CRM (customer relationship management) combined with Big Data is the practice of integrating big data into internal business processes with the aim of improving customer service and predicting customer behavior, finding patterns and trends to take advantage of sales opportunities, adjusting product and service offerings to increase profits among others.
This combination improves customeranalysis and leads to the creation of different data models. Businesses using these tools seek to obtain systems that can process data in real time and, therefore, connect with customers quickly, helping to make predictable decisions, as well as give information on inventories, customer segmentation and help in the development of products and services.
Why Big Data in CRM?
You may be interested in: “Big Data models most commonly used in business.”
1. Effectively facilitates and transforms the relationship between the customer and the company.
Using it to examine the world from the customer’s perspective, organizations get to know their customers better, so they can maximize their marketing strategies, leading to better engagement through more personalized campaigns and communication.
The better the Big data connection, the better the results. When businesses effectively use their data to feed back customer satisfaction levels, you can know if, when and why customers intend to buy again, allowing you to anticipate and adapt your product and service offerings.
Big data insights have a positive correlative effect on the customer experience: for example, fewer calls can be made to customer service, marketing can be targeted more precisely (also reducing overheads) and, therefore, customer satisfaction can be increased.
2. Enables organizations to know how to build loyalty and track trends.
Data analytics tools enable companies to actively engage their customers rather than simply responding to any complaints. By providing a quantitative and qualitative view of the business, Big Data analysis helps to extract meaningful trends that can be translated into better products, services or operational activities.
Creating a more complete picture, the information can be used to create a level of personal communication between businesses and customers: increasing loyalty by addressing problems before they arise, and reducing costs by minimizing irrelevant or misdirected advertising and motivational campaigns.
3. Enables organizations to be more personal with customers.
When a customer contacts a company a conversation is beginning, an important point of interaction that defines a business. It is also a moment to maximize the use of personal information in order to engage them in a meaningful and productive conversation.
Organizations that use the richness of offline and online media to integrate data in the most relevant and engaging way, customer relationships, loyalty and brand reputation gain improvements across all communication channels.
4. Helps organizations understand and track customer behavior and motivations.
Big data analytics can even be used to find out what is behind customer behavior when they have not been explicit. Reports from back office services can be used along with behavioral analysis to find out why people interact and what the implications are. For example, what happens if a customer calls to cancel a subscription, without giving a reason? By using the associated data, organizations can review the type of experience that particular customer has had, i.e., have the systems been slow or has he or she received poor service? This allows informed inferences to be made about their behavior, and acted upon accordingly.
Finally, Big data driven and connected strategies have the potential to transform relationships and are the key to productive communication and experiences between customers and businesses: brands and organizations must connect better to get better results.
Also see: “Big Data to Infer Relationships between Companies.”
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