Untitled presentation (1)

AI for Sales - Guided Selling

Authored by Ric Ratkowski on April 16, 2019


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.

The next blog will focus on sales opportunity management and sales rep coaching.  This can also be described as sales pipeline management and sales pipeline hygiene.  It includes tools to: understand deals with the highest likelihood of closing; detail buyer/seller interactions; and support the weekly 1:1 sales call. 

The ultimate objective of both of these areas is to understand sales pipeline reality - is the pipeline “real”.

Current State of Guided Selling

Selling is hard.  Being successful is even harder.  Sales reps have to keep track of the current state and next steps for many different sales opportunities. These opportunities have different objectives, could be focused on different products and need to solve different problems.  In addition, sales teams typically don’t have enough collective tribal experience from closed deals to know what works and what doesn’t in different sales scenarios.

The sales process is further clouded because sales team like to think they own the sales process.  They have a sales process that defines the progressive steps to bring a sales opportunity from initial lead through close-won.  However, in most cases there is very little similarity between the seller defined sales process and what really takes place.  The reality is the buying team purchases the product when they have completed all their necessary tasks to feel comfortable with their purchase decision.  The buyer controls the sales process.

Although the sales team doesn’t own the process, they can use AI to understand common traits and tasks of past closed deals and anticipate and manage the sales cycle to the typical processes of close-won opportunities.  They also use the standard sales process vs current buyer sales process to understand when the opportunity is in trouble.

Three AI Use Cases for Guided Selling

The following three use cases are designed to help the selling team better manage sales opportunities through guided selling.  The table below maps key challenges in the sales process to specific AI use cases.


AI Use Case

  • Understanding the appropriate sales process and steps for different sales scenarios (personas, products, pain points, industries)
  • Identify the historic actual sales processes and cycles for the different sales scenarios, to optimize the process for the buyer requirements
  • With so many opportunities, and so much noise around the sales processes, it is hard for the sales reps to focus on critical next steps
  • Guide the sales rep and enforce sales rep behavior to focus on typical next steps in the buyer journey
  • With so many interactions around an opportunity it is difficult, and time consuming for the sales manager to develop their independent impression of the current sales stage and must rely on the sales reps “best guess”
  • Identify required sales stage changes, either forward or backward in the sales cycle based on an unbiased interpretation of on the sales interactions.

The first use case of AI for guided selling helps the sales reps apply the historic actual sales process to a current opportunity based on the particular sales situation.  It is accomplished by applying classification and regression algorithms against the various tasks and processes that were part of historic closed-won and closed-lost opportunities.  The objective is to understand the signals, triggers and time frames resulting in wins and losses.

Technically, the algorithms analyze close-won and close-loss opportunities across 20+ opportunity attributes and compare them to dynamic baselines of effectiveness measures.  This information can then be extended to current opportunities to understand when opportunities are on track, stalled or lost. 

This is communicated to the sales rep via a horizontal stacked bar graph with two bars.  The horizontal axis is time.  The stacked bars represent the different sales stages.  The top horizontal bar represents the historic sales cycle for previous close-won opportunities in the same sales scenario.  The bottom horizontal bar shows the current bar of sales cycle stages. The stacked bar within each stage represents the time in days for each sales stage.   This allows you to compare the historic sales cycle for this sales segment to the current sales cycle.

The second use case of AI is to provide process guidance and enforcement via alerting and allowing the rep to take action on the alert in the same interface.  The alerts prescribe the next and best action to take with an account and highlight red flags on the opportunity.  Alerts can be both predictive - generated by AI or prescriptive - generated by manual rule creation.  Manual rules help accelerate the learning process around infrequent by significant events in the sales process. 

The two screens below highlight the alerting process and how to take action on an alert.  The screen on the left is a series of predictive and prescriptive alerts on the opportunities.  This needs to be available at the sales rep, sales team or sales org levels and is shown based on the filters and security rights applied to the current pipeline view.  The screen on the right shows the results of clicking on the “eye” of an alert to take action to resolve the alert by making the stage change.

Screen Shot 2019-04-16 at 2.48.16 PM

Ideally, before the sales rep weekly 1:1 meeting with their sales manager all the alerts are resolved.  Alerts are key to the guided selling process.

The third use case of AI is to prescribe sales stage changes either forward or back in the sales cycle based on the type, frequency and content of buyer/seller interactions. These interactions are compared to the baseline of typical close-won opportunities for this sales scenario.  They provide an unbiased interpretation of sales activity.  If the current opportunity is achieving advanced milestones and having advanced interactions the AI engine may suggest the sales opportunity be move up to a higher sales stage.  If the current opportunity is not having the right interactions with the right personas/prospect roles/milestones it may suggest the sales opportunity should be moved back in the sales stage.    

These stage changes could be thought of as a higher-level alert and part of the second use case.  It is important to call out a key aspect of AI.  AI is not a singular application that sprinkles pixie dust on data and creates recommended next steps and alerts out of thin air.  AI is a series of different algorithms that perform specific tasks and answer specific questions.  Think of it as layers of algorithms that are applied when information changes.  Some of the algorithms look at dates and activities to determine if the close date is reasonable based on past history.  Other algorithms look at changes in milestones and sales interactions to determine if the opportunity is in the right stage. Still other algorithms may be designed to classify and segment historic close-won and close-lost to build statistical correlation models to be used the first two algorithms.

In Summary

AI to support guided selling is an important aspect of AI for Sales.  Alerting and resolving the alerts through action is a key component to drive a consistent guided selling process and maintain a realistic sales pipeline.

Gartner calls this out as one of the impacts in their research “Optimize Sales Execution With Artificial Intelligence for Guided Selling, 2019” by stating:

“AI functionality has permanently transformed the guided selling capabilities that sellers use to engage with prospects, manage deals and generate quotes”

Check out this link to see how these three use cases can be addressed with software. 

Fifth in a blog series on “AI for Sales”

This is the fifth blog in the series - AI for Sales Forecasting. 

The first blog: Artificial Intelligence [AI] For Sales Forecasting

The second blog: AI for Sales - AI/Machine Learning Primer for Sales

The third blog:  AI for Sales - In the Marketing Funnel

The fourth blog:  AI for Sales - Enhanced Data Collection

The next blog will be on: AI in the sales pipeline to provide insight to understand sales pipeline reality and to coach the sales rep.

Subscribe to our newsletter!

Leverage these best practices with automation and AI driven by TopOPPS

Learn how our customers are winning with artificial intelligence in their CRM:

  • Predictive Sales Forecasting
  • Automated Pipeline Management
  • Significantly More Updates from Reps

Watch Videos

More Recent Posts:

January 21, 2020

Best Practices for B2B Sales Pipeline and Forecast Management

New year, new blog series!   The new blog series will focus on “Best Practices for B2B Sales Pipeline and Forecast Management”.   This covers a big area so this series could take most of 2020 to complete and its frequency will be more often than once a month.    The reason for this blog series is companies continue to rely on human intuition and instinct to produce sales forecasts.  They continue to spend significant time managing, manually reviewing and updating the sales forecast despite advances in sales technology. ...

Sales Pipeline Management, AI for Sales, Guided Selling, best practices

January 21, 2020

Brainshark and TopOPPS Form Partnership to Combine Sales Readiness with AI-Driven Sales Pipeline and Forecast Management

The Integrated Solutions Will Provide Deep Insights into Pipeline Activity and Forecasting - Enabling Targeted Learning that Elevates Sales Performance WALTHAM, Mass. and ST. LOUIS, Jan. 21, 2020 /PRNewswire/ -- Brainshark, Inc., the industry's only data-driven sales readiness platform, and TopOPPS, a leading provider of artificial intelligence (AI)-based sales pipeline management and forecast predictability solutions, today announced they have formed a strategic partnership. The partnership – which includes an integration of Brainshark and TopOPPS solutions – will empower sales organizations to deliver "in-the-moment" guidance that improves reps' skills at key points throughout the sales cycle. ...

AI for Sales, Sales Enablement, Guided Selling

December 13, 2019

Sales Superpowers Need 'In-Context' for Sales Engagement

  SiriusDecisions outlines “One Solution for Sales Superpowers”.  [Spoiler alert] - it is sales engagement.   If it is “the one solution” to supercharge your revenue engine, why isn’t it widely used?   Why isn’t it the most popular application in the “sales world”?  We will get back to that, but first lets make sure we are on the same page. Sales Engagement Defined  Sales engagement is defined as interactions that take place between the buyer and seller.  Sales engagement includes four core functions based on SiriusDecisions definition:  calling/dialing, email, calendarizing and reporting. ...

Sales Operations, Sales Tools, Sales Pipeline Management, Strategic Partnerships

November 25, 2019

Strengthening the CFO-CRO Relationship Through the Sales Forecast

  The sales forecast is the linchpin of a company’s future.  If it is right and can be trusted the companies’ operations run smoother and its financial stability is more secure.  Typically this isn't easy.  The sales forecasting process is shared by the Chief Revenue Officer[CRO] and the Chief Financial Officer[CFO].  The challenge is both have different motivations on its accuracy and neither have a complete vision of its drivers or its accuracy.   When the forecasting process is trusted and transparent it relieves stress on both the CRO and the CFO.  This blog reviews how this can be accomplished.  ...

Sales Operations, Sales Tools, Sales Pipeline Management, Strategic Partnerships

October 23, 2019

Where 1 + 1 = 3 in the Sales Application Stack - Sales Enablement

  In my previous blog I outlined 21 different sales technology categories for the Sales Application Stack .  These categories were consolidated from various industry analysts research. That blog highlighted the difference between data integration and application embedding and highlighted the benefits of application embedding and selecting software vendors who have strategic partnerships with other software providers in the CRM application space.   The concepts of application embedding needs to be expanded with the concept of “application in context”.  “Applications in context” is applications working “in context” with applications to solve a series of problems in a consistent and cohesive manner without derailing the users thought process. ...

Sales Operations, Sales Tools, Sales Pipeline Management, Strategic Partnerships

September 20, 2019

The Emperor [CRM] is Naked

  One of the things I like to track are stories I heard in kindergarten that persist through life.  The Emperor’s New Clothes is one of them.  I can’t tell you how many times I’ve been in meetings, listening to what is being discussed and ideas explored and wanted to yell out, “THE EMPEROR IS NAKED”. ...

Sales Operations, Sales Tools, Sales Pipeline Management, Strategic Partnerships

August 16, 2019

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. ...

Sales Operations, Sales Tools, Sales Pipeline Management, AI for Sales

August 6, 2019

TopOPPS + Outreach Galaxy: AI Enhanced Guided Selling to Increase Win Rates

  Ever had the situation where: an important sales opportunity is in danger because of inactivity and it goes unnoticed; the opportunity is sold but they don’t have the budget till next quarter so the sales rep needs to “stay close”; or the opportunity wants to buy but “isn’t there yet” and needs further ongoing education?   ...

Pipeline Optimization, Artificial Intelligence, Sales Pipeline Management, Guided Selling, guide winning behaviors