Growth marketing analytics guide: What to track and how

Growth marketing analytics help uncover the tactics that work, from identifying your highest-value audiences to optimizing conversion funnels and retaining loyal users.

In fact, our 2025 Marketing Data Report found that 42% of marketers package to invest in A/B testing and campaign experimentation this year. That's a clear signal that data-driven iteration is becoming central to modern marketing strategy.

In this guide, we'll explore which metrics matter most and how to analyze them effectively to drive smarter marketing decisions.

Advanced techniques for analyzing growth marketing data

Growth marketing differs from other marketing methods in its focus on revenue and customer growth, which requires specialized analysis methods.

Growth marketers use different types of marketing analytics to understand how audience behavior contributes to high growth. They run experiments that seek to pinpoint growth levers and scale the marketing tactics that work.

Target audience analysis

Customer data and sales tools that collect and store customer data can indicate the brand's target audience. Segmenting customer data based on age, gender, and location can allow you to draw conclusions as to who your actual customers are.

When combined with purchasing behavior — including seasonality, average order size, total order size, and number of repeat orders — you can understand (for example) what age group purchases the most often, which locations have the highest average order sizes, and whether marketing campaigns should target Valentine's Day or Flag Day.

When learning how to analyze marketing campaigns, growth marketers need to gather their data in a centralized location, like a marketing data management platform. This allows them to cross-reference these metrics instead of switching back and forth between sales and customer information tools.

Revenue and conversion rate analysis

A critical piece of growth marketing starts with understanding where and under what circumstances customers make purchases. A brick-and-mortar boutique with an ecommerce store will want to understand they’re getting sales both online and offline.

Once segmented into digital and in-person purchases, you should investigate which of the digital campaigns drives the most conversions. You may look at the website analytics to understand what source the purchasers come from, like the newsletter, online ads or search engine traffic. When the highest sources of purchaser traffic is identified, you can then look into the particular ads, newsletter copy or web pages that contribute the most to that traffic.

Once you know where conversions or purchases come from, you can attempt to replicate the elements of those campaigns across other campaigns or channels using A/B testing.

Competitor and market research analysis

In addition to watching what competitors put out into the market to stay ahead of trends, you can use several digital tools that will indicate competitor strengths and movements.

Search engine optimization (SEO) insight tools like Semrush and Ahrefs can identify web traffic, keyword ranking, and keyword targeting trends for competitors to understand the moves competitors make on their websites and how that affects sales.

Social listening software scans social media platforms for mentions of products, brands, and other keywords to understand who the target audience talks about and whether those conversations are positive or negative.

Funnel performance deep dive

A deep understanding of the customer journey to purchase comes from analyzing the customer funnel.

The top of the funnel contains the awareness stage, where customers hear about the brand or product. Mid-funnel stages include consideration and comparison stages, where customers learn more about the product and begin to make decisions. And the bottom of the funnel is the purchase stage.

Marketers can expect potential customers to drop off throughout the funnel. But careful analysis of campaigns through segmentation and cross-referenced data can identify precise drop-off points and iterate on them to optimize.

For example, marketers might analyze their mid-funnel and realize customers drop off at a critical information-gathering phase of the funnel. They can then make product information easier to understand and support outreach more accessible to engage customers for longer.

Cohort-driven retention strategies

Grouping users by acquisition time or behavioral patterns can reveal long-term retention trends and lifecycle insights, pinpointing when and why engagement drops and responding with interventions.

For example, a cohort analysis of an online subscription product might include all customers who converted during a fall campaign and follow their behavior over the next three months. This analysis may reveal that 20% of customers never use the product after that initial sign-up, and another 30% only use the product once more before cancelling their subscription.

These insights can help marketers plan personalized follow-ups for individuals who exhibit warning signs of these behaviors, improving monthly recurring revenue.

Multitouch attribution and channel strategies

Multitouch attribution models and strategies that track campaign touchpoints across several channels provide advanced insight for growth marketers with mature marketing efforts.

These analytics strategies indicate how each digital interaction contributes to conversion or deeper customer engagement, helping marketers understand the relative value and effectiveness of each channel used during the campaign.

Marketers might map a customer's journey across social media posts, sponsored ads, and newsletter interactions by feeding each of those data sources into a data analytics platform.

When the data is centralized and segmented by campaign, it shows which combinations of channel tactics drive the highest conversions. Marketers can replicate and improve on that information to continue to grow revenue.

Real-time data monitoring and agile optimization

High-volume and fast-paced campaigns require frequent analysis via real-time data monitoring, so marketers can respond quickly to changing markets. Dashboards that track key metrics like traffic, sales, or online engagement help marketers spot campaign tactics or customer sentiment changes that require swift responses.

And by adding notifications and alerts to metrics for campaign monitoring purposes, marketers can track campaigns while doing other work.

These agile optimizations can drive bigger sales and engage more users quickly. Real-time monitoring might indicate the need for a mid-campaign pivot because an influencer goes viral referencing your product, requiring a response campaign to capitalize on the increased audience.

The most important growth marketing metrics to track (and why)

Of the millions of metrics growth marketers could track, several metrics for performance marketing analytics indicate customer and revenue growth:

• Annual recurring revenue (ARR): Shows how much revenue grows year over year to help you track overall revenue trajectory on a large scale.
• Monthly recurring revenue (MRR): Shows how much revenue grows month over month to track how individual or sets of campaigns impact revenue in the short term.
• Lifetime value (LTV): How much revenue you expect each customer to bring to the brand, which may indicate customer satisfaction and product development direction.
• Customer acquisition cost (CAC): How much you spend to attract each customer, which comes from the total marketing spend divided by the number of customers and indicates the company's return on investment (ROI) for marketing.
• Return on ad spend (ROAS): How much revenue ads in particular generate, which can be identified by tracking important pay-per-click (PPC) metrics.

Many other metrics can contribute to these and should be tracked alongside; although, these are likely to be the metrics the executive team wants to hear about most.

Best practices in growth marketing data analysis that can be applied to any strategy

Feel like a growth marketing pro already? Great! Let's give you some best practices for analyzing marketing data to support that feeling with facts. You can also reference these advanced Supermetric use cases to improve your reporting, to give you some places to start.

Defining goals and KPIs

Setting clear goals and key performance indicators (KPIs) give you a guidepost to measure your performance against. When defining your goals and metrics:

• Choose goals that drive previously set business objectives.
• Make them measurable and time-based.
• Identify the metrics you'll use as KPIs prior to beginning analysis.

These elements will guide your analysis by ensuring you align current performance with business objectives rather than setting goals based on current performance. While many KPIs contribute to a business objective, only a few tactics control each KPI, allowing you to pinpoint and optimize those tactics with the biggest impact.

Data exploration and trend identification

Marketers who use data visualization and correlation analysis pull data from several sources together to identify trends and uncover patterns. These tools help you understand when traffic and conversion bumps correlate to newsletter sends, for example, or the time of day your customers engage with your social media posts.

Understanding these patterns can inform strategic adjustments to campaigns or individual tactics that ultimately improve the strategy.

Outlier detection and handling

Marketers often detect outliers through data visualization when there's a spike or dip in a graph. For example, your blog post is featured in a popular newsletter, spiking the blog traffic for a single day. That outlier might skew the total blog traffic for that month in a way that's not easily repeated.

A marketer who identifies that outlier and discounts the exceptional traffic will have a clearer view of their overall campaign than the marketer who leaves that in.

Concluding insights on growth marketing analytics

Growth marketing analytics isn't just about tracking numbers. It's about uncovering the story behind the data.

By combining the right metrics, tools, and analytical strategies, marketers can continuously refine their approach to drive real, measurable growth. As the market evolves, your ability to analyze, adapt, and act on performance data will be the key to staying competitive.