3 major problems data silos cause to the retail industry
The business entities operating in the retail industry are facing a significant challenge in satisfying their clients. The reason for this are the constantly evolving customer demands, needs, and wants, which combined all together form the perfect order.
Nowadays, it is not enough to deliver the right product with the right quality, to the right place, at the right time, on the right price. In order to fully satisfy the buyers, the companies should also have the right approach, deliver relevant, tailored product offerings, benefits, promotions, provide excellent buying experience, and ensure efficient and attentive customer aftercare service. In other words, every product sold should go along with customer services, which add value to the purchasing experience.
Having access to all the client data available allows organizations to build 360 degrees view over their customers, understand their needs, wants, and behavior better, and identify any trends and tendencies in their purchasing conduct.
Unfortunately, data silos disable the businesses’ to unite all the obtainable customer data-sets, and this way restricts the access to these data and limits the ability of the organizations to entirely engage and satisfy their clients. As a result, those silos are the root of data duplication, inefficient decision-making process, and eventually, lack of profit optimization.
Let’s see in more detail each of those three major problems, which data silos cause to the retail industry.
Duplication of data
The existence of silos ensures uneven distribution of data throughout the organization’s departments, as well as duplication of data-sets. This leads to inconsistency and lack of coordination between the different data silos.
The reason for the duplication is the fact that the different databases in the business entity collect, process, store, and organize data in different ways. As a result, the data format varies across silos and diverse locations, as it can be outdated, incomplete, faulty, or with insufficient quality. All these factors disable the employees to have access to the right information at the right time.
The problem with data duplication is essential in the marketing and sales sector. Storing customer data in different categories, such as “newsletter data-set,” “CRM,” or “Social media,” causes the creation of data silos. In those three categories, the collected data is usually formatted as “name,” “address,” “telephone,” “e-mail,” and others. But there may be specific terms that each team and each department uses to categorize the company’s clients. What is more, the marketing employees may update their customers’ data once a month, and the sales department only once a year. In both of the cases, a big percent of the customers’ collected data is duplicated in the marketing and sales databases, but at the same time, it is inconsistent and contradictory.
For example, one particular client may be targeted with different content. If he is in the consideration phase of the customer journey, he might need to know more about the products of the company, its features, and characteristics. And as the marketing department has their “newsletter data-sets” updated, they will approach him with the right type of content to influence his decision. But if at the same time the sales department reaches the same customer with another e-mail, containing a different message, the person may consider this as aggressive advertising or spam.
This lack of data integration limits the retail organizations to provide high-quality buying experience to each individual client. What is more, this restricts the creation of customized offers and messages, as well as personalized offerings throughout physical and digital channels.
Data-driven insights from all organizational departments are the main catalyst for high-quality decision-making. But in order to obtain those insights, the company should have access to integrated customer data, stored in one location, and available to all the departments to both add and extract data-sets. This way, the decision-making process in all organizational levels will be enhanced. Integrated departmental goals, united with the culture and mission of the business entity, help the management to create business objectives and long-term goals.
In this sense, the problem which data silos create is related to the fact that they prevent integrated data availability across the departments, and this causes difficulty in the creation of united strategy and objectives.
On the other hand, having segregated, decentralized, unevenly distributed data results in an inability to build a 360-degree customer view. Therefore, the retail organization will experience several disadvantages that can fade its competitive advantage.
- Lack of customer knowledge (including their behavior, desires, needs, etc.)
- Insufficiency of consistent data to identify tendencies and trends in the clients’ purchasing behavior.
- Inability to provide personalized/tailored content, experience, offerings, or discounts to loyal customers through both physical and online promotional channels.
- Inability to build and establish an evidence-based marketing strategy.
By breaking down the silos, the retail business entity will benefit from better collaboration between departments and increased data trustworthiness, visibility, accessibility, and readability. What is more, the integration of data-sets will provide a holistic view of the customers and will drive better business insights, opportunities, decision-making, strategy building, and performance.
Lack of profit optimization
This third major problem regards one of the most important factors in every business entity- the profit margin. It is a result of the duplication of data and inefficient decision-making, caused by the presence of data silos. Let's have an example.
If the sales department needs to utilize data from specific data-set, which is only accessible to the financial department, a confusing situation is created, where both of the departments should deviate their focus from the main task, they are doing. The finance employees have to spend time transferring data manually from one place to another, and after that, the salespeople should change the data format according to their needs. This way, time is lost in additional tasks, which can be easily avoided by breaking down the data silos.
Such daily task duplications and mistakes lead to operational delays, and faulty prioritization, which by themselves cause lack of profit optimization. Because after all, delays mean higher costs and high costs mean lower profit margin.
Together with this, being unable to fully satisfy their clients make business entities vulnerable in terms of customer retention, and consequently, in the generation of constantly increasing revenue levels.
Data silos are an enemy of the organizations in the retail industry, as they bring many disadvantages and drawbacks. However, by adopting high-quality data governance strategy to break down data-silos and achieve data integration, the companies will be able to gain competitive advantage, retain loyal customers, improve their planning and risk assessment processes and enhance their profits.