During the pandemic, online communication channels have become essential to the survival of millions of businesses. Many of them had to quickly adopt a digital strategy, and had to combine massive amounts of direct customer data.
Many companies are still unprepared for the huge amount of live data that comes their way once a new customer channel is activated. If this data is left unprocessed, unorganized and unorganized, it brings no value to the business and starts spreading. Not only is this a missed opportunity, but the problem can become even more costly if left unresolved.
Sorting can seem like a daunting task. Where should businesses start?
1. Understand the meaning of Good ” Given
good people” Data is data I say first hand, collected directly from customers, with their consent, to understand how they use products and services. Unlike data received from third parties, it is accurate and reliable. Therefore, it provides customers with highly personalized and valuable experiences. To get the most out of it, you need to make sure it’s not fragmented; The goal is to get a comprehensive view of the customer journey. So the first step is to make sure all the dots are connected.
Another important aspect is standardization. For the data to be meaningful, it must be compared on the same basis. The idea then, in whatever form you collected it, is to be consistent with all the data, so you can properly measure and analyze it.
To detect patterns from statistics, segmentation of usable data, according to various criteria, is an essential step. “Partitioning” the data according to, for example, demographics, expenses incurred or loyalty, makes it possible to highlight interesting trends, not necessarily otherwise visually (examination of characteristics of customers who stop consuming, cross-referencing of what they have in common backgrounds, etc.).
2. Develop a plan to combat data fragmentation
Data collection is not an end in itself – you must understand it first and foremost to know why it is being used. Is it about measuring and then improving the customer experience at different stages of the customer journey? Is it about using information to better personalize communications? Monday?
It is therefore necessary to ask to whom this data is being exploited: CMO? commercial? Customer Service Manager? After defining these criteria, the goal is to identify technical needs and think about the source of the data that will be used (history of interactions with customer service, open rate of marketing campaigns, etc.). When developing your plan, the goal is for you to consider all the areas of the business that you want to reach to extract value.
This planning step builds the foundation for a well-managed data organization.
3. Anticipate growth
It is important to plan for more than is calculated during the storage needs assessment phase to anticipate the future. Indeed, if the volume of data entering the company today is indeed a major topic, we should think about what this could look like in a couple of years, when the number of customers or the number of products sold increases.
So the best advice is to be aware of data inconsistencies as a business grows because it usually increases with the addition of data sources and tools.
4. Everything is based on foundations
A solid structure is necessary to create a data structure. It is also at this stage that a large number of basic problems can be solved.
Centralized infrastructure such as Customer Data Platform (CDP) It can help aggregate live data, eliminate silos, and all the clutter that can ensue, and ensure that all saved data is accurate, up-to-date, and stored in the same format.
After this step, the data can be used more easily within the organization, in different departments. Therefore, by having a clear idea of what data is being kept and how it is collected, it is much easier to remain compliant with data privacy regulations.
5. Prioritize security and compliance
Companies must comply with an increasing number of data regulations (GDPR, HIPAA, CCPA). By taking into account the above elements, it is not only possible to achieve a measurable return on investment in terms of marketing and business results, but alsoEnsure better long-term compliance with current regulations
For example, the General Data Protection Regulation (GDPR) states that European customer data should only be collected for specific and legitimate purposes, so ensuring that consent is included in the data collection process is a must. Likewise, creating a robust data infrastructure helps ensure the accuracy and relevance of customer data collected on a consensus basis, which is another principle of this regulation.
Above all, it is important to take security seriously and ensure that the company, its partners, and its suppliers all have security and data security compliance certifications. Finally, technology and process are just two essential components of an effective security program. The third depends on the team. Since safety is everyone’s responsibility, it is essential to ensure that regular training is incorporated into the company’s culture.
6. Think Flexibility
Today, there is a large and ever-growing number of data storage, management, and analytics solutions on the market. It is not always easy to choose the right tools that will last for several years. However, there is a solution: avoid buying a restrictive software suite that locks out a certain set of tools and limits the ability to adapt to changing needs. Most companies evolve their tools as their priorities change. Providing flexibility avoids the trap of imposed technology that limits future data potential.
7. Audit, audit and more audit
Regular data audits ensure that existing procedures meet expectations of standards and policies defined as part of the data management strategy.
If the stored data is not used by teams, simply delete it or move it to a file data lakeTo facilitate its storage and sorting. Even better, stopping the storage of the data in question is a powerful gesture but one that can make a huge difference in combating the spread of data.
In any case, a lot of cluttered data is useless, but it can become a real obstacle to the success of a business.
Although processing and analyzing this volume of data may be daunting at first glance, its true potential can be exploited using technologies such as artificial intelligence, machine learning or CDP (Customer Data Platform), which helps to understand customer habits better and dramatically. Improving the performance of critical action points.
In today’s competitive and digital environment, embracing and controlling live data is key.