read the page, and decide whether the product is right for them.

That journey is beginning to change.

Increasingly, the first visitor evaluating your brand may not be a person. It may be an AI assistant researching products, comparing alternatives, or recommending a solution on someone’s behalf.

That means your brand now has two audiences.

The person making the decision.

And the machine helping them make it.

Traditional search gave brands a list of links to compete within. AI systems often give users something very different: a synthesized answer containing a short list of recommendations.

That creates a new strategic question:

Does the AI understand your brand well enough to recommend it?

This is no longer theoretical. Adobe Analytics data reported by Reuters found that consumers referred to retail websites by large language models generated 53% more revenue per visit than visitors from non-AI sources.

Those shoppers are not merely experimenting. Some are arriving with stronger intent because an AI assistant has already helped them narrow the field.

But an AI can only recommend what it can find, understand, and verify.

Founders sometimes resist describing their companies in familiar category language because they want the brand to sound original.

Instead of “accounting software for independent restaurants,” they write something like:

Reimagining financial possibility for modern hospitality.

That might sound more visionary. It also makes the company harder for humans and machines to categorize.

Distinctiveness matters, but it should sit on top of clarity.

Your website should explicitly communicate:

This information should appear in actual text, not only inside graphics, videos, or clever headlines.

The goal is not to write robotically. It is to remove the ambiguity that forces both customers and AI systems to guess what you mean.

AI systems form impressions by gathering information from multiple sources. Your website may describe the company one way, while LinkedIn, review platforms, press coverage, app listings, and founder interviews describe it five other ways.

That inconsistency weakens your brand twice.

It confuses potential customers and makes it harder for an AI to identify a stable, credible description of your company.

Choose a clear category, audience, central promise, and set of differentiators. Then reinforce them consistently everywhere your brand appears.

Repetition may feel boring from inside the company. From outside the company, repetition creates recognition.

An AI is less likely to trust a claim simply because your homepage makes it.

If your company says it is the easiest, fastest, or most trusted option, what supports that assertion?

Customer reviews, independent articles, case studies, detailed product documentation, comparison pages, public benchmarks, and expert references all help establish credibility.

This makes earned media and customer advocacy increasingly important. Third-party validation is not merely good publicity. It may influence whether an AI system considers your company credible enough to recommend.

Start with a simple exercise.

Ask several AI assistants the questions a prospective customer might ask:

Do not treat every answer as definitive. Look for patterns.

If your company is missing, miscategorized, or poorly explained, examine whether the necessary information exists publicly and consistently.

Tools such as Profound and Peec AI can help brands monitor how they appear in AI-generated answers. A lesser-known option, Otterly.AI, tracks prompts, citations, and brand visibility across multiple AI search experiences.

The fundamentals of brand building have not been replaced. They have acquired a new audience.

Clear positioning, consistent language, useful content, credible proof, and third-party recognition still matter. But now they help machines understand your brand as well as people do.

The next time a customer asks an AI for a recommendation, your brand needs to be in the room to make its case.

Make sure it has already left behind enough evidence to be invited to the party.

Best,

Edwin