How was the Dove simulation run?

Theo Nakamura is a synthetic digital twin, a test buyer built from a real shopper profile. They worked through Dove's live product page with a goal to buy, and every point where they hesitated or moved on is recorded in this report.

What is the single biggest fix on Dove's page?

Soft Sensitive naming undercuts a clinical-strength claim. In the source simulation, this specific word choice was the reason heavy-sweat buyers moved on, regardless of the actual formula.

Who is this built for?

The ranked findings report is built for a design team, the buyer-level briefs for a copy team, and the buyer map as the starting point both teams work from.

eLLMo AI runs test buyers against a product page before a brand spends a dollar on ads, and audits whether AI engines like ChatGPT and Perplexity can find and recommend a brand. Both come back as a ranked list of fixes, not a grade.

How do I get a report like this for my own page?

Book a demo at tryellmo.ai. Most teams get first findings on their own product page within 15 minutes of sharing it.

How is an eLLMo simulation different from real user research?

eLLMo buyer simulations run in 15 minutes, require no participant recruitment or scheduling, and are matched to the customers you actually sell to before any live traffic is committed.

Does eLLMo offer a free way to start?

Yes. See current plans on the pricing page.

What conversion blockers did the Dove simulation identify?

The simulation identified two ranked findings: (1) Soft Sensitive naming undercuts clinical-strength claim, causing heavy-sweat buyers to move on; (2) Retail availability and low price are real advantages for brand-familiar, price-sensitive buyers.

What is the purchase intent score for this simulation?

The purchase intent score was 30%, with only 2 out of 10 test buyers still buying at the end of the simulation.

How was the Dove simulation run?

Theo Nakamura is a simulated buyer, built from real buyer data. They shopped Dove's live product page with a goal to buy, and every point where they hesitated or moved on is recorded in this report.

What is the single biggest fix on Dove's page?

Soft Sensitive naming undercuts a clinical-strength claim. In the source simulation, this specific word choice was the reason heavy-sweat buyers moved on, regardless of the actual formula.

Who is this built for?

The ranked findings report is built for a design team, the buyer-level briefs for a copy team, and the buyer map as the starting point both teams work from.

eLLMo AI sends simulated buyers, built from real buyer data, through a product page before a brand spends a dollar on ads, and audits whether AI engines like ChatGPT and Perplexity can find and recommend a brand. Both come back as a ranked list of fixes, not a grade.

How do I get a report like this for my own page?

Start free at tryellmo.ai, or book a demo. Most teams get first findings on their own product page within 15 minutes of sharing it.

How is an eLLMo simulation different from real user research?

eLLMo buyer simulations run in 15 minutes, require no participant recruitment or scheduling, and are matched to the customers you actually sell to before any live traffic is committed.

Does eLLMo offer a free way to start?

Yes. See current plans on the pricing page.

Example simulation report

What eLLMo finds on Dove in 15 minutes.

Dove Clinical Soft Sensitive. Broad familiarity wins a small, brand-loyal segment, not the serious-sweat buyer.

Start free Book a demo How simulations work

Named simulated buyer on this trip: 1; Named simulated buyer on this trip
Still buying at the end: 2/10; Still buying at the end
Purchase intent: 30; Purchase intent
Ranked things to fix: 2; Ranked things to fix

What happened

Wins only brand-familiar, low-need buyers

dove.com

The finding

Who: Theo Nakamura, simulated buyer comparing antiperspirant strength claims
Their words: “Soft Sensitive sounds gentle, not strong. I don't think this is for someone who actually sweats a lot.”
How many: One named buyer
Where: The product name, Soft Sensitive
The fix: Make the clinical-strength claim louder than the gentle name

The buyer

Theo Nakamura

Simulated buyer comparing antiperspirant strength claims

Picks the familiar name fast when the need is not urgent.

Patience

Price sensitivity

Research depth

Purchase intent30%

Why this score

Dove's 48-hour claim and Soft Sensitive language read as gentle, not clinical-strength, to a heavy-sweat buyer.

Familiarity is real. It does not read as strength.

In the source simulation, Dove Clinical Soft Sensitive won only a small, brand-familiar, older-retail segment. Heavy-sweat buyers interpreted the Soft Sensitive name as insufficient clinical strength, and its 48-hour claim compared unfavorably to Secret's 100-hour claim and Carpe's premium clinical positioning.

Fix these

Ranked by how much each one cost the sale. The first one explains where still buying ended.

01
Weak
Soft Sensitive naming undercuts a clinical-strength claim
In the source simulation, this specific word choice was the reason heavy-sweat buyers moved on, regardless of the actual formula.
02
Present
Retail availability and low price are real advantages
For a brand-familiar, price-sensitive buyer, these remain genuine strengths.

eLLMo AI ran this simulation on the public dove.com product page, with simulated buyers built from real buyer data.

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What every simulation ships

A buyer map, ranked findings, and briefs you can use today.

Every simulation ships a buyer map, ranked findings, and briefs designed to land in your design brief, copy brief, and stakeholder deck.

Starting point

Buyer map

Who your buyers are and how they shop, built from your brand, your product, and your competitors. Ready for your team and your AI writing tools.

Ship to design team

Ranked findings

Every problem ranked by how many buyers hit it. Each one names the buyer, their words, and the spot on the page.

Ship to copy team

Buyer briefs

How each buyer made their decision, in their own words. Paste them into your creative brief or any AI tool.

Questions and answers

Common questions about this report

Run it on your own product page.

Same method, your product page. First findings in 15 minutes.

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