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Top Enterprise Sales Trends in 2017

How AI and machine learning are boosting sales

Top Enterprise Sales Trends in 2017

Enterprise sales technology is exploding.

With the compartmentalization of many functions in the enterprise sales team, it is now possible to streamline individual actions – from messaging to analytics and productivity tracking. The top trends of 2017 showcase not only the best technology has to offer to the enterprise, but the future workflow for sales professionals in the field.

Conversational Analytics

Data analysis has never been particularly flashy. Spreadsheets, pivot tables, and big data analysis in sprawling databases was not only time consuming; it was also frustrating and prone to user error. New applications are being developed that not only streamline that process, but provide an accessible, user-friendly interface to review the data.

Bouquet.ai is a good example of where this technology is leading us – providing a personal analytics assistant powered by natural language artificial intelligence. Users can ask questions about data with increasing levels of specificity and receive answers in the format that best matches their needs. Bouquet currently supports text responses, data visualizations, emailed reports, and printable PDFs outlining key data points.

Bouquet and other advanced UIs for data analysis are making it easier to access and use the highly valuable information in enterprise databases.

AI Assisted Training and Research

Continuing the trend of artificial intelligence assisting sales teams with day-to-day tasks, there is a growing demand for training and research tools that can provide instant access to vital resources for sales teams.

Gong.io, recently underwent a Series 1A round of funding to bring their total funding to $26 million, and is designed to provide real-time processing of sales data. It can actively listen to all audio as it happens and provide real-time suggestions to sales people when on calls. With advanced speech recognition and language processing technology, it acts as a coach for sales teams, both during training and in the field.

Once a call is complete, Gong processes the call and uses data to determine future tasks, recommendations for follow ups, and more within a CRM. Most interesting is that the tool uses AI to detect and provide recommendations for potentially awkward situations in conversations – able to recognize emotional triggers in both the prospect and sales person’s voice.

Self-Service Sales Using Machine Learning

To most sales teams, the idea of self-service is terrifying. Without the ability to directly interact with a prospective customer and gauge interest level, how can you build the trust needed to close the sale? Technology is providing an interesting solution to this problem with the implementation of data-driven solutions that use machine-learning to provide self-service options for consumers at key stages in the sales cycle.

With the growth of eCommerce and the ability to compare and shop online, consumers are more driven by choice and access to information than ever. It’s expected that they will have the keys and that there will be no gatekeeper for that information. Assisted service takes longer due to limitations in key staff, and there is a very real potential for error.

Consumers opt for self-service options when offered more than half the time because wait times are shorter (keeping them engaged), they feel empowered to use the service as they deem fit, and they can customize the experience to fit their needs. As machine learning advances, it’s increasingly possible for these self-service solutions to be agile and smart enough to address all consumer questions accurately.

Streamlined Productivity Support

Project management software has evolved in the last decade from massive, on-premise installations that take months to set up and even longer to learn. That evolution has created a new opportunity for smarter, data-driven project management.

Tools like Goodwerp Studio Manager make this possible by gathering and evaluating the most important data points from a project management perspective. Team member productivity and task tracking, invoicing and payment response time, collaboration tools for active and out-of-office team members and performance evaluation to see what your top performing clients and customers have in common.

The combination of traditional project management tools with machine-learning that can provide real-time insights into what is and is not working with any individual project provides team leaders unprecedented insights into their organizations.

Utilizing the Next Generation of Enterprise Sales Technologies

Enterprise sales technology will continue to evolve in the years to come, tapping into the rapid advancement of machine learning and AI accessible at the enterprise tier. From applications providing key insights into new accounts to real time support, new opportunities are driving smarter, faster sales processes in businesses around the globe. 

This is a YourStory community post, written by one of our readers.The images and content in this post belong to their respective owners. If you feel that any content posted here is a violation of your copyright, please write to us at mystory@yourstory.com and we will take it down. There has been no commercial exchange by YourStory for the publication of this article.
Shezagary has been a Project Strategist since 2009 and also involved in the launching of startups and tech companies in New York for over 5 years. She has keen interest in writing her own experiences about business plans and upcoming business supporting technologies. She loves public speaking.

Stories by Sheza Gary