Advancements in digital technology have enabled businesses to keep track of the details of their customers and their behavior. As the modern marketing era calls for companies to satisfy the needs of multiple market segments, the companies should know more about their customers to cater to their personalized needs. Big data technologies, ERP systems, cloud technology, and AI have allowed companies to store large amounts of customer data and make an accurate analysis of each customer. Such analysis, in turn, allows the company to efficiently manage the customer relationship and thereby increase the customer lifetime value. However, managing a customer database is not an easy task. So, what are the challenges faced by businesses in customer database management?
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Challenges in Customer Database Management
Volume of Data
As businesses start keeping track of multiple facets of a single customer data, the volume of data grows at an exponential rate. Businesses have to process large volumes of data in order to make critical datasets available to stakeholders in the time of need. Such data needs to be made available to multiple stakeholders across various devices and platforms, which, in turn, rapidly increases the storage and processing costs. Such large volumes of customer database will have to be managed with state of the art ERP systems and software.
Data Collection and Storage
The modern-day business environment is getting more competitive with each passing day, and customer satisfaction seems to be prioritized in their agenda. The rapidly changing customer behavior is causing problems for decision-makers to decide on what’s best for the customers. The rise of omnichannel shopping has increased the amount of customer data that a business generates. Businesses are having a hard time managing such vast amounts of data. On top of that, they are also struggling to decide whether to take into account a single customer view or cohort view while making an analysis.
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Tracing Customer Journey
The most popular method of inspecting sales performance is by using the customer journey cycle. To do so, companies need to keep track of multiple real-time customer data including interaction touchpoints, consumer sentiment, behavioral stages, and cross-team resourcing. Such charts paint a picture for decision-makers to take strategic decisions, which can subsequently improve customer experience. However, the challenge arises on methods to track the process of how consumers move from the stage of brand awareness to conversion. In particular, it is hard to pinpoint where exactly in the customer journey map a given customer can be located.
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Choosing the Right Technology
Another problem faced by businesses in terms of customer database management is to select the right technology for their set of requirements. From multiple software and ERP systems to cloud-technology or on-premise technology, each has its own benefits and costs associated with it. Additionally, the technology may also need to be customized to match their requirements. Also, the type and form of customer data also dictate what kind of technology would be right for the organization. For instance, two completely different technologies would be required for processing structured and non-structured databases.
Privacy of Customer Data
One of the biggest challenges in customer database management is ensuring the privacy of customer data. Some customer data can be sensitive in nature, which is why issues in data security could cost companies millions in terms of lost customers or legal battles. Companies are continually battling to safeguard customer database against cyber-attacks and hackers.