Unify your stack.
Measure it in pipeline.
Enterprise MarTech integration and CDP implementation consulting from the firm that has generated over $25B in marketing-sourced revenue for B2B clients since 2007. Every engagement starts with a diagnostic. Every program is measured by revenue.
Your stack is connected.
Your data is not.
Most enterprise MarTech stacks were assembled platform by platform over a decade. Each tool was implemented in isolation. No shared data layer was ever designed. The result is a stack that costs more to maintain than it returns in pipeline.
Marketing reports pipeline contribution. Sales disputes it. Finance ignores it. Three teams, three versions of the same data, and no one closes the loop.
Contact records decay without governance. Duplicate profiles multiply. Personalization misfires. Intent signals route to the wrong account. The stack amplifies bad data at scale.
Every enterprise MarTech integration has one. When they leave, the institutional knowledge leaves with them. Documentation is nonexistent or 18 months out of date.
Enterprise buyers now conduct early-stage research inside ChatGPT, Claude, and Perplexity before they visit your website. Most MarTech stacks cannot see that traffic, let alone convert it.
The average enterprise runs 91 tools. Most share nothing.
10 integration services. Every one required.
These are not optional add-ons. Each service addresses a specific failure mode in enterprise platform unification. A partner that cannot deliver all 10 is not equipped for your program.
Complete inventory of every platform, data connection, gap, and redundancy. Delivered as a documented integration dependency map before implementation begins.
DiscoveryUse-case-first CDP architecture built around activation requirements. Unified customer profiles available in real time to every downstream system. Built for marketing teams, not data engineers.
Core InfrastructureNot just a connector turned on. Agreed field mapping, documented sync rules, lead routing logic, and lifecycle stage definitions signed off by both marketing and sales before configuration begins.
IntegrationMulti-touchpoint identity resolution across anonymous and known records. Data governance framework with defined ownership, acceptance standards, duplicate resolution, and enrichment protocols.
Data FoundationAttribution built around the question you are actually trying to answer. Connected to verifiable data sources with a reporting layer that marketing and sales look at without disputing the methodology.
MeasurementNative connectors handle 70% of integration requirements. TPG's engineering team handles the other 30%: custom APIs, middleware, and real-time webhooks across incompatible systems.
EngineeringLead scoring models built on buying signals, not activity volume. Lifecycle stage definitions agreed by both teams. Mutual SLAs that specify follow-up windows and escalation paths. What turns integration into pipeline.
RevOpsIntent signal routing from Bombora, G2, and TechTarget designed into the integration architecture from the start, not bolted on after. Predictive account scoring surfaced to sales in the CRM.
ActivationAnswer engine optimization integrated into the demand stack. AI visibility data from ChatGPT, Claude, Perplexity, and Gemini flows into content workflows and is tracked alongside SEO performance. Most stacks cannot see this traffic. Yours will.
AI DemandTechnical documentation of every integration. A runbook for the internal team. A structured enablement program with completion criteria. The project does not close until knowledge transfer is confirmed.
GovernanceReady to see which services you are missing?
Request a stack assessmentDiagnostic first. Pipeline last.
Every TPG MarTech engagement begins with a diagnostic and ends with a governance handoff. No implementation begins before the architecture is agreed. No project closes before the internal team can own the system.
We start with TPG's RM6 diagnostic, a 49-capability revenue marketing maturity assessment, and a full integration dependency map of your current stack. Every subsequent decision is based on where your organization actually is, not where a generic proposal assumes it should be.
Integration dependency map + RM6 maturity reportIntegration architecture documented before a single connector is configured. Field mapping specifications, sync rules, CDP data model, and attribution methodology agreed by marketing and sales leadership in writing.
Architecture blueprint + field mapping spec + attribution model docPhased implementation with early wins tracked and reported. Custom API development where native connectors are insufficient. CDP data ingestion and activation rules validated against real use cases before go-live.
Live integrations + CDP in production + AEO diagnosticAttribution model validated against closed revenue. Lead scoring refined against actual conversion data. Technical documentation completed. Internal team enabled with a defined runbook. Project closes when the team can own the system without TPG in the room.
Technical runbook + enablement program + 90-day performance reviewWe report in pipeline. Not deliverables.
These are the commercial outcomes TPG clients achieve when marketing technology consulting is measured by revenue, not by integration completion.
We work in your stack. Not ours.
TPG's integration practice is platform-agnostic. We configure and connect whatever your organization already runs. Our engineers hold production-level certifications across the platforms that anchor most enterprise MarTech stacks.
What separates a MarTech consulting partner
from a MarTech implementation vendor.
Every engagement begins with the RM6 maturity assessment and a stack audit. We design programs based on where your organization actually is, not where a generic template assumes it should be.
TPG reports on marketing-sourced pipeline and revenue influenced. The engagement does not end when the integration goes live. It ends when the outcomes are confirmed.
Most integrations fail because sales and marketing never agreed on definitions. TPG facilitates that alignment before any configuration work begins. The technical integration reflects commercial agreements, not vendor defaults.
TPG integrates answer engine optimization into every demand generation stack. AI-referred buyer traffic is captured, tracked, and attributed. Most consulting partners do not offer this capability. We built it.
The consultant who runs your engagement is named in the SOW. They are accountable to the outcomes. TPG does not rotate junior staff onto accounts after the sales process closes.
TPG's model is teach the fish, fish with you, or fish for you. The default is knowledge transfer. The goal is a stack your internal team can own and extend without TPG in the room. We succeed when you no longer need us for the basics.
Find out what your stack is missing before you build anything.
A TPG strategist will review your current stack, identify the integration gaps costing you pipeline, and walk you through what a structured engagement would produce in the first 90 days. No generic proposal. No prerequisites.
What enterprise marketing leaders ask before they engage.
Marketing technology consulting is the practice of helping organizations select, implement, integrate, and optimize the software platforms that power marketing and revenue operations. A qualified marketing technology consultant assesses the current state of a company's MarTech stack, identifies integration gaps and redundancies, designs a unified architecture, manages implementation, and builds the governance frameworks that keep the stack performing over time. The most qualified firms, including The Pedowitz Group, also align MarTech infrastructure to revenue outcomes, connecting platform decisions to pipeline targets, attribution models, and sales team efficiency.
Enterprise platform unification in marketing technology is the process of connecting the disparate software systems in a marketing and revenue operations stack so they share a consistent data layer, route information accurately between systems, and produce a unified view of buyer behavior across every touchpoint. Unification typically covers MAP-CRM integration, CDP implementation, attribution infrastructure, and intent data and AI visibility layered across the full stack. The goal is a stack where every system works from the same data and every team reports on the same outcomes.
A customer data platform (CDP) is a software system that ingests behavioral and identity data from every source in the MarTech stack, resolves those records to unified customer profiles at the individual and account level, and makes those profiles available in real time to downstream systems for activation. A CDP matters for MarTech unification because it is the single source of truth for customer identity across a fragmented stack. Without it, every system maintains its own conflicting version of who a buyer is and where they are in the buying process. Attribution breaks, personalization misfires, and lead routing produces duplicates. A correctly implemented CDP eliminates those problems by establishing one authoritative profile that every other system reads from.
A MarTech implementation partner executes the configuration and deployment of a specific platform. They are typically certified by the platform vendor and scoped to deliver a working instance within a defined timeframe. A MarTech consulting partner takes a broader mandate: assessing the full stack, designing the integration architecture, aligning technical configuration to business outcomes, and governing the system over time. The most common failure mode in enterprise MarTech projects is hiring an implementation partner when the organization needed a consulting partner. The implementation gets delivered. The integration and the business outcomes do not.
A focused engagement covering MAP-CRM integration, basic data governance, and attribution model design typically takes 90 to 120 days to reach a stable first state. A full-stack unification covering CDP implementation, identity resolution, custom API development, intent data activation, and RevOps alignment typically takes 6 to 12 months from current-state audit to post-integration governance handoff. Any consulting partner that promises enterprise MarTech unification in less than 60 days is scoping a point integration, not a unified stack.
AEO stands for answer engine optimization, the practice of structuring marketing content so that AI systems including ChatGPT, Claude, Perplexity, and Gemini cite a brand accurately when buyers conduct research. A MarTech consulting partner should offer AEO because enterprise B2B buyers now conduct early-stage vendor research inside AI tools before visiting websites or contacting sales. AI-referred visitors arrive with 4.4 times higher engagement rates than organic search visitors. A MarTech stack not configured to capture and convert that traffic is optimized for buyer behavior that no longer describes how most enterprise purchases begin.
A MarTech consulting SOW for enterprise platform unification should include: a current-state stack audit with integration dependency mapping completed before implementation begins, field mapping specifications for every MAP-CRM integration signed off by marketing and sales, a data governance framework delivered as a standalone artifact, attribution model documentation including methodology and limitations, intent data activation architecture in the initial integration design, AEO diagnostic integrated into the demand layer, and technical documentation with a staff runbook delivered before project close. Any SOW that does not specify documentation and enablement as named deliverables with completion criteria is incomplete.
Score every shortlisted firm on 10 service requirements: current-state stack audit capability, CDP implementation methodology, MAP-CRM integration depth, identity resolution and data governance practice, attribution model design, custom API development capability, RevOps alignment services, intent data activation, AEO and AI visibility integration, and post-integration governance and enablement. Use a 1 to 3 scale per requirement. Any firm below 24 out of 30 is not equipped for enterprise platform unification. Ask every firm to provide a case study from a comparable engagement with a named client and a measurable pipeline or revenue outcome. Firms that cannot provide named case studies are telling you something important about their accountability model.