In a data driven era like the one we live in, an e-commerce strategy to improve online sales must start from a correct data analysis.

There are dozens of very valid tools available.

But a recipe book written in Thai cannot help us prepare a cake: It's not enough to have analytics, you need to know how to interpret them. 

Many of the reports you will see are organized in eye-catching graphics, but they do not reveal to us which metrics we need to work on to improve our online presence.

For example, are “people reached” on Facebook a sensible metric? Are they useful? In any case: do they correspond to our sales?

What are the “right” data for an e-commerce?

When faced with e-commerce metrics, there are usually two reactions: 

• The thrill of the amount of data;
• The terror. 

In both cases, a digital consultant can help us understand something more. But first of all, we must be careful not to fall victim to “vanity metrics”.

Marketers call them that because they often tickle our ego, but have no real power over our strategy. For example? Followers on the Instagram page.

The illusion is that you have the situation under control, even if, perhaps, sales are poor.

In general, e-commerce benefits from analytics in two main ways:

1) Conversion rate and related metrics

Be careful: it is not always equal to the number of customers or the number of followers! Rather, it is the number of users who choose to do what you had decided to have them do.

You created a vacuum cleaner campaign for Millennials under 30, but then Facebook only brought you women over 40?

This can make you better define your initial target. But it also gives you the opportunity to decide if Facebook is the right platform for you!

And most importantly: have you considered what the cost of acquisition was for those customers? Was it worth it?

2) Understand how customers behave to improve online sales

You just created a great new product line. But somehow it’s not taking off (low conversion rate).

Analytics can tell you, first of all, whether customers viewed and browsed the products. Were they loyal customers or new customers? How long did they stay on the catalog page? Did they get to the point of looking at the price?

Is critical understand at what point in the purchase the customer stopped. 

Was it in the mobile version, and only stopped at checkout?

You can consider whether to include mobile-friendly payment methods, improving user experience.  

The possibilities are endless, for those who learn to really read analytics. For example, you can decide when it’s time to send a buy again newsletter to old customers, or a “you might also be interested in.”

You can evaluate new lines, or create product bundles.

Data is the perfect recipe for the success of an e-commerce. For this reason, it is essential to know how to translate them.