Give the customer what they want without asking for it

Knowing consumer behavior and translating that data into concrete actions when offering a service or product increases the profitability of companies.

Companies are now betting on offering the customer what they need, even before they ask for it. Not that they are magicians or fortune tellers, the help of Business Intelligence and Data Science technologies make this process possible for companies.

The objective of a predictive customer model is to obtain relevant consumer data, such as tastes or needs based on their shopping history in stores or online, as well as their search engine activity, geographical location and presence on social networks. With this information, companies can create customer behavior models that will then be used in planning better and more direct sales strategies.

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The goal is that customer data not only informs about the past, about what they have already purchased or done, it should also help predict the future.

By knowing “what could happen if...” companies are able to make more accurate forecasts about how much they will sell, to what audience and at what time, allowing them to plan marketing strategies in a focused way and meet their objectives. Also, when it comes to complaints, there is the possibility of improving customer service because those responsible for the area will be better prepared to deal with the irregularities they face.

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How does this type of intelligence work?

It has become common that when you are browsing the Internet you suddenly see an advertisement related to the content you are viewing, or that when you go to a store “casually” there is an offer related to or that complements what you are about to purchase. These actions are carried out after analyzing data that the same customers left as a footprint in previous visits.

In this case, Business Intelligence and Data Science technologies help to collect data on what consumers buy, when and how often to transform them into knowledge that helps companies create or innovate well-aimed strategies to obtain better results and increase sales.

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How do you get the information?

There are different ways, but systems can be programmed to monitor calls with customers and identify keywords that help classify them into segments; it is also possible to analyze the clicks that are made on web pages to determine that that user is interested in a certain product or service and, in response, more options can be automatically given to him so that he can choose the one that best suits him.

Accumulating the history of purchases per customer generates very valuable information, such as making predictions on the behavior of the consumer who is looking for something, predicting if they are likely to accept a similar offer or if they will cancel a service that is not being to their liking.

To make decisions within the company, there are also benefits such as automating the integration of data from different sources and sending daily reports and alerts to sellers and, at the management level, having access to sales dashboards segmented by date, branch, best-selling products, best customers, etc.

By using Business Intelligence and Data Science to know the customer and predict their behavior, the effectiveness of sales campaigns can be increased by up to 20%, provided that the data is properly analyzed to be able to focus and optimize what is going to be offered, as well as where and when, increasing the chances of the consumer buying what is proposed to them.