How to Supercharge Your MarTech Stack
Recipe for a "Secret Sauce", Centralised Data Platforms, and the Before and After of Implementation
This piece is a community contribution from Michele Nieberding, Director of Product Marketing at MetaRouter. She is passionate about devising robust strategies for customer centricity and has solid expertise on data platform nitty-gritty, approach, and practices that ensure a state of user-first experience at all times. We highly appreciate her contribution & readiness to share her knowledge with MD101.
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Data is the lifeblood of modern businesses, driving decision-making, enhancing customer experiences, and fueling growth. However, the value of data lies not just in its quantity but in its quality, reliability, and compliance with today's stringent enterprise standards.
As businesses navigate the convergence of trends like AI and data regulations, the importance of investing in a robust server-side data collection and syndication tool becomes increasingly apparent (and important) as a means to fuel the effectiveness of the overall tech stack.
Garbage In, Garbage Out Is a Real Thing
Garbage in, garbage out. It's a mantra echoed throughout the realms of data science and analytics. No matter how sophisticated your algorithms or how powerful your processing capabilities, they prove ineffective if you don’t have high quality data.
Imagine trying to cook a gourmet meal with spoiled ingredients – the results wouldn't be pretty. Or trying to build a house on a shaky foundation—inevitable catastrophe! That's what happens when you build a MarTech stack on a foundation of messy, siloed customer data.
Before we dig in, let’s talk about the harsh reality of customer data ecosystems today.
Data Labyrinth
Your data collection process might be a complex web of disconnected tools, leading to inaccuracies and security risks.Data Drudgery
Cleaning up poorly formatted data is a time-consuming nightmare that drains resources.Missing Pieces
Incomplete data, like missing customer IDs, hinders your marketing reach and personalization efforts.
Sound Familiar? These data issues can render even the most sophisticated MarTech tools ineffective.
Throwing Money at the Problem (and Missing the Mark)
Think about the MarTech investments you've made to solve these problems. Despite investing in various technologies to address these challenges, businesses often encounter lingering issues that impact the effectiveness of their tech investments, and find they are still struggling with data quality issues that limit their effectiveness.
Here’s what we hear all the time:
Trying to Improve AI Models: While Data Lakes or Data Warehouses aim to improve data quality, the time-consuming process of cleansing data from various sources persists.
Real-time Personalization: Investments in Customer Data Platforms (CDPs) fall short as businesses miss addressing a significant portion of their target audience (aka anonymous users).
Ad Spend Optimization: Tools reliant on third-party cookies, such as Data Management Platforms (DMPs), face challenges with disappearing cookies and tracking performance.
Data Security: Investments in consent management systems are critical but may not fully integrate with existing infrastructures, or collect and manage consent, but don’t enforce it consistently across vendors.
The “Secret Sauce,” Start with Better Data Collection
That’s why investing in a centralized, fully first-party, and privacy-centric customer data collection tool upfront (aka as your foundation) is a game-changer for your MarTech stack’s overall performance and ROI.
A modern customer data collection tool serves as the foundational pipeline component for ensuring data integrity and maximizing the benefits of other tech investments. It collects data from all sources, cleans it up in-flight, ensures compliance, and makes it readily available for your entire MarTech stack.
Think of it as the clean water source that allows you to use all your other tools effectively, without the need for constant purification in downstream tools.
A single pipeline and infrastructure allows data teams to review incoming data and flag non compliant data faster…This will be essential to scale.
~ Michael Borrelli , Co-founder AI and Partners
Your existing MarTech tools become more effective with high-quality data feeding them. A study by Scott Brinker & Frans Riemersma (The State of Martech 2024) even found a correlation between increased MarTech maturity and a higher company revenue-per-employee ratio, but only when the data quality was sufficient. Investing in a modern data collection tool can help you achieve that data maturity.
📝 Note from Editor
Learn more about central platform models here
Learn more about standard centralised collection model here and here
Added Benefits of a Modern Data Collection Tool
Improved Data Quality
As we’ve discussed, clean, consistent data fuels better insights and decision-making across your MarTech stack. Imagine the impact on your customer lifetime value (CLTV) calculations or customer segmentation if your data were higher quality.
But data quality is one of those things that requires an ongoing strategy. If you’re not constantly keeping tabs on your data accuracy and consistency, you’re bound to end up in a mess of inaccurate data in a matter of months or even weeks. A modern data collection tool gives structure to your data practices, imposes procedures that ensure accuracy, and raises red flags when things seem to be going wrong.
Streamlined Workflows
Having all customer data in one place streamlines operational processes. Instead of navigating multiple systems or having to manually clean up data in various places, teams can access the information they need from a single source, saving time and reducing the risk of errors. Your marketing team will be thrilled because they focus on crafting targeted campaigns instead of wrestling with messy data.
Increased Efficacy and Signal Density
Enable long-lasting, first-party cookies for 12 months (instead of a couple weeks!). This enhances marketing efforts and CDP visibility with more comprehensive insights into customer behavior for known and unknown visitors. It also improves measurement efficacy with more deterministic IDs without having to surface a large amount of browser details.
Anonymous User Tracking
While ID spines and clean rooms offer valuable solutions, they often rely on data points that are increasingly unavailable due to privacy regulations. Server-side data collection and augmentation empowers you to access valuable identifiers that wouldn't be readily available through traditional methods.
Let’s look at an example. A company may want to tell Meta about a purchase executed on their website, as it may be critical to converting on an advertising campaign. But what if they don’t want Meta’s tag to have uninhibited access to their website? Most server-side tag managers can deliver this data from the server, but only if the user has previously provided an email, thus deprecating the need for Meta’s site tag to collect this data directly. But what if the user has never provided any PII?
In this scenario, you need a data collection tool that can create a common, anonymous link between the website and Meta’s servers, even if PII is never provided. This is a game changer for any company, especially those experiencing a majority of anonymous traffic.
Deeper Customer Understanding
Get a complete view of your customers for better personalization and marketing campaigns. A holistic understanding of your customers across all touch points empowers you to deliver exceptional experiences that foster loyalty.
Centralized customer data collection tools can track customer interactions across multiple domains or platforms. This capability is particularly valuable for businesses with diverse online properties, such as separate websites for different brands, product lines or regional markets. By linking these interactions, businesses gain a holistic understanding of the customer journey, enabling more accurate attribution and optimization of marketing efforts.
Improved Security & Compliance
A modern data collection tool helps ensure data security and compliance with evolving regulations. With data breaches becoming more common, a modern data collection tool can be a critical line of defense for your customer information by protecting you from data leaks and vulnerabilities. A modern data collection tool should also integrate with a Consent Management Platform (CMP) or in-house consent tool to enforce your users’ unique consent preferences across your entire vendor ecosystem—because consent that you collect and manage is only good if you enforce it!
Building an Optimized MarTech Stack
A modern data collection tool is the foundation for a data-driven marketing strategy that delivers real results, maximizes your return on investment, and unlocks the true potential of your customer data.
The future of a performant MarTech stack isn't just about consolidation or composability, but rather about enhancing the value of the entire stack by leveraging data integration and tag management capabilities to enrich customer data (see Quadrant 1 in the image below)
📝 Note from Editor
Learn more about semantics (tags, descriptions, and overall context)
Learn more about standard context implementations
According to Scott Brinker and Frans Riemersma, while efficiency in martech is important, focusing on effectiveness, particularly in generating revenue with a customer-centric approach, is crucial. Research indicates a correlation between a company's revenue-per-employee ratio and its MarTech maturity, suggesting that investing in MarTech can positively impact overall company value.
However, the relationship between MarTech maturity and business value isn't always straightforward, as different industries and companies experience varying outcomes, necessitating a nuanced approach to MarTech investment decisions based on performance correlations and quadrant analysis, such as the one below for Banking and Financial Services.
Better data = better results, and this amplifies the ROI of your entire tech stack, wherever that customer data is being sent.
What makes centralised data platforms the best way to accelerate the performance and ROI of a MarTech stack is the ability to feed downstream tooling like CDPs, Data Warehouses, Analytics tools, and other MarTech/AdTech platforms with the most consistent, accurate, and compliant customer event data possible - and all in real time!
The Process: How to Get Started
Step 1: Define Your Goals & Needs
Before diving headfirst into tools, take a step back and define your goals. What are you hoping to achieve with your customer data? Here are some questions to consider:
What customer insights do you need to make better marketing decisions? (e.g., purchase behavior, churn rate, customer lifetime value)
What marketing channels do you use? (e.g., email marketing, social media, website)
What level of personalization do you want to achieve? (e.g., basic segmentation, individual customer recommendations)
What are your data privacy and security requirements?
Step 2: Assess Your Current Customer Data Landscape
All data sources are not created equal. Some sources, like manual entries from a support or retail setting, will require more standardization to ensure accuracy.
Take stock of your existing data sources and tools. This includes:
Customer data sources: Look at your CRM, digital properties including your website, marketing automation platform, and social media platforms.
Data storage solutions: Data warehouse, data lake, etc.
Data analytics tools: Business intelligence (BI) dashboards, and marketing analytics tools.
Step 3: Prioritize a Modern Data Collection Tool
Think of this as the cornerstone of your data stack–garbage in/garbage out is a real thing! It acts as a central hub, collecting data from all your sources, cleaning it up, and ensuring consistency before that data is sent anywhere else. This high-quality data becomes the fuel for the rest of your MarTech tools.
Investing in a modern data collection tool upfront can significantly improve the effectiveness of your entire stack; from overcoming browser restrictions and ad blockers to collect more events to improving conversion tracking accuracy to ensuring compliance from the start to bot filtering so you don’t waste ad spend on non-human interactions.
Step 4: Choose the Right Tools for Your Needs
Now, it's time to explore specific tools based on your goals and data needs. Here are some key categories to consider:
Customer Data Platform (CDP): Unifies customer data across touchpoints for a 360-degree customer view and personalized marketing campaigns.
Data Management Platform (DMP): Manages audience data for ad targeting and campaign optimization. (Remember, with the decline of third-party cookies, look for a DMP that leverages first-party data and identity solutions.)
Customer Relationship Management (CRM): Tracks customer interactions and manages relationships throughout the customer journey.
Marketing Automation Platform (MAP): Automates marketing tasks such as email campaigns and lead nurturing.
Data Analytics Tools: Provide insights into customer behavior, campaign performance, and overall marketing effectiveness.
Customer Engagement Platform: Designed to help businesses interact with their customers across various touch points and channels in a meaningful and personalized way.
Step 5: Integrate and Automate Your Data Flow
Once you have your tools, ensure seamless data flow between them. Most tools offer APIs or connectors to facilitate integration. This allows for automated data transfers, minimizing manual work and ensuring data consistency.
Example here with MetaRouter + GrowthLoop + BigQuery
Step 6: Focus on Data Quality and Governance
Data quality is paramount. Invest in data cleaning processes and establish clear data governance policies to ensure data accuracy, security, and compliance with regulations like GDPR and CCPA.
Think of data governance at the point of collection like the water supply in your own home. Imagine if you had a dozen taps, and each one poured out unfiltered water. To make that water safe to drink, you'd have to clean and boil it at every single tap, a process that's not just time-consuming but also terribly inefficient.
Now, picture an alternative scenario. What if, right at the source, you could filter and purify the water once? This way, you'd ensure that clean and safe water flows from every tap in your house. It's all about preventing data pollution and ensuring that your data is clean, compliant, and top-notch quality right from the very beginning. Instead of trying to clean it up at multiple downstream locations, you take care of it right at the source.
We hear this all the time– that when data gets where it needs to go (i.e. straight into Facebook for conversion and measurement), then it's too late to flag it for potential compliance concerns. An MDM may identify a risk and alert you that “some identity data got collected that violates policies,” but if it's already sitting inside Facebook, you’ve already had a violation, you now have to report that, and now you’re in triage.
By starting with a data collection tool that integrates data governance and compliance into their tool, such as Advanced Consent Enforcement, you can proactively ensure your data is secure (and avoid hefty fines).
Step 7: Continuously Monitor and Optimize
Your data stack is a living organism, not a set-it-and-forget-it system. Regularly monitor data quality, track key performance indicators (KPIs) aligned with your goals, and iterate on your stack based on insights and evolving needs.
Also check for redundancy in tracking tags, and identify which third-party tags you can remove.
Final Note
In the complex landscape of customer data management, investing in a modern data collection and integration channel like MetaRouter is crucial for ensuring data quality, reliability, and compliance of your customer data from the start–before it reaches any downstream tooling. By centralizing and harmonizing customer data, businesses can unlock the full potential of their tech investments and drive meaningful growth.
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