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Assume All Of Your Shopify Customers Started Out Loyal

assume-all-of-your-shopify-customers-started-out-loyal

A lot of stores try to convince their customers to become loyal. There’s loyalty programs, incentives, offers, deals… the list goes on.

What if you had the attitude that all of your customers started out loyal but something your store did lost their loyalty.

Maybe the product wasn’t as good as they were lead to believe?

Maybe shipping took too long?

Maybe the product was okay but it cost too much?

Reversing the lens you look at loyalty can help you find areas you can improve your actual customer loyalty. Maybe some product development can to make them easier to use, or finding a faster shipping carrier, or reducing the costs so you can sell the product for less.

I’m not saying you should take the blame for everything a customer expects. More that you look for ways to improve things that you can control.

You’ll never reach perfection with 100% loyal customers but perhaps you can get an extra 10%, 20%, or more customers to stick around and buy again. It wouldn’t take that many to have a significant impact on your bottom line.

For product-level analysis, you’ll want to start with Repeat Customer Insights’ Customer First Product report. It’ll help you see which products lead to repeat customers (and which ones lose customers).

Focus on the product’s Repeat Purchase Rate, especially if it’s lower than your typical store average. The new Downturn Focus I added recently can help find those automatically for you too.

Combine improving those products’ performance with better overall customer development (e.g. customer service, new customer welcomes, shopping experiences, etc).

Eric Davis

Use cohorts to find out who the best customers are in your Shopify store

Repeat Customer Insights will automatically group your customers into cohorts based on when they first purchased. This will let you see how the date customers bought would impact their behavior.

Install Repeat Customer Insights for Shopify

This originally appeared on the LittleStream Software Blog and is made available here to cast a wider net of discovery.
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