# Actions: Content
Source: https://docs.frictionai.co/actions/content
Run and review domain content readiness audits for AI discoverability issues.
# Actions: Content
Actions: Content is the domain content readiness audit. It checks whether website pages are clear, current, entity-rich, and useful for AI systems that need to understand or cite the brand.
![Content readiness audit showing score, category breakdown, and audited page rows]()
## What the audit returns
A top-level score for how well the audited site supports AI discoverability.
Scores by audit category, such as clarity, entity signals, structure, and freshness.
Aggregated issues grouped by severity so you can prioritize work.
Page-level results with failed checks and issue details.
## Run an audit
Make sure the selected brand has a website configured in [Brand Profile](/workspace/brand).
Go to Actions -> Content.
Select **Run First Audit** or **Run New Audit** when available.
The audit updates automatically when it finishes.
## Audit availability
Only one audit can run for a brand at a time. After an audit completes, the page shows when another audit is available.
Add the website in [Brand Profile](/workspace/brand), then return to Actions: Content.
Wait for the current audit to complete before starting another.
The score card shows when another audit can be run.
## How to use results
High-severity content issues are more likely to explain weak AI answers or missing citations.
Repeated failures across pages usually point to a template, schema, or content-system fix.
Pair the audit with [Actions: Prompts](/actions/prompts) to fix pages that support high-value prompt blindspots.
Run a new audit when enough content or structure has changed to make the comparison useful.
# Actions: Prompts
Source: https://docs.frictionai.co/actions/prompts
Find underperforming prompts and inspect the response evidence behind recommended fixes.
# Actions: Prompts
Actions: Prompts surfaces prompts where the brand underperforms across visibility, sentiment, or purchase intent. It is the fastest way to move from score diagnosis to a fix list.
![Actions prompt hub showing blindspot counts, underperforming prompts, and a detail drawer]()
## What appears here
Prompts where the brand is weak, missing, negatively framed, or losing the recommendation.
Filter by all metrics or a single metric: visibility, sentiment, or purchase intent.
Filter by provider and inspect how each model responded.
Open prompt evidence, response text, recommendations, sources, and search keywords.
## Filters
Use all metrics for triage, then isolate visibility, sentiment, or purchase intent when you need a cleaner fix list.
Filter by custom prompts or system prompts so you know whether the issue came from your own tracking set or brand-health analysis.
Filter to one provider when a weak answer appears to be model-specific.
Search prompt text when you are investigating a category, product line, campaign, or competitor.
## Use the detail drawer
Click an underperforming row to open the right-side detail panel.
Confirm which metric is weak and how severe the issue is.
Look at the explanation, response text, competitor mentions, source evidence, and recommendation cards.
Most fixes are content coverage, source quality, comparison positioning, product proof, or entity clarity.
## Fix patterns
Create or improve content that directly answers the missing prompt intent. Strengthen source authority and category association.
Address the source or narrative creating cautious, mixed, or negative framing. Add recent proof, reviews, customer outcomes, or corrections.
Improve comparison, use-case, pricing, review, and product proof pages so AI has evidence to recommend you.
Prioritize prompt blindspots that repeat across providers or map to high-value commercial intent. One weak answer is less important than a repeated pattern.
# Analysis
Source: https://docs.frictionai.co/brand-audit/analysis
Diagnose brand health across visibility, sentiment, purchase intent, providers, prompts, sources, and trends.
# Analysis
Analysis is the deep-dive view for brand health. Use it to understand why AI Score is moving and which metric, provider, source, or prompt explains the movement.
![Brand audit analysis page with AI Score, performance trends, metric tabs, and model comparison]()
Brand health analysis is available on Growth, Professional, and Enterprise plans.
## What to inspect
Top-level recommendation strength across the selected period.
Switch between visibility, sentiment, and purchase intent.
See whether movement is recent, sustained, or isolated.
Compare performance across available AI providers.
Review the prompts and responses that contributed to the score.
Inspect cited domains and search keywords tied to brand health.
## Core metrics
Measures whether the brand appears in relevant answers, how prominent it is, and how consistently it appears across providers and prompt types.
Measures the tone and framing of brand mentions. Weak sentiment often points to outdated sources, mixed reviews, or competitor-led narratives.
Measures whether AI guides users toward choosing or buying from the brand in high-intent contexts.
## Workflow
Start with 30 days. Use 7 days for recent changes and longer windows for stable trend interpretation.
Open the metric tab that changed most or is weakest against expectations.
A provider split often reveals whether the issue is model-specific, search-specific, or broad.
Use prompt evidence to see the answer text and citations behind the score.
Use CSV export for source, keyword, or stakeholder reporting workflows.
## Common diagnostics
Check whether competitors gained share of voice, owned pages disappeared from sources, or prompt coverage shifted.
Look for negative or cautious language in responses and identify the sources that support it.
Compare the answer against competitors. AI may mention you but choose another brand as the recommendation.
If one provider behaves differently, inspect that provider's citations, retrieval behavior, and answer style before making a global conclusion.
## Related pages
See whether AI recognizes your brand before relying on live search.
Compare brand health trends against the promoted deep-dive competitor.
Turn underperforming prompt evidence into recommended fixes.
Audit website pages for AI-discoverability issues.
# Competitor
Source: https://docs.frictionai.co/brand-audit/competitor
Compare your brand against a promoted deep-dive competitor across AI Score and core brand health metrics.
# Competitor
Competitor is a head-to-head deep-dive against one promoted competitor. It compares AI Score, brand recognition, visibility, sentiment, and purchase intent over time.
![Head-to-head competitor comparison with AI score cards and trend lines]()
Competitor deep-dive is available on Growth, Professional, and Enterprise plans. Starter can still track competitors for broader context.
## What this page shows
A direct AI Score comparison between your brand and the promoted competitor.
Separate charts for brand recognition, visibility, sentiment, and purchase intent.
The page reflects the providers available for the selected plan and data window.
If the comparison is still being prepared, progress appears before the full charts are available.
## Promote a competitor
The brand settings page is where competitor management happens.
Go to [Brand Profile](/workspace/brand).
Add tracked competitors that represent your category and buyer alternatives.
Growth and higher tiers can choose one competitor for deeper head-to-head analysis.
The comparison appears when enough competitor data is available.
## How to read it
You are stronger across the measured prompts and providers. Inspect weaker submetrics so the lead does not hide specific gaps.
AI mentions the competitor more often. Compare prompt evidence and sources to understand why they appear.
AI frames the competitor more positively. Look for reviews, analyst pages, case studies, and public proof that support that framing.
AI is more willing to recommend the competitor in buyer contexts. Inspect comparison pages, pricing clarity, and social proof.
Use Competitor for strategic review, then use [Actions: Prompts](/actions/prompts) and [Actions: Content](/actions/content) to decide what to fix.
# Entity
Source: https://docs.frictionai.co/brand-audit/entity
Measure whether AI models understand your brand as a real-world entity before and after live search.
# Entity
Entity measures whether AI models know your brand as a real-world entity. It separates foundation signals, training-data understanding, and live web search uplift.
![Entity understanding visual with foundation, training data, and web search layers feeding an entity score]()
Entity understanding is part of brand health and is available on Growth, Professional, and Enterprise plans.
## The three layers
Structured identity signals such as brand name, domain, schema, and known profile data.
What models appear to know before live browsing or retrieval changes the answer.
How live sources change or improve the brand answer.
## Why it matters
If models do not understand the brand as an entity, prompt and shopping performance can be unstable. Entity gaps often show up as:
* Incorrect or incomplete brand descriptions
* Confusion with similarly named companies
* Weak association with the right category
* High dependence on live search to answer basic brand questions
* Provisional or low-confidence reconciliation
## How to use the page
Start with the headline score and search uplift to see whether live search materially improves the answer.
Check foundation, training data, and web search separately. Each layer points to a different fix.
Provider-specific issues can reveal whether a model knows the brand or relies on retrieval.
Compare historical snapshots to see whether entity understanding is improving after content and structured-data work.
Use the prompt inspector when a layer needs evidence.
## Fix paths
Improve structured brand signals: website schema, consistent names, organization data, social profiles, and canonical domains.
Increase durable public references and clear category association. This may take longer to influence models.
Live search is doing most of the work. That can be good, but it also means source quality and freshness matter heavily.
AI may have found a likely match but not enough evidence to strongly confirm it. Check naming ambiguity and entity source consistency.
# Dashboard Overview
Source: https://docs.frictionai.co/dashboard/overview
Use the friction AI dashboard to read AI Score, prompt performance, shopping coverage, sources, and experiments.
# Dashboard Overview
The dashboard is the command center for a selected brand. It combines brand health, user prompts, shopping prompts, sources, competitor context, and experiment status into one review surface.
![Dashboard overview with AI Score cards, prompt table, sources, and experiments panel]()
## What you see
A summary of overall recommendation strength plus visibility, sentiment, purchase intent, and brand recognition where available.
The highest-signal prompts and search queries from [Prompts](/tracking/prompts).
A compact read on buying questions from [Shopping Prompts](/tracking/shopping).
Domains AI cites most often across tracked prompts and responses.
Where your brand appears alongside or behind competitors in responses.
Experiment summaries appear when available; plan access determines whether you can create tests.
## Use the dashboard as a triage page
Look for broad changes in AI Score and the metric cards before drilling into a single prompt.
Find whether weak movement is coming from custom visibility prompts, shopping prompts, or both.
Source shifts often explain score movement. New citations, missing owned pages, or competitor-heavy sources are action signals.
Move from dashboard cards into [Prompts](/tracking/prompts), [Shopping](/tracking/shopping), [Analysis](/brand-audit/analysis), or [Actions](/actions/prompts).
## Time filters
The dashboard supports multiple review windows, including short-term and longer-term periods. Use short windows for fresh changes and longer windows for strategic trends.
If a score looks unusual, compare the same brand in the 30-day and 90-day windows before changing content strategy.
## When data is still preparing
After onboarding or after adding new prompts, dashboard sections may populate in stages. This is normal: some results appear quickly, while deeper brand, shopping, or competitor views need more data before they are useful.
If a card is empty, first check whether the feature is included in your plan and whether you have configured the related prompts, website, or competitor. Then open the related page for the most detailed view.
## Next pages to open
Inspect prompt-level visibility, model filters, sources, and tags.
Review purchase readiness, AI commerce signals, and recommended websites.
Diagnose brand health across metrics, models, source citations, and prompt evidence.
Turn weak prompts and content issues into a prioritized fix list.
# AI Score
Source: https://docs.frictionai.co/guides/ai-score
Understand friction AI's composite score for AI recommendations and brand discovery.
# AI Score
AI Score summarizes how strongly AI assistants recommend your brand across tracked prompts and model responses. It is not just a mention count. It favors outcomes that indicate preference: appearing in the answer, being described positively, and being recommended in purchase or selection contexts.
## What it combines
Whether your brand appears in the response and how consistently it appears across providers.
Whether the response frames your brand positively, neutrally, or negatively.
Whether the response recommends your brand when a user is comparing, choosing, or buying.
## How to read it
AI recognizes the brand, mentions it in relevant prompts, frames it positively, and recommends it in buyer contexts.
AI may like the brand when it appears, but the brand is absent from too many category or comparison answers.
The brand appears, but the response is cautious, outdated, negative, or positioned behind competitors.
AI may mention the brand, but it does not guide the user toward choosing or buying it.
## Where AI Score appears
The fastest top-level read on whether your AI recommendation position is improving or declining.
The place to inspect metric trends, provider differences, prompt evidence, sources, and exportable data.
A head-to-head view of your AI Score and metric trends against a promoted competitor.
A practical list of prompts dragging down visibility, sentiment, or purchase intent.
## Common patterns
AI knows you, but it does not recommend you as the choice. Improve comparison pages, use-case positioning, reviews, and proof that supports buyer decisions.
When AI mentions you, the framing is strong. The issue is coverage. Expand content, citations, category pages, and prompts around the categories where you should appear.
Different providers use different retrieval and answer patterns. Use provider filters in [Prompts](/tracking/prompts), [Analysis](/brand-audit/analysis), and [Entity](/brand-audit/entity) to find the source of the split.
Adding prompts changes the measurement set. Compare the prompt-level evidence before interpreting the movement as a market-wide gain or loss.
## What to do next
Confirm whether the score movement is broad or isolated to a specific widget.
Use [Analysis](/brand-audit/analysis) to check visibility, sentiment, and purchase intent individually.
Use [Actions: Prompts](/actions/prompts) to see the response text and recommendations for weak prompts.
Use [Actions: Content](/actions/content) for website readiness gaps and [Prompts](/tracking/prompts) for query coverage gaps.
AI outputs can vary. Focus on trends, repeated evidence, and provider patterns rather than one isolated answer.
# First Week Checklist
Source: https://docs.frictionai.co/guides/first-week
A practical checklist for getting useful AI visibility data during the first week.
# First Week Checklist
Use the first week to make the dataset useful. You do not need hundreds of prompts. You need the right categories, competitors, and review habits.
## Day 1: finish setup
Check brand name, website, logo, and competitors in [Brand Profile](/workspace/brand).
Open [Prompts](/tracking/prompts) and remove anything that is too vague, duplicated, or outside your market.
Cover discovery, comparison, brand, and high-intent questions. Keep them close to real buyer language.
If customers buy products online, set up [Shopping Prompts](/tracking/shopping) early so purchase intent has time to build history.
## Day 2 to 3: read the first results
Start with [Dashboard](/dashboard/overview), then inspect the pages behind any weak cards.
Find prompts where the brand is not mentioned or is mentioned below competitors.
Inspect the responses and sources that shape the sentiment score.
Check whether AI gives direct recommendations, vague mentions, or competitor-led answers.
Verify whether AI understands the brand before relying on live web search.
## Day 4 to 5: prioritize actions
Use Actions after enough analysis has completed.
Sort underperforming prompts by metric, source, and provider. Open the detail drawer for response evidence.
Run or review the content readiness audit to find pages with clarity, freshness, or entity-signal gaps.
Start with fixes that affect multiple prompts or high-intent shopping questions.
## Day 6 to 7: create a review habit
Create a short recurring review:
* Check the dashboard once a week
* Add new prompts when customers, sales calls, or campaigns reveal new questions
* Watch source changes after content updates
* Use the competitor page after major category or messaging changes
* Run experiments only when you have a clear hypothesis and enough prompt coverage
Do not optimize every weak prompt one by one. Prioritize sources, pages, and positioning issues that explain several weak answers at once.
# Getting Started
Source: https://docs.frictionai.co/guides/onboarding
Complete onboarding and create the first brand measurement graph in friction AI.
# Getting Started
Onboarding turns a brand website into the first measurement graph: brand profile, market context, competitor context, prompt coverage, and optional shopping coverage.
![Six onboarding steps from brand discovery through dashboard readiness]()
## Before you start
Have these ready:
* Your primary brand name and website domain
* The industry or category you want to be measured in
* One or more competitors to benchmark against
* A few prompts customers might ask AI before choosing a vendor or product
* Product or shopping pages, if you want to track purchase intent
## Brand onboarding flow
Enter the brand name and website. friction AI enriches the profile with logo, domain, description, and basic entity signals.
Confirm the suggested industry or select a better fit. Industry controls the category and prompt suggestions shown later.
Pick focused subcategories that represent where the brand should appear. Start narrow if you are unsure.
Add competitors for benchmarking. Growth and higher tiers can promote one competitor into the head-to-head deep-dive.
Add or accept suggested prompts for discovery, comparison, category, and brand-awareness questions.
Add optional buying prompts if purchase intent matters for your brand or products.
## What happens after completion
After onboarding, friction AI begins analyzing your brand context and selected prompts. Dashboard sections may populate in stages as results become available.
The first place to check after onboarding. It shows summary scores, prompt performance, top sources, shopping prompts, and experiments.
Review the prompts you added during onboarding and add more specific tracking coverage.
Use the brand health view when Growth or higher access is enabled.
After analysis completes, use blindspots to find prompts that need action.
## Choosing good competitors
Use competitors that make the benchmark meaningful:
* **Direct competitors**: brands customers already compare with you
* **Search competitors**: brands or publishers AI often cites in your category
* **Aspirational competitors**: category leaders you want to catch
Do not add unrelated market leaders just because they are large. The competitor view is most useful when the comparison reflects a realistic buying or discovery decision.
## Choosing good prompts
Good prompts are specific enough to reflect a customer moment, but broad enough that AI can answer naturally.
```text theme={null}
What are the best AI visibility platforms for agencies?
Which tools help marketing teams track ChatGPT recommendations?
```
```text theme={null}
friction AI vs Profound for AI visibility tracking
Best alternatives to Otterly AI for AEO teams
```
```text theme={null}
What is friction AI?
Is friction AI good for tracking AI recommendations?
```
```text theme={null}
Where can I buy [product]?
Best [product category] for [use case]
```
## Individual onboarding
The individual product has a separate onboarding path for AI identity tracking. It asks for profile details, categories, channels, markets, and optional competitors.
Use this flow when the product is monitoring a person rather than a company or product brand.
## Troubleshooting setup
Initial results can appear in stages. Check again shortly, or open the related page for the most detailed view.
Use the brand selector in the sidebar. If the brand profile itself is wrong, go to [Brand Profile](/workspace/brand).
Some pages depend on plan access or setup. See [Subscription](/workspace/subscription) for plan details.
# friction AI Docs
Source: https://docs.frictionai.co/index
Product documentation for tracking AI visibility, recommendations, shopping intent, brand health, and AI identity.
# Track what AI recommends, then improve it
friction AI shows how your brand appears across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. Use these docs to set up tracking, interpret your scores, find blindspots, and turn AI responses into concrete actions.
![friction AI product console showing AI Score, prompts, shopping, brand audit, and actions]()
## Start with the product map
The app is organized around five workflows.
Add your brand, website, industry, competitors, and first tracking prompts during onboarding.
Review AI Score, prompt performance, shopping prompts, cited sources, and experiment status from one view.
Add custom LLM prompts and search queries that represent the moments where customers discover or compare you.
See whether AI recommends your products, where it sends buyers, and which competitors capture purchase intent.
Diagnose visibility, sentiment, purchase intent, model performance, source citations, and prompt-level evidence.
Find underperforming prompts and content pages, then prioritize the fixes most likely to move scores.
## What friction AI measures
A composite score for how strongly AI assistants recommend your brand. It is driven by visibility, sentiment, and purchase intent. Start with [AI Score](/guides/ai-score).
Whether your brand appears in AI answers for the prompts and search queries that matter to your market.
Whether AI describes your brand positively, neutrally, or negatively when it mentions you.
Whether AI recommends your brand or product in high-intent buying and comparison contexts.
Whether models recognize your brand as a real-world entity from structured signals, training data, and live web search.
Whether your website gives AI systems enough clear, recent, entity-rich content to understand and cite you.
## Recommended path
Create the first brand profile and let friction AI run the initial analysis. See [Getting started](/guides/onboarding).
Use [Dashboard overview](/dashboard/overview) to understand what changed and where to investigate.
Use [Prompts](/tracking/prompts) for specific discovery, comparison, and recommendation questions.
Use [Analysis](/brand-audit/analysis), [Entity](/brand-audit/entity), and [Competitor](/brand-audit/competitor) to diagnose why scores move.
Use [Actions: Prompts](/actions/prompts) and [Actions: Content](/actions/content) to convert evidence into work.
New users should follow the [first week checklist](/guides/first-week). It focuses on the few setup and review habits that make the product useful quickly.
## Plans and access
Feature access depends on your subscription tier.
Prompt tracking and basic AI visibility monitoring for one brand.
Brand health, shopping prompts, entity understanding, and competitor deep-dive access.
A/B testing, expanded provider access, and larger limits for active teams.
For current plan details, open [Pricing](https://www.frictionai.co/pricing) or review [Subscription](/workspace/subscription) in the app.
# Individual AI Identity
Source: https://docs.frictionai.co/individuals/ai-identity
Use friction AI for individuals to monitor recognition, visibility, sentiment, sources, and competitors.
# Individual AI Identity
Individual AI Identity is for people rather than brand accounts. It tracks whether AI systems recognize, recommend, and describe a person accurately.
![Individual AI identity dashboard showing recognition, visibility, sentiment, category rankings, sources, and competitors]()
## What it measures
Whether AI knows who the person is, what they do, and which achievements or roles matter.
Whether the person appears in relevant category queries and recommendation contexts.
How AI frames the person, including tone, associations, and narrative quality.
## Individual onboarding
Add the person and core profile details.
Select categories where the person should be visible or recommended.
Add channels or public profiles that help AI understand the person.
Add markets or geographic context where visibility matters.
Optionally add people to compare against. You can skip and add them later.
## Dashboard sections
The top-level identity summary and score view.
Where the person appears or does not appear for selected categories.
Recognition, visibility, and sentiment details with provider context.
Topics, achievements, sources, and signals AI used to construct the answer.
A comparison view when competitors were added during onboarding.
## When to use it
Individual AI Identity is useful for:
* Founders, executives, creators, public figures, and experts
* PR and communications teams
* Talent managers and speaker bureaus
* Personal branding teams
* Political, reputation, or visibility advisory teams
For companies and products, use the brand workspace docs starting with [Getting Started](/guides/onboarding). For people, use this individual workflow.
# A/B Testing
Source: https://docs.frictionai.co/tracking/experiments
Create experiments that test whether prompt or content changes improve AI visibility.
# A/B Testing
A/B Testing lets you test a clear hypothesis against control and variant prompt buckets. Use it when you want to know whether a messaging, content, or positioning change affects AI visibility.
![Experiment lifecycle from draft to prompt buckets, scheduled run, completed result, and decision modal]()
A/B Testing is available on Professional and Enterprise plans.
## When to run an experiment
Run an experiment when all of these are true:
* You have a clear hypothesis
* The prompts reflect one intent area
* Control and variant prompts are comparable
* You can wait for the run to complete and measure the result
* You are willing to record a decision after the run
## Create an experiment
Go to Tracking -> A/B Testing and select **New Experiment**.
Use a name that captures the content or positioning change.
Example: "Use-case-focused prompts will improve visibility versus feature-focused prompts."
Choose one available provider/model for the experiment.
Add prompts to control and variant buckets. The app enforces minimum prompt requirements before a started run.
Save a draft while building. Start when the buckets are ready.
## Experiment status
The experiment exists but has not been scheduled. You can edit details and prompt assignments.
The experiment is waiting to run.
The selected AI model is processing the prompt buckets and collecting results.
Results are ready for review. Use the decision modal to record whether to ship, iterate, or archive.
The run did not complete. Review the error and create or retry the experiment depending on the failure.
## Good experiment design
Test one change at a time. Mixing product copy, pricing, and page structure makes results hard to explain.
Control and variant prompts should have the same intent and difficulty.
Use enough prompts to reduce noise, but keep the experiment focused.
Record a decision after completion so the experiment history remains useful.
Experiments measure AI response behavior for the configured prompts and model. They do not prove that every AI assistant will change in the same way.
# Prompts
Source: https://docs.frictionai.co/tracking/prompts
Create and analyze custom prompts and search queries for AI visibility tracking.
# Prompts
Prompts is where you track the specific questions and searches that should surface your brand. Use it for category discovery, competitor comparison, branded questions, and search queries.
![Prompts table with filters, visibility scores, sources, and tags]()
## What this page answers
Visibility score shows whether your brand appears in responses for the tracked prompt.
Brand mention stacks show competitors and other brands that appear in the same answer.
Source panels show the domains AI cites when forming an answer.
Provider filters let you compare OpenAI, Claude, Gemini, Perplexity, and Google AI Overviews where your plan allows.
## Prompt types
Natural-language questions sent to AI assistants.
```text theme={null}
What are the best AI visibility platforms for AEO teams?
How does friction AI compare to Profound?
```
Search-style queries used to evaluate AI search and retrieval surfaces.
```text theme={null}
best AI visibility platform
friction AI alternatives
```
## Add prompts
Go to Tracking -> Prompts in the sidebar, then select **Add Prompts**.
Paste your own prompts or use friction AI suggestions based on the selected brand and category.
Use tags like `comparison`, `brand`, `category`, `product`, or `campaign` so filtering remains manageable.
Analysis starts automatically. Results populate the table as they become available.
## Filters
Filter the table by prompt text or tags.
Switch between all prompts, prompts where your brand appears, and prompts where your brand is missing.
Review 7-day, 30-day, 90-day, 180-day, or 1-year windows depending on available data.
Filter to specific providers when the plan includes those providers for prompt tracking.
Use tags to group prompts by campaign, funnel stage, product line, or market segment.
## How to interpret a weak prompt
Click a prompt row to inspect provider responses, aggregate scores, source citations, and brand mentions.
Check whether the problem repeats across providers or appears only in one model.
If AI cites competitor or third-party pages, decide whether your owned pages answer the same intent clearly enough.
Use [Actions: Prompts](/actions/prompts) to review underperforming prompts with recommendations.
## Prompt writing guidance
Good prompts match real discovery language.
Write prompts the way a prospect would ask before choosing a tool, brand, product, or service.
Include direct comparisons and alternative searches where competitors are likely to appear.
Avoid changing prompt text constantly. Stable prompts create cleaner trend history.
Intent tags make it easier to separate awareness, comparison, shopping, and retention prompts.
Start with 10 to 20 high-quality prompts before adding more. A small, representative set is easier to interpret than a large noisy one.
# Shopping Prompts
Source: https://docs.frictionai.co/tracking/shopping
Track purchase intent, product recommendations, shopping websites, and AI commerce signals.
# Shopping Prompts
Shopping Prompts tracks how AI responds when the user is close to buying. It measures whether AI recommends your brand or product, how confidently it recommends it, and where it sends the buyer.
![Shopping prompt dashboard showing commerce score, purchase readiness, AI commerce signals, and top websites]()
Shopping prompt tracking is available on Growth, Professional, and Enterprise plans.
## What this page measures
A combined view of shopping-context performance across visibility, readiness, and recommendation signals.
Whether the answer is close to driving a purchase or still vague and informational.
The strength of recommendation language such as best choice, top pick, recommended, or where to buy.
The domains and platforms AI recommends for purchase, including your site, marketplaces, and competitors.
## Prompt examples
```text theme={null}
Where can I buy [product]?
Best place to purchase [product category]
```
```text theme={null}
Should I buy [brand] or [competitor] for [use case]?
Best [product category] for [customer type]
```
```text theme={null}
Is [product] worth buying?
[brand] reviews before buying
```
```text theme={null}
Best [product category] under [price]
Affordable [product category] options
```
## Add shopping prompts
Go to Tracking -> Shopping in the sidebar.
Add buying, comparison, and where-to-buy prompts.
Product URLs help connect prompts to the pages AI should understand or cite.
Use tags like `where-to-buy`, `comparison`, `reviews`, `price`, or product line names.
## Reading results
Your brand appears in buying answers, receives stronger recommendation language, and is associated with useful purchase surfaces.
AI may mention your brand, but the answer does not confidently guide the user toward a purchase.
Competitors are capturing the purchase context. Inspect their cited pages and compare the answer quality to your own product pages.
AI may recommend marketplaces or competitor sites instead of your owned product pages. Check product page clarity, schema, pricing, reviews, and availability signals.
## What to fix first
Make product names, use cases, prices, availability, comparisons, reviews, and FAQs obvious.
Reviews, credible lists, and product pages on trusted platforms often influence shopping answers.
If competitors are repeatedly recommended, inspect what evidence AI cites for them.
Use the same prompt set to measure whether readiness and recommendation signals improve.
# Brand Profile
Source: https://docs.frictionai.co/workspace/brand
Manage the selected brand, website, competitors, and brand-level context used throughout friction AI.
# Brand Profile
Brand Profile controls the context friction AI uses when analyzing your AI visibility. Keep it accurate before interpreting scores.
## What to manage
Brand name, domain, logo, and website identity.
The domain used for content readiness audits, source matching, and entity context.
The brands used for benchmarking, prompt context, and head-to-head analysis.
The promoted competitor used by [Competitor](/brand-audit/competitor) when plan access allows it.
## Competitor strategy
Choose competitors that make AI comparison meaningful.
Use tracked competitors for broad context and benchmarking. They should represent real alternatives in your category.
Promote the competitor you most need to beat or explain. The deep-dive comparison is more detailed and available by plan.
## When to update the brand profile
Update the brand profile when:
* The brand changes domain, name, or positioning
* A competitor becomes more relevant
* A competitor is no longer a useful benchmark
* You are entering a new subcategory or market
* Content readiness audits report no website or incorrect pages
Changing brand context can affect future analysis. Keep notes on major changes so score movement is easier to interpret later.
## Related pages
Initial brand setup and onboarding flow.
Head-to-head analysis against the promoted competitor.
Website audit results tied to the configured brand domain.
Plan access for competitors, brand health, shopping, and experiments.
# Subscription
Source: https://docs.frictionai.co/workspace/subscription
Understand plan access, trials, billing status, and upgrade paths.
# Subscription
Subscription shows the current plan, billing status, trial details, feature access, and upgrade or plan-change options.
## Feature access
Feature availability depends on plan and provider access.
Available across paid brand plans, with prompt and provider limits based on tier.
Growth and higher tiers unlock Analysis, Entity, and Competitor deep-dive workflows.
Growth and higher tiers unlock shopping prompt tracking and commerce metrics.
Professional and Enterprise tiers unlock active experiments.
## Billing status
The app shows remaining trial days and the trial end date when available.
The plan is active and feature access follows the current tier.
The app may show payment warnings and ask you to update the payment method.
Access can change after cancellation or trial expiry. Use Subscription to choose a plan or restart billing where available.
If a downgrade or plan change is scheduled, the effective date appears on the subscription page.
## Unavailable features
Unavailable sidebar items take you to Subscription. Use the plan comparison to confirm which tier includes the feature.
Shopping prompts require Growth or higher access.
Brand health views require Growth or higher access.
Experiments require Professional or Enterprise access.
For public pricing and current plan details, open [Pricing](https://www.frictionai.co/pricing).