January 27, 2021

Guest Post at Livechat.com: How To Predict Cart Abandons and Save Them With Live Chat

Cart and checkout abandons are the most significant cause of lost revenue for any eCommerce store.

By
Jon Tucker
CEO HelpFlow
Guest Post at Livechat.com: How To Predict Cart Abandons and Save Them With Live Chat

Cart and checkout abandons are the most significant cause of lost revenue for any eCommerce store. Depending on your industry and the time period you review, you'll see an average cart abandonment rate of around 75%. This can be even worse, with mobile cart abandonment rates over 80%.

In this blog post collaboration between HelpFlow and Livechat.com, we discussed how to effectively predict when a visitor abandons. By doing this, you will be able to engage with the visitor before leaving the sales process. In cases wherein you could not hold them off from abandoning, we also discussed other ways to engage with them outside and driving them back to your website.

At HelpFlow, we provide 24/7 live chat teams to over 100 e-commerce stores. After over six years in business and millions of chats, we've learned how to save a lot of abandons with live chat. We use a combination of technical wizardry and chat experience to make this happen, and we've broken this down for you so you can do the same.

You will not be able to save all abandons, but by being proactive in engaging with them will help you save a big chunk of them. Read the blog post by clicking here.

Your Store Needs a 24/7 Live Chat Team

HelpFlow can drive sales by having our team of human agents available on live chat 24/7 to predict and save abandons before they happen, proactively reach out and engage with visitors via SMS and email after they abandon, and by answering visitor questions live on your website to convert visitors.

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Need Help Run CX Operations While Driving Revenue?

HelpFlow can help make your CX Operation world class.  We can also help level up every aspect of your business with insights from CX that drive higher revenue, lower cost, higher customer LTV and customer happiness.

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