04.10.2016 | Blog

What are the benefits of real-time analytics?

Can you imagine what today’s popular online services would be like without real-time analytics and elements that adjust to each user’s actions? What would Amazon’s user experience be like if the service was not able to tell which products other people who viewed the same item had purchased? Would Netflix be equally addictive if you didn’t know which items were popular at any given time? What if Twitter was unable to list hashtags that are currently popular around the world? The point I am trying to make is that without addictive and interesting elements these services would be lost in the crowd.

Online service giants have introduced various interesting methods to evoke customer interest and to make customers commit to revisiting the service. The user experience has been made both personal and communal. These qualities are facilitated by analytics and continuous reacting to user actions.The ability of the services to operate in real-time creates various opportunities for committing the customers. While user cases are different in each service, they can be roughly divided into the following classes:

1. The user is offered content that he or she is interested in

Targeting of content can be done either based on the present session or on site history, or by comparing the user’s behaviour to user profiles that have been created in advance.  Using the service will become a personalized experience that at its best also includes a social element.

2. Targeted advertising is added or transaction opportunities are introduced in situations where it would not be meaningful or even possible to do so otherwise

For example, product packages can be offered based on the interests of the user or product prices optimized based on demand. This allows for marketing to be seen as being part of the service instead of rudely pushing the products to the customers.

3. Statistics are collected of the use of online services

Service patterns are identified and observations made on the situations and conditions causing the service to be used in a certain way. This information can be utilized in the two previous points or when the sales potential of the service is being determined.

In addition to enriching the user experience by means of the above methods, predictive analytics can be used to predict customer actions. Information on customer behaviour can be processed immediately, which enhances e.g. the efficiency of product recommendations based on whether or not the recommendation had any impact on the customer’s behaviour.

Online service giants such as Amazon and Twitter have shown the opportunities provided by the ability of the service to operate in real-time. Thanks to digitalization, the number of possible information sources is higher than ever before and, on the other hand, the price of solutions is constantly increasing. Can you afford to have your service remain as one of many, or do you wish to make it stand out from the crowd?