Part 7 of 11: Launch and Execution

Use Robust QA to Prevent Tracking Errors and Budget Slip-Ups with AI Design Sprint™

This article is part of a series on how to use the AI Design Sprint to improve agency processes. In our previous articles, we’ve explored how AI can transform various stages of agency work, from initial planning to content creation. Now, we turn our attention to a critical phase: launch and execution.

Launching and executing campaigns are pivotal moments for any agency, where meticulous attention to detail can make or break the success of a project. However, many agencies face challenges in ensuring accurate tracking and staying within budget, leading to errors and financial setbacks. Implementing robust Quality Assurance (QA) measures is essential to prevent tracking discrepancies and budget overruns, yet achieving this consistently can be daunting.

Today, I want to share how the AI Design Sprint™ can revolutionise your launch and execution phase. By integrating AI, agencies can establish robust QA processes, accurately track campaign performance, and manage budgets effectively. The outcome? Flawlessly executed campaigns, minimised errors, and financial stability that fosters client trust and satisfaction.

If your agency is struggling with tracking inaccuracies, budget slip-ups, or inefficient QA processes during campaign launches, this article is for you. Let’s explore how you can refine your launch and execution strategy with precision and innovation.

Understanding the Agency

The Agency That Struggled with Launch and Execution

Let me take you on a journey about an agency that was experiencing rapid growth. They began as a small digital marketing firm but soon expanded their services to include comprehensive branding, advertising, content creation, and digital strategy. With this growth came new roles: Campaign Manager, QA Specialist, Finance Manager, Creative Director, Data Analyst, and Project Managers.

Exciting times, right? But with great growth came significant challenges. Their launch and execution processes were fragmented. Tracking campaign performance accurately was a nightmare, often resulting in data discrepancies. Budget management was inconsistent, leading to overspending or underutilization of resources. Additionally, the lack of standardised QA procedures sometimes caused critical errors to slip through, risking client satisfaction and agency reputation.

Sound familiar?

Symptoms of Inefficiency

Every campaign launch felt precarious, making it tough to ensure flawless execution. Multiple team members involved without a streamlined QA process led to tracking errors and budget miscalculations. In the rush to launch campaigns, they occasionally exceeded budgets or failed to allocate resources optimally, risking financial stability. Manual QA and tracking processes stretched the time from campaign approval to launch, making them less competitive.

The Six Staff Members: Why Each Role Matters

Let’s meet the stars of their story.

The Campaign Manager (CM) oversees the entire campaign lifecycle but struggles with aligning tracking and budget management simultaneously. The QA Specialist (QA) ensures campaign quality but finds it challenging to maintain consistency across multiple projects. The Finance Manager (FM) manages budgets but is often delayed by inaccurate tracking data. The Creative Director (CD) maintains the creative vision but is hampered by resource misallocations. The Data Analyst (DA) provides critical performance insights but is limited by fragmented data sources. Lastly, the Project Manager (PM) coordinates the launch process, battling disjointed workflows and communication gaps to keep everything on track.

Bringing these roles together in an online AI Design Sprint™ workshop was a game-changer. Facilitated by a certified expert, their goal was clear: overhaul their launch and execution process, unify team inputs, and embed AI-driven efficiencies from the ground up.

The Steps

Transformations like these need a roadmap. They followed a structured AI Design Sprint™ process, ensuring every detail was covered and every voice was heard.

Mapping the Current Launch and Execution Process (Steps 1–3)

Step 1: Check Whether the Process Describes Reality

They kicked things off with Zoom and Miro, mapping out their existing launch and execution workflows. Everyone shared how campaigns were launched, tracked, budgeted, and executed. Within an hour, their current state looked something like this:

1. Campaign Approval: Final approval of campaign plans and budgets.
2. Resource Allocation: Assigning team members and resources to the campaign.
3. Tracking Setup: Implementing tracking tools and ensuring proper configuration.
4. Creative Production: Developing creative assets for the campaign.
5. QA Review: Conducting quality assurance checks on campaign elements.
6. Budget Monitoring: Tracking expenditures against the budget.
7. Campaign Launch: Executing the campaign across chosen channels.
8. Performance Tracking: Monitoring campaign performance and collecting data.
9. Reporting: Compiling performance reports for internal review and client presentation.
10. Feedback and Adjustment: Making necessary adjustments based on performance data.
11. Final Evaluation: Assessing campaign success and financial outcomes.

During this step, the team discussed how each stage was executed and identified discrepancies between the documented process and actual practices. This conversation highlighted areas where informal practices deviated from the intended workflow, providing a realistic view of their launch and execution process.

Step 2: Mark and Describe Pain Points with Red Post-Its

Using red sticky notes, they pinpointed the major obstacles. The lack of standardised QA templates led to inconsistency during quality checks. Manual tracking processes created bottlenecks in budget monitoring. Messaging inconsistencies during performance reporting sometimes led to misinterpretations, and tracking campaign performance became a mess during ongoing stages. The team shared their frustrations and experiences, discussing how these pain points affected their daily work and the overall efficiency of the launch and execution process. This open dialogue ensured that everyone was on the same page regarding the challenges they faced.

Step 3: Mark High-Value Points with Green Dots

They then prioritised the most critical issues with green dots. Standardised QA templates, a streamlined tracking process, consistent performance reporting, and automated budget monitoring emerged as their focus areas for AI integration. In a lively discussion, team members voted on which pain points would deliver the most significant improvements if addressed. This prioritisation helped them focus their efforts on the areas that would make the biggest impact.

AI Cards and Prioritisation (Steps 4–5)

Step 4: Go Through AI Cards Two at a Time, Copy Them If Relevant

They explored AI solution categories.

• AI Workflow Automation systems streamline tracking and budget management processes.
• AI Data Integration solutions consolidate performance data from various sources.
• AI Content Generation tools assist in drafting consistent performance reports.
• AI Compliance Checks ensure all QA procedures meet ethical and industry standards.

The team examined each AI category, discussing how these solutions could address their identified pain points. By understanding the capabilities of each AI tool, they could better match them to their specific needs.

Step 5: Prioritise the Three Most Important AI Cards for Each Step

Through dot-voting, they landed on AI Workflow Automation to streamline tracking and budget management, AI Data Integration to unify performance data, and AI Content Generation to ensure consistent performance reporting. After reviewing the options, the team collectively agreed that these three AI solutions would most effectively tackle their top pain points. This consensus ensured that their focus was aligned and that they were prioritising solutions with the highest potential impact.

Focusing the Sprint (Steps 6–7)

Step 6: Select Two Process Steps to Focus On

They decided to zero in on the tracking setup process and the budget monitoring phase. Ensuring accurate and consistent tracking setups and streamlining budget monitoring were identified as the most impactful areas for improvement. The team discussed which stages of the launch and execution process would benefit most from AI integration. By focusing on these two critical areas, they aimed to create a solid foundation for improving overall efficiency.

Step 7: Move and Reformulate the Two Selected Focus Points

These became their anchor points: the AI-Powered Tracking Optimizer, which ensures accurate and consistent tracking setups, and the Automated Budget Monitor, which streamlines budget tracking and management with minimal manual intervention. During this step, they redefined their focus areas to clearly outline how AI would enhance each process. This clarity helped the team understand the specific roles AI would play in their launch and execution workflow.

Integrating and Examining Neighbouring Steps (Steps 8–9)

Step 8: Integrate the Anchor Points into the Existing Process

They introduced the AI-Powered Tracking Optimizer to configure and validate tracking tools based on standardised templates and campaign inputs. Simultaneously, they implemented the Automated Budget Monitor to track expenditures, send automated alerts for budget thresholds, and generate real-time budget reports. They mapped out how these AI tools would fit into their current workflow, ensuring a seamless transition. The team discussed the integration points and how each role would interact with the new systems.

Step 9: See How Neighbouring Steps Are Influenced

AI can now suggest optimal tracking configurations based on campaign data during the tracking setup phase. Consistent performance reporting enhances the clarity and professionalism of their client communications. Additionally, automated budget tracking ensures timely alerts and accurate financial oversight, reducing the risk of overspending. The team evaluated the ripple effects of integrating AI into their launch and execution process. This foresight helped them anticipate and address potential changes in related stages, ensuring a holistic improvement.

Big-Picture Review & People-AI Interactions (Steps 10–12)

Step 10: Rethink the Entire Process

They stepped back to ensure their revamped workflow addressed the initial pain points without introducing new challenges. It was about making sure AI would enhance their efficiency and consistency while keeping their strategic and creative edge intact. The team engaged in a thorough review, discussing whether the new integrations aligned with their overall goals and maintained their agency’s unique value proposition. This step was crucial for ensuring that the AI tools complemented rather than compromised their launch and execution processes.

Step 11: Add How and Where People Could Help AI Perform Well

The Campaign Manager (CM) oversees the AI-Powered Tracking Optimizer, providing strategic inputs and refining outputs. The QA Specialist (QA) collaborates with AI tools to conduct thorough quality checks and ensure tracking accuracy. The Finance Manager (FM) utilises the Automated Budget Monitor to manage and adjust budgets based on real-time data. The Creative Director (CD) ensures that campaign elements align with tracking setups and budget allocations. The Data Analyst (DA) supplies data-driven insights to inform tracking and budget strategies. Lastly, the Project Manager (PM) coordinates the Automated Budget Monitor, ensuring smooth budget tracking and timely adjustments. They delineated each team member’s role in the AI-enhanced process, ensuring that everyone knew how to interact with the new tools effectively. This clarity fostered ownership and accountability within the team.

Step 12: Mark Sketches Where a Person Interacts with AI

They created a flow diagram to visualise interactions. The Campaign Manager inputs campaign requirements into the AI-Powered Tracking Optimizer. The QA Specialist reviews and personalises AI-generated tracking setups. The Finance Manager monitors and adjusts budgets using the Automated Budget Monitor. The Creative Director ensures alignment with creative standards. The Project Manager utilises the Automated Budget Monitor to track and manage budget timelines. By mapping out these interactions, the team gained a clear understanding of their touchpoints with the AI tools. This visual aid facilitated smoother collaboration and highlighted areas where human input was essential.

Refining Anchors & Tasks (Steps 13–14)

Step 13: Revisit Anchor Points and Improve Descriptions

They refined their anchor points to ensure clarity and precision. The AI-Powered Tracking Optimizer now ensures accurate and consistent tracking setups based on standardised templates, campaign inputs, and data-driven insights. The Automated Budget Monitor manages budget tracking, sends automated alerts, and generates real-time reports through AI-driven task assignments and notifications. This step helped the team fully grasp the functionalities and benefits of each AI tool, facilitating better implementation.

Step 14: Break Each Anchor Point into Four Sub-Steps

For the AI-Powered Tracking Optimizer:

1. Template Configuration: Define standardised tracking setup templates with consistent parameters and metrics.
2. Campaign Data Integration: Input campaign-specific information and tracking requirements into the AI system.
3. Tracking Setup: AI configures tracking tools based on templates and campaign data.
4. Human Verification: QA Specialist reviews, edits, and personalises the AI-generated tracking setups.

For the Automated Budget Monitor:

1. Submission for Budget Tracking: Campaign budgets are automatically routed to the Automated Budget Monitor.
2. Budget Allocation: AI allocates budgets based on campaign requirements and historical data.
3. Automated Alerts: AI sends automated alerts when budget thresholds are approached or exceeded.
4. Final Budget Approval: Finance Manager oversees the final budget approval process, ensuring budgets are realistic and adhered to before campaign launch.

Breaking down each anchor point into actionable sub-steps provided a clear roadmap for implementation. The team could now follow these detailed steps to ensure each aspect of the process was addressed effectively.

Final Declarations & Ethical Checks (Steps 15–17)

Step 15: Restate the AI Technologies Used

They utilised AI Workflow Automation through machine learning algorithms for tracking setup and budget management. AI Data Integration consolidated campaign performance data from various sources, enhancing the depth and accuracy of insights. AI Performance Analytics ensured accurate tracking and reporting of campaign outcomes. They reiterated the technologies involved to ensure everyone was on the same page regarding the tools they were implementing. This step reinforced the technical foundation of their new process.

Step 16: Give the New Process a Catchy Name

They named their new process “LaunchSync,” highlighting the seamless synchronization and intelligent automation it brings to their campaign launch and execution workflows. Choosing a memorable name helped the team embrace the new process. It fostered a sense of identity and ownership, making it easier to communicate and refer to the system internally.

Step 17: Individually Select Relevant AI Ethics Cards

They selected Transparency, Privacy, Fairness, and Accountability. Transparency ensures they clearly communicate AI involvement in tracking and budget management. Privacy safeguards client and campaign data within the AI systems. Fairness avoids biased resource allocations and ensures equitable treatment of all campaigns. Accountability maintains human oversight over AI-generated tracking setups and budget allocations to ensure accuracy and integrity. Addressing ethical considerations was paramount. The team discussed how to uphold these principles, ensuring their AI integrations were responsible and trustworthy.

Scenario Planning & Realignment (Steps 18–21)

Step 18: Write Best- and Worst-Case Scenarios

In the best-case scenario, LaunchSync streamlines tracking and budget management, enhances data accuracy, and reduces campaign launch and execution time by 50% within three months, leading to a 20% increase in client satisfaction and retention. In the worst-case scenario, AI-generated tracking setups are inaccurate, leading to tracking errors and budget slip-ups, resulting in a decline in client trust. The team brainstormed potential outcomes, both positive and negative. This foresight helped them prepare strategies to maximise benefits and mitigate risks.

Step 19: Reflect on Implications for the AI Solution

To mitigate risks, they implemented rigorous Quality Assurance measures to ensure accuracy in AI-generated tracking setups and budget allocations. Continuous Training of AI models with new data improved relevance and authenticity. Additionally, Feedback Loops encouraged team feedback to refine AI tools continuously. They discussed practical steps to address the worst-case scenarios, ensuring that their AI tools remained effective and trustworthy.

Step 20: Share with the Team and Align

They held an all-hands virtual meeting to present LaunchSync. Each role understood their responsibilities and the importance of collaboration in the AI-enhanced workflow. The team was excited and committed to the new process. Sharing the plan with the entire team fostered alignment and enthusiasm. Everyone felt involved and motivated to contribute to the successful implementation of the new system.

Step 21: Go Back to the Solution and Refine

Based on team feedback, they integrated advanced tracking verification features for QA Specialists to easily modify AI-generated setups, simplified the Automated Budget Monitor for easier navigation and management, and scheduled comprehensive training sessions to ensure all team members were proficient with the new tools. Refining the solution based on feedback ensured that the tools were user-friendly and met the team’s needs effectively. This iterative improvement was key to smooth adoption.

Note: Typically at this point a “Tech Check” is done by either external partners or internal tech teams to see if the proposed solution is viable from a technical point of view. If yes, there would be an agile prototype phase to develop and fine-tune before going into full development and integration.

Pilot & External Feedback (Steps 22–24)

Step 22: Pitch the Solution to External Users

They rolled out a pilot version of LaunchSync with select clients. Clients appreciated the professional and accurate campaign launches, but some desired more personalised tracking setups, prompting further refinement. Engaging external users provided valuable insights into how their launch and execution processes were perceived, highlighting both strengths and areas for improvement.

Step 23: Seek Feedback

They compiled feedback into a Miro board, highlighting strengths such as improved tracking accuracy and reduced budget overspending, alongside areas for improvement like enhanced personalisation and flexibility in tracking parameters. Organising feedback systematically allowed them to identify common themes and prioritise adjustments effectively.

Step 24: Discuss Feedback and Improve the Concept

Key adjustments included configuring AI tools to incorporate client-specific nuances and preferences, enabling the AI-Powered Tracking Optimizer to learn from past successful campaigns and client feedback for better future outputs, and improving the workflow interface’s usability based on client and team suggestions. Implementing these refinements ensured that LaunchSync was more responsive to client needs and user-friendly for their team. With these refinements, LaunchSync was ready for full-scale implementation.

The Final Solution – “LaunchSync”

Recap of Pain Points Addressed

By the end of their 24-step journey, they had successfully tackled several key issues. Tracking Errors were resolved through standardised QA templates and AI-powered tracking optimisations, ensuring uniformity and accuracy across all campaigns. Budget Slip-Ups were unified with AI Workflow Automation, bringing together budget tracking from Campaign Managers and Finance Managers seamlessly. Overload Capabilities were mitigated by Automated Deadline Managers that incorporated checks to prevent team overload and ensure timely campaign launches. Finally, Time-Consuming Processes were significantly reduced through AI Workflow Automation, streamlining the campaign launch and execution timelines.

The Pilot & Next Steps

Next Steps

Looking ahead, they plan to integrate machine learning models to enhance tracking optimisations with more nuanced and personalised insights. They aim to incorporate deeper personalisation features to cater to diverse client needs and implement AI-driven analytics to predict campaign success rates and optimise their strategies accordingly.

Why a Step Process Works

Thoroughness vs. Speed

While the temptation to deploy AI solutions rapidly is strong, the complexity of campaign launch and execution demands a thoughtful approach. Their structured AI Design Sprint™ ensured comprehensive problem identification, tackling root causes rather than just the symptoms. Systematic AI exploration allowed them to methodically evaluate AI solutions to find the perfect fit. Inclusive team involvement engaged all relevant roles, fostering ownership and collaboration. Robust testing and feedback integration validated solutions through pilot testing and iterative refinements.

Everyone Sees Their Part in the Puzzle

From the Campaign Manager overseeing AI-powered tracking optimisations to the Analytics Specialist leveraging unified data for strategic decisions, every role understood their contribution. This holistic involvement ensured LaunchSync was seamlessly integrated and embraced across the agency.

AI with Purpose, Not Gimmick

Each AI solution directly addressed specific pain points. AI Workflow Automation enhanced consistency and efficiency in tracking and budget management. AI Data Integration unified campaign data for coherent and comprehensive execution. AI Performance Analytics ensured accurate tracking and reporting of campaign outcomes. Ethical considerations, such as transparency and accountability, were integral, ensuring AI served as a tool for empowerment rather than replacement.

Key Takeaways

The Resulting “LaunchSync”

Their final LaunchSync includes standardised campaign tracking templates, ensuring consistent quality and accuracy across all launches. The AI-Powered Tracking Optimizer drafts comprehensive tracking setups based on standardised templates and campaign inputs. Human Verification allows QA Specialists to personalise and enhance AI-generated tracking setups. The Automated Budget Monitor tracks and manages campaign budgets, ensuring timely alerts and accurate financial oversight. Unified Data Integration consolidates inputs from Campaign Managers, QA Specialists, and Finance Managers into a single launch system. Lastly, their ethics framework maintains transparency about AI involvement and ensures client data privacy.

Lessons

Tailoring AI tools to address specific pain points rather than adopting generic solutions was crucial. Engaging all relevant roles ensured a comprehensive and cohesive strategy implementation. Upholding ethical standards maintained trust and integrity in their AI-driven processes. Continuous feedback and iterative refinement enhanced the effectiveness and adaptability of their AI tools.

Forward-Looking Upgrades

With LaunchSync in place, their agency plans to develop a machine learning-based tracking optimiser to enhance personalisation and contextual relevance. They aim to expand to multimedia campaign tracking by incorporating AI tools for generating and integrating multimedia performance metrics. Additionally, integrating predictive analytics will help forecast campaign success rates and proactively adjust their strategies.

Last Thoughts

In the fast-paced world of digital marketing, blending strategic planning with precise execution is key. Integrating AI into your campaign planning and production strategy isn’t just about keeping up with trends—it’s about strategically implementing tools that solve real challenges and drive meaningful results.

For agencies struggling with tracking inaccuracies and budget slip-ups, embracing a structured AI Design Sprint™ can lead to a unified, efficient, and data-driven campaign ecosystem. Gather your team, dive into a collaborative AI Design Sprint™, and watch your campaign launch and execution efforts transform into a synchronised and impactful force.