Digital transformation is accelerating across companies and data has become the number one asset as teams look for competitive advantages, growth avenues, or cost-cutting opportunities. This is permeating throughout organizations and impacting how leaders manage business units and prioritize strategic initiatives, buying decisions, and human capital. Coinciding with this growing data-driven mentality is the adoption of Artificial Intelligence, which is enabling software applications to learn from, act on, and disseminate information created by businesses’ customers and employees. The combination of these two trends are key drivers in implementing and adopting Intelligent Software – data provides the fuel and the machine intelligence provides the outsized value. As a result, teams are leveraging these solutions to augment their capabilities, leading to better outcomes and rapid growth.
“Today, the typical enterprise sales person spends two-thirds of their time NOT selling. Fortunately, Intelligent Software solutions that automate and augment critical sales workflows are ushering in a new era of data-driven efficiency and unprecedented productivity gains within the enterprise Sales function.”
—OMEGA VENTURE PARTNERS
These intelligent solutions have historically been built for technical data science and development roles, but in the past several years, we have seen a democratization of these tools to more business-centric departments, particularly sales organizations. Sales has long been talked about as one of the most relevant roles that could benefit from AI-enabled solutions given the manual, data-oriented nature of the job. Sales reps have been burdened with prospecting leads in ZoomInfo, , transcribing spreadsheet information manually into their system of record, leveraging Outreach to customize follow ups and scheduling, and building out pipeline / forecast approximating with basic software (Excel) – all leading to the majority of their time not actually focused on selling.
Sales managers have been left to guess the likelihood of revenue targets being met, where to best allocate their time, or how to best align their respective teams.
As organizations generate increasing amounts of data, sales teams are beginning to see the benefits of being able to aggregate, govern and leverage this information for insights into both past and future sales efforts, helping them better understand customer needs and their own strengths and weaknesses. A large part of this can be attributed to the integration of intelligent sales technologies into critical workflows across the entire selling process, increasing efficiency and ultimately, allowing members to spend more time on selling. Sales reps are able to better understand when and how to best communicate with customers, learn in real-time what to say to increase the likelihood of closing prospects, and access relevant information to equip them with the right tools for the entire customer journey. Sales managers now have the opportunity to repeatedly build sales pipelines and forecast team’s deals, monitor rep performance and areas of improvement, and optimize sales playbooks to coach with data rather than emotion.
As a result, we are starting to see a new set of tools – the Intelligent Sales stack – used by sales teams to acquire and retain customers as well as manage forecasts and commissions. Each layer in the stack is dependent on the other and all require deep integration to maximize the ability to understand customer preferences, sentiment, and actions. This is not an entirely new category – the CRM is still the single source of truth for customer interactions. However, this category has emerged as teams become more data-driven and look to segment the selling process into several disparate key actions.
The Intelligent Sales Stack
Three Key Tailwinds Driving Sales Innovation
1) Explosion of SaaS Applications
One of the biggest trends we’ve seen over the past few years has been the number of software applications available to knowledge workers. Through the combination of a shift from on-premise to cloud and decreasing barriers to entry, it has never been easier, quicker, or cheaper to create and launch a SaaS product. Because of the ubiquity of these applications, organizations can buy products for very niche aspects of their business. Rather than choose a specific platform that covers all essential functions, teams are now moving towards a best-of-breed model to uniquely address and augment every aspect of their respective function.
2) Democratization of Buying Power
As we have mentioned in past posts, there has been a shift in the buying power at most organizations from the CIO level down to the individual end user, where employees are able to sample, test, and discover which applications are best suited for their specific needs. In turn, CIOs now advise and empower business units rather than drive purchasing decisions. This has been driven partly by the abundance of applications mentioned above. However, a primary driver of this shift is that SaaS offerings enable a frictionless, affordable, product-led GTM strategy. This strategy significantly decreases the cost of ownership for these products, allowing users to easily switch from one to the other without having to get executive approval. Given the multi-faceted job of sales reps, this provides them with the ability to potentially have a unique application for evert aspect of their job, regardless of its relevance to other functions or even other sales reps!
3) Increased Reliance on Data
Like almost every other sector of business, sales organizations are embracing data. This increased reliance on data is driven from a rising level of trust in these software applications, the growing amount of data from general cloud adoption, and the continued benefits of data network effects. Sales organizations are charting a clear path forward by using data to identify and target the strongest industries, geographies, and accounts and to analyze and improve performance. According to the LinkedIn State of Sales Report, more than half of respondents say their companies are using data to assess the performance of salespeople and drive decisions across the sales org.
Four Key Drivers of Value
1) Democratization of best practices
Training and ramping new sales hires costs money and takes time away from managers. Firing underperforming reps costs even more time and money while putting the company at a disadvantage by not operating at full capacity. By leveraging various intelligent sales tools like Gong and Otter, teams are able to record and analyze conversations with customers, capturing relevant and important data points from certain individuals that can be used to their advantage. For example, the actions of top performers can be taken and disseminated across the sales team to advocate best practices, teach new hires the proper tactics, and develop a playbook that gives reps an easy and understandable way to succeed. Additionally, sales engagement tools like Outreach not only give reps relevant and timely information, but also nudge them to act at times most critical to closing prospects. These solutions provide reps with information that spur best practices and allow new hires to ramp faster and more effectively.
2) Personalization is expected not rewarded
The consumerization of the enterprise is pushing customer expectations to all-time highs, and sales organizations are constantly trying to keep up. Enterprise prospects expect a personalized, consumer-like experience that reflects a deep understanding of their interests, problems, and future needs. As a result, teams are turning to more data-centric sales approaches, primarily driven by AI / ML, to promote cross-functional collaboration, surface and understand all relevant information, and coach them to be most effective. Intelligent software solutions provide behavioral, sales and profile data that can help deepen customer relationships, thus providing a better experience overall for customers and increasing their propensity to buy
3) Break down information barriers
For these solutions to leverage intelligent applications or, at the very least, enable them, they need access to customer data generated from touchpoints across all customer-facing departments – marketing, sales, product, support, and customer success. However, as companies digitally transform, many times these organizations create unwanted data silos in each department that act as bottlenecks from getting the wholistic picture of the customer or opportunity. Fortunately, the emergence of sales enablement and revenue operations tools like Salesloft and Clari act as intermediaries or system connectors that allow various niche applications to speak to one another. They enable teams to communicate and, importantly, align across goals and timing, while automating various manual sales workflows in the process.
4) Realignment of priorities / focus areas – deeper not wider
In the same way we’re seeing the rise of new roles including revenue operations, we’re also seeing a rise of new tools that take a narrow focus within the sales workflow. Part of this can be attributed to barriers of building software being lower than ever before, but it is mainly due to a shift from platform to best of breed that I mentioned earlier. Previously, teams were handicapped to a solution like Salesforce that was the central source of information, where automated workflows could be triggered in-app only. Now, because of enhanced API integrations and disparate workflow automation platforms like Tray.io or Workato, teams are able to turn to a best of breed approach where solutions are more customizable, flexible, and specific to a certain action without worrying about data quality or breadth of automations. Subsequently, knowledge workers are enabled to have a more quantifiable impact in their specific responsibilities without sacrificing information quality or productivity gains.
A Brief Overview of the Sales Augmentation Stack
The CRM is the single source of truth for all revenue-generating teams – the system of record for customer information that spans across their entire lifecycle. The CRM handles all of the information that goes to and from other components of the revenue stack. While the majority of the intelligent capabilities lie in the layers above, there is a great deal of innovation occurring with CRM’s, particularly around data ingestion / quality, predictive lead scoring, and account recommendations.
As customers demand more contextualization and personalization across their entire buying journeys, sales teams are turning to a more collaborative approach. To enable this, they are embracing various communication methods to effectively engage and close potential customers. Incumbents including Slack, Zoom, and Microsoft Teams as well as new entrants such as Rocket.chat, Quill, and Huddl, have gained significant traction after seeing massive increases in adoption. While these tools don’t necessarily include AI / ML in their core functionality, they enable / enhance the effectiveness of other tools by nurturing and collecting important, relevant, and large amounts of data.
Business intelligence enables sales teams to gather, manage, and interpret information on both potential and existing customers to help sales reps know who they should be speaking with, what they should be talking to them about, how to best contact them, and when they should reach out. Given the manual and data-oriented process, equipping these tools with intelligent functionality has become a huge advantage in the prospecting workflow. Startups like Seamless.ai leverage AI to best match leads with companies ideal contact persona and automatically verify emails / phone number in real-time, ensuring teams have the most relevant information at their fingertips.
While the CRM is integral in collecting / managing customer data, sales enablement tools bring together applications used by sales teams during the selling process. These platforms serve as the central content management system that augment sales reps to maximize their productivity and effectiveness. Startups like Seismic, Highspot, and Guru are heightening this value by incorporating AI to deliver semantic search, intelligent contextual recommendations, and prospect scoring – all essential features that allow sales teams to close deals and generate revenue in a repeatable and scalable way.
Sales engagement tools augment sales teams as they look to connect with prospects in an effective way. By combining the rep’s intellectual capabilities with intelligent solutions like Outreach, Groove, or RingDNA, teams are equipped with this information to better connect with customers at the right time with the right messaging, significantly increasing their chances of closing. Additionally, as these solutions become more integral in the sales workflow, they will learn from the results of prior interactions and improve to deliver more effective suggestions and insights.
By recording and analyzing customer calls, solutions such as Gong, Dialpad, and Otter help reps understand what tactics, words, or phrases can be used in real-time to convert prospects into customers as well as capture successful approaches to serve as best practices for low-performing reps or new hires. Additionally, capturing calls gives managers an understanding of reps processes, a detailed overview of what the customer is focused on, and confirmation that messaging is aligned across the organization.
Revenue Operations drives more predictability and accountability in the forecasting proces, helping teams be more aligned on revenue targets, and more likely to drive successful outcomes. This has shown as public companies with revenue ops teams saw 71% higher stock performance. Intelligent solutions such as People.ai, Clari, and Aviso offer sales managers predictive insights to build sales pipeline and forecast their team’s deals more consistently. These products analyze and learn from the behaviors of top-performing reps to benchmark and predict the health of deals as well as give managers a better understanding of how their team spends their time, if they’re conducting the right activities, and if there are any deals that are at-risk or could be pulled forward.
Sales Compensation Planning
Motivating sales reps is a complex task, and becomes more difficult as the sales org grows and a “one-size-fits-all” approach through the CRM is no longer applicable given the different personas, coverage models, and roles. Companies are using sales performance management solutions such as CaptivateIQ and Forma AI to turn compensation/commission planning into a scalable and repeatable process. With a focus on flexibility and customization, these platforms leverage data from other aspects of the sales augmentation stack to provide AI-powered compensation plans, territory segmentation, and incentive structures that are most appropriate for each respective rep.
Sales involves a mix of creativity, hustle, and strategy – all areas that require human intelligence. However, as more companies digitally transform and vast amounts of relevant data are created daily, there becomes an obvious need for AI – primarily to better understand your end customer, know how to efficiently manage and identify prospects, and for more precise forecasting sales for upcoming quarters. We are seeing the continued adoption of AI / ML products in the sales department, a trend that I believe will only continue as teams realize the productivity gains and data network effects that come from relying on an Intelligent solution.