Household Appliance AI Search Case Study

In a 3-month long campaign with close to 200 engagements, this campaign generated an estimated $122,454.73 in total estimated monthly branded value. That included $119,757.18 in organic keyword value and $2,697.55 in LLM-cited pages value.

Methodology note: Directional estimate based on tracked keyword visibility and modeled paid-equivalent value. Not exact attribution.

As shoppers increasingly relied on online communities and AI summaries to compare home appliances, this brand saw product discovery shift away from product pages alone. 

They partnered with CiteWorks Studio to build visibility where recommendations are formed, across high-intent public discussions and the sources AI systems reference when generating answers.

Key Outcomes

What we achieved from a 3-month long campaign with 200 engagements: 

• Drove a 400% month-over-month lift in ChatGPT brand mentions
• Ranked for 13,679 keywords in Google’s top 10
• Optimized 100 online community threads to improve brand context in AI citations

What Changed in the Market

Where Shoppers Decide Now: Comparisons + AI Summaries

In home appliances, a small number of high-authority community forums, particularly those focused on home improvement and long-term purchase value, disproportionately shape what AI tools recommend. The brand had limited visibility in exactly those sources.

At the same time, the brand was seeing competitors outrank them on Google page 1 for high-intent searches like best household appliance product and comparison-style queries.

Google AI Overviews, Gemini, and ChatGPT also became common tools for researching and comparing household appliances. More shoppers started trusting AI-generated summaries that pulled recommendations into a single answer, often before they clicked through to any site.

In practice, ranking position wasn’t the full story anymore. AI answers reflect what the web already says, especially third-party reviews and real-user discussions, which shapes how buyers perceive performance, reliability, and value. The brand needed to win both page-1 search visibility and LLM visibility inside AI recommendations to stay competitive.

What the Brand Needed

Win visibility in AI answers

The brand needed a clearer way to diagnose and improve how it appeared across both traditional search results and AI-driven product discovery.

To do that, they needed a repeatable measurement framework that could track:

• Mentions: how often the brand was named in AI-generated answers
• Citations: which websites and pages AI systems referenced when describing the product
• Share of voice: how frequently the brand appeared compared with competing household appliance brands

The aim wasn’t only to climb Google page 1. It was also to build reliable LLM visibility, so the brand showed up consistently when shoppers were making high-intent comparisons at the moment.

What We Did

1. Mapped how AI recommendations were being formed

We began by reviewing how leading AI tools described the household appliance brand and which sources they pulled into those summaries. Our visibility reporting tracked citation patterns across AI Overviews, ChatGPT, Gemini, AI Mode, Perplexity, and Copilot. This showed which product pages, reviews, and online discussions most often shaped how the brand appeared in AI answers.

2. Tracked lift month over month and optimized continuously

We monitored month-to-month movement to see whether new activity led to more brand mentions, stronger citations, and improved share of voice in AI responses. This made it easier to identify which shopper questions and comparison themes (features, pricing, ease of use, performance) were gaining traction. We then adjusted based on results, doubling down on what worked and pausing what didn’t produce measurable lift.

3. Strengthened the sources AI systems relied on

For consumer appliances like vacuum machines, purchase decisions are heavily influenced by what people recommend, compare, and validate on public forums. Since third-party sources and online community conversations were already influencing AI-generated summaries, we focused on strengthening accurate, positive brand context in those environments.

Rather than relying only on generic blog output, CiteWorks Studio executed an AI citation strategy designed to increase the quality and consistency of brand references tied to common “best household appliance” and comparison searches.

The Outcome

Measurable gains across SERPs and AI-generated recommendations

Across traditional search and AI-generated product summaries, the brand saw measurable improvements in visibility for high-intent queries.

• Average ranking position of #7 secured for all high-intent keywords
• 400% increase in brand mentions in ChatGPT across 100+ high-intent queries
• 13,679 keywords appearing in the top 10 results, covering 3.9M in combined monthly search volume and ~$4,866 in paid-search benchmark value (keyword volume × cost per click)
• Brand context strengthened across 100 high-impact community sources and cited pages influencing AI answers

These gains weren’t just a short-term spike. They created a stronger foundation for sustained discovery across both Google and AI answers.