01Active
Platforms buyers and AI systems actually use
Signal quality over platform familiarity
Technology
A performance stack built for SEO, GEO, AI visibility, and paid search.
We work in the platforms buyers actually use, connect the data honestly, and layer AI where it saves time without replacing judgment.
PerspectiveTools only matter when they help you
Tools only matter when they help you
see the truth faster.
Silverback runs a deliberate stack across search intelligence, AI discovery, paid media, analytics, web performance, and automation. We choose tools for signal quality, not novelty, then apply senior strategy to turn those signals into action.
Search intelligenceAI discoveryPaid mediaAnalyticsWeb performanceAutomation
The tool is never the strategy. The signal it produces is what matters.
Any platform that gives us better signal faster earns a place in the stack. Any one that adds noise without clarity gets cut.
How we think about the stack
02Always
Manual review before automation takes over
Humans verify before systems scale
03Required
Tracking that ties spend to pipeline, not vanity metrics
Revenue attribution over impression counts
04By design
Custom AI workflows for analysis, not autopilot strategy
AI augments judgment, never replaces it
05Every month
Reporting leadership can act on in one read
Clarity over completeness every time
06Goal
Systems that improve quarter over quarter
Compounding performance, not one-off wins
The stack is a means, not a differentiator. What separates good work from average work is not the tools used. It is whether the people using them can tell the difference between signal and noise, and make the right call faster because of it.
See our approachSearch intelligence
SEO and GEO tools for technical depth and topic clarity.
Organic visibility still starts with crawl health, indexation, internal structure, and content that answers real buyer questions. We pair classic SEO tooling with AI-assisted research so traditional rankings and generative discovery improve together.
SEO/GEO AuditLive scorecard
0A
SEO0
GEO0
Technical SEO0
Topic coverage0
GEO readiness0
Schema & entities0
SEO and GEO analysis acrosssearch, crawl, and AI signals
1
Technical crawls, log review, and indexation diagnostics
Find what search engines cannot reach, what is being crawled unnecessarily, and what should be indexed but is not.
Screaming FrogGSCLog analysis
Active2
Keyword, topic, and competitive gap analysis
Map the full keyword universe, identify topic clusters, surface gaps competitors own, and prioritize by intent and conversion potential.
SEMRushGSCBigQuery
Ongoing3
GEO and answerability reviews for AI-readable content
Audit content structure, definition clarity, and citation potential across ChatGPT, Gemini, Perplexity, and AI Overviews to improve how AI systems cite the brand.
ClaudeChatGPTPerplexity
Per audit4
Schema, entity, and structured data validation
Implement and validate Organization, Article, FAQ, BreadcrumbList, and Product schema so AI systems and search engines can accurately interpret every key page.
Schema MarkupRich ResultsGSC
Per buildTraditional SEO and AI visibility are not separate programs. The same crawl health, content clarity, and structured data that improves Google rankings also makes a brand easier for AI systems to cite. We run them together, not in parallel tracks.
See the full stackAI discovery
Platforms we monitor for AI visibility and citation quality.
AI answers are now part of the buyer journey. We test how major LLM and AI search surfaces describe, cite, compare, and name your brand, then connect those findings to content, schema, and authority work on your site.
Monitoring active across 9 platforms
AI visibility testing acrossmajor discovery platforms
1
Prompt testing across ChatGPT, Claude, Gemini, Perplexity, and Grok
We run structured prompts that buyers actually use and document how each platform describes, positions, and compares your brand against alternatives.
ChatGPTClaudeGeminiPerplexity
Per audit2
Google AI Overviews and Bing Copilot monitoring
Track when and how your brand appears in AI-generated search summaries, which queries trigger citations, and how coverage shifts after content and schema updates.
AI OverviewsBing CopilotSearch Console
Weekly3
Competitive AI visibility benchmarking
Compare how AI platforms describe your brand versus named competitors across the same queries. Find where you are absent, underrepresented, or accurately described and act on the gaps.
All platformsCompetitor setBenchmark report
Quarterly4
Custom GEO reports and AI readiness reviews
Structured audit documents covering citation gaps, entity clarity issues, schema coverage, content answerability scores, and a prioritized fix list tied directly to the platforms showing the weakest coverage.
GEO auditSchema reviewFix roadmap
Per engagementAI citations are not random. They follow patterns: brands with clearer entity definitions, better structured data, and more corroborated claims get cited more consistently. We audit the gaps and close them.
See AI visibility servicesPerformance media
Paid search and media platforms for efficient, measurable demand.
Paid media should create and capture demand with clean tracking behind it. We manage Google Ads, Microsoft Ads, LinkedIn, Meta, and retargeting programs with conversion paths, audience logic, and reporting tied to qualified pipeline.
Campaigns active
5+Platforms managedActive
CRMFeedback loopsIntegrated
SQLReporting metricNot MQL
Paid media execution acrosssearch, social, and retargeting
1
Google Ads and Microsoft Ads search and Performance Max
Full-funnel search programs with smart bidding strategies, negative keyword management, asset group structure, and conversion-based budget pacing.
Google AdsMicrosoft AdsPerf Max
Always on2
LinkedIn and Meta campaigns for B2B and DTC demand
ICP-matched LinkedIn targeting with Lead Gen Forms, matched audiences, and Insight Tag. Meta campaigns built around intent signals, lookalikes, and CRM retargeting pools.
LinkedIn AdsMeta AdsLead Gen Forms
Active3
Retargeting, Customer Match, and audience orchestration
Layered retargeting across site visitors, CRM segments, and video viewers. Customer Match and RLSA strategies that keep high-intent buyers engaged through longer sales cycles.
Customer MatchRLSAAudience lists
Running4
Enhanced conversions and offline conversion import where available
First-party conversion signals, enhanced conversion setup with hashed data, offline import from CRM and sales pipeline so bidding algorithms optimize against actual revenue outcomes.
Enhanced conv.Offline importCRM integration
PriorityPaid media without clean conversion data is just spending money in the dark. Every program we run starts with the tracking architecture, then the campaigns. Bidding strategies are only as good as the signals you feed them.
See paid media servicesMeasurement
Analytics, tracking, and CRM tools for honest performance readouts.
If the data is wrong, every optimization decision is wrong. We build GA4, GTM, BigQuery, HubSpot, and Salesforce setups that help teams see source quality, funnel movement, and cost per qualified opportunity, not just sessions and clicks.
Conversion path coverage
Impressions
100%
Clicks
62%
Key events
38%
SQLs
14%
Measurement and CRM feedback acrossthe full conversion path
1
GA4, GTM, and event architecture for forms and key actions
Custom event taxonomy, dataLayer implementation, form tracking, scroll depth, file downloads, video engagement, and click events mapped to the actions that predict revenue.
GA4GTMdataLayerEvents
Foundation2
HubSpot and Salesforce source, lifecycle, and SQL tracking
Original source preservation, lifecycle stage automation, lead scoring alignment, and SQL definition mapping so marketing and sales agree on what a qualified opportunity actually looks like.
HubSpotSalesforceLifecycle stages
Always on3
BigQuery pipelines for blended search, paid, and CRM reporting
Raw event exports from GA4 into BigQuery, joined with CRM deal data and ad spend, producing blended dashboards that show true cost per SQL and channel contribution to closed revenue.
BigQueryLooker StudioSQL pipelines
Advanced4
Page speed and Core Web Vitals monitoring on priority templates
Ongoing CWV monitoring on homepage, product, landing, and blog templates. PSI benchmarks tracked per deploy so performance regressions are caught before they affect rankings or conversion rate.
PageSpeedCWVGSCLighthouse
MonitoredGood reporting is not a dashboard full of numbers. It is a clear answer to three questions: where did qualified leads come from, what did they cost, and what should we do differently next month. That is what we build every reporting setup around.
See analytics servicesWeb and experience
Development and experience tools for fast, conversion-ready sites.
Landing pages, service sites, and conversion paths need to load quickly, track cleanly, and give both humans and machines a clear read on what you do. We build on modern stacks with performance and measurement built in from day one, not bolted on after launch.
98PerformanceLighthouse score
<2sLCP targetLargest content
EdgeDeploymentGlobal CDN
A+Perf gradeCore Web Vitals
Web development on a modernperformance-first stack
1
Next.js, React, WordPress, and Vercel deployments
Modern JAMstack builds and headless WordPress setups optimized for Core Web Vitals, SEO, and structured data from the first deploy. CI/CD pipelines with preview environments and rollback support.
Next.jsReactWordPressVercel
Primary stack2
Cloudflare Workers and edge tooling for speed and security
Edge caching, Workers for dynamic routing and redirects, DDoS protection, bot management, and performance rules that keep pages fast and servers protected without sacrificing crawlability.
CloudflareWorkersEdge cache
Always on3
Conversion-focused landing page and CRO implementation
High-converting landing pages with A/B test infrastructure, heatmap integration, form optimization, mobile UX review, and conversion path analysis tied back to campaign-level CPA targets.
CRO testingHeatmapsForm optimization
Ongoing4
Analytics, schema, and tracking wired in before launch
GA4, GTM, structured data, canonical tags, XML sitemaps, and consent management implemented and validated on staging before any page goes live. No retrofitting, no missed events.
GA4GTMSchemaConsent mgmt
Pre-launchA site that is slow, untracked, or unreadable by machines is not a growth asset. Everything we build is designed to perform for humans, rank for search engines, and get cited by AI systems from the moment it goes live.
See web servicesAI engineering
AI tooling for analysis, automation, and repeatable marketing workflows.
We use AI where it removes repetitive work and sharpens analysis. Custom agents, workflow automations, and reporting scripts help us move faster without handing strategy to a black box. Humans stay in the loop on every decision that matters.
$ run geo-audit --site example.com --output report.json
Scanning 9 AI platforms for brand citations...
Found 3 citations across ChatGPT, Perplexity, Gemini
Running schema validation...
Schema coverage: 68% - 4 gaps identified
Generating fix roadmap...
$
AI engineering for analysis,Automation and reporting
1
Custom SEO, GEO, and paid media analysis agents
Purpose-built agents that pull data from GSC, Semrush, ad platforms, and AI citation tests, then synthesize findings into prioritized recommendations without manual aggregation or copy-paste reporting.
Claude APIChatGPTPythonCustom agents
In production2
Workflow automations for reporting and QA
Automated data pulls, report generation, anomaly flagging, and QA checks that run on schedule. Frees strategists from assembly work so they spend time on analysis and decisions, not spreadsheet management.
n8nZapierMakeGoogle Apps Script
Always running3
Cursor, Claude Code, Codex, and Copilot for internal velocity
AI-assisted development for internal tooling, reporting scripts, data pipelines, and site implementations. Senior developers stay in control of architecture and review, but ship significantly faster with AI pair programming.
CursorClaude CodeGitHub Copilot
Daily use4
Cloudflare Workers AI for lightweight production workflows
Edge-deployed AI functions for classification, content routing, real-time personalization signals, and lightweight inference tasks that run at the CDN layer without adding latency or server load.
Workers AICloudflareEdge inference
ProductionAI does not replace the strategist. It removes the work that keeps strategists from doing strategy. Every agent we build has a human review step for anything that affects a client or goes out the door. Speed is the goal. Accuracy is the constraint.
See AI servicesOperating principles
What separates a useful stack from an expensive dashboard collection.
Tools are only as good as the discipline behind them. These four principles govern how we select, configure, and use every platform in the stack so the technology serves the work instead of the other way around.
Principle 01
We connect search, paid, web, and CRM data so performance conversations start with facts, not channel silos.
Disconnected data produces disconnected strategy. Every platform we run feeds into a unified view so attribution questions have real answers and budget decisions are grounded in actual pipeline contribution.
Connected dataPrinciple 02
We test AI visibility manually across major LLM platforms, then validate findings with crawl data, schema review, and content structure.
AI citation patterns change weekly. Manual testing across ChatGPT, Gemini, Perplexity, and Claude is the only way to know what is actually happening to a brand in AI-generated answers right now.
Manual validationPrinciple 03
We automate repetitive analysis with custom agents and workflows so senior time goes to prioritization, messaging, and client decisions.
Senior strategist hours are the scarcest resource in the program. Anything that can be systematized without losing quality gets systematized so the people who matter most are focused on what only they can do.
Automation layerPrinciple 04
We report what changed, why it matters, and what to do next. The stack exists to make that answer clearer, not louder.
A report full of metrics is not a report. It is a data dump. Every reporting output we produce answers three questions: what changed, what caused it, and what the team should prioritize in the next period as a result.
Clear reportingThe bottom line on the stack
Every tool we add has to earn its seat. It has to produce a signal we cannot get another way, integrate cleanly with what is already running, and make the work more accurate — not just more automated. That is the bar. Most tools do not clear it.
Talk about your stackNo sales pitch. Just a direct conversation.
Operating rhythm
How the stack supports the work.
The stack is not a feature list. It is an operating system for the program. These six steps repeat every engagement cycle, powered by the right tools at each stage so nothing gets missed and nothing gets invented on the fly.
WeeklyMonthlyQuarterly
01
Step 01
Audit with the right sources
GSC, Semrush, GA4, AI citation tests, and log files pulled together before any recommendation is made.
Quarterly02
Step 02
Connect tracking and CRM feedback
GA4 events, GTM triggers, HubSpot and Salesforce source data verified so attribution is accurate before the cycle starts.
Monthly check03
Step 03
Run manual and automated analysis
Agents handle data aggregation and anomaly detection. Senior strategists handle interpretation and recommendations.
Weekly + monthly04
Step 04
Prioritize by business impact
Impact vs effort scoring against revenue and pipeline goals, not channel metrics. Work is ordered by what moves the outcome fastest.
Monthly05
Step 05
Execute across search, paid, and web
Campaigns, content, schema, CRO, and automation deployed across the channel mix with QA checkpoints at each stage.
Ongoing06
Step 06
Report, retest, and refine
What changed, why, and what to do next. AI visibility retested. Rankings checked. Pipeline attribution reviewed. Cycle repeats.
Monthly + quarterlyThis is not a one-time engagement model. The six steps repeat every cycle because markets change, algorithms update, and what worked last quarter may not be what moves the needle this quarter. The stack is built to keep the loop running cleanly.
See how we workWhere to start
See the stack in action on our core services.
Most teams come to us for search, AI visibility, paid media, or measurement first. These service pages show how the same stack supports real client work — the tools, the process, and what we actually deliver.
Most common first conversations
- Teams who need better search rankings and AI citation
- Teams who need cleaner paid media and CRM attribution
- Teams who need reporting leadership can actually act on
- Teams who need to show up in AI-generated answers
Popular starting points
SearchSEO and GEORankings, AI citations, crawl health, and content answerabilityAIAI VisibilityCitation audits, schema, entity clarity, and platform monitoringPaidGoogle Ads ManagementSearch, Performance Max, bidding strategy, and conversion trackingPaidMicrosoft Ads ManagementBing search, LinkedIn audience import, and cross-platform attributionDataAnalytics and TrackingGA4, GTM, BigQuery, HubSpot, and pipeline-tied reportingAI EngineeringAI AutomationCustom agents, workflow automation, and reporting scripts
Not sure which service fits your situation? Most programs start with an audit that clarifies which part of the stack is most undersupported. Start there and the rest becomes obvious.
Start with an auditAbout Silverback
Keep exploring the company.
Every page here answers a specific question about how we work and what we stand for. Find the section that matches what you are trying to figure out.
Company
About Silverback Marketing
Who we are, how we are structured, what kinds of teams we work with, and why the approach is built around outcomes rather than service packages.
Explore
How we work
Our Process
The five-phase framework that runs every engagement, from the first audit through ongoing execution, reporting, and quarterly replanning.
Explore
Culture
Company Values
The principles that govern how decisions get made, how we communicate with clients, and what we will not compromise on when the work gets hard or the easy answer is wrong.
Explore
Join us
Careers
We hire strategists and builders who want to do the work, not manage the people doing it. Open roles, what we look for, and what it is actually like to work here day to day.
Explore
Every page on the site is built to be useful before you contact anyone. Read what you need, explore what fits your situation, and reach out when you are ready to talk about a specific problem or program.
FAQ
Frequently Asked Questions
Trusted answers covering SEO, AI visibility, paid media, measurement, web development, CRO, and marketing automation.
Built for AI engines
and the full performance stack.
Every answer opens with a direct definition, then expands with linked vendor sources and the structure AI systems prefer when citing technical content. Built around the six stack layers Silverback actually runs in client work.
Answer-first format
What is the Silverback Marketing tool stack?
The Silverback Marketing tool stack is a six-layer system of search, AI, paid media, analytics, web, and automation platforms that work together to produce honest performance signal across roughly forty connected tools. Each layer feeds one diagnostic view senior strategists use before recommending a fix.
Layer 01
Signal over novelty
Tools earn a seat when they produce signal the team cannot get another way. Platforms that add noise without clarity get cut, regardless of brand recognition.
Layer 02
Connected data
Search, paid, web, and CRM data feed one unified view so performance conversations start with facts rather than channel silos.
Layer 03
Human review always
AI visibility is tested by hand before findings are trusted. Every agent and automation has a strategist review step before anything client-facing ships.
6
stack layers from search intelligence through AI engineering
40+
Connected platforms configured per engagement, not on every account
Always
Senior strategists stay in the loop on every diagnostic and report
Why this FAQ is structured the way it is: Generative engines cite content that leads with a clear definition, uses labeled sections, and links to primary vendor sources. This FAQ follows that standard so ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews can quote it accurately.
Overview
The full stack at a glance
How the six layers connect, how many tools are involved, and what makes this stack different from a typical agency toolset.
Key takeaways
- Six layers: Search Intelligence, AI Discovery, Performance Media, Measurement, Web and Experience, AI Engineering.
- The stack is a menu configured per engagement, not a checklist run on every account.
- Discipline and signal quality matter more than the brand names on the logo wall.
Questions3 answers
The Silverback Marketing tool stack is a six-layer system of search, AI, paid media, analytics, web, and automation platforms that work together to produce honest performance signal. It spans roughly forty connected tools, but the count is not the point. The point is that each layer feeds a single diagnostic view senior strategists use before recommending a fix.
- Search Intelligence — crawl health, rankings, topic clarity
- AI Discovery — brand visibility inside AI answers
- Performance Media — demand capture with clean tracking
- Measurement — source quality and pipeline attribution
- Web and Experience — fast, trackable, conversion-ready sites
- AI Engineering — analysis, automation, repeatable workflows
Cited sources: Silverback Tool Stack page
Layer 01
Search Intelligence
SEO and GEO tools for technical depth and topic clarity — crawl health, indexation, keyword gaps, schema validation, and AI-assisted research.
Key takeaways
- Technical crawls pair Screaming Frog, GSC, and log analysis.
- Semrush, GSC, and BigQuery drive keyword and topic gap work.
- Classic SEO tooling and AI-assisted research run together, not in parallel tracks.
Questions5 answers
Silverback runs technical crawls, log review, and indexation diagnostics to find what search engines cannot reach, what is being crawled unnecessarily, and what should be indexed but is not. The core crawler is Screaming Frog, paired with Google Search Console for index coverage and performance data, plus server log analysis. Page experience is checked with Google PageSpeed Insights.
Cited sources: Screaming Frog SEO Spider · Google Search Console · Google PageSpeed Insights
Layer 02
AI Discovery
Platforms monitored for AI visibility and citation quality — how major LLM and AI search surfaces describe, cite, compare, and name your brand.
Key takeaways
- Nine platforms monitored including ChatGPT, Perplexity, Gemini, Claude, AI Overviews, and Bing Copilot.
- Prompt testing is done manually because citation patterns change week to week.
- Custom GEO Reports tie citation gaps to prioritized fixes per platform.
Questions4 answers
Silverback monitors brand visibility across the major AI discovery surfaces: ChatGPT, Perplexity, Google Gemini, Claude, Google AI Overviews, and Bing Copilot, with Grok included in prompt testing. The team also watches Apple Intelligence discovery surfaces as on-device AI search matures.
Cited sources: ChatGPT · Perplexity · Google Gemini · Claude · Google AI Overviews · Microsoft Copilot · Grok · Apple Intelligence
Layer 03
Performance Media
Paid media platforms managed with conversion paths, audience logic, and reporting tied to qualified pipeline.
Key takeaways
- Google Ads, Microsoft Ads, LinkedIn Ads, and Meta Ads with GTM conversion tracking.
- B2B programs lean LinkedIn; DTC and broader demand lean Meta.
- Enhanced conversions and offline CRM import feed real revenue back into bidding.
Questions4 answers
Silverback manages paid programs across Google Ads, Microsoft Ads, LinkedIn Ads, and Meta Ads, with conversion tracking wired through Google Tag Manager and feedback loops into HubSpot and Salesforce. Search programs include smart bidding, negative keyword management, asset group structure, and Performance Max.
Cited sources: Google Ads · Microsoft Advertising · LinkedIn Marketing Solutions · Meta for Business
Layer 04
Measurement
Analytics, tracking, and CRM setups that show source quality, funnel movement, and cost per qualified opportunity.
Key takeaways
- GA4 and GTM with a deliberate event taxonomy mapped to revenue intent.
- HubSpot and Salesforce wired for original source and SQL definition alignment.
- BigQuery plus Looker Studio for blended pipeline reporting.
Questions4 answers
The measurement foundation is Google Analytics 4 and Google Tag Manager, with a custom event taxonomy and dataLayer implementation that maps form submits, scroll depth, file downloads, video engagement, and click events to the actions that predict revenue. Events are defined deliberately so reporting reflects intent, not just traffic.
Cited sources: Google Analytics 4 · Google Tag Manager
Layer 05
Web and Experience
Development and experience tools for fast, conversion-ready sites with performance and measurement built in from day one.
Key takeaways
- Next.js, React, and WordPress deployed on Vercel with Cloudflare at the edge.
- GA4, GTM, schema, and consent validated on staging before launch.
- Cursor and Claude Code used as AI pair programmers with human architecture control.
Questions4 answers
Silverback builds on a modern, performance-first stack: Next.js and React for JAMstack and headless builds, WordPress where a familiar CMS fits, and Vercel for deployment with preview environments and rollback support. Builds are optimized for Core Web Vitals, SEO, and structured data from the first deploy.
Layer 06
AI Engineering
Custom agents, workflow automations, and reporting scripts that remove repetitive work without handing strategy to a black box.
Key takeaways
- Custom SEO, GEO, and paid media agents on Claude and ChatGPT APIs.
- n8n, Zapier, Make, and Apps Script for recurring workflow automation.
- Every agent has a human review step before anything client-facing ships.
Questions5 answers
Silverback builds purpose-built SEO, GEO, and paid media analysis agents on the Claude API and ChatGPT, orchestrated with Python. These agents pull data from Search Console, Semrush, ad platforms, and AI citation tests, then synthesize prioritized recommendations without manual aggregation or copy-paste reporting.
Operating model
How tools get selected and used
The bar every platform has to clear, the four principles that govern the stack, and how tools run through a live engagement cycle.
Key takeaways
- Every tool must produce unique signal, integrate cleanly, and improve accuracy.
- Four principles: connected data, manual validation, automation layer, clear reporting.
- A six-step audit-to-refine cycle repeats every engagement.
Questions3 answers
Every tool has to clear one bar: it must produce a signal the team cannot get another way, integrate cleanly with what is already running, and make the work more accurate rather than just more automated. Most tools do not clear that bar, which is why the stack stays deliberate instead of sprawling.