web analytics

Successful Digital Strategy: From Big Data to Smart Data

Improving the customer experience and meeting the growing demands of customers are the two main motivations of companies for the development of digital strategies. It is essential to understand the customers during their entire journey. Personas, customer experience cards and contact point strategies are used as analytical tools for today’s businesses. We collect a lot of customer data; but how can we turn it  from Big Data to smart data?

However, the reality in companies is often different despite these findings. It turns out that the most common obstacle to digitization is the good use of Big Data. Without intelligent data processing, the targeted customer focus cannot be put into practice. Data feeds the brain of computers which allows it to become more intelligent (principle of machine learning). It is by feeding on data that the analytic system develops its intelligence.

From Big Data to Smart Data

The amount of data available is not a problem now. Indeed, companies have never had access to as much customer data as today. In the digital age, almost any action generates new data. Every click, purchase or abandonment of purchase, every connection or search history on online stores is recorded, as are important logistical data such as quantities stored or stockouts, and this is a huge volume of data of great value! Business models such as omnichannel or click and collect are helping to further fragment this data and to be present at different points of the customer journey.

This is why the first challenge is to avoid creating silos of isolated data, to collect and centralize data from all channels, to segment them in a coherent way and to make them less complex.

The second challenge is of greater magnitude. It is about building valuable information from large volumes of data so that you can then adopt well-targeted strategies and actions. In fact, better data management will only be effective if the data collected contributes to the optimization of processes and customer relationships.

According to a study by Roland Berger, nearly 50% of respondents consider Big Data analysis  as the most important skill that companies must acquire by 2020. Whether online or at points of sale, it is ultimately a matter of making good use of the information generated in order to design the customer journey in the most fluid and pleasant way possible.

The Road that will Take the Big Data

Data that is used intelligently allows you to personalize the advice to customers and optimize the shopping experience. Modern technologies offer many possibilities for developing personalized offers. Indeed, by analyzing the purchasing behavior adopted until today, algorithms transmit in real time tailored recommendations. Thus, it is through retargeting that targeted advertising messages are sent to interested persons after their visit to the store. In-store sellers are informed in real time of preferences, orders or requests for assistance. If a possible out-of-stock situation arises, the computer system automatically checks in time the subsidiaries, warehouses or suppliers where the product is still in stock.

And the possibilities of using such relevant data (from Big Data to smart data) are constantly increasing: technological advances such as Artificial Intelligence and Augmented Reality offer new perspectives in terms of customer approach and customer loyalty. Used wisely, forecasting and pricing tools, chats, chatbots, vendor robots and delivery drivers will provide critical competitive advantages in the future.

Conclusion

The time when the upper echelons of the enterprise made decisions based on intuition alone is over.  Almost all current business models and innovative technologies depend on a strong database. A good understanding of Big Data and powerful innovative data analytics tools is an integral part of the decision-making DNA of successful leaders.

You may also like

(Views: 154)

Leave a Reply

Your email address will not be published. Required fields are marked *