--- title: "Marketing Tool Stack | SEO & GEO" site: "Silverback Marketing" domain: "silverbackmarketing.com" type: "About" description: "Explore the SEO, GEO, AI visibility, paid search, analytics, web, and automation tools we use to diagnose problems and drive performance." canonical: "https://silverbackmarketing.com/about/tool-stack" markdown: "https://silverbackmarketing.com/about/tool-stack.md" --- 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. [Request an audit](/contact/request-an-audit) [Book a discovery call](/contact/book-a-discovery-call) ## Silverback runs on a modern SEO, GEO, AI, and paid media stack - Google Search Console - Screaming Frog - SEMRush - GA4 - Claude - Perplexity - ChatGPT - Grok - Gemini - Big Query - Apple - Claude Code - Codex - Cursor - AntiGravity - Cloudflare Perspective ## 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 intelligence - AI discovery - Paid media - Analytics - Web performance - Automation 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 #### 01: Platforms buyers and AI systems actually use Signal quality over platform familiarity Status: Active #### 02: Manual review before automation takes over Humans verify before systems scale Status: Always #### 03: Tracking that ties spend to pipeline, not vanity metrics Revenue attribution over impression counts Status: Required #### 04: Custom AI workflows for analysis, not autopilot strategy AI augments judgment, never replaces it Status: By design #### 05: Reporting leadership can act on in one read Clarity over completeness every time Status: Every month #### 06: Systems that improve quarter over quarter Compounding performance, not one-off wins Status: Goal 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 approach](/about/process) Operating 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. ### 01: connect 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. Signal: Connected data ### 02: test 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. Signal: Manual validation ### 03: automate 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. Signal: Automation layer ### 04: report 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. Signal: Clear reporting 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 stack](/contact/book-a-discovery-call) No 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. - Weekly - Monthly - Quarterly ### 01: Audit with the right sources GSC, Semrush, GA4, AI citation tests, and log files pulled together before any recommendation is made. Frequency: Quarterly ### 02: Connect tracking and CRM feedback GA4 events, GTM triggers, HubSpot and Salesforce source data verified so attribution is accurate before the cycle starts. Frequency: Monthly check ### 03: Run manual and automated analysis Agents handle data aggregation and anomaly detection. Senior strategists handle interpretation and recommendations. Frequency: Weekly + monthly ### 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. Frequency: Monthly ### 05: Execute across search, paid, and web Campaigns, content, schema, CRO, and automation deployed across the channel mix with QA checkpoints at each stage. Frequency: Ongoing ### 06: Report, retest, and refine What changed, why, and what to do next. AI visibility retested. Rankings checked. Pipeline attribution reviewed. Cycle repeats. Frequency: Monthly + quarterly This 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 changes the outcome this quarter. The stack is built to keep the loop running cleanly. [See how we work](/about/process) Search 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. - 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. - 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. - 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. - 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. AI discovery ## Platforms we monitor for AI visibility and citation quality. AI answers now shape how buyers research and decide. 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. - 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. - 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. - 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. - 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. Performance 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. - 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. - 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. - 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. - 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. Measurement ## 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. - 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. - 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. - 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. - 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. Web 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 before launch, not bolted on after launch. - 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. - 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. - 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. - 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. AI 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. - 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. - 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. - 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. - 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. Where 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 Search #### SEO and GEO Rankings, AI citations, crawl health, and content answerability [Explore SEO and GEO](/services/seo-and-geo) AI #### AI Visibility Citation audits, schema, entity clarity, and platform monitoring [Explore AI Visibility](/services/ai-visibility) Paid #### Google Ads Management Search, Performance Max, bidding strategy, and conversion tracking [Explore Google Ads Management](/services/google-ads) Paid #### Microsoft Ads Management Bing search, LinkedIn audience import, and cross-platform attribution [Explore Microsoft Ads Management](/services/microsoft-ads) Data #### Analytics and Tracking GA4, GTM, BigQuery, HubSpot, and pipeline-tied reporting [Explore Analytics and Tracking](/services/analytics-tracking) AI Engineering #### AI Automation Custom agents, workflow automation, and reporting scripts [Explore AI Automation](/services/ai-automation) 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 audit](/contact/request-an-audit) Ready when you are ## Build a smarter growth strategy. An audit takes 15 minutes of your time and gives you a prioritized 30‑60‑90 plan, whether or not we ever work together. [Request an audit](/contact/request-an-audit) [Book a discovery call](/contact/book-a-discovery-call) - No vendor pitch - Senior strategist call - Plan you can keep