Solutions by need 6 of 8

Brand sentiment in AI: see how AI describes you to buyers

Being named isn't enough if the answer calls you expensive or limited. MentionX reads every stored answer that names you and records whether it describes you positively, neutrally or negatively, and why.

Start free See how it's calculated

Answers read this scan800

Mention Rate55%

Positive share45%

Negative share19%

Example: Vela CRM is an invented brand, scanned on Nova (200 prompts × 4 engines).

The definition

What is brand sentiment in AI answers?

Brand sentiment in AI is how AI engines describe your brand when buyers ask: positive, mixed or negative, and the strengths, objections, pricing and comparisons behind that view. MentionX extracts it from every stored answer that names you.

Extracted, then counted: AI reads the claims in each answer; the counts and shares are calculated in MentionX's code.
Next to your rivals: The same view for every tracked competitor, on the same prompts.
Tracked weekly: See whether a fix changed how engines describe you.

Is Vela CRM a good choice for a 20-person sales team?

Vela CRM is easy to set up and good value for small teams. Its reporting is more basic than Kestrel's, so larger teams may outgrow it.

No sources cited in this answer.

Recorded for Vela CRMMixedTwo strengths and one objection: the reporting gap.

Easy setupGood valueBasic reporting

Example answers. Vela CRM and Kestrel are invented brands.

Four readings

Every answer that names you carries a view

MentionX reads each answer that names you and records its tone, with the claims behind it. Positive and negative shares use only those answers.

Not mentioned

The answer doesn't name you, so there's nothing to read.

…Kestrel and Pipewise are the usual picks.

Negative

Objections lead: price, gaps or a rival's strength.

Vela CRM is missing some integrations…

Mixed or neutral

Strengths and objections balance, or there's no clear view.

Easy to set up, but reporting is basic…

Positive

Strengths lead, with few or no objections.

Reviewers like Vela CRM's fast onboarding…

Mention Rate counts these3 readings

Negative share

Positive share

The calculation

How brand sentiment is counted

Each square below is one stored answer, coloured by how it describes Vela CRM. Positive and negative shares are calculated over the answers that name you.

PositiveMixed or neutralNegativeNot mentioned

49%

ChatGPT

43%

Gemini

46%

Google AI Overviews

42%

Google AI Mode

Each block is one engine: 200 prompts, 200 squares.800 answers this scan

Positive share = answers that describe you positivelyanswers that name you

197 ÷ 436 = 45%436 = answers that name you

81 answers lead with an objection about Vela CRM. Each one opens to the claim and the sources behind it.

Example data for an invented brand. Counts are calculated in code from stored answers; formulas are published on the methodology page.

Positive shareNegative share

Week over week

Fix the source, then watch the tone

Engines repeat what their sources say. When you correct a source, weekly re-runs show whether the description changed.

Positive shareWeek 1 to week 8+4 pts

Negative shareWeek 1 to week 8−5 pts

Example data for an invented brand.

The method

How to track brand sentiment in AI, step by step

Day 0
Ask how buyers ask
Brand, comparison and pricing prompts, generated from your URL and market.
Day 1
Read every description
Each answer that names you is stored with the claims it makes.
Week 1
Group the claims
Strengths, objections, pricing and the rivals you're paired with.
Weeks 2–4
Fix the source
Find the pages behind each objection, then update yours and earn better ones.
Monthly
Report the shift
Positive and negative share by engine, next to each rival.

Reading the results

Five patterns worth acting on

A description is only fixable once you know where it comes from. These patterns point you there.

Every chart here uses one colour code

Coral: absent, or a rival aheadBlue: mentioned, not pickedMint: recommendedSilver: first choice, or you

One objection repeats across engines

A widely cited source says it.

First move: Find the source in the citations and answer it with proof.

Citation & Source Intelligence

Positive on one engine, negative on another

The engines read different sources about you.

First move: Compare the cited pages engine by engine.

Cross-Engine Monitoring

Named often, rarely positive

You're known, but buyers hear the objection first.

First move: Lead your pages with the proof buyers ask for.

Action Board

Negative share rises after a new review

A new review or thread is being cited.

First move: Open the answers that changed and respond at the source.

Answers & Evidence

A rival is always called the safe choice

Engines frame you as the risky alternative.

First move: Publish customer proof for the same use case.

Brand Sentiment & Positioning

The tools behind it

The MentionX features that do the work

Plans

How much each plan tracks

Answers per scan is prompts × engines, re-run 4 times a month. Spark and above include unlimited seats and competitors; Starter includes 3 of each.

SparkSelf-serve

$149 /mo

100 prompts × 3 engines = 300 answers a scan

Each square is 10 answers1,200 a month

ChatGPT, Gemini and Google AI Overviews

Choose Spark

NovaSelf-serve

$249 /mo

200 prompts × 4 engines = 800 answers a scan

Each square is 10 answers3,200 a month

Adds Google AI Mode

Choose Nova

GalaxySelf-serve

$599 /mo

300 prompts × 5 engines = 1,500 answers a scan

Each square is 10 answers6,000 a month

Adds Perplexity

Choose Galaxy

Questions

Brand sentiment in AI, answered

The questions buyers ask before they start. Your first scan answers the rest with your own data.

Read the methodology

How does AI describe my brand?

MentionX collects every claim engines make about your brand in answers to buyer prompts and groups them into strengths, objections, pricing and comparisons.

How is sentiment classified?

AI reads each stored answer and extracts the claims about you; MentionX's code counts them and calculates the positive and negative shares.

What is positive share?

Answers that describe you positively, divided by all answers that name you.

Can I fix a negative description?

Engines repeat what their sources say. Find the sources behind the claim, update your own pages and earn better coverage, then check the next weekly scan.

Does it cover competitors?

Yes. You see the same view for every tracked competitor, on the same prompts.

Which engines are included?

Every engine in your plan: 3 on Spark, 4 on Nova and 5 on Galaxy.

Other needs

Start from a different question

Free forever, no card needed. Free is a plan ($0, no card, ChatGPT): 20 prompts the first week, then 10 a week. There is no 7-day trial

Hear what AI tells buyers about you

Prefer to talk first?

Talk to the founder· 20 min

Your first scan reads every answer that names you and shows the claims that help and hurt.