AI search optimization for agencies

Turn AI visibility gaps into work your agency can deliver.

Find where AI answers leave out your clients or get their facts wrong. Prepare content and structured-data fixes, review and publish them, then measure what changes in subsequent tests.

Multi-client workspace·Reviewed drafts·Follow-up testing

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ChatGPTClaudeGeminiPerplexity
ChatGPTClaudeGeminiPerplexity
ChatGPTClaudeGeminiPerplexity

The matter

Deliver more than a visibility report.

Junctra helps SEO and content agencies test buyer questions, inspect missing mentions and inaccurate answers, and prepare content and structured-data fixes. Manage multiple client brands, work with your team, and share read-only client reports. Your team reviews and publishes each change, then uses follow-up tests to measure subsequent results.

Prioritize brands across your client roster, prepare drafts for review, and share published work alongside follow-up results.

Demo data · Illustrative
  • Mentioned72%
  • Recommended46%
  • Cited31%
  • Described correctly64%
Illustrative reading · four measures, never averaged

The method

From a missing mention to a published fix.

Find the gap. Deliver the fix. Measure the change.

  1. I

    Establish the baseline

    Review the client’s profile and buyer questions. Test configured AI systems and see mentions, recommendations, citations and answer accuracy separately.

  2. II

    Choose a gap to address

    Inspect missing mentions, competitor appearances and facts that conflict with the client’s own information. Use the evidence to decide what to change.

  3. III

    Prepare and publish the fix

    Draft homepage copy, FAQs, comparison content, fact corrections or structured data. Review the output and publish through your usual process.

  4. IV

    Measure the follow-up

    Mark the fix as published and run another test. Compare subsequent answers, with AI referral visits and conversions where tracking is installed.

Inside Junctra

The product, not only the pitch.

An illustrative view of the workspace: separate measures, observed changes and an opportunity to investigate.

Demo data · Illustrative

Overview

AI visibility for Retivo

184 buyer questions · last run today, 06:12

Mention rate
18%+4 pts

Are you named?

Recommendation rate
9%+3 pts

Are you recommended?

Description accuracy
58%-6 pts

Is it correct?

Citation rate
21%+5 pts

Is your site cited?

Twelve weeks · Jul 7 to Sep 22 · each measure on its own line

Jul 7Sep 22
  • Mention rate
  • Recommendation rate
  • Description accuracy
  • Citation rate

A fact worth checking

The client’s own pages give conflicting prices.

  • Homepage · €99 / month
  • Pricing page · €149 / month
Illustrative · sample data for a fictional retailer

i.

Measure

  • Overview
  • Visibility report
  • Search simulator
  • Prompts

ii.

Diagnose

  • Competitors
  • Sources
  • Knowledge graph

iii.

Fix

  • Content fixer
  • Action center

iv.

Monitor

  • Brand monitor
  • Alerts
  • Agent readiness

v.

Prove

  • Demand

The loop

Inspect the evidence. Prepare a fix. Test again.

An illustrative optimization cycle. Your team reviews and publishes the change before measuring subsequent answers.

What AI says today

Asked

“What is the best loyalty platform for a mid-market retailer?”

Answered

Popular options include Yotpo, Smile.io, LoyaltyLion and Antavo, each with strong Shopify support and public pricing.

RetivoNot mentioned

Evidence to investigate

  • Pricing is not stated plainly
  • The product is described inconsistently
  • The Shopify integration is poorly documented
  • No comparison content exists
  • AI cites your rivals’ pages, not yours

Drafts for your team to review

  • Homepage copy
  • Pricing FAQ
  • Comparison page
  • Schema markup
Ask again

Asked

“What is the best loyalty platform for a mid-market retailer?”

Answered

Options include Yotpo, Smile.io and Retivo, a loyalty platform for retail brands with public pricing from €99 a month [1].

RetivoRecommendedCited

Illustrative workflow — not a customer result. Follow-up results may improve, stay unchanged or decline. A before-and-after difference does not prove causation.

In practice

What your clients may be told.

Example observations to investigate before choosing a change. A cited source does not prove why a model selected a brand.

Asked

“Best CRM for a growing software firm”

The answer

Three competitors are named before you. When you appear, the price is wrong.

Found by · Search Simulator

Asked

“Does the product work with Shopify?”

The answer

The answer is no. The client’s own documentation says the integration is supported.

Found by · Visibility Audit

Asked

“Is it worth the cost?”

The answer

AI quotes a price you changed a year ago. Your site says otherwise.

Found by · Knowledge Graph

Give your next client audit a next step.

Start with one client, review the evidence, and prepare the work your team can deliver.