Analysis in e-commerce – how to measure effects?

The ability to correctly analyse data plays a key role in the functioning of online shops today. It often determines the competitive advantage and success in a dynamically changing Internet environment. Why? Because the e-commerce sector is evolving rapidly and the benefits of the analysis and proper use of business information obtained in this way are crucial for achieving even better results. What benefits can data analysis bring to your e-commerce and how to measure its effects?

 

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Why is data analytics in e-commerce so important?

Systematic data analysis in e-commerce allows for obtaining valuable business information, which in turn supports making key decisions. They may concern the choice of assortment, channels of communication with customers, promotions or delivery conditions. The analysis also makes it easier to compare the most important indicators or sources of traffic in an online shop. Thanks to it we can also estimate the conversion, which ultimately translates into increased revenues.

In order to have an insight into the condition of the e-commerce conducted, the most important indicators should be monitored on an ongoing basis:

  • sales – you need to know which products generate the highest profit and which pricing strategies are most profitable,
  • assortment – the seasonality and popularity of individual products within the category should also be analysed,
  • marketing – during the analysis, it is worthwhile to pay attention to the effectiveness of particular customer communication channels or website traffic.

How to measure the effects of the activities carried out in an online shop?

In fact, there are many variables and factors that can be analysed in an e-shop. For this reason, it is very important to choose the indicators that we will analyse accordingly. When making decisions, we should, above all, be guided by the strategy of the conducted e-commerce and the objectives adopted to achieve them – both short and long term.

The key indicators in e-commerce are:

1. Conversion rate 

It tells us how many visits to the online shop actually end up placing an order. We calculate this ratio as a proportion of the number of people placing an order to the number of all users visiting the e-shop. If we constantly monitor the conversion results, we are able to optimise this ratio so that the increase in sales revenue is at a level that satisfies us. 

The conversion can be monitored using the free tools available in Google Analytics. It should be remembered that its value may vary significantly depending on the sector in which we operate. Bearing this fact in mind, the best solution is to develop your own KPIs and analyse the e-commerce conversion rate in your industry, taking into account your own data. 

2. Traffic in an online shop

Equally important indicators in e-commerce analysis are those concerning website traffic. In this case, you should focus on visits to the site, which inform us about how many page views each user makes within one session. It is also worth analysing the average duration of the visit, the bounce rate or the percentage of returning users. In this way, we will find out whether the advertising activities conducted effectively encourage recipients to visit an online shop, or whether they inspire their trust and willingness to buy. 

For example, a low percentage of returning users may mean that our e-commerce is underdeveloped in terms of UX and thus discourages customers from placing orders. It also may suggest inappropriate ads targeting and reaching customers who are not really interested in our product range. On the other hand, if the average number of subpages visited by users during the session is high, it means that they are interested in our offer and the promotional activities are effective.

3. Value of orders

E-commerce analysis also allows for an accurate estimation of the order value – both as a whole and on average in relation to the average value of the shopping cart or the average customer value. This allows us to make conscious business decisions based on understanding our customers' shopping habits and using the most effective tools as well as marketing channels on which our efforts are primarily worth focusing. For example, the LTV (Customer Lifetime Value) indicator, which shows us the total profit that individual customers generate, will be helpful in this. If this ratio is at a high level, then increasing the expenses on customer acquisition will not generate the risk of going below the profitability threshold. 

So, as you can see from the examples above, data analysis in e-commerce plays a key role. Keeping track of e-commerce indicators over time is the only way to optimise both conversion and budget. It is also the only way we can verify the development of our online shop over time. Without reference to real, measurable values, we can only speculate on the condition of our business. And this, as we know, does not allow us to set precise goals and achieve satisfactory revenues from our business.