DECODING SOCIAL CUSTOMER RELATIONSHIP MANAGEMENT FOR YOUR SOCIAL CHANNELS
Social Customer Relationship Management, or social CRM, is defined as the methods and implementation of customer relationship management tools over various social channels. The tech tools used are different in nature as compared to the ones used for the regular business CRMs. Unlike traditional & professional CRM, a social CRM deals with a large pool of unstructured information (data without a pre-structured data model). This information is mainly text-based but may have dates, figures, etc whose import is clear to humans but tough for regular algorithms to comprehend. Much of the data may be the same in a booth, but linguistic nuances like colloquialism, sarcasm, or slang words are better gauged by humans than programmed tech stuff.
A social CRM is more comprehensive and free-flowing as compared to CRM (which are transaction based, operates via fixed channels, compartmentalised by teams and automated through processes.) A social CRM is in other words an “omni channel” - ongoing and smooth interaction across channels, starting off on one channel and left on another. This meets the requirements of the new age customer who is always on various social media platforms and expects quick engagement matching their lifestyle.
The end objectives of social CRM and traditional CRM is mainly the same, just the technology used in their construction and stated features differ for obvious reasons. Social CRM has many CRM features with the additional factor of social media management. Still social CRM, like traditional CRM remains clearly oriented within the compartments of sales, marketing and customer support departments within an organisation.
The emerging technologies powering the future of social CRM include:
Natural Language Processing (NLP) – It pertains to a field of languages, computer science, and AI dealing with the engagement between computers and human language, especially how to program computers to process and review a huge cache of natural language data. Statistical NLP is ideal to study social media text, which comes from many sources with large differences in styles, content and formatting.
Text mining - Also known as text data mining. It refers to the process of obtaining valuable information from text and using the same for future actions. Text mining uses various AI technologies to automatically process data and obtain valuable insights, allowing businesses to undertake informed decisions based on them. Text mining has scope for segmentation of text by type, tone, and similarity, from concept to lexicon, as well as concising documents, ferreting out data, and review author opinion or idea.
Machine learning - It is a part of artificial intelligence. Machine learning helps computers to perform programs that they are not otherwise programmed to do. It is a form of data analysis that operates analytical model construction. It is being enabled in all most all industries, leading to a big rise in demand for professionals skilled in it. It is widely believed that this industry would command USD 9 billion approximately by 2022. It is widely used for data mining, data analytics, and pattern recognition
This is a gentle introduction to Social CRM, and we shall be putting out more posts on this topic in the coming days. Stand by for the same. Ciao.