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eCommerce & marketing analytics dashboards that you should not miss in 2020

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How much revenue did you make this week? How many leads did you generate? Are we increasing our website engagement rate? Which channel sources are driving the most traffic?

To build a successful eCommerce business it is critical to track and understand how your business is performing against your goals and KPIs. Monitoring conversion rates, new customer traffic, customer retention and channel revenue provides insights for marketing optimization to identify new opportunities and achieve expected growth. 

In 2020, every business will revolve around data that’s why it’s very important to visualize the key points and trends so that digital marketers including business decision makers can easily point out areas for improvement or key trends on any given day.

Creating marketing and eCommerce analytics dashboard to consolidate and organize your marketing data will enable your marketing team to immediately display information they need to generate powerful actions to optimize performance of PPC, SEM and SEO campaigns. 

In this post, I’ll walk you through some of the marketing and eCommerce analytics dashboards that you should bring with you in 2020.

Multi-channel attribution dashboard

Depending on which model you use e.g., Last Google Ads Click, First interaction, Linear, Time Decay, Position Based or Data Driven this dashboard keeps you track which marketing channels were involved in the process of converting sales or conversion on your website. 

Why create this dashboard?

This analytics dashboard helps preventing any marketing activities from being discredited just because they aren’t exactly associated with driving conversions. This dashboard provides greater insights for understanding performance of your marketing channels,  budget allocation, identifying correlations and revenue forecasting.

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Key metrics that should be included but not limited to are sessions (website traffic), ecommerce transactions, lead conversions, media cost, acquisition cost, ROI, AOV and conversion rates.

Here is an example of an eCommerce revenue attribution dashboard using Time Decay as model with seven days looks back window. You can also visit my article about how to use data analysis using python.

Customer retention rate dashboard

Customer retention rate dashboard keeps you track the percentage of customers that comes back to make a repeat action on your site e.g., a purchase, a content engagement or a form submission. It also helps you to analyze your customers lifetime value.

Why create this dashboard?

It helps you identify your loyal customers and understand why they come back to maintain a long lasting relationship with you. This dashboard should be able to provide the WHY’s e.g., are they coming back because of the discounts, does it have something to do with promotions? do they follow any content posted on the site? Or, what are the site features that keeps them coming back?

More meaningful insights are revealed when connecting your retention report with your NPS scores, ICF (Instant Customer Feedback), marketing spent or website downtimes.  

Here is an example of customer retention rate dashboard for 2019 using Tableau data analytics.

Conversion funnel dashboard

Conversion funnel dashboard keeps you track the numbers for each step in the funnel, what are the conversion rates for each layer and where are the drop offs. It also helps you track user experience on website and mobile as well.

Why create this dashboard?

Using this dashboard helps you immediately see where the bottlenecks are and work to improve them. Quantitatively it shows you the numbers for each step, however to get the real argument of conversions or drop offs this dashboard is best supported by session tracking tools such as Hotjar.

By prioritizing which layer should be improved first, Hotjar can quickly tell you specifically if the drop off has something to do with UX, web form completion, website downtimes or even user intent.

Creating this dashboard will also help you to efficiently optimize the user flow and understand on how you can move the users further down the funnel. You can focus on steps with the higher drop off rates and investigate any possible distractions that drives users away from completing the transaction.

Here is an example of an eCommerce funnel dashboard.

This report is available in Google analytics eCommerce funnel steps.