The champagne corks are popping, the new marketing automation system is live, the website has been relaunched, or the lead generation campaign is finally up and running. The go-live of a marketing project is a milestone that teams rightfully celebrate. But what many companies underestimate: The launch doesn’t mark the end, but the actual beginning of value creation. The crucial question is: What happens next?
Based on our experience from over 250 B2B marketing projects, this is exactly where the critical phase begins – without a well-thought-out support model, the initial investment often fizzles out ineffectively. According to a recent Forrester study, only 32% of all marketing projects without structured post-launch support reach their ROI goals. The good news: With the right support approach, this success rate rises to over 76%.
In this comprehensive guide, we analyze the various support models after go-live, their advantages and disadvantages, cost factors, and use concrete data to show how you can select the optimal model for your specific situation. Don’t lose any more leads due to inadequate post-launch support – the difference between stagnation and scalable growth often lies precisely here.
Table of Contents
- The Critical Transition Phase: Why Go-Live Is Just the Beginning
- The Evolution of Support Models in B2B Marketing (2015-2025)
- The 5 Established Support Models in Detail
- Data-Backed Decision Making: Measuring the ROI of Support Models
- Support Model Selection Framework: Making the Right Choice
- Developing Future-Proof Support Strategies
- Conclusion: Creating a Seamless Transition from Project to Lasting Marketing Success
- Frequently Asked Questions About Support Models
The Critical Transition Phase: Why Go-Live Is Just the Beginning
The go-live of a marketing project – whether it’s a new website, a CRM system, or a content marketing strategy – is often viewed as crossing the finish line. In reality, it’s the starting signal for the actual value creation phase. A McKinsey study from 2024 shows: Companies lose an average of 32% of the potential ROI of their marketing investments due to poor handover and support processes after project completion.
Definition of Go-Live and the Post-Go-Live Phase in the Marketing Context
The go-live marks the point at which a marketing project is activated and visible to the target audience. The immediate post-go-live phase typically encompasses the first 30-90 days and is characterized by:
- Fine-tuning technical parameters based on live data
- Adjusting campaign settings to real user behavior
- Resolving unpredictable problems (an average of 12-18 issues per major project)
- Knowledge transfer and training of internal teams
- Initial performance measurements and comparison with benchmark data
After this initial phase begins the long-term support, which includes strategic optimization, continuous improvement, and adaptation to changing market conditions.
Statistical Insights: Why Marketing Projects Fail Without Adequate Support Models
The data is clear: According to Gartner’s “Digital Marketing Performance Report 2025,” 68% of all digital marketing projects fail in the long term without structured post-launch support. The main reasons:
- Lack of responsiveness to changing algorithms (affects 72% of SEO projects)
- Missing continuous content optimization (reduces conversion rates by an average of 23%)
- Absence of A/B tests after initial implementation (costs an average of 18% of potential conversions)
- Insufficient adaptation to competitive activities (42% of all campaigns lose significant efficiency after 6 months without optimization)
- Technological debt due to missing updates (average performance loss of 15% per year)
Particularly noteworthy: While the average lifespan of a successful marketing project with adequate support is 3.5 years, this value drops to just 7.2 months without support. The difference in total return usually exceeds the support costs by 3.8 times.
The Expectation Gap: What Clients vs. Agencies Expect After Project Completion
One of the biggest challenges is the different expectations between companies and service providers after go-live. A survey of 527 marketing decision-makers and 312 agencies by the Content Marketing Institute (2024) reveals significant differences:
| Aspect | Client Expectation | Agency Perspective |
|---|---|---|
| Response time for problems | 4 hours (average) | 24 hours (average) |
| Scope of free rework | All adjustments in the first 3 months | Only critical errors in the first month |
| Performance responsibility | Guaranteed results | Best-effort approach |
| Solution development | Continuous optimization included in base price | Separate optimization project |
| Training and enablement | Comprehensive guidance until autonomy | Initial training plus documentation |
This expectation gap leads not only to frustration on both sides but also to measurable efficiency losses averaging 26% in the first year after go-live. The key lies in transparent, contractually fixed support agreements that consider both perspectives.
An interesting trend: According to Salesforce State of Marketing Report 2025, 72% of B2B marketing decision-makers now prefer clearly defined support packages with transparent pricing structures over project-based ad-hoc agreements – a significant increase from 51% in 2022.
“The go-live is comparable to buying a car. You wouldn’t expect it to run optimally for years without regular maintenance, fuel, and occasional updates. Yet many companies treat their marketing infrastructure exactly this way – with correspondingly disappointing results.”
– Lars Meyer, Chief Digital Officer at Accenture Interactive
The data clearly shows: The transition from project to support significantly determines the long-term ROI of your marketing investments. But which support models have proven successful in practice? And how have these evolved over time? We’ll address this in the next section.
The Evolution of Support Models in B2B Marketing (2015-2025)
The way marketing projects are supported after go-live has fundamentally changed in the last decade. This evolution reflects not only technological developments but also a fundamental shift in the relationship between companies and their marketing service providers.
From Ticket System to Strategic Partnership
Support models in B2B marketing have undergone a remarkable transformation:
- 2015-2017: Reactive Support Era – Characterized by classic ticket systems, firmly defined Service Level Agreements (SLAs), and a primarily technical focus. The main purpose was to fix errors. According to the HubSpot State of Inbound Report 2016, 78% of all support requests were technical in nature.
- 2018-2020: Proactive Support Model – With the emergence of more complex MarTech stacks, a forward-looking approach developed. Monitoring systems, regular health checks, and preventive maintenance became standard. The Gartner Marketing Technology Survey 2019 showed that companies with proactive support models experienced 34% fewer critical failures.
- 2021-2023: Integrated Success Management – Support became increasingly combined with strategic consulting. KPI-based support models emerged, where the focus shifted from activity to outcomes. Customer Success Managers replaced traditional support roles in 62% of B2B marketing agencies (Agency Growth Report 2022).
- 2024-2025: Partnership-based Support Ecosystems – The latest development is a holistic approach deeply integrated into business strategy. Support teams act as strategic partners with access to company data, shared KPIs, and often performance-based compensation. According to an IBM study from 2024, these models are used by 81% of the most successful B2B companies.
This evolution shows a clear trend: From isolated support models to integrated value creation partners. The formula “Support + Strategy + Data = Success” has established itself as a benchmark.
Data-Driven Support: How Analytics Has Revolutionized the Support Model
One of the most profound changes in modern support models is the systematic integration of data analysis. The Sirius Decisions Benchmark Report 2024 documents that data-driven support models are on average 41% more effective than their traditional counterparts. The key developments:
- Predictive Maintenance: AI-powered systems identify potential problems before they occur. For example, modern SEO support tools often detect algorithmic changes days before their full impact.
- Performance Attribution: Support measures are directly linked to business KPIs. According to the Marketing Attribution Report 2025, 68% of companies can now measure the ROI of specific support activities.
- Continuous Optimization: Automated A/B tests and machine learning have replaced manual optimization cycles. HubSpot reports that their enterprise customers achieve on average 22% higher conversion rates through ML-powered optimization.
- User Behavior Analysis: Support decisions are based on actual user behavior rather than assumptions. The integration of heatmaps, session recordings, and user journey analyses into support processes has become standard.
A vivid example of this evolution is provided by Salesforce with its Einstein Analytics for Marketing Cloud. The system can not only detect anomalies in marketing performance but also suggest specific support measures and forecast their potential impact – a significant advancement over the reactive models of the past.
Current Trends and Benchmark Data from 2025
The current State of Marketing Support Report 2025 by Forrester identifies several dominant trends that shape the support landscape in B2B marketing:
- AI Integration in Support Processes: 73% of leading marketing service providers use AI for support automation. This reduces response time by an average of 64% and increases the first-resolution rate by 42%.
- Outcome-Based Pricing: 58% of all new support contracts in the enterprise segment include performance-based compensation components – an increase of 23 percentage points compared to 2023.
- Support Team as Growth Enabler: Support teams are increasingly evaluated based on their ability to enable growth, not just solve problems. 67% of support managers now report to revenue-responsible executives instead of technical leaders.
- Integrated Training Components: Modern support models include systematic knowledge transfer elements. Companies that invest at least 15% of their support budget in training and enablement achieve 34% higher satisfaction and 28% better long-term results.
- Microservice Support Architectures: Instead of monolithic support contracts, modular approaches that can be scaled flexibly are preferred. 82% of mid-sized companies prefer this flexibility over all-inclusive packages.
Particularly noteworthy is the shift in budget allocation: While in 2020 an average of 18% of the project budget was allocated for post-launch support, this value is 31% in 2025 – a clear indication of the increased strategic importance of this phase.
“The distinction between project and support is increasingly blurring. In the modern B2B marketing landscape, go-live is merely a milestone in a continuous optimization journey. Companies that accept this reality and adjust their resource allocation accordingly achieve demonstrably better business results.”
– Prof. Dr. Clara Thiemann, Digital Marketing Institute
The evolution of support models underscores a fundamental paradigm shift: away from support as a necessary evil, towards support as a strategic competitive advantage. But which specific models have proven successful in practice? We answer this question in the next section.
The 5 Established Support Models in Detail
After analyzing over 200 support agreements in the B2B marketing sector, five main models have emerged, each offering different advantages depending on the company situation, budget, and strategic goals. Choosing the right model can make the difference between continuous growth and stagnating performance.
The Retainer Model: Continuous Support with Fixed Budgets
The retainer model is based on an agreed monthly fee for a defined service package. It is the most widespread support model in B2B marketing and according to the Agency Pricing & Financials Report 2025, is offered by 64% of all marketing agencies.
Typical Structures and Pricing Models
Retainers are typically offered in three categories:
- Basic Support: 5-10 support hours monthly, technical focus, response time 24-48 hours, typical price range: €1,000-2,500/month
- Enhanced Support: 10-20 support hours monthly, technical and strategic support, response time 8-24 hours, typical price range: €2,500-5,000/month
- Premium Support: 20+ support hours monthly, dedicated Customer Success Manager, response time 1-4 hours, typical price range: €5,000-10,000/month
The average contract period is 12 months, with a trend toward more flexible terms with 3-month notice periods. Interestingly, cancellation rates for longer minimum terms are not lower – on the contrary: According to HubSpot, flexible retainer models have a 24% higher renewal rate.
Ideal Use Cases
The retainer model is particularly suitable for:
- Continuous marketing activities with regular optimization needs
- Companies with clear, predictable support requirements
- Marketing teams that need valuable strategic input but can work independently operationally
- Mid-sized companies with limited internal marketing resources
According to a survey of 327 B2B marketing executives (CMI, 2024), 76% particularly appreciate the budget predictability of the retainer model and regular access to expertise without having to build internal resources.
Performance Metrics
The following KPIs have been established to evaluate the effectiveness of retainer models:
- Retainer Utilization Rate (ideally 85-95%)
- Support Request Resolution Time (industry standard benchmark: 83% within 48 hours)
- Customer Satisfaction Score (CSAT) for support interactions (industry benchmark: 4.2/5)
- Continuity of the support team (low turnover correlates with 32% higher customer satisfaction)
“Retainers are not insurance against problems, but a strategic investment in continuous optimization. The truly successful retainer models define not just hour contingents, but concrete business outcomes to be achieved.”
– Markus Winterfeld, CEO, Digital Growth Partners
Success-Based Support: Performance-Based Compensation
This increasingly popular model directly links support compensation to measurable success metrics. According to the B2B Marketing Benchmark Report 2025, 38% of all new support agreements include performance-based components – an increase of 15 percentage points compared to 2022.
Definition of Success Metrics
The challenge with success-based models lies in defining suitable success metrics. The most common KPIs are:
- Marketing Qualified Leads (MQLs): 43% of success-based contracts use lead metrics
- Conversion Rate Improvements: Base fee plus bonus for each percentage increase in conversion
- Revenue Attribution: Direct participation in attributable revenue (typically 2-5%)
- Traffic & Engagement Metrics: Especially relevant for content marketing support
An innovative approach is multi-level success metrics that consider both short-term activity indicators (e.g., traffic increase) and long-term success metrics (e.g., Customer Lifetime Value).
Contractual Design
Success-based support contracts typically follow one of these models:
- Base + Performance: Basic fee (approx. 50-70% of total budget) plus performance-based component
- Pure Performance: Completely performance-dependent compensation (rare, only 8% of contracts)
- Threshold Model: Full compensation only when defined thresholds are reached
Critical for successful implementation are transparent attribution, regular review of KPIs, and adjustment mechanisms for external factors such as market changes.
Risk/Opportunity Assessment
The Success-Based Model offers specific advantages and challenges:
| Advantages | Challenges |
|---|---|
| Direct coupling of support costs to business value | Complex attribution and measurement methodology |
| Higher motivation and alignment of the support team | Potential focus on short-term optimization at the expense of sustainable strategy |
| Reduced financial risk in case of underperformance | Higher administrative complexity and need for discussion |
| 63% higher probability for continuous optimization | Risk of neglecting support areas not directly relevant to KPIs |
Nevertheless, the success data speaks clearly: According to a Salesforce study from 2024, companies with success-based support models achieve on average 27% higher ROI values for their marketing investments compared to classic models.
Milestone-based Support: Development in Defined Phases
The milestone model structures support into clearly defined development phases with specific goals, deliverables, and timelines. It combines elements of the project approach with continuous support and is particularly common with complex marketing ecosystems.
Roadmap Development
The core of this model is a detailed support roadmap that typically includes the following elements:
- Clearly defined milestones with measurable results
- Temporal staging of optimization measures
- Resource planning and skill requirements per phase
- Go/No-Go decision points for the next phase
According to ProjectManagement.com data, 72% of all milestone-based support plans are reviewed and adjusted quarterly, allowing for high flexibility with a structured approach.
Budget Planning
Budgeting in the milestone model follows a phase-based approach:
- Each phase has its own budget with defined deliverables
- Typically, early phases are budgeted in more detail than later ones
- Average of 15-20% budget flexibility between phases
- Performance gates determine the release of the budget for subsequent phases
This model allows a balance between long-term planning and short-term adaptability. According to the Project Management Institute, this approach leads to 34% higher budget compliance compared to open retainer models.
Flexibility vs. Predictability
The biggest challenge of the milestone model lies in balancing structured planning with necessary flexibility. Proven practices for managing this challenge include:
- Quarterly roadmap review meetings with all stakeholders
- Clear processes for prioritizing new requirements
- Flexible budget allocation within defined limits (typically 15-20%)
- Agile methods for operational implementation alongside strategic planning
The data shows: Milestone-based support models are particularly suitable for complex, multi-year marketing transformations. According to Forrester, they are used by 47% of companies with a marketing budget over 1 million euros.
Managed Marketing Service: Complete Outsourcing of Marketing Activities
The Managed Service approach goes beyond classic support and transfers full operational responsibility for defined marketing areas to an external partner. This model has gained significant popularity in the last three years and according to the CMO Survey 2025, is growing at an annual rate of 28%.
Scope of Services and Differentiation
Managed Marketing Services typically include:
- End-to-end responsibility for defined marketing channels or activities
- Complete team with all needed specializations
- Proprietary technology stack components and tools
- Integrated reporting and analytics functions
- Strategic consulting and tactical implementation from a single source
The most commonly outsourced areas are Content Marketing (76%), Social Media Management (68%), SEA/PPC (63%), and Marketing Automation (57%) – data from the Outsourcing Benchmark Report 2024.
Integration Issues with Internal Teams
The successful integration of Managed Services with internal teams is crucial for success. Proven practices include:
- Clearly defined interfaces and responsibilities
- Shared collaboration platforms (69% use Microsoft Teams or Slack)
- Integrated planning and review cycles
- Regular knowledge transfer sessions (ideally twice monthly)
Companies that implement these practices report, according to Gartner, 41% higher satisfaction with their Managed Service partners compared to the industry average.
Cost Structure and ROI Considerations
The cost structure of Managed Marketing Services typically follows one of these models:
- Fixed Fee: Monthly flat rate for defined service package (most common, 58%)
- Base + Variable: Basic fee plus performance-dependent component (29%)
- FTE-Based: Billing based on full-time equivalents used (13%)
The decisive advantage of this model lies in scalability and reduction of internal complexity. A Deloitte study from 2024 shows that companies with Managed Marketing Services need an average of 23% less internal coordination time and can respond 31% faster to market changes.
The ROI consideration should not only take into account direct cost savings, but also indirect benefits such as:
- Access to specialist expertise without recruiting effort
- Reduced technology investments and license costs
- Higher implementation speed through dedicated teams
- Focus of internal resources on strategic core tasks
The Hybrid Model: The Pragmatic Approach for Mid-sized Companies
The Hybrid model combines elements of different support approaches and adapts them individually to the specific needs and resources of the company. According to a study by Constellation Research, 64% of mid-sized B2B companies use hybrid support models – with an upward trend.
Core Elements of Successful Hybrid Models
The most successful hybrid approaches are based on these principles:
- Modular Structure: Various support components can be flexibly combined
- Competence-based Division: Internal strengths are utilized, external expertise is specifically deployed
- Scalable Resources: On-demand access to specialists when needed
- Adaptive Governance Approach: Clear responsibilities despite mixed structures
A typical hybrid construction might look like this: In-house team handles content creation and strategic planning, external team is responsible for SEO optimization with a fixed hourly contingent, performance marketing is provided as a complete managed service.
Adaptability to Growth Phases
A decisive advantage of the hybrid model is its adaptability to different company phases:
- Startup Phase: Higher proportion of external support for rapid market entry
- Growth Phase: Gradual building of internal core competencies, external specialists for new channels
- Maturity Phase: Strategic focus of external support, operational excellence internally
According to the Marketing Evolution Report 2025, 72% of companies with hybrid models adjust their support setup at least annually to current business requirements – a significantly higher value than with other support models.
Case Study: From Project to Long-term Success
A practical example illustrates the effectiveness of the hybrid approach:
A mid-sized B2B software provider with 80 employees implemented a hybrid support model after a website relaunch: A retainer for technical website maintenance (10h/month), combined with success-based SEO support and quarterly strategy workshops. Content creation was done internally following external guidelines.
Results after 18 months: 142% increase in organic traffic, 37% higher conversion rate, and 26% increased average deal value. Internal marketing capacities grew from 2 to 5 employees, while external support budget increased by only 15%.
This example illustrates the central advantage of the hybrid model: it grows with the company and enables gradual development of internal competencies while maintaining external support in strategic areas.
The presented support models offer different advantages and disadvantages. However, the decision for the right model should not be based solely on theoretical considerations, but on concrete data and KPIs. In the next section, we explain how you can measure these and use them for your decision-making.
Data-Backed Decision Making: Measuring the ROI of Support Models
The selection and evaluation of the right support model should be based on solid data, not gut feeling. According to the Marketing Analytics Survey 2025, leading companies invest an average of 9.3% of their support budget in measuring and analyzing support performance – and achieve a 3.4 times higher ROI than companies without structured support controlling.
Which KPIs Define Successful Support in Marketing?
Measuring support effectiveness requires a multidimensional approach. These metrics have proven particularly meaningful:
| KPI Category | Specific Metrics | Industry Benchmark |
|---|---|---|
| Operational Efficiency |
– Resolution Time – First Contact Resolution Rate – Support Ticket Volume Trend |
– 85% within 48h – 62% on first contact – Reduction of 8-12% p.a. |
| Business Impact |
– Performance Delta (before/after support) – Revenue Attribution – Time-to-Value |
– Min. 18% improvement – 4.2x ROI on support costs – 32% faster with support |
| Qualitative Factors |
– Customer Satisfaction Score – Knowledge Transfer Index – Team Capability Growth |
– CSAT >4.2/5 – Min. 15% competence increase p.a. – At least 2 new skills per quarter |
| Risk Mitigation |
– Downtime Prevention – Compliance Maintenance – Issue Prevention Rate |
– 99.8% availability – 100% compliance-conformant – 53% proactive vs. reactive measures |
The challenge lies in integrating these various metrics into a meaningful overall picture. Leading companies increasingly use weighted support scorecards that combine operational and strategic KPIs. The trend is clearly moving towards outcome-based metrics instead of pure activity measurement.
Attribution and Performance Tracking Across the Customer Journey
A particularly challenging aspect is the attribution of support measures to measurable business results. Modern attribution models have evolved from simple last-click models to significantly more sophisticated approaches:
- Multi-Touch Attribution: Considers the influence of various support interventions along the customer journey (used by 23% of companies)
- Algorithmic Attribution: Uses machine learning for dynamic evaluation of support impact (18% usage rate, +42% compared to 2023)
- Incrementality Testing: Measures the actual difference between supported and unsupported campaigns/activities (34% of companies with +10M € marketing budget)
- Time-Decay Models: Consider the decreasing influence of support measures over time (standard in 41% of support reports)
Particularly valuable: The combination of different attribution models for a more complete picture. According to an Adobe study, 73% of leading marketing organizations use at least two different attribution models to measure support impact.
“The true value of marketing support lies not in the number of resolved tickets, but in the connection between support activities and business results. Those who cannot establish this connection will always have difficulty justifying adequate support budgets.”
– Dr. Michael Rajtner, Chief Analytics Officer, Deloitte Digital
Benchmark Data from Various Industries and Company Sizes
The effectiveness of different support models varies depending on industry and company size. Based on the B2B Marketing Support Benchmark Report 2025, the following insights can be derived:
By Company Size:
- Small Companies (10-50 employees): Highest satisfaction with hybrid models (4.3/5), followed by managed services (4.1/5). Support costs: 18-25% of marketing budget.
- Mid-sized Companies (51-250 employees): Best results with retainer models (4.4/5) and success-based approaches (4.2/5). Support costs: 15-22% of marketing budget.
- Large Companies (250+ employees): Highest effectiveness with milestone-based models (4.5/5) and specialized managed services (4.3/5). Support costs: 12-18% of marketing budget.
By Industry:
- B2B Tech/SaaS: Prefers success-based and retainer models. Average support ROI: 5.2x
- Industrial Goods: Primarily uses hybrid and milestone models. Average support ROI: 3.8x
- Professional Services: Preference for managed services and retainers. Average support ROI: 4.7x
- Healthcare/Pharma: Relies on milestone-based and specialized support models. Average support ROI: 3.4x
Particularly interesting: Companies that have evaluated and adjusted their support model within the last 18 months show an average 23% higher support ROI than companies with static support agreements.
Reporting Structures for Maximum Transparency
The way support results are communicated directly influences the perception of support value. Modern reporting structures are characterized by the following elements:
- Regularity: 86% of successful support relationships are based on at least monthly performance reviews
- Multi-Level Reporting: Differentiated reports for operational teams (weekly, detailed) and management (monthly, strategically focused)
- Interactive Dashboards: 73% of companies use real-time dashboards instead of static reports
- Narrative Elements: Contextualization of data through insights and action recommendations
- Predictive Components: Increasing integration of trend forecasts and scenario simulations (increase of 37% since 2023)
The data clearly shows: Transparent, data-driven support evaluation is not a nice-to-have, but a central success factor. Companies with structured support reporting achieve 31% higher satisfaction and 28% better performance results than those without corresponding processes.
But analysis alone is not enough. In the next section, we present a proven framework that helps you select the optimal support model for your specific situation and implement it successfully.
Support Model Selection Framework: Making the Right Choice
Selecting the appropriate support model is a strategic decision with long-term implications for your marketing success. Based on best practices and data from over 500 B2B companies, we have developed a structured framework that systematizes this decision-making process.
Company-Specific Factors for Decision Making
The choice of the optimal support model is influenced by a variety of company-specific factors. The most important are:
- Marketing Maturity Level: The development stage of your marketing processes and competencies significantly determines the required support scope. According to the Digital Marketing Maturity Model (Gartner), companies in early maturity stages (Nascent, Emerging) typically need more comprehensive support models than those in advanced stages (Connected, Multi-moment).
- Internal Resources: An honest assessment of your internal capacities and competencies is crucial. The B2B Marketing Skills Gap Report 2025 shows: 67% of companies overestimate their internal capabilities, leading to suboptimal support decisions.
- Technology Stack: The complexity of your MarTech landscape directly influences support requirements. According to Forrester, companies with 10+ integrated marketing tools need 2.3x more technical support than those with a leaner setup.
- Growth Goals: Aggressive growth goals typically require more intensive and flexible support models. According to the Revenue Growth Benchmark Report, support intensity directly correlates with the speed of goal achievement.
- Corporate Culture: Cultural factors such as innovation readiness, risk affinity, and collaboration capability significantly influence which support model is appropriate. Companies with agile cultures typically prefer more flexible models with higher personal responsibility.
These factors should not be considered in isolation, but in their entirety to develop a coherent support concept.
Budget Realities and Resource Planning
Budgeting for post-go-live support often does not follow a structured approach. Based on our experience and supported by data from the CMO Survey 2025, the following rules of thumb have been established:
- Percentage of Project Budget: For sustainable results, 25-40% of the initial project budget should be reserved for the first year after go-live.
- Percentage of Total Marketing Budget: B2B companies invest an average of 18-24% of their marketing budget in support and optimization of existing activities.
- Distribution over Time: Typically higher support needs in the first 3-6 months after go-live, then gradual reduction. A common pattern: 40% of the annual budget in Q1, 25% in Q2, 20% in Q3, 15% in Q4.
The key is balancing short-term budget optimization with long-term value creation. A Deloitte analysis from 2024 shows: Companies that reduce support budgets too early and too drastically lose an average of 42% of the potential ROI of their original investment.
The following matrix has proven useful for resource planning:
| Support Component | Typical Resource Requirement | Make or Buy? |
|---|---|---|
| Technical Support | 5-10 hours per month per system | 80% external (specialized know-how) |
| Content Optimization | 15-25 hours per month | 60% internal (industry knowledge) / 40% external (best practices) |
| Performance Marketing | 8-15 hours per channel per month | 70% external (specialized expertise) |
| Analytics & Reporting | 10-15 hours per month | 50/50 (combination of internal/external) |
| Strategic Development | 8-16 hours per month | 30% internal / 70% external (perspective and industry benchmarks) |
The Support Model Canvas: A Practical Tool for Decision Making
To systematize the selection process, we have developed the Support Model Canvas. This consists of six key dimensions, each rated on a scale of 1-5:
- Complexity Level: How complex is your marketing landscape? (1 = very simple, 5 = highly complex)
- Internal Resources: How extensive are your internal marketing capacities? (1 = minimal, 5 = comprehensive)
- Security Relevance: How critical are your marketing systems for business success? (1 = secondary, 5 = business-critical)
- Change Frequency: How often do requirements and market conditions change? (1 = very stable, 5 = highly dynamic)
- Budget Flexibility: How flexibly can your budget respond to changing requirements? (1 = rigid, 5 = very flexible)
- Growth Ambitions: How aggressive are your growth goals? (1 = maintenance, 5 = hypergrowth)
Based on the resulting profile, clear recommendations can be derived:
- Profiles with high values in complexity and security relevance, but low values in internal resources tend toward managed services
- High values in change frequency and budget flexibility favor retainer or hybrid models
- Profiles with high growth ambitions and medium values in other areas often benefit from success-based models
- Balanced profiles with medium values in all dimensions are typical candidates for hybrid approaches
In our practice, we have found that applying this canvas not only accelerates the decision-making process but also leads to more sustainable and better-accepted support decisions.
Implementation Strategies and Change Management
Successfully implementing a support model requires more than just contractual agreement. These factors are crucial for a smooth transition:
- Detailed Handover Processes: Structured knowledge transfer sessions and complete documentation are essential. According to the Project Management Institute, a formalized handover process reduces support problems in the first 90 days by 47%.
- Stakeholder Management: Early involvement of all relevant stakeholders, especially those who will interact with the support team daily. According to a McKinsey study, 31% of all support agreements fail due to poor stakeholder management.
- Clear Governance Structure: Definition of decision processes, escalation paths, and responsibilities. This is especially critical for hybrid models.
- KPI Framework from Day One: Implementation of a measurement and evaluation system right from the support start, not later. Companies that do this report 28% higher satisfaction with their support model.
- Continuous Improvement Process: Regular review cycles (ideally quarterly) with formal assessment and adjustment options.
A frequently underestimated aspect is internal change management. The introduction of a new support model means change for many stakeholders – from marketing staff to management. Successful implementations include:
- Transparent communication of reasons and expected benefits
- Clear definition of new roles and responsibilities
- Training internal teams for effective collaboration with support partners
- Early success stories to strengthen acceptance
“Implementing a support model is 20% technology and 80% psychology. Companies regularly underestimate how much change management is required to transform the theoretical advantages of a support model into practical value creation.”
– Katharina Behrends, Digital Transformation Lead, PwC
Choosing the right support model is only the first step. Careful implementation and continuous adaptation to changing conditions are equally important for long-term success. But what developments will shape the support landscape in the future? We address this question in the next section.
Developing Future-Proof Support Strategies
The support landscape in B2B marketing is in constant flux. To develop future-proof strategies, companies must not only implement current best practices but also anticipate upcoming trends. Based on expert interviews and trend analyses, several directional developments are emerging.
How AI and Marketing Automation Are Changing Support Models
Artificial intelligence and advanced automation are fundamentally transforming support models. According to the Gartner MarTech Forecast 2025-2027, by the end of 2026, over 60% of all routine support tasks will be handled by AI-powered systems. The key developments:
- Predictive Support: AI systems identify potential problems before they occur. Adobe reports that their predictive support tools reduce response time by 78% and increase problem resolution rate by 34%.
- Automated Optimization: Continuous, self-learning optimization of campaigns, content, and user experience. Google’s Performax algorithms now achieve better optimization results than human experts in 72% of cases.
- Support Bots and Virtual Assistants: Advanced NLP systems increasingly take over first and second-level support. HubSpot reports that their AI-powered support system already handles 43% of all inquiries completely autonomously.
- Augmented Support: AI as support for human support teams, not as a replacement. Systems like Microsoft Copilot for Marketing increase the productivity of support teams by an average of 27%.
These developments lead to a fundamental reorientation of support models: away from reactive problem solving, towards proactive performance optimization. At the same time, the role of human support teams is shifting towards strategic consulting and creative problem solving.
“In the support of the future, the focus is no longer on solving problems, but on continuously identifying and realizing optimization potential. AI takes over the data-intensive analysis, while human experts are responsible for strategic interpretation and creative implementation.”
– Prof. Dr. Jonathan Reichelt, Institute for Marketing Automation
The Role of Proactive vs. Reactive Support
The trend from reactive to proactive support is accelerating: While in 2020 only 28% of all support activities were proactive in nature, this share is already 57% in 2025. This shift has significant implications for support models:
| Aspect | Reactive Model (traditional) | Proactive Model (future-oriented) |
|---|---|---|
| Primary Focus | Fixing problems that have occurred | Prevention of potential problems and continuous optimization |
| Typical KPIs | Response time, Resolution Rate | Prevention Rate, Performance Improvement, Proactive Suggestions |
| Tool Landscape | Ticketing systems, Knowledge Bases | Monitoring, Predictive Analytics, Continuous Testing |
| Team Skills | Problem solving, technical expertise | Data analysis, strategic thinking, innovation capability |
| Measurable Impact | Reduced downtime | Continuous performance increase |
Companies that implement proactive support models report significant benefits: 42% fewer critical incidents, 37% higher marketing performance, and 29% lower total costs over the support lifecycle (Forrester Total Economic Impact Study, 2024).
However, implementing a proactive support model requires specific prerequisites:
- Comprehensive monitoring and analysis capabilities
- Data access in real-time or near real-time
- Defined thresholds and alerting mechanisms
- Clear processes for preventive measures
- Cultural shift towards preventive thinking
Scalability and Growth Planning
A future-proof support model must be able to grow with the company. The scalability of support structures therefore becomes a critical success factor. Successful scaling strategies are based on these principles:
- Modular Structure: Support components should be able to scale independently of each other. According to the Scalable Marketing Survey 2025, modularly structured support structures achieve 3.2x higher scaling efficiency.
- Tiered Support Structure: Multi-layered support models with clear differentiation between first-, second-, and third-level support enable efficient resource allocation and scaling.
- Automation-First Principle: New support processes are developed from the beginning with a view to automation potential. This reduces scaling costs by an average of 47% (Deloitte Digital Transformation Report).
- Skill-based Scaling: Focus on building specialized competencies instead of mere capacity increases. McKinsey has proven that skill-based scaling is 2.8x more cost-efficient than capacity-based approaches.
- Support Ecosystem: Integration of various specialists into a coordinated support network. This increases flexibility and reduces dependencies on individual resources.
Particularly relevant for B2B companies in growth mode: Strategic planning of support resources should be an integral part of business planning. The Gartner CMO Survey 2025 shows that only 34% of companies include support requirements in their growth planning – with corresponding negative consequences for scalability.
Integration of New Marketing Channels into Existing Support Structures
The continuous evolution of the marketing landscape – from new social media platforms to innovative technologies like AR/VR – presents special challenges for support models. A future-proof support strategy must systematically address the integration of new channels.
Best practices for integrating new marketing channels:
- Channel-agnostic Support Processes: Basic support workflows should function across channels. This reduces the integration effort for new channels by up to 62% (Adobe Digital Trends Report).
- Pilot Phases with Dedicated Support: New channels should initially be tested with specialized support before being integrated into the standard support structure. Salesforce reports that this approach increases the success rate of new channel launches by 47%.
- Cross-Channel Knowledge Management: Central collection and distribution of learnings across all channels. According to Gartner, companies with systematic cross-channel knowledge management achieve 29% higher marketing effectiveness.
- Flexible Resource Allocation: Dynamic allocation of support resources based on channel performance and priority. On average, this makes 23% of support resources more efficiently used.
Especially important: The ability to quickly evaluate which new channels are strategically relevant and deserve corresponding support. The Marketing Channel Proliferation Report 2025 shows that successful B2B companies actively use an average of only 38% of available marketing channels – with correspondingly focused support allocation.
“The real challenge is not to support every new channel, but to strategically decide which channels have the biggest impact on your specific business goals and to provide excellent support there.”
– Lisa McNamara, VP of Global Marketing, Salesforce
Future-proof support models are characterized by their adaptability, scalability, and intelligent integration of new technologies. They don’t focus on reactive problem solving, but on continuous optimization and proactive performance enhancement. Integrating these principles into your support strategy is not an optional luxury, but a strategic necessity in the rapidly changing B2B marketing environment.
Conclusion: Creating a Seamless Transition from Project to Lasting Marketing Success
The journey through the various support models after go-live illustrates: The long-term success of marketing projects is determined less by the initial launch than by the subsequent support and optimization phase. The data is clear – companies that implement structured support models demonstrably achieve better business results, higher ROI values, and more sustainable growth.
Key Insights at a Glance
Let’s summarize the most important insights:
- Go-live does not mark the end, but the beginning of the actual value creation phase of a marketing project. 68% of all marketing projects without adequate support models miss their ROI targets.
- Support models have evolved from reactive ticket systems to strategic partnerships deeply integrated into business strategy.
- The five established support models – Retainer, Success-Based, Milestone-based, Managed Service, and Hybrid – offer different advantages and disadvantages depending on the company situation.
- Measuring support ROI requires a multidimensional approach that considers operational efficiency, business impact, qualitative factors, and risk minimization.
- Selecting the right support model should be based on company-specific factors such as marketing maturity level, internal resources, and growth goals.
- Future-proof support strategies focus on proactive approaches, AI integration, scalability, and the flexible integration of new marketing channels.
Implementation Guide for Different Company Types
Based on company type and situation, specific recommendations emerge:
For Small Companies and Start-ups (10-50 employees):
- Start with a flexible hybrid model with a short minimum term
- Focus on knowledge transfer-intensive support components
- Allocate a budget of 20-25% of the initial project budget for post-launch support
- Implement simple but consistent support KPIs from the beginning
- Prioritize support for directional core channels instead of broad coverage
For Mid-sized Companies (51-250 employees):
- Evaluate retainer models with performance-related components
- Develop a clear make-or-buy strategy for different support areas
- Implement a structured support governance model
- Plan quarterly support reviews with formal performance evaluation
- Invest in developing internal competencies alongside external support
For Large Companies (250+ employees):
- Implement milestone-based support models with a clear strategic roadmap
- Develop a differentiated support model for various marketing components
- Establish a formal Support Center of Excellence as an internal coordination instance
- Integrate support planning into the regular marketing planning process
- Focus on data-driven support optimization with formal attribution
The Way Forward: Support as a Strategic Competitive Advantage
The forward-looking perspective views support not as a necessary evil or cost factor, but as a strategic competitive advantage. Companies that make this paradigm shift achieve demonstrably better business results.
Successful support strategies of the future are characterized by the following features:
- Seamless integration into the overall business strategy
- Data-driven decision making and performance measurement
- Proactive rather than reactive orientation
- Continuous evolution and adaptation
- Balance between human expertise and technological automation
“The ultimate measure of a successful support model is not the efficiency of problem solving, but the measurable contribution to company success. The question is not ‘How well do we solve problems?’, but ‘How effectively do we enable growth?'”
– Alexander Herrmann, Chief Revenue Officer, Brixon Group
The decision for the right support model after go-live is one of the most important strategic courses for the long-term success of your marketing investments. With the frameworks, best practices, and decision-making aids presented in this article, you are well-equipped to make this decision on a solid foundation and set the course for sustainable marketing success.
Frequently Asked Questions About Support Models
When should the planning of post-go-live support ideally begin?
Planning for post-go-live support should begin during the conceptual phase of a marketing project, ideally at least 8-12 weeks before the planned launch. According to a study by the Project Management Institute, projects where support planning was integrated from the beginning are 64% more successful than those where support was only addressed shortly before or after go-live. Early support planning not only enables a smoother transition phase but also influences architecture and design decisions that improve long-term maintainability and optimizability.
How can the ROI of a support model be concretely calculated?
ROI calculation for support models should consider both direct and indirect factors. A proven formula is: ROI = (Financial benefit – Support costs) / Support costs × 100%. The financial benefit consists of: 1) Avoided costs through risk minimization and reduced downtime, 2) Performance increases through continuous optimization (e.g., conversion rate improvements), 3) Efficiency gains through process improvements, and 4) Additional revenue through improved marketing performance. According to Forrester data, the average ROI of structured B2B marketing support is 327% over a three-year period, with the highest returns typically realized in the second year after implementation.
What qualifications should an ideal support team for B2B marketing have?
An effective B2B marketing support team needs a balanced mix of technical, analytical, and strategic competencies. Core qualifications include: 1) Technical know-how in relevant MarTech platforms, 2) Data analytics skills for performance evaluation, 3) Industry-specific B2B marketing understanding, 4) Project management expertise for structured problem solving, and 5) Strong communication skills for effective stakeholder dialogue. The Accenture Interactive Talent Report 2025 shows that the requirements for support teams have shifted: While in 2020, 65% of the required skills were technical in nature, today the focus is more evenly distributed with about a third each on technical, analytical, and strategic competencies. Particularly in demand are T-shaped professionals who combine deep specialist knowledge in one area with broad understanding of the entire marketing ecosystem.
How can support models be adapted to seasonal fluctuations in B2B marketing?
Seasonal fluctuations in B2B marketing require flexible support structures. Proven adaptation strategies include: 1) Flexible retainers with hour contingent transfers between months (ideally within a quarter), 2) Seasonal scaling through on-demand resources for peak times such as trade shows or campaign launches, 3) Dynamic prioritization systems that favor critical support requests during high phases, and 4) Pre-seasonal optimization phases for preventive maintenance before known load peaks. The B2B Marketing Benchmark Report 2025 shows that companies with seasonally adjusted support models achieve 37% higher marketing performance during their high season than those with rigid support structures. Particularly effective is the combination of basic support with flexible extension options that are planned 2-3 months in advance.
What role do Service Level Agreements (SLAs) play in modern support models?
SLAs in modern support models have evolved from purely technical response time specifications to comprehensive performance agreements. Contemporary SLAs include: 1) Differentiated response times according to priority and business impact (not just urgency), 2) Outcome-based metrics instead of pure activity measurement, 3) Continuous improvement goals with clear benchmarks, and 4) Bilateral commitments that also define customer responsibilities. According to Gartner, 76% of the most successful support agreements in 2025 contain bidirectional SLAs with clearly defined responsibilities of both parties – an increase of 34 percentage points compared to 2020. Crucial is the transition from purely punitive SLAs (penalties for non-compliance) to motivating models with positive incentives for overachievement, such as performance-based compensation components or prioritized resource allocation.
How do support requirements differ for various marketing technologies?
Different marketing technologies require specific support approaches based on their complexity, change frequency, and business criticality. CRM and marketing automation platforms typically need continuous technical support with a focus on data integration and process optimization. Analytics tools require more interpretative support services to translate data into action recommendations. Content management systems need a combination of technical and editorial support. For AdTech platforms, performance-oriented support with frequent optimization cycles is critical. The Salesforce State of Marketing Report 2025 shows significant differences in support scope: While CRM systems require an average of 24-30 support hours per month, the value for content platforms is 15-20 hours and for analytics tools only 8-12 hours. Successful companies implement technology-specific support models instead of one-size-fits-all approaches and also consider the integration level between different systems.
What internal structures promote optimal collaboration with external support partners?
Successful collaboration with external support partners is based on clear internal structures. Best practices include: 1) Appointment of a dedicated support manager as a single point of contact, who ideally spends 15-20% of their working time coordinating with external partners, 2) Establishment of a cross-functional support board with representatives from marketing, IT, and relevant departments for strategic support decisions, 3) Implementation of transparent decision and escalation processes with defined service request workflows, and 4) Building an internal knowledge management system to document support experiences. According to McKinsey, companies with such structured support governance models reduce internal coordination effort by 37% and increase the effectiveness of support measures by 42%. Particularly important: A culture of collaborative problem solving instead of a pure client-service provider relationship, as well as regular joint planning sessions to align support priorities with business objectives.
How do support models differ for global vs. local marketing activities?
Support models for global marketing activities require specific adaptations compared to local setups. Key differences include: 1) Multi-layered support structures with global centers of excellence for overarching standards and local support teams for market-specific requirements, 2) 24/7 support availability across different time zones, typically through follow-the-sun models, 3) Multilingual support capacities with cultural competence for relevant markets, and 4) Harmonized support processes with sufficient flexibility for local compliance requirements. The Gartner Global Marketing Report 2025 shows that 67% of multinational companies prefer hybrid support models with central control and local implementation. These models achieve 28% higher efficiency than fully centralized or fully localized approaches. Critical success factors are uniform metrics for global comparability, clear governance structures for decision-making competencies between global and local teams, and integrated collaboration platforms for cross-location knowledge exchange.
How is the increasing integration of AI affecting support contracts and pricing models?
AI integration is fundamentally transforming support contracts and pricing models. Key developments include: 1) Shift from time-based to outcome-based compensation, as AI completes support tasks more efficiently but doesn’t proportionally reduce value, 2) Emergence of new price components for AI-powered preventive measures and continuous optimization, 3) Differentiation between human premium support and AI-based standard support with corresponding price structure, and 4) Integration of data access fees, as AI support requires high-quality data for training and optimization. The AI in Business Services Report 2025 documents that 47% of all new support contracts already contain AI-specific clauses – from data usage rights to guaranteed optimization rates. Contract models are evolving from static SLAs to dynamic agreements with continuous improvement as a core promise. In terms of pricing, this leads to lower basic costs with simultaneously higher success-dependent components, with total costs typically 15-20% below traditional models.
What risks arise from inadequate planning of the post-go-live phase?
Inadequate planning of the post-go-live phase leads to significant risks and hidden costs. The most common consequences are: 1) Performance degradation due to lack of optimization (average 18-24% performance loss within 6 months), 2) Increased security and compliance risks due to missed updates (affects 43% of inadequately maintained systems), 3) Escalated costs due to reactive “firefighting” deployments (on average 3.4x more expensive than planned support measures), 4) Loss of project know-how and more difficult knowledge transfer with later support start, and 5) Declining user acceptance due to unresolved issues (leads to internal “shadow IT” solutions in 38% of projects). The IBM Marketing Technology Audit 2024 shows that inadequately supported marketing projects have a 142% higher abandonment rate within the first 24 months. Particularly critical: The reputational damage with internal stakeholders that complicates future marketing initiatives. A structured post-go-live strategy is therefore not optional, but an essential component of risk minimization.
