Blog Series: AI for Sales

This blog series focused on the mechanics infusing AI through out the entire sales process.

Artificial Intelligence is often thought of as a “magic bullet”.  Turn it on and it solves the world’s problem.  While that is how it is often thought of, implementation is far different from how it is thought of.  Artificial intelligence must be applied in different areas to answer different questions or highlight different actions.  To be effective artificial intelligence should be applied in a “glass box” approach so you can see what is driving the decisions, recommendations and forecasts, rather than a “black box” approach.

There are 8 blog posts that make up this theme.

Artificial Intelligence [AI] For Sales Forecasting*

When you hear the phrase “AI for sales forecasting” it feels like the solution is an algorithm to predict “the sales number”.   This is only partially correct. While the ultimate goal is an accurate sales forecast, AI for sales forecasting requires artificial intelligence to be infused throughout the entire sales process.

AI for Sales – AI/Machine Learning Primer for Sales

I had planned my blog “AI for Sales – In the Marketing Funnel” to be posted  before now.  It was a challenge writing it because I had to include terminology and background in Artificial Intelligence (AI), Machine Learning (ML), and Advanced Analytics, to set the right perspective. This blog takes on the task of trying to level set around terms and characteristics of Artificial Intelligence(AI) and Machine Learning(ML).  My next blog, [in two weeks] will discuss the AI for the marketing funnel.

AI for Sales – In the Marketing Funnel

The topic of artificial intelligence [AI] for Marketing covers many different areas including content delivery, content generation, social media, personalizing emails, attribution, and optimizing lead gen, just to name a few.  This blog focuses on applying AI in the marketing funnel for optimizing lead gen and marketing attribution[MTA].

AI for Sales – Enhanced Data Collection

An accurate sales forecast requires a crystal clean sales pipeline.  A crystal clean sales pipeline requires a deep history on most buyer/seller interactions for each opportunity.  By having a deep history of these interactions you can apply AI to identify buyer patterns and better guide the sales process.   Unfortunately most sales organizations do not have enough information about each opportunity to apply AI to assist in the sales process.

AI for Sales – Guided Selling

The next two blogs cover AI for the sales pipeline.  This blog focuses on AI for guided selling.  Guided selling is the process of prescribing optimal sales execution steps to the sales reps to enforce an efficient sales process.  The tasks and process are based on sales patterns of past close-won, and close-lost opportunities.  Guided selling is key to maintaining a realistic sales pipeline.

AI for Sales – Sales Pipeline Management and Sales Rep Coaching

This is the second of two blogs reviewing artificial intelligence use cases to support sales pipeline accuracy.    The first blog focused on artificial intelligence for guided selling. Guided selling is key to maintaining a realistic sales pipeline by ensuring that sales team rigor, discipline and process are consistent across all opportunities. This blog focuses on sales pipeline management and sales rep coaching.  It includes tools to help.

AI for Sales – Calculating the Sales Forecast

I mentioned in my first blog on AI for Sales, when you hear the phrase “AI for sales forecasting” it feels like the solution is an algorithm to predict “the sales number”. This is only partially correct. While the ultimate goal is an accurate sales forecast, AI for sales forecasting requires artificial intelligence to be infused throughout the entire sales process. The last 6 blogs have walked through different AI use cases for each of the different areas supporting the sales process to build a foundation for applying AI to create a more accurate sales forecast. With that background we are ready to review AI use cases for calculating different versions of the sales forecast.

AI for Sales – Business Examples

The last seven blogs provide a business-case approach to infusing AI through the entire sales process.  One of the purposes of this blog series was to demystify AI by using AI for Sales as an  example.  Media tends to portray AI as a magic bullet.  Actual implementations show the less “black box” an AI solution is and the more “glass box” approach, the more utility it provides to the user.  The utility is created by uncovering the key drivers of an outcome and managing those drivers to increase results.

ROI Analysis:

Understand the ROI of AI for Sales Forecasting

Research conducted by Washington University found companies using AI for Sales Forecasting and Sales Pipeline Management were able to:

  • Handle 19% more opportunities per year
  • Make 58% more money per sale
  • Reduce sales cycle by up to 59%

SiriusDecisions Research:

Foundation of an Accurate Sales Forecast

SiriusDecisions Service Director, Dana Therrien, illustrates the foundation of an accurate sales forecast. Learn how artificial intelligence increases sales effectiveness and changes how sales teams operate on a daily basis.

Expert Webinar:

A Structured Approach to Driving Holistic Predictable Revenue

In this webinar we cover:

  • Top 3 challenges to deliver an accurate forecast
  • Examples of a well structured sales proocess
  • The building blocks and advanced capabilities that support an accurate forecast