Real Store performance dashboard example

Get the actual Store performance dashboard example used by Porter to monitor your E-commerce performance.

Meet the author

Porter

This template is built by the same marketers behind all our tutorials, support, and our template gallery.

+40,000 marketers have downloaded our dashboards

Template setup

Copy-paste the same dashboards that other teams and agencies use to monitor their E-commerce performance

Store performance dashboard example overview

With this performance monitoring dashboard example, monitor key metrics such as page load time, server response time, and network latency. Segment the data by different geographical regions, device types, or browser types to identify performance issues in specific areas. Suggest users share the dashboard as a PDF, link, or email to easily influence teams or clients. This way, they can showcase the performance improvements achieved or highlight areas that need attention for better user experience. Answer questions like “Which webpage has the longest average load time?”, “How does the server response time vary across different devices?”, or “Which region experiences the highest network latency?” to gain insights and make data-driven decisions for optimizing performance.

Metrics and dimensions included

Customize the template’s metrics and dimensions as you like. See all available fields.

Metrics

Sales

– Total revenue – Average order value – Conversion rate

Customers

– Total number of orders – Average order value – Order conversion rate

Acquisition

– Conversion rate – Traffic source – Average order value

Dimensions

Campaign

– Audience targeting – Marketing channels – Campaign objectives

Audience

– Age – Gender – Income level

Time

By hour, day, week, month, quarter, or year

Features

100% custom charts

White-label

Custom metrics​

All-time historical data

Schedule email alerts​

Filters

Interactive

Goals​

Data blending

FAQs

A store performance report should include metrics such as visibility, engagement, and conversion. These metrics should be broken down by campaign, channel, audience, content, objective, and date. For example, the report may include the number of impressions, click-through rates, and conversion rates for each campaign or channel. By segmenting the data in this way, one can analyze the effectiveness of different campaigns and channels in reaching the target audience and driving conversions.
To analyze store performance data, we need to include the following metrics: 1) Visibility metrics: These can include website traffic, impressions, reach, and social media followers. For example, we can measure website traffic by the number of unique visitors or page views. 2) Engagement metrics: These can include click-through rates, time spent on site, social media likes/comments/shares, and email open rates. For example, we can measure click-through rates by dividing the number of clicks by the number of impressions. 3) Conversion metrics: These can include sales revenue, conversion rates, average order value, and return on ad spend. For example, we can measure conversion rates by dividing the number of conversions by the number of website visits. To add context to the report, we should compare the metrics against previous periods, budget spent, and industry benchmarks. For instance, we can compare website traffic for the current month with the previous month to identify any fluctuations. We can also analyze conversion rates in relation to the ad spend to determine the return on investment. In order to segment the data, we should consider campaigns, channels, audience demographics, content types, objectives, and date ranges. For example, we can compare the performance of different marketing campaigns in terms of click-through rates. We can also analyze website traffic based on the channels through which visitors are coming, such as organic search, paid search, social media, and email marketing. Segmenting data allows us to identify successful strategies and optimize our marketing efforts accordingly.
To build a store performance dashboard, 1) connect your data and accounts from sources like POS systems, e-commerce platforms, and customer databases. 2) Select metrics such as sales volume, revenue, customer footfall, and conversion rates to monitor performance. 3) Segment or break down data by campaign, sales channel (online or in-store), audience demographics, product categories, customer content (reviews or feedback), objective (sales or customer satisfaction), and date. 4) Add filters or buttons for real-time data manipulation and to make your report interactive, such as filtering by date range or product category. 5) Share the dashboard via PDF, scheduled emails, or links to relevant stakeholders.
A Store Performance Dashboard is a visual tool that displays key business metrics related to a store’s performance, such as sales, customer traffic, and inventory levels. It is significant for businesses as it provides real-time insights, enabling quick decision-making and strategy adjustments. Tools like Looker Studio are commonly used to create these dashboards, which typically include elements like sales data, customer demographics, and product performance. Real-time data monitoring is crucial as it allows businesses to respond promptly to changes in performance. For learning how to create a marketing dashboard using Looker Studio, visit our YouTube channel: https://www.youtube.com/@porter.metrics.

Yes, Looker Studio allows you to download your report as a PDF. To do it, follow these steps:

Before downloading your report choose the date range you want to visualize on your report.
Click on the “File” menu at the top left corner of the screen.

Select “Download as” from the drop-down menu and choose “PDF.”

You can choose which pages you want to download, and also you can add a password to protect the report and add a link back to the online report.

Click on “Download” to save the report on your device.