BadData Quick Start: Onboarding

Welcome to BadData! Your time is valuable, so we’ll be quick.

Our goal is to help sales organizations qualify deals better to close more sales. Bad data in the sales process results in time spent on the wrong opportunities, wasting a team’s time and resources. Identifying bad data helps individuals in your team improve deal qualification. Managers and individuals can then spend more time focusing on higher probability deals. Let’s begin.

1. Add BadData to Salesforce's navigation menu

1.1. Install Salesforce package: Click link

1.2. Click “Setup”

1.3. In Quick Find, search for “App Manager.” Click “App Manager”

1.4. Select “Sales,” Click “Edit”

1.5. Click “Select Items.” Add BadData to the column on the right, then move it up the list

1.6. Return to your “Sales” homepage. BadData is now in the navigation bar

2. Connect Salesforce account

2.1. Create an account

  • Navigate to the BadData tab
  • Click “Create an account”
  • Check your email, then click the confirmation link

2.2. Connect to Salesforce

  • Enter your Salesforce username, password, and security token (instructions included in the visual below for clarity)

2.3. Customize BadData

  • Example: If your current fiscal year is FY2019 and began in Feb. 2018, select “FY2019” and “February”
  • Example: If you would like to analyze “ARR” instead of “Amount”, select “ARR” from the field selection

3. See early insights

3.1. Data Quality
See tendencies of each sales rep and team. Personas, such as sandbagger and optimist, give you an immediate picture of how each rep can improve in deal qualification. In sales qualification is the great magnifier—improving return on sales effort.

  • The BadData Score reflects the extent of misforecast and unexpected deals
  • Misforecast deals reflect areas of improvement for deal qualification
  • Unexpected deals reflect vital data that may be hidden from the team
  • The overlap in the Venn Diagram shows deals forecasted accurately
  • Personas in the bottom table reflect patterns of contributing misforecast and unexpected deals. They provide a quick way to see how you can coach individuals and teams
  • Forecast includes any deal that, at the beginning of the time range, had a close date within the time range
  • Closed includes any deal that closed within the time range
  • “Select Stages” refers to the stages deals were in at the beginning of the time range
  • Click “+” in the bottom table to drill down by individual and by team

Example: Hanna at Capgemini sees that the BadData score for FY17 Q1 is 90%. At the beginning of FY17 Q1, her teams had forecasted $56 million in consulting engagements to close by the end of that quarter. By the end of the quarter, although $15 million had closed, only $6.1 million had closed from the original forecast. Hanna has already excluded early-stage, low probability deals from the analysis

After drilling down the data by team and by engagement manager, Hanna can identify where bottlenecks and hidden data occur per person, coach her teams on qualifying deals, and focus their efforts on the most promising deals in future quarters

3.2. Leaderboard
Rank stack reps and teams by ability to qualify deals in pipeline, so sales leaders can offer incentive bonuses outside of the traditional performance bonus structure, while quickly identifying reps who may need coaching.

  • Good Data = 1 - BadData Score
  • After closing out a quarter, these charts help identify individuals managing misforecast or unexpected deals, helping you find the root causes of slips or surprises quickly so that you can better prepare for the upcoming quarter

3.3. Coverage Ratios
How much coverage do you need per rep and team? 3x, 4x, 5x? See coverage and conversion for this quarter and in the recent past. As qualification improves coverage ratios become more manageable—making the entire business from marketing to sales more efficient.

  • Green: Deals forecasted and closed
  • Orange: From deals forecasted to close, the amount of sales that exceeded the original forecast
  • Grey: Unexpected deals
  • The bottom chart shows any consistency in the coverage ratio across quarters

3.4. Linearity
Get a day-by-day view of your quarter and see when deals close, slip, are lost, or come in from outside the forecast so you can quickly correct course within the quarter. The dreaded “hockey stick” (where deals all come in the last few days of a quarter) reduces predictability and increases the negative impact of chance.

3.5. Rolling Pipeline
See your rolling 90-day forecast. See how reliable your forecasts have been historically so you can direct marketing spend and remove bottlenecks by qualifying deals early.

  • Each horizontal bar shows you a snapshot of the pipeline as it looked from Day 1 of the guiding quarter (value in blue on the left column).
  • Comparing snapshots taken from different quarters (different horizontal bars), about forecasts for any particular quarter (vertical columns), indicates the reliability of long-range pipeline

4. Troubleshoot

The BadData package installation will fail if field history has not yet been enabled

4.1. Click “Setup”

4.2. Click “Object Manager”

4.3. Scroll down to “Opportunity.” Click “Opportunity”

4.4. Click “Fields and Relationships.” Then click “Set History Tracking”

4.5. Click “Enable Opportunity Field History.” You can track as many fields as you would like, but select at minimum “Close Date,” “Amount,” “Opportunity Owner,” and “Stage.” Then click “Save”

4.6. Install BadData again: Click link. The installation will be successful

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