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Sales Insights Training Guide 

This is a general guide. Not all features may be available to you. Please contact your Salesforce Admin for further details.


The SalesChoice product suite, available on the Salesforce App Exchange, is a Cloud-Based Sales Analytics solution that uses predictive and prescriptive analytics to provide high accuracy predictions and insights for each of your sales opportunities, and helps you get the most out of your sales teams.

The SalesChoice Insight EngineProduct Suite offers three different solutions to aid in your sales analytics needs:

SalesChoice Sales Insights™: Predictive & prescriptive sales analytics is the base product that makes use of a host of AI/ML algorithms to analyze current and historical sales data to make predictions about future sales life outcomes and new opportunities. It also includes Data Completeness to reveal the real-time state of data on Salesforce. It uses Predictive and Prescriptive techniques to transform your company’s Sales Data to identify risks and opportunities and increase your likelihood of success, using advanced machine learning methods. You can access a product video here.

SalesChoice Account Insights™: A product add-on, it combines the findings of predictive analytics to reveal the account-level performance. It looks at the recency, frequency & effectiveness of account activities and can also be expanded to include Relationship Insights as a further add-on.

SalesChoice Mood Insights™: A product add-on, it offers a daily employee survey to reveal the motivation levels of salespeople, its drivers and key insights or operational risks that is unknown to the management. It therefore brings a human dimension to improve sales performance and reduce churn risks.

Getting Started

The SalesChoice Insight EngineTM has three core components: Opportunities, Team and Accuracy.

Important note before use: SalesChoice requires that users self-authorize our App the first time that they visit the SalesChoice tab. This happens through a pop-up window. If the pop-up window does not initiate, please check if your browser is set to block pop-ups.

After this step, please refresh your page again to bring up the SalesChoice Dashboard.

To get started with Insight EngineTM, once the installation of the SalesChoice is done by your Salesforce Admin, you can add it to your Salesforce menu bar by going to the All Tabs section and selecting SalesChoice under the tab options.

Note: If using Salesforce Lightning, you can access all apps by clicking on the 9 dots on left side, and searching for “SalesChoice”. On Salesforce Classic, you will have to click on the ‘+’ sign on the menu bar instead to find the app.

Once the SalesChoice core app has been installed on your Salesforce system, you will see three main components:

  • Opportunities: The place to view all the pipeline insights and predictions for opportunities predicted to be won.
  • Team: The place to view the ongoing and predicted performance of your team (subject to your visibility permissions on Salesforce).
  • Accuracy: The place to monitor the accuracy of predictions made by Insight EngineTM.


The SalesChoice Opportunities page contains your Filter Settings, Opportunity insights and stage/lead source graphs.

1. Filter Settings

This board allows the manager to set the preferred filters and reload the SalesChoice tab at different levels throughout the hierarchy of the organization and for different time periods and target/quota totals. Custom filters can also be added for a client upon request.

The core settings on this board are as follows:

  • Date Range: Time period to view prediction for.
  • User Role: Dropdown to select the team you want to view predictions for.
  • Target/Quota: Sales target or gap for the selected sales hierarchy during the defined period.
  • Update: Button to initiate the prediction simulator

Important: You will need to input the overall target/quota for the chosen user and time period. This is a key input to run the SalesChoice predictive simulator. A cookie will be created when you input the Target/Quota/Gap value for the first time, to remember that value. It will remain in your setting parameters, until you change or reset a different parameter.

Date Range Selector:

This feature grants its users the ability to generate predictions across any time period. Users can choose from one of the preset options or a Custom date range.

Custom Date Range: If you select Date Range -> Custom, you would be able to see two new date selectors: Start Date and End Date.

2. Dashboard Stats

This board displays the results of the sales simulation as per the filters set in the settings board.

The various parts of this board are as follows:

  • Target Status: This data point shows whether the selected sales team/individual is “On Target” or “Off Target” in meeting the target (based on the number entered previously in Filter Settings). It follows the below mentioned logic:
    • If predicted Total Revenue < Target: “Off Target”
    • If predicted Total Revenue >= Target: “On Target”
  • Current Pipeline: Total Revenue to Target ratio. It indicates the health of the pipeline by revealing what multiple of the Target the predicted Total Revenue is.
  • Ideal Pipeline: Given the chosen user role’s average win rate, it reveals what the pipeline ideally should be in order to achieve the Target.
  • Closed Revenue: The value of opportunities that are Closed Won within the time period selected in Filter Settings.
  • Predicted Revenue: The SC predicted value of all Open Opportunities marked to close within the chosen date range. For context, the little number in grey shows the total value of all open opportunities in the pipeline with the close date within the chosen time period.
  • Total Revenue: This is the overall revenue predicted for the chosen user within the chosen time period. It is the SC predicted value of all Open opportunities added to the value of Closed Won opportunities within the chose date range. For context, the little number in grey shows the absolute value of all Open opportunities added to the value of Closed Won opportunities.

3. All Opportunities

This table shows all your open opportunities (or those of the User Role chosen in Dashboard Settings) that have a Close Date within the chosen date range.

Each column is sortable and filterable. Clicking the three dots next to each column name will allow you to filter the table by that column parameter. If a filter has been applied, the corresponding column header will be highlighted. To avoid any confusion later, please ensure that you click on ‘Clear All Filters’ once done.

The various columns in the table are as follows:

•  Opportunity: The sales opportunity name followed by its corresponding Account name mentioned below.
•  Owner: The sales professional who owns the opportunity on Salesforce
•  Amount: The value of the opportunity as recorded on Salesforce
•  Stage: The stage of an opportunity in the sales pipeline as recorded on Salesforce
•  Prediction: The SalesChoice (SC) probability of winning the deal
•  Rating: The SalesChoice (SC) quality rating assigned to the opportunity
•  FC (Optional): The Forecast Category for the opportunity, if recorded on Salesforce
•  Close Date: Opportunity close date.

If the estimated age of the opportunity (based on its current close date and the date it was created) is significantly higher or lower than the average age of opportunities of this type in your organization, then the Close date is flagged in Red. You can hover over it to see the details. This is how we flag Too Late or Too Optimistic Opportunities.

How is the Quality Rating Assigned?

The SalesChoice quality rating is a relative ranking of opportunities in the division-wide sales pipeline, based on weights calculated using the historical information of similar opportunities and the stage of the opportunity. The ratings then assigned are as follows:

• A: Win – Highest quality opportunities (those with highest probability of reaching the Closed Won stage) in the sales pipeline.
• B: Debatable Outcome – Opportunities that can go either way and have uncertain probability of reaching Closed Won stage in the sales pipeline.
• C: Loss – Lowest quality opportunities (those with lowest probability of reaching the Closed Won stage) in the sales pipeline.

4. Playbook

The Playbook explains why an opportunity has the prediction score it does. For any opportunity, the Playbook can be viewed by clicking on the small black arrow sign on the left of that opportunity’s name. This is prescriptive insight into the historical Win and Loss factors for similar type of opportunities.

The various columns in the table are as follows:

  • Rank: The relative importance level of a factor to opportunity outcomes. It reflects how strongly correlated a factor has been to won opportunities historically.
  • Win Factors: Factors that are most relevant to determining the outcome of that particular opportunity. The list includes fields on Salesforce as well as those calculated by SalesChoice. For simplicity, only the top factors in the AI model are shown here. The full list can be viewed in the “Data Completeness” graph on the Team tab.
  • Win Spread: The prescribed range i.e. the range of values in a particular win factor that have historically worked for opportunities of this type.
  • My Opportunity: The corresponding value in this opportunity for that win factor. It is accompanied by a Green or Yellow sign which indicates whether your corresponding value is within or out of the prescribed range, respectively.
  • Simulator: An option to test different values in a win factor for an opportunity hypothetically. The simulator function can be enabled/disables for win factors of your choice upon request. Once you have entered your hypothetical values, please click on “Simulate” below the table to view the new Prediction score. You can click on “Reset” to revert to original values. The Simulator function thus allows sales professionals to test and plan changes to an opportunity without actually changing them on Salesforce.

5. Opportunity History

The Opportunity History graph sits in a separate tab beside the Playbook. It helps you see the journey an opportunity has gone through so far. This allows you to track the nature, frequency and impact of changes reps have made to an opportunity and how it has increased/decreased the % score for that opportunity, giving you a better handle on increasing their odds of success with current or future pipeline.

The information showing in the table are as follows:

•  Graph: Shows how the opportunity’s prediction % score has trended over time.
•  What Changed?: Lists all changes (rep-made or automatic) that have occurred in this opportunity at any one point in time.

Note: The visibility of this feature depends on whether SalesChoice has been allowed permission by your Salesforce Admin to store data in order to map the information on the graph.

6. Coaching

The Opportunities Coaching panel displays key highlights and stats related to the chosen opportunity. This includes the number of win factors within or outside the prescribed win range, time the opportunity has spent in its current stage or since the last change, and the impact of recent changes of its prediction score.

7. Open Opportunities by Lead Score

This graph shows the spread of open opportunities by the Lead Source that they originated from. It is displayed if Lead Source is an actively tracked field linked to all opportunities. The opportunities are further colour-segmented by their ABC ratings to reveal not only the volume but also the quality of opportunities coming from each Lead Source.

Note: A similar graph is also available to see the Closed Opportunities (won/lost) by each tracked Lead Source.

8. Stages

This graph shows the spread of open opportunities across the sales stages by their quality. It allows users to see whether early stage opportunities are already looking good, or whether late-stage opportunities are at risk with regards to their probability to being won.


9. Team

This is a list of all sales reps/teams that fit into the dashboard settings selection under the chosen user/sales team. If no filter has been set, this table shows the top level of team and reps/teams that roll up to the logged in user.

The table provides the following information per user:

  • Name: This column displays the name and role of the sales reps/individuals reporting into the user selected in Settings
  • Win Rate: The corresponding DOG code
  • Won/Lost: Number of opportunities that have been marked as Closed Won in the chosen time period
  • Number of opportunities that have been marked as Closed Lost in the chosen time period
  • Revenue Share: This column displays the Total Revenue from the team/rep. That is the sum of Confirmed revenue from closed won opportunities and Predicted Revenue from open opportunities. Underneath each revenue number if a percentage (%) number indicating what share of the parent user’s Total Revenue is predicted to come from the respective team/rep.
  • Open: The total number of open opportunities in the pipeline with Close Date within the chosen time period
  • Pipeline Quality: The number of open opportunities in the pipeline within the chosen time period, rated A, B or C respectively, according to the likelihood of them being Closed Won
  • #A: Number of open “A” opportunities i.e. opportunities the highest probabilities of being Closed Won in the chosen time period, relative to other pipeline opportunities.
  • #B: Number of open “B” opportunities i.e. opportunities with debatable or uncertain likelihood of being Closed Won in the chosen time period, relative to other pipeline opportunities.
  • #C: Number of open “C” opportunities i.e. opportunities with the lowest probabilities of being Closed Won in the chosen time period, relative to other pipeline opportunities.

Note: If you click on the arrow beside any Name, it will expand the view to the next level of teams or sales reps.

10. Coaching

The Team Coaching panel displays key highlights and stats related to the user’s ongoing and predicted performance. This includes the size of the current pipeline relative to his/her ideal pipeline, the current win rate compared to historical performance and the number of opportunities flagged on Close Dates.

Note: Clicking on “See the Opportunities tab” will jump the screen to the Opportunities table in the Opportunities tab. The table will be auto-filtered to only show opportunities where the Close Date has been flagged.

11. Data Completeness

This view shows the relative level of completeness of data for each team or sales rep across all CRM fields in the database that are relevant to the outcome of deals, on a scale of 0% to 100% colour-coded from Red to Green.

12. Opportunity Quality Distribution

This graph shows the breakdown of SalesChoice ratings across the teams or sales reps reporting into the user chosen in Filter Settings. Each bar represents in percentages opportunities that are A, B or C.

13. Revenue Status

This graph shows the Closed Revenue and Total Predicted Revenue by each team or sales rep reporting into the user chosen in Filter Settings. The size of the bubble represents the number of opportunities belonging to that team or sales rep. Hovering the mouse over the bubble reveals all these details for easier reading.


This view helps you monitor the accuracy of the predictions made by SalesChoice Insight EngineTM, for all the closed opportunities in your Salesforce system, by comparing the predictions to the actual results.

At the top of the page, we have the following three accuracy insights:

  1. Overall Accuracy of the all the predictions made
  2. Accuracy of Won Predictions
  3. Accuracy of Lost Predictions

Note: The definitions of Won or Lost may be different in your SalesChoice environment. Please check with your Sales Operations team for further information.

These visualizations are followed by the Accuracy table, which has the following columns:

  • Opportunity: Name of the opportunity closed and the Account they belong to
  • Owner: The sales professional who owns the opportunity
  • Amount:  Revenue earned or lost from the opportunities outcome.
  • Close Date: Date the opportunity was closed
  • Prediction: The SC prediction of the opportunities (probability of being Closed Won).
  • Outcome: The actual outcome of the opportunity upon closing
  • Accurate: Whether the SalesChoice prediction of the outcome was correct or incorrect.

Note: The prediction % scores that qualify as “won” or “lost” predictions may be different in your SalesChoice environment. Please check with your Sales Operations team for further information.



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Growth Matters

• Increases top-line revenue growth by 5-10%.
• Shortens your sales cycles by understanding your funnel quality, and drivers of wins and losses.
• Use integrated external market data insights to identify new sales prospects and uncover coverage opportunities (upsell/cross-sell)

Focus Matters

• Predicts outcomes accurately by 85% or more.
• Guides your sales professionals to focus on the best leads and opportunities to increase conversion and win rates.
• Allows management to identify potential losses early and deprioritize.
• Sales Analytics users are 93% more likely to walk away from bad deals (Aberdeen, 2015)
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Forecasting Matters

• Reduces your forecasts risks by 30%-50% by predicting sales more accurately.
• Analyzes your historical win and loss patterns with other data sources to provide you with more reliable sales forecasts.
Asset 39

Resourcing Matters

• Enables you to focus your resources on the best sales opportunities.
• Reduces your sales ramp time by 20%-30%.
• Reduces your cost of sales and improves resource utilization.
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Predictive Analytics Matters

• Big Data leaders: Companies that effectively use predictive analytics to guide decision-making beat out their competitors by an average of nearly 8% CAGR (Source: McKinsey, 2015).
• Predictive analysts enabled sales teams increase sales performance by 50% (IBM,2015)
• Organizations using predictive analytics are twice as likely to identify high value customers and make appropriate offers (Source: Aberdeen, 2015)
• ROI average was 150% for sales organization using Predictive Analytics (IDC, 2015)