Smart Sales: How Collective Intelligence is Improving Enterprise Sales at Pluralsight
Pluralsight, an EdTech company, is utilizing artificial intelligence, machine learning and collective intelligence to improve the efficiency and effectiveness of its sales team.
After decades of lofty promises and predictions, artificial intelligence (AI) and machine learning are finally achieving real-life benefits for companies.1 In a recent study, McKinsey estimates that tech giants spent $20 billion to $30 billion on AI in 2016 and VC and PE investments added an additional $6 billion to $9 billion.2 However, despite the heavy investment from the tech industry, the same study also found that only 20% of companies outside of the tech industry use AI at scale or in any part of their business.3 Many firms do not understand the practical business use of AI and worry about the return on investment.4 Experts believe that AI may have the greatest impact on the marketing and sales function.5 Pluralsight, a Utah-based EdTech company, is an example of a company that has leveraged AI and machine learning to use their sales reps more efficiently and increase sales.
I selected the megathread “How Companies Are Using Machine Learning to Get Faster and More Efficient”6 due to the critical importance of the sales team at Pluralsight. Pluralsight is a cloud-based learning platform that provides technology skills training and certification courses to companies and individuals.7 Like many software as a service (SaaS) companies, Pluralsight’s growth relies heavily on the success of their inside sales team to find, close and retain customers. Machine learning is helping Pluralsight use their sales reps more efficiently which is leading to more closed sales and increased revenue.
One of the challenges sales reps face is determining how to best spend their time.8 The company uses a customer relationship management (CRM) system to keep track of their information of current and potential customers. Sales reps then use this database to solicit new business and renew expiring contracts. However, all leads are not created equal. A sales rep must determine which leads have the best potential of converting to sales – an inefficient and challenging task.9 According to a study performed in 2017, researchers estimate that sales reps spend more than 60% of their time on activities other than selling.10
To help make this process more efficient and effective, Pluralsight uses third party software which automatically logs the details of all sales calls and emails – date, time of day, answered/unanswered, geography, industry, title…etc. The software also pools Pluralsight’s data with other company’s anonymized historical sales data to identify patterns and correlations of a successful lead. Similar to intelligent navigation, which utilizes the collective intelligence of all drivers to determine the optimal route, AI uses the entire pool of data to rank potential customer leads based on likelihood of success.11 The software can even draw correlations based on weather, customer stock price, company life cycle and other notable events.12
Thus, each time a sales rep opens their CRM portal they are presented with a list of the highest potential leads, resulting in more closed deals and increased revenue. It would be challenging to determine the exact dollar impact that the AI provides, but the top-line growth of the company has been impressive. Since 2015, revenue has increased from $108 million to $212 million in LTM Sep-18 (CAGR of 25%) with 65% of the Fortune 500 subscribed to their growing library of training content.13
As Pluralsight gets better at analyzing its current data it can then begin to leverage additional relevant data. Information that currently exists outside of the CRM system but could be beneficial in analyzing sales opportunities might include post-sale product utilization, demand elasticity and customer or industry spending patterns. Additionally, the company could begin to use the data it has already collected to draw correlations in other areas. For example, AI may be able to help predict which customers are likely to expand its purchasing or cancel its service. Successful implementation of these additional steps would require the company to develop its own algorithms or find a way to incorporate the data into its current software provided by a third party.
Pluralsight has seen great benefits from utilizing AI, machine learning and collective intelligence within its inside sales group. However, the future of sales remains unclear. Is it possible for AI to replace sales reps entirely? If a machine can already identify the most promising leads, send customized emails, dial phone numbers and leave voicemails will organizations see a need for large sales teams in the future? Or will sales groups transition into teams of data scientists who are constantly working to improve their internal algorithms to better identify opportunities for the firm? One thing is clear, AI and machine learning will continue to create tremendous value and optimization for sales teams and organizations.
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Endnotes
- Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Dahlström, P., Henke, N., & Trench, M. (2017, June). How artificial intelligence can deliver real value to companies. Retrieved November 12, 2018, from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies
- Ibid.
- Miremadi, M. C. (2018, July 24). Most of AI’s Business Uses Will Be in Two Areas. Retrieved November 12, 2018, from https://hbr.org/2018/07/most-of-ais-business-uses-will-be-in-two-areas
- Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Dahlström, P., Henke, N., & Trench, M. (2017, June). How artificial intelligence can deliver real value to companies. Retrieved November 12, 2018, from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies
- Miremadi, M. C. (2018, July 24). Most of AI’s Business Uses Will Be in Two Areas. Retrieved November 12, 2018, from https://hbr.org/2018/07/most-of-ais-business-uses-will-be-in-two-areas
- J. Wilson, S. Sachdev, and A. Alter. How companies are using machine learning to get faster and more efficient. Harvard Business Review Digital Articles (May 3, 2016).
- Pluralsight Investor Deck. (2018, September). Retrieved November 12, 2018, from https://investors.pluralsight.com/static-files/1dcba45b-efa5-47ba-ba2b-1c55cb167d87
- Mulqueen, T. (2017, November 10). Sales Reps Spend Less Than 37% of Their Time Selling (and Only 18% Inside CRM), New Research Shows. Retrieved November 12, 2018, from https://www.huffingtonpost.com/entry/5a05affce4b0f1dc729a6a3a
- Ibid.
- Ibid.
- Antonio, V. (2018, July 31). How AI Is Changing Sales. Retrieved November 12, 2018, from https://hbr.org/2018/07/how-ai-is-changing-sales
- Krogue, K. (2018, January 05). Using AI For Sales? Forget The Hype. Retrieved November 12, 2018, from https://www.forbes.com/sites/kenkrogue/2018/01/05/using-ai-for-sales-forget-the-hype/#1ce107032111
- Pluralsight Investor Deck. (2018, September). Retrieved November 12, 2018, from https://investors.pluralsight.com/static-files/1dcba45b-efa5-47ba-ba2b-1c55cb167d87
Great article on the use of machine learning to support sales. I do not think that AI will replace sales reps entirely – machine learning makes its predictions based on patterns from the past. That means it will keep going after customers who look like the previous ones, and that isn’t necessarily what one wants especially if say moving into a new line of business, with different products and a totally different customer audience. And on the “soft” side of things, sales teams are essential for establishing and maintaining client relationships, which can be quite important in B2B. In the future, there are likely to be many more EdTech companies that pop up, and one way PluralSight can head off the competition is by leaning on long-term relationships with their existing clients. It’s similar to how many clients stay with certain consulting firms because they have a long relationship with those specific ones.
I don’t think AI or machine learning will be able to replace sale team or a human salesperson. There are intangible qualities required to be an efficient and effective salesperson that cannot be mimicked. For instance, successful sales requires high EQ and knowing how to use various approaches based on the client and his or her personality. A machine might be able to send a email, but it is not able to change the tone/structure of that email based on the client. As the sales industry becomes more automated, more clients are starting to seek out companies that provide a more human and personalized experiance. Therefore, machine learning should be used as a tool that can assist sales and make salespeople more efficient (generating leads, analyzing data, providing specific untapped markets/industries), but not replace them.