Ventana Research Analyst Perspectives

The Art and Science of Sales from the “Inside Out"

Posted by Stephen Hurrell on Nov 25, 2020 3:00:00 AM

Although historically there has been a hard divide between what are colloquially called “Inside and Field Sales,” changes over the last 10 years have narrowed the distinction. The pandemic has only accelerated the path to unifying sales activities commonly performed to engage buyers and customers. Characterized by a very disciplined and controlled endeavor, inside sales teams have been heavier users of technology. This has enabled more productive engagement including emails and calls, as well as provided techniques such as gamification to set competitive internal dynamics that help motivate sales professionals.

Over the past decade, the proportion of sales revenue generated via inside sales reps has been rising. Conversely, the overall quota attainment for field sales reps has been falling. There have been many rationales proposed for this, but a major reason is that the breadth and depth of product and review information available via the internet means that many buyers are well-advanced along the buyer journey before they engage with vendors. In addition, there are more people involved in the buying process than in previous years, increasing the level of effort and activity of achieving a successful sale. This again emphasizes the need for sellers of all types to incorporate better sales technology and tools that help both with the efficiency of the sales engagement process, and prospecting and identification of upsell and cross sell opportunities.

Now, with the pandemic and travel severely restricted, organizations are asking themselves how much difference really exists between an inside and a field seller?

An inside sales group is most typically differentiated by the dependence of the teams on technology to effectively reach out to leads and prospects in a prescribed and repeatable fashion. Typically, the inside sales team have scripts and is playbook driven, where technology is used to:

  • Prioritize lead follow-ups based on qualification that is done manually or through use of rules or AI
  • Provide auto-generated personalized email and texts to create more effective engagement
  • Enhance internal competition through gamification of activities to enable group incentives and challenge

Our research has shown that with diminished prospects for new sales and not wishing to lose good salespeople who are unable to make a consistent living, companies are changing how to assess field sales organizations. Moving away from only measuring success—and hence, compensation—based purely on sales and quota attainment, organizations are incorporating prospecting and pipeline activities into incentives. With this focus on prospecting, sales technology more typically deployed for inside sales teams are becoming just as appropriate for field sales teams as well.

Our research has also highlighted efforts by many sales applications providers, as well as more specialized organizations that exist in these ecosystems, to provide both labor-saving functionality and sales process enhancement tools to field sales teams in an approach similar to the functionality provided to inside sales teams. Field sales is increasingly able to adopt technology and process from its inside counterparts.

One major area of labor savings is the automatic capture of activity data from common tools such as email, calendars, phone calls and texts. Rather than relying on a salesperson manually entering data into the CRM, more modern capabilities enable this information to be dynamically captured and correctly associated with the underlying CRM account, contacts, opportunity and activity data store. This process has the added benefit of improving data hygiene that has often held back the deployment of more predictive analytics, pipeline and opportunity scoring, ultimately leading to AI-driven next-step recommendations

Another area of sales technology support is in helping to identify and navigate key buying personnel and influencers in a prospect’s or customer’s organization. The first generation of tools allowed a salesperson to hunt and peck to find key people. The newest generation uses a combination of existing CRM data combined with third-party data to automatically generate relationship and influence maps.

Although AI has been available for opportunity scoring for some years now through a variety of different providers, the quality of the scores has often been mistrusted by concern around the quality and timeliness of the data. In addition, when surfacing reasons as to why the scores are what they are, many of the explanations, although statistically correct, are often observational rather than actionable. As CRM data hygiene improves and is combined with third-party data, more prescriptive suggestions will be forthcoming in terms of recommendations of actions.

Although most focus today is on supporting analysis of deals and opportunities, we believe that by 2023, more focus will be placed on using sales technology in support of the salesperson, enabling the targeting of individual salespersons and their needs for skills development and coaching. Today, too much of the support provided is once a year, one-size-fits-all training as opposed to really understanding an individual’s data needs. Although by no means downplaying the “art” side of selling, it is clear that data will help with the “science” part of the equation.

As sales leadership looks to 2021 and a very changed landscape, successful sales organizations will recognize the importance of using data to help all aspects of selling. This is especially true when data can help identify talent and coaching needs to ensure salespersons develop the necessary skills to take on new roles like prospecting, and to improve the ability to execute sales processes. At the end of the day, deals and opportunities do not close themselves. Salespeople do.


Stephen Hurrell

Topics: Sales, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Sales Performance Management (SPM), natural language processing, AI and Machine Learning, intelligent sales, sales enablement

Stephen Hurrell

Written by Stephen Hurrell

Stephen is responsible for the overall research direction for the Office of Revenue at Ventana Research, including the areas of digital commerce, price and revenue management, product information management, sales enablement, sales performance management and subscription management. He brings 20+ years of experience in product and CS leadership, developing data-driven applications in sales enablement, financial reporting and planning, and billing and monetization platforms, helping to scale product teams and support customers such as Workday, NCR, Thomson Reuters, Broadridge Financials, JP Morgan Chase, Unilever and AAA (NCNU), before moving into an analyst role. Prior to joining Ventana Research in 2020, Stephen was General Manager at where he was responsible for the acquisition of C9 Analytics, VP of Product and AI strategy at RecVue and held roles at Oracle, Exigen and Aviso. Stephen earned his BS in Economics from the London School of Economics.