Best Locations

The success of your business growth depends on selecting the right target audience and identifying the best locations to reach them. Whether you're expanding internationally or fine-tuning your geographic strategy, understanding where your high-value and most loyal customers are located is key to driving success.

Let's see how the Best Locations report can help you understand your performance per country and city!

The report allows you to toggle between a country-level and city-level analysis of your locations:

Performance Metrics

When analyzing the performance of your locations, it's important to look beyond just the number of customers acquired in a specific country or city. You also need to assess the quality of these customers. For instance, what if the location where you're spending the most on media is actually underperforming in terms of profitability? Imagine if those customers are one-time buyers, have a high product return rate, and contribute to poor gross margins. To fully understand this, it's crucial to take a holistic view of your locations, particularly by monitoring the Customer Lifetime Value (LTV) per location.

Use the following metrics to gain deeper insights into various aspects of your locations' performance:

New Customers

Understand how many new customers were acquired in each location based on their shipping address. When you change the time period, only customers with their first order within that period are considered. This metric shows where your brand and products are most popular.

LTV

RetentionX provides the Customer Lifetime Value (LTV) per location informing you about the quality of these newly acquired customers. It measures the total value a customer brings to your brand throughout their lifetime. LTV is calculated by (Sum of Net Revenue - Sum of COGS) per customer. In addition to the overall LTV, RetentionX provides a breakdown at 1 year. Learn more here.

AOV

Analyze the average order value (AOV) per location to understand spending behavior. The AOV refers to the average amount of money a customer spends on each order placed with your store, calculated by Sum of Gross Revenue / Number of Orders. Learn more here.

Product Return Rate

Product returns can vary widely by location, with certain countries (e.g., China at 66% versus U.S. at 48%) having higher return rates. Understanding the return rate per location is critical, as high returns impact handling costs. This metric is calculated as Items Returned / Items Sold.

Orders

Track the number of orders shipped to each location within the selected time period.

Revenue

Monitor both gross and net revenues per location. Gross revenue represents the total money generated from sales, after discounts and excluding sales tax and shipping fees. Net revenue is the gross revenue after accounting for returns, with returns automatically attributed back to the original order date. Learn more about RetentionX's revenue definitions and how to change them here.

Monitor Performance Over Time

Click on a country or city to monitor its performance over time:

For all KPIs not affected by product returns (e.g. orders) and for ongoing observation periods that haven’t yet been completed (e.g., the current month or year), RX extrapolates the run rate based on historical data. Learn more about the run rate here.

Use Cases

To ensure you're spending your time and money on the most impactful locations, it's essential to understand their performance. Here are some key use cases:

• Focus on the best-performing locations to maximize growth.

• Recalibrate and reassess locations that aren’t delivering measurable value.

• Identify locations that are developing positively (or negatively) over time.

• Check if certain segments, such as your Top Customers, are concentrated in specific locations.

Let's see how to get started:

After reviewing the LTV 1 Year per location, you can begin to assess how much it varies by region. Focus your efforts on high-quality customer locations to optimize customer acquisition costs (CAC) and maximize profitability. Here’s a step-by-step approach:

1. Take a look at your average LTV 1 Year across locations.
2. Export the data as a CSV, then filter for locations with a significant number of new customers.
3. Create three clusters based on LTV (e.g., top, average, and underperforming locations).
4. Scale the highest-performing clusters first to maximize the quality and revenue of your customers with the same advertising budget. Learn more about setting geo-targeted bids and budget here.

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