The Future of Sales: An 11,000 ft. View

Part One: Key Trends Every Sales and Marketing Executive Should Be Cognizant of in 2017

Just a few short weeks ago, nestled in the picturesque canyon of the Snowbird Resort in Sandy, Utah, insidesales.com hosted their annual Accelerate Conference.  Historically, it’s an event defined as a user conference that boasts 2,000+ attendees from all walks of life. This year, however, insidesales.com decided to flip the script. With an attendee list of 350 invite-only Sales, Marketing, and Operations Executives, the elevated nature of who was in the room matched that of the content that was presented.

I had the pleasure of participating as an attendee and speaker at the conference, which not only was enriching but also fascinating. The topics at the conversational forefront comprised of how to create predictive revenue models, the importance of data-driven decision making, cross-generational workforce management strategies, and the role AI will play in the present and future.  All in all, the challenges that Sales Executives face today are unprecedented.  But unlike the movie Everest, there’s hope.

In an effort to navigate those challenges, let’s break down the first of three key takeaways that every top Sales and Marketing executive should be cognizant of:

1. Sales as a Science: Data is Your Compass

More than just a sexy marketing tagline, it’s the practical application of a principle that is dependent on the indoctrination of a formulaic culture that analyzes the quantitative nature of activities needed to achieve a desirable result. Now in English, that means having the ability to conclude/predict what are the minimum number of activities necessary to create a positive event.

So, whether that positive event is booking a qualified meeting or closing a deal, there’s a series of understood levers and variables that empower an employee to create that positive event whether that be dials, correct contact rates, emails, touchpoints, face to face meetings, references, or any number of actions.  The moral of this story being, if you allow the data that is being captured at every moment of client interaction to deliver an understood model of success, you can build predictive/formulaic revenue processes.

Once that’s known, applying the scientific method to that process is the final frontier to achieving that environment.  In challenging the status quo, companies can continually test and allow for an iterative process to manifest itself in the pursuit of optimization.  In today’s day and age, that’s empowered by an emphasis on data integrity, technologies, and stellar day-to-day operations that enable a repeatable and agile process to occur.

In the context of sales development, it quantitatively resembles a model that looks like this:

Screen Shot 2017-03-10 at 2.11.25 PM

Understanding and breaking down the importance of each of those metrics seen above allows a sales and marketing leader to make informed, data-driven decisions to determine where the greatest impact can be made to improve performance.  Let’s play out a scenario to better illustrate this practical application.  

Hypothetically, the sales development team is below forecast in pipeline generation.  It’s quickly identified that the call to appointment rate is below an industry standard or proprietary benchmarks.  A sales leaders mind should immediately jump to a diagnosis that determines the variables that affect that number.  Is it the quality of the leads? Suboptimal response rates? An ineffective touchpoint schedule?  Without that original data point, in this case, the call to appointment rate, that sales leader would be left in the dark to determine exactly why this team is not hitting the goal.

A scenario where this type of analysis does not occur no matter the team or division, as a basis to substantiate decision making for positive change, could very well lead to changes in strategy that would exacerbate the suboptimal nature of the team.

Moreover, this type of approach provides leadership the ability to precisely articulate the levels of productivity necessary for a team member to deliver on in order to hit their individual goals.  I cannot emphasize the importance of how incredibly powerful this message is to tell.  As an organization, culturally indoctrinating the belief that you are placing a rep in a position to be successful with such specificity and transparency leaves little room for discontent or lack of direction in creating meaningful impact. Win-Win.

Financial modeling, forecasting, and operations are the final beneficiaries of this strategy. Wouldn’t it be nice to know the ROI that each rep represents?  We understand the dynamics at play when creating forward-looking models to achieve revenue goals (which are nothing short of complex).  Book versus Bill, AVG sales cycles, AVG contract values, the DNA of that revenue, marketing vs direct sales attribution, and a myriad of other variables are at play.

Nonetheless, there’s an understood gap in revenue to achieve and in order to fill it you must determine where it’s going to come from.  Increased marketing spend? Additional hires and where? Technology implementations to improve efficiency? Expansion of TAM? Regardless, a dollar allocated ‘here’ represents x return, whether that be human or marketing/sales variable capital investment.  Accessibility to integral data points, the principles for your assumptions, allow you to build a formulaic approach is answering the elusive question of ‘who, where, and how much.’

All benefits aforementioned aside, effectively mitigating risk in missing goals predictively is a desired place to be. With data as your compass, your gilding and unwavering tool for direction, that dream can be a reality.

If you missed part two or three of this series, check out the links below!

Part Two | Part Three

  1. […] If you missed part one of this series, click here! […]

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