Mastering Ecommerce Metrics with Katja Kokatjuhha

Katja Kokatjuhha runs the very popular ecommerce analytics mastery on ‘Learn with Katja.’ In this session, Katja shares her inside tips on how to get more out of your ecommerce data and build better metrics.

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“If the team doesn't understand the calculation, then, of course, they will not be able to improve the metric.”

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Katja Kokatjuhha
Learn with Katja

Making metric tracking simple

Most metrics are confusing because they’ve been overcomplicated. It’s a common misconception that metrics must be built on complex calculations.

In my experience, there’s often a lack of clarity and understanding among team members about what they have to do to change a metric. Inevitably, overcomplication hinders the ability to derive actionable insights from the data.

I advocate for simplicity. By adopting straightforward calculations, teams can encourage clarity and alignment, improving the tracking of essential metrics.

Making metric tracking simple

Here are a few key principles as you assess your ecommerce analytics strategy (and whether it's working for you).

#1. Distinguishing operational and strategic metrics

It’s important to make the distinction between operational and strategic metrics.

Operational metrics include data on sales (like top selling products, new vs. returning customers) and overall marketing spending. These metrics offer real-time insights into the daily business operations. Then there those that are weekly, like Return of Ad Spend (ROAS) and Acquisition Marketing Efficiency Ratio (AMER), and Contribution Margin, which clearly show how well things are running.

#1. Distinguishing operational and strategic metrics

Strategic metrics often include those all-important customer cohorts, revenue stats, profitability, and CLV calculations, which outline when a customer becomes profitable. These metric types give businesses a long-term perspective on performance.

It’s essential to strike a balance between strategic and operational metrics. Businesses can gain a holistic understanding of performance when approaching each variation with the same enthusiasm, helping make informed decisions that drive growth.

For example, I've previously seen a direct-to-consumer brand focus solely on operational metrics. This meant important areas like customer retention tracking and lifetime value were neglected. As a result, the organization struggled to understand exactly how well their marketing efforts were impacting and failed to retain valuable customers for extended periods.

The business eventually shifted its focus to strategic metrics, looking at them with the same importance as operational metrics. Following the shift, the business better-identified areas for improvement. The team implemented targeted strategies created from their findings and inevitably saw an upward drive for long-term growth.

#2. Continuously improving your attribution model

Attribution models and tooling serve as a cornerstone in understanding the intricacies of the customer journey. The importance of adopting a comprehensive approach to attribution must be emphasized across teams.

Integrating data from various touchpoints helps you gain a holistic view of how effective your marketing efforts are. You can analyze attribution data to optimize your marketing strategies and allocate resources where they are most needed.

I often employ advanced attribution models to gain deeper insights into customer behavior patterns. Analyzing multi-touch attribution data uncovers valuable trends that would otherwise go unnoticed, enabling marketers to refine their strategy. Although, it’s important to recognize the limitations of attribution tools, so things like post-purchase surveys can still prove useful, uncovering insights that the tools miss.

By placing efforts in attribution models, businesses can identify high-performing channels. Marketing teams can then allocate their budget to fuel channels that are more likely to drive engagement and conversion.

#2. Continuously improving your attribution model

#3. Predicting trends through cohort analysis

Cohort analysis is a powerful tool for uncovering valuable insights into customer behavior and revenue trends.

With cohort analysis, businesses can track customer retention, assess the effectiveness of marketing campaigns, and refine their approach to maximize customer lifetime value.

By segmenting customers based on their specific behaviors, a business can identify common patterns and assume potential outcomes based on previous results. Any developing strategy can be tailored to meet evolving customer needs as and when they happen.

#3. Predicting trends through cohort analysis

The value of the post purchase survey in getting an understanding of key customer segments - such as purchaser demographics, who they were buying for, what was the motivation for the purchase, etc.

Beyond customer cohorts, look at revenue cohorts. These can be useful in forecasting future revenue from returning customers. This provides insight into what it will take to hit future revenue goals.

Final thoughts: Navigating the path to success

When it comes to ecommerce metrics, it’s clear that simplicity, clarity, and strategic insight are all fundamental pillars to holding up the success of a business within the digital landscape.

By simplifying how we calculate and assess those all-important metrics, the life of a marketer becomes that much easier. Embracing cohort analysis, understanding the limitations of attribution models, and effectively balancing operational and strategic metrics can make a huge difference in a business’s marketing strategy. With these tactics, you can unlock the full potential of your campaigns and thrive within the ecommerce environment.

Teams should focus on education and transparency. Knowledge sharing through comprehensive explanations during training sessions lays the groundwork.

Another common failure point is overtracking. There are always so many metrics that people want to track. Overtracking is really a problem. Teams will track more and more metrics and what happens is, they either forget them or just don’t look at them anymore.

If the metric doesn't change your behavior, it's a bad metric.

Ensuring everyone thoroughly understands the calculation process fosters a healthy culture of data management and literacy that benefits the functionality and reporting of success within a business.

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