Retail companies who use multiple databases and servers for their daily operations often face the challenge of having all the gathered data in one joint place. Such business entities are limited in achieving a 360-degree view of their customers due to the formation of data silos, which lead to data duplication, inefficient decision-making, and lack of profit and asset optimization.
What is more, those retail companies are unable to have access to all the available data to conduct high-quality analytics. And because of the different data sources, many outliers, inconsistencies, and errors occur, making the data untrustworthy, with low quality and hidden pieces.
And last but not least, such organizations often fail to fully understand their customers’ desired, needs and wants, and to satisfy them with the products and services they provide.
However, a smart solution to this complex issue exists: Data consolidation.
What is data consolidation?
Data consolidation is a type of data integration technique, which combines data from different sources (usually network servers) into one integrated data store.
Often, big retail companies possess at least several physical location stores and a webshop. And as each shop generates tons of data on a daily basis, the total amounts of collected data are usually over the roof, which makes their governance complex and time-consuming.
Nonetheless, automated data consolidation manages to tackle this challenge, as this process extracts the data from each separate source in real-time, transforms it into a consistent-format joint data-set, and loads it into consolidated storage, most often a database. The loaded data is written as a manipulative file, which can be used for analytics, monitoring, controlling, evaluating business practices, extracting information, and many other purposes.
The consolidation process uses ETL tools in order to ensure the consecutive flow of the data and guarantee that all the sets are effectively collected, reformatted, and stored.
This gives retail organizations multiple benefits in various sectors of their operations. Let’s see them.
What are the benefits?
Control
First, by consolidating their data, companies achieve better control over their data assets. The reason for this is the break down of data silos, which contributes to the adoption of better, high-grade data governance strategy. This improves the quality of the data and ensures trustworthy analytics, without outliers, errors, and mistakes. As a result, the data becomes a key, powerful tool for generating customer and operational insights.
High-quality analytics
The ETL tools used for consolidating data make sure that the target storage contains only formatted data of a specific type, eliminating any omniformat pieces. This makes the analytics highly trustworthy, as 100% of the data used is consistent, compatible, unbiased, and unmanipulated.
Better decision-making
The availability of high-grade data analytics contributes to enhanced decision-making processes within retail organizations. As the business entities know that they can fully base their decisions on the integrated data, they can achieve better planning and risk management.
As a result, companies can lock the value of the consolidated data by making data-driven, evidence-based decisions about product innovation and differentiation, marketing and sales strategy, customer services, investment in new tangible capital, optimization of human and capital assets, etc. By doing so, the efficiency of performance will be enhanced, and the organization will achieve a higher level of financial and operational success.
Build a 360-degree customer view
For the retail sector, customers are the number one priority. That is why it is key to understand them in order to provide them with excellent experience and satisfy their needs and wants.
Data consolidation helps retail organizations to convert data into information and extract essential and detailed insights about customer behavior, their desires, expectations, needs, interests, etc. Such practices help the business entities to become customer-centric, provide personalized CX and base their operations on the clients’ demands by identifying past events and trends, recognizing future tendencies in behavior, and predicting needs and wants.
As a result, retail companies are enabled to target their customers with tailored offerings, discounts, and customized marketing messages. Besides, they can use the right types of communication channels to reach them (for example, email or social media platforms), and utilize relevant types of content pieces to engage them with the brand and make them feel special and unique. This way, companies ensure a higher conversion rate, a larger number of loyal customers, and better client reviews.
Real-time response to business needs
Having all the collected data in one specific storage, available for usage, facilitates the data analytics processes. As the consolidated data is ready to be manipulated, the company can instantly and directly extract the pieces it needs at a specific moment. This way, no time is wasted on preparation, reformatting, structuring, and integration of data sets. The process is fully automated, which ensures smooth operational flow, time efficiency, and quality.
Besides, such an automated practice can not only decrease the time and the costs generated by the IT department for manual consolidation of data but also improve the learning curve and diminish errors.
Conclusion
All in all, data consolidation is one of the most powerful tools, which retail organizations can take advantage of, in order to make the best out of the data they generate on a daily basis. This process offers them the opportunity to enhance their financial and operational performance and to become customer-centered.
