Picture entering a home crammed with a disordered medley of furniture—an overwhelming abundance of disparate chairs, a deficiency of tables, and an array of both undersized and oversized couches spanning the 80s, 90s, and 2000s. It’s a haphazard mishmash, creating an environment where a casual stroll could quickly turn into a precarious situation, with the risk of tripping or taking an unexpected fall.

It sounds like an interior designer’s nightmare, but the scene actually mirrors the way many organizations have constructed their technology stacks – bloated, outdated and full of mishaps waiting to happen.

Welcome to the age of the analytics “frankenstack:” a haphazard, disjointed collection of digital analytics tools and technologies that have been pieced together over time. It’s a scenario that typically plays out when different teams or departments within an organization adopt various analytics solutions independently. It wasn’t on purpose – it represented the culmination of years of isolated decision-making.

The result? Data overload. Our recent benchmark report, 2023 Digital habits: Inflation and beyond, found that 66% of digital teams see more than half of their customer insights available simply go unused each month. There is also overlap, with 31% of digital leaders say the data in their tech stack is repetitive. 

The lesson learned is clear: it’s time to modernize and optimize our analytics tech stack. But doing this involves carefully curating the right mix of tools, capabilities and systems to align seamlessly with our business objectives.

So how can digital teams optimize their stack to boost cross-team alignment, customer-centricity and business ROI? It all starts with following a few simple steps to audit and consolidate the various parts of your tech stack today. 

Recognizing the triggers to re-evaluate your tech stack.

There are pivotal moments that can compel your company to re-evaluate and optimize your analytics stack. Understanding these triggers is key to ensuring that your technology ecosystem remains agile, efficient, and aligned with your evolving business needs. Let’s delve into the events that might signal it’s time.

• You’re launching a new product: With any new site, app, page or feature, you need deeper insights into user behavior and performance, so you know what’s working/what’s not and how to fine-tune the user experience.
• Your tech stack blew up (or is slowly imploding): Critical data outages and/or customer-facing issues pop up regularly due to a mess of intertwined code, tools and systems. It’s time to re-platform and modernize. Additionally, budget changes may mean you’re looking to consolidate your tech stack for cost savings.
• Your contract is renewing: Contract renewals can trigger vendor evaluations/RFIs. Or you may need to upgrade or migrate existing analytics software, like GA4. 
• You’re launching a new campaign: You’re investing big money to get people to your website/app. This means maximizing ROAS and marketing spend, reducing bounce rates and abandonment to ensure you squeeze the juice from every marketing dollar.

Identifying analytics needs for every team.

Discover how each team can unlock the full potential of an optimized analytics stack tailored to their specific needs.

5 steps to optimize your analytics tech stack.

1.Uncover data landmines.

In the quest for the ideal analytics mix, your first mission is to take a deep dive into your siloed data ecosystem. Unearth those hidden landmines –  outdated, intertwined analytics tags or code that might be waiting to blow up in your face, causing a critical data outage or customer-facing issue. At the same time, scrutinize your analytics tools for any gaps or redundant and overlapping capabilities. The goal? Uncover all the inefficiencies that might be preventing customer insight.

• Key questions to address:
  • Tool redundancy: How many overlapping categories of analytics tools do you currently have? Is your product analytics tool separate from experience analytics which is separate from web analytics?
  • Shared view of customer experience: How do you ensure your analytics stack fosters a unified and holistic view of the customer?
  • Data capture efficiency: How long does it take to define data capture requirements and add new tracking tags (and maintain old ones) for each product release? Is autocapture available?

2. Bridge the gap between business, behavioral, and technical data (and mobile).

Effectively optimizing your analytics stack means dismantling data silos and fostering improved communication and collaboration. This can be achieved by linking three essential data types—business, behavioral and technical data – into a unified platform, thereby providing a single view of customer-defined truth for all team members and stakeholders. This leads to enhanced product optimization through nuanced insights such as evaluating conversion rates across web and native app customers.

• Key questions to address:
  • Continuous monitoring: Can you monitor and detect behavioral anomalies and quantify frustration in a single platform in real-time?
  • Collaboration: To what extent does your current data infrastructure facilitate seamless communication and collaboration between business and technical teams?
  • Business, technical + behavioral data: Do you seamlessly capture business, technical and behavioral data in one platform for a comprehensive view of your business and customers?
  • Mobile insights: Are web and native app data connected, and is there parity?

3. Watch for “bolt-on” capabilities. 

As analytics tools rapidly converge and adopt new capabilities for innovation, be vigilant as you shop around. Be wary of tools relying heavily on competitive acquisitions, leading to questionable integrations with bolt-on capabilities that may not seamlessly align with the overall technology. For instance, many vendors acquire session replay without effectively integrating it into their tool set. Ensure each component aligns strategically with organizational goals, maintaining a streamlined and purposeful analytics stack while avoiding unnecessary complexities.

• Key questions to address:
  • Growth through acquisition: Have you witnessed analytics tools adding new capabilities only by acquiring their competitors over time?
  • Integration quality: How well are their bolt-on capabilities integrated? Do you still find yourself using a data lake and a CDP to stitch various data sources together?
  • Strategic alignment: Are the newly acquired capabilities in line with your strategic goals and objectives?
  • Quantified impact: Does your analytics tool seamlessly quantify the impact of frustration with the customer experience at scale?

4. Consolidate without sacrificing quality.

As you embark on the consolidation journey, remember, it’s not just about efficiency; it’s about better business outcomes and enriching the lives of customers. Streamline your analytics stack to unlock enhanced insights and improved ROI. Yet, don’t compromise on the richness, reliability and speed to insight.

But your consolidation efforts cannot survive in a vacuum. You need a customer-centric analytics stack that delivers tangible returns. Measure and showcase the ROI resulting from this consolidation. Highlight how a unified stack elevates your understanding of customer behavior, contributes to cohesive decision-making, and ultimately boosts customer satisfaction. This step is all about aligning metrics with a unified truth about your customers.

• Key questions to address:
  • Efficiency vs. outcomes: How can we strike a balance between streamlining our analytics stack for efficiency and ensuring it leads to better business outcomes?
  • Customer-centric focus: In what ways can we ensure that our consolidation efforts are centered around creating a customer-centric analytics stack?
  • Richness, reliability, and speed: How do we maintain the richness, reliability, and speed to insight in our analytics stack while consolidating?
  • Tangible returns: What metrics should we use to measure and showcase the tangible returns resulting from the consolidation of our analytics tools?
  • Unified understanding: How can a unified analytics stack contribute to a cohesive understanding of customer behavior, facilitating more informed and unified decision-making?
  • Boosting customer satisfaction: In what specific ways does a consolidated analytics stack contribute to boosting customer satisfaction, and how can we measure these impacts?

5. Continuously refine.

Your analytics journey is a perpetual evolution. Keep the customer at the epicenter of every decision. Regularly reassess and refine your analytics stack, adapting to technological advancements and evolving business objectives. This ensures that your data ecosystem remains agile, relevant, and steadfastly aligned with your organizational goals.

• Key questions to address:
  • Perpetual evolution: How can we establish a mindset of continuous refinement in our analytics journey using Continuous Product Design?
  • Customer-centric approach: What strategies can we employ to ensure that the customer remains at the epicenter of every decision during the refinement process?
  • Regular reassessment: What are the specific criteria and triggers for regularly reassessing our analytics stack?
  • Adaptation to technology: How do we stay abreast of technological advancements and integrate them into our analytics stack?
  • Alignment with business goals: In what ways can we ensure that the ongoing refinement aligns steadfastly with our evolving organizational goals?
  • Agility and relevance: What measures can be implemented to maintain agility and relevance in our data ecosystem throughout the continuous refinement process?

Get ready for a new era of analytics convergence.

For years, we’ve journeyed through the maze of fragmented analytics tools. Today, let’s paint a picture of a fresh paradigm—an analytics ecosystem that aligns insights seamlessly across teams. Envision a world where these tools converge to provide not just fast insights but a singular, customer-defined truth. 

This consolidation isn’t just about eliminating redundancies; it’s about transforming the very essence of how we understand and optimize customer experiences. Step into this new era of analytics, where unity becomes the catalyst for profound insights and unparalleled digital optimization.