Machine learning and predictive behavioral analysis are two practices having a decisive impact on a number of industries, as this article published by The Business Times points out. In the public safety sector, the analysis and correlation of massive amounts of data allows for the identification of behavioral trends; which in turn enables law enforcement agencies to predict and anticipate crises. Meanwhile, in the healthcare industry, genetic information and big data are used to provide customized treatment for patients. As for FinTech companies, they are harnessing disruptive technologies in order to develop innovative solutions that build a previously unattainable level of connection with customers.
These industry-specific examples all have one thing in common: they use data to analyze and improve past activity. The Business Times piece describes the implementation of machine learning within the public safety industry in terms of “situational awareness” and “efficiency in resource planning.” These qualities, which have indeed become invaluable to law enforcement, can be applied in a wider sense to the situation. One in which commercial teams face when engaging in social selling; regardless of their industry sector.
Machine Learning: The Science of Social Selling
Machine learning makes it possible for social selling teams (in close cooperation with marketing departments) to adapt their activity based on what has and hasn’t worked in the past. What generates the most leads and, ultimately, deals; direct InMails sent on LinkedIn or the sharing of downloadable content that requires interested audiences to fill out a contact form? It is by drawing such comparisons that social sellers can develop a situational awareness; followed by evaluating their activity and deciding whether or not they are investing time and energy in the right areas.
Data analysis is also an incredibly effective way of planning new social selling resources, and iterating on existing ones. If client testimonials generate more interest among audiences than whitepapers, a company should consider investing more in customer storytelling and less in the production of reports. Identifying content that is most effective for social sellers is crucial to the conception of new sales support material. And also to marketing resources that are designed to be shared at an early stage of the prospection funnel; in order to generate interest and engage target audiences.
The Intricacy that Sets Leading Companies Apart
The most valuable aspect of big data and machine learning in the context of social selling, is the level of intricacy it is possible to achieve; not to mention a number of other business practices. Machine learning has the potential to reveal the times of day at which audiences are most receptive; beyond identifying the most impactful types of content and the social channels on which sales professionals are most likely to achieve success. As well as trends relating to demographics such as age, geography, interests, and level of seniority. As this business2community article explains, some companies have “elevated predictive sales analytics to a science”
Companies that invest in sophisticated social selling software (which is usually an ecosystem of tools) are more likely to become leaders in their field. By harnessing big data and machine learning, commercial teams can fine-tune their awareness of market sentiment. Additionally, they can plan and iterate on resources in a more effective way, carry out in-depth performance tracking; and, above all, increase their chances of engaging in truly valuable exchanges with audiences on social media.
Sociabble is the leading provider of social selling software. Our unique platform organizes brand, third-party, and user-generated content onto themed channels. From these channels, users can share on social media and track subsequent traffic and lead generation.
Available natively for Android, iOS, and Windows Phone, Sociabble features include gamification, newsletters, calls-to-action, advanced analytics, lead tracking, and individual performance dashboards. The platform also integrates with a number of CRM, curation, listening and retargeting tools, including Office 365, Salesforce, and RadiumOne. Used in over 60 countries, Sociabble’s client base includes companies from multiple sectors including; energy, tech and communications, finance, government, education, and media.
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