What Your Data Doesn't Tell You
As a growth-minded GTM leader, you rely on data to guide your decisions. You track MQLs, conversion rates, and pipeline contributions. But what about those times when numbers don’t tell the whole story? When your conversion rates fluctuate unexpectedly despite no apparent changes to your marketing efforts?
Even more intriguing - what about when performance unexpectedly improves? When your lead-to-opportunity conversion rate spikes for no apparent reason? These unexpected shifts (which can be either positive or negative) can have explanations that don't appear in your standard reports.
Your GTM performance exists within a complex ecosystem influenced by numerous factors that may not appear in your analytics. Let's explore these external factors that might be affecting your numbers, because context around the data also matters.
Macroeconomic Factors
Economic conditions can drive shifts in your funnel metrics that have little to do with your actual marketing and sales activities.
Imagine you've been running an evergreen campaign, yet your conversion metrics have significantly changed from last quarter to this quarter. Consider the broader economic environment:
Current events: Major global or national events can shift buying priorities and timelines without warning (a great example of this is what happened during the COVID-19 pandemic with Zoom).
Industry-specific fluctuations: Your target vertical might be experiencing budget constraints or unexpected growth.
Seasonal budget cycles: Some industries have variable spending patterns tied to fiscal quarters.
Market uncertainty: Economic uncertainty can lead to extended decision-making timelines.
These macroeconomic factors typically don't show up in your attribution data but can significantly influence buying decisions. Buying committees' behaviors shift in response to external pressures and opportunities, creating conversion and/or win rate changes unrelated to campaign effectiveness.
Organizational Changes
Internal processes or dynamics of your organization can create downstream impacts to your data. What appears as a marketing or sales performance issue might actually be the result of organizational evolution.
Changes within your company can create ripple effects throughout your funnel:
Sales team transitions: New sales reps need time to ramp up, which impacts capacity and conversion rates.
Misaligned process changes: Sales might modify qualification criteria without realizing how it impacts marketing’s ability to measure their KPIs.
Changes in lead scoring: Adjustments can create artificial spikes or drops in conversion rates.
An example scenario: SQLs (Opportunities) decrease while MQLs remain steady because a sales leader adjusted opportunity creation criteria without updating the marketing team or analysts. The data indicates a conversion issue, but the underlying cause is an alignment gap.
Technical Infrastructure Changes
As technology platforms evolve, your ability to track, attribute, and measure performance shifts. These changes can create apparent performance fluctuations that have nothing to do with your actual marketing effectiveness.
Here are some examples:
Cookie consent and privacy regulations: Recent changes are reducing visibility into organic traffic and compromising attribution capabilities, creating artificial spikes to direct traffic and dips to organic traffic even when buyer behavior remains stable.
Marketing automation system changes: Updates to your platform can alter how leads are processed and scored, potentially creating sudden shifts in MQL volume or quality.
Attribution model changes: Shifts in attribution methodology can create apparent performance increases or decreases unrelated to actual effectiveness changes.
These technical shifts can create misleading data patterns that mask real issues or suggest problems where none exist.
Competitive Landscape Changes
Markets are dynamic ecosystems where competitive moves can rapidly reshape buyer behavior. When your metrics change without internal explanation, the answer may lie in how your competitive position has evolved.
Some common scenarios are:
Competitor pricing changes: When competitors adjust pricing, it impacts how prospects evaluate your solution. A competitor's discount can slow your conversions, while their price increase might create an opportunity surge.
New market entrants: Emerging solutions can divide your audience's attention or validate your market category and accelerate your pipeline.
Competitive feature releases: When competitors release features addressing customer pain points, it affects win rates and conversion velocity, but can also create differentiation opportunities.
These competitive dynamics typically aren't visible in your CRM data, but they significantly alter the environment in which your GTM motions operate.
Finding Signal Through the Noise
So how can you account for these external factors and make informed GTM decisions? When your data shows unexpected changes - whether positive or negative - looking beyond the dashboard becomes critical. The goal isn't just to understand what happened, but to develop systems that help you identify and respond to these external influences proactively.
Contextual Data Collection
Building a more complete picture of your GTM performance requires intentionally capturing information that traditional analytics systems miss. This contextual information provides the backdrop against which your performance metrics can be properly understood and interpreted.
Expand your data collection beyond core metrics to include contextual information:
Win/loss analysis: Document why deals are won or lost, including external factors mentioned by prospects. Patterns in these comments often reveal external forces affecting your funnel.
Sales feedback loops: Create structured processes for sales to report market conditions and competitive dynamics they observe in customer conversations.
Economic indicator tracking: Monitor macro and industry-specific economic metrics alongside your marketing data to identify correlations between market conditions and performance shifts.
Internal change logs: Document significant internal changes (personnel, processes, systems) and correlate them with performance shifts. Often the answer to conversion rate changes lies in these seemingly minor internal adjustments.
A practical approach is maintaining a "GTM context log" where the team records significant events (both internal and external) that might impact performance. This contextual information becomes valuable when analyzing unexpected data trends, whether positive or negative.
Cross-Functional Visibility
External factors affect different parts of your organization in different ways. Creating visibility across functions helps connect dots that might otherwise remain separate, revealing patterns and causes that no single department could identify alone.
Reduce information silos:
Regular cross-team syncs: Establish consistent communications between marketing, sales, product, and customer success to share observations about market changes and their impacts.
Customer advisory boards: Gather direct feedback on market conditions from your customers, who often have valuable perspectives on industry trends and competitive dynamics.
Competitive intelligence sharing: Develop systematic ways to collect and distribute competitive insights across departments, ensuring everyone understands how the competitive landscape is evolving.
Cross-functional alignment: Make sure marketing and sales are in regular communication about process, definition or personnel changes, and are aligned on how to handle the buying journey.
Final Thoughts: Context Matters
As GTM teams, we value the insights data provides. However, even comprehensive dashboards tell only part of the story. When conversion rates unexpectedly increase or decrease, the explanation can reside in the space between your dashboards - in the external factors that influence buyer behavior but don't appear in your reports.
The next time your numbers show an unexpected trend, take time to look beyond your immediate metrics. Ask: "What else might be happening that our dashboards aren't capturing?" By considering the external factors we've discussed, you can develop a more complete understanding of your GTM performance and avoid both false alarms and misattributed successes. Effective data analysis combines quantitative metrics with qualitative understanding of the broader context in which your business operates.
Further Reading:
https://martech.org/how-to-put-marketing-data-into-meaningful-context/
https://www.crayon.co/blog/competitor-analysis-trends