What is Suggestion?


Ecomfit Suggestion is a smart algorithm giving suggestion based on the collected data that are customized for your store. Suggestion saves you time and money on interpreting, analyzing reports to make decisions, as you would usually do with Google Analytics.


Currently, our Suggestion focuses on 3 important data metric (Traffic Source, Product and Engagement) to predict future action for you. Here are the reasons why and how Suggestion feature works.

Based on Traffic Source

In the world of web analytics, all traffics can be divided into 4 categories. They are: 

  • Search traffic: Traffic that comes directly from search engines like Google, Bing, and Yahoo. 
  • Referral traffic: Traffic that comes directly from a link on a different website. 
  • Campaign traffic: Traffic that has been tagged by the marketer. 
  • Direct traffic: Traffic that doesn’t have a known source.


If you are using Google Analytics, you might be familiar with these 4 categories already. But Ecomfit doesn't stop there. We take one step further by making urgent suggestions. By doing so, you can act immediately without hesitation. 

With Traffic Suggestions, we divide it into 5 indicators:

  • Potential traffic to boost sale


  • Traffic brings the most revenue

  • Traffic has visitors going to convert into buyers
  • Traffic needs to review 
  • Traffic supports revenue generation

With proper help from our Suggestion, you will know what works and what doesn't. Therefore, you can focus on the most effective traffic channels, allocate resources reasonabnly, and save money on unnecessary advertisement.

Based on Product

Product performance provides valuable insights into how customers are interacting with your products. 

Built with detailed metrics and segmentation capabilities, they can transform the way you measure product performances and make decisions across every aspect of your business.

With Ecomfit Product suggestion, you can easily understand these metrics and how to utilize them. Raising your conversion rate and optimizing marketing budget would be easy now. 

Products are divided into 4 indicators:

  • Potential products
  • Products are about to convert into sale
  • Products need improvement and adjustment
  • Products bring the most revenue

Understanding your product so you can scale your marketing campaigns to capture the most return on your investment.


Based on Engagement

Engagement is divided into 4 indicators:

  • Engaged by Device
  • View to buy
  • Visit to buy
  • Date to buy

Enaged by Device give you hints on where to distribute your advertisement and how to improve mobile device responsiveness. These device suggestions not only optimize conversion rate but also provide your customers with seamless experiences.



View to buy records the total number of page views it takes before customer make payment. 

Specifically, it indicates how many time of page view needed to result in how many percentages of conversion.

This helps you make proper decisions and tweaks when customers are about to leave the page. 

For instance, you may consider offering a promotional code or free shipping after they stay on the product page for long enough.

Visit to buy records the total number of website visits needed before customers actually make payment. 

Based on this information you can run effective re-marketing campaigns. 

Let's say it takes 4 store visits before a customer makes a purchase. So you can extend the re-marketing campaign according to target those who already visit your website 4 times. Since re-marketing costs quite a lot, you may want to aim your target precisely.



Date to buy suggests how long it takes (counted by days) for customers to make their first purchase, since their first visit. 

These suggestions will make fine ground to set up your remarketing campaigns. 


Here are all about Suggestion Function of Ecomfit. 


Feel free to contact us via email: help@ecomfit.com


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