How to set up your Deal Score in Dear Lucy

Introduction:

Dear Lucy’s Deal Score helps you to identify “Hot” and “At-risk” opportunities in your sales funnel, provides you with a second-opinion on your Sales Forecast and pinpoints exactly why an opportunity is scoring high or low.

Using historical data, the deal score calculates how similar a current open sales opportunity is to your average Closed Won opportunity, over 10 separate variables.

Furthermore, it allows you to modify the weighting of each variable yourself and create different Deal Score Rulesets for different teams, opportunity types or pipelines.

You can watch a video tutorial on how to set up your Deal Score in Dear Lucy here.

Deal Score Insights Dashboard:

If you have connected both the Sales and Activity connector to Dear Lucy, and it is included in your subscription plan, you will have access to a functioning Deal Score Insights dashboard.

Given that the Deal Score compares each sales opportunity with the characteristics of the average Closed Won deal in your company, the feature is particularly useful in looking at opportunities that will soon close, e.g. the current month or quarter.

Deal Score Setup:

Dear Lucy’s Deal Score feature is based upon the logic of comparing your current open opportunities to your average Closed Won opportunity historically. While you can certainly use the Deal Score with the default variable settings, you might also want to set up different Deal Score Rulesets for different types of opportunities if they vary greatly in process or characteristics.

For example, the sales process for New Business is typically quite different compared to the process for Existing business, and also the deal sizes, deal lengths and win rates are normally quite different. Therefore, there should be one Deal Score Ruleset for each of these opportunity types, to ensure that apples are compared to apples.

To configure different Deal Score Rulesets and change variable weightings in Dear Lucy, first navigate settings in the bottom right corner.

Open the menu for “AI & Analytics” and select Deal Scoring Rules from the dropdown menu.

In this section you are able to select which variables to include or exclude and change the weightings for each of the 10 Deal Score variables.

You can choose whether you would only like to keep the “Default” Deal Score rule and the current weightings, but you are also free to create new Rulesets for different use cases.

The following steps explain how you can create a new Ruleset for your Deal Scores:

1. Press “+Add Ruleset” in the top right corner. A new Ruleset window appears on top and the first point of action is to give the ruleset a new name.

2. Look through and adjust the weightings of the variables to ensure that the most important variables are given high representation in the new Ruleset.

3. Once you're happy with the weighting, you can review which Activity types are included in the Activity variables. 

4. Last but not least, you can choose to add Benchmark Data filters to the Ruleset. This is critical, as it defines what historical data the open opportunities will be compared to. 

5. Now that I have configured the Ruleset correctly, I scroll up on the page and Save the new Ruleset.

To test the ruleset you can use a Ruleset Verification table, which allows you to look at the score for all individual opportunities for each specific variable and for all your different rulesets. This makes it easier to see how the different rulesets are generating different scores.

If you’re unhappy with how the scoring turned out, you can always go back to the editor and configure your Ruleset.

Hot tip when setting up a new Ruleset

The aim should be to build a Ruleset where strong deals end up with a deal score of 75% or above. 

Before building a new Deal Score Ruleset, we recommend that you look at one of the already high-scoring deals in your pipeline from the Default ruleset, that you know is a strong case in reality as well, and look at the variables where this opportunity scores high and low. Use this deal as a base to weigh the variables accordingly.

Key benefits of Dear Lucy's Deal Score feature:

Identify Deals at Risk: 

The Deal Score Insights dashboard helps you to quickly identify the likely outcome of the opportunities in your pipeline that are expected to close in the short term. It will enable you to see which deals that may have an over-optimistic position in your pipeline and may need more support in order to close.  

Identify Hot Deals:

The deal score will also help you to see which deals that might be under-valued in your pipeline and that actually have a higher chance of success than previously estimated.

Recent Activity Level:

Monitor the activity level (which is typically a strong indicator of the success of a deal) of opportunities closing within the current month.

Top Deals:

Through a visual bubble chart, you can easily spot the Deal Score of your Top Deals, to quickly get a sense of the likelihood of success for your largest sales opportunities closing within the next 30 days.

Insights per Pipeline, Team, Account Executive or more:

The Deal Score Insights dashboard works with all business dimensions available in your Dear Lucy, allowing you to filter and drilldown on everything from a Pipeline level down to an individual sales person level.

Deal Score Variables:

1. Total Activities: Total number of activities (selected activity types) towards the deal, compared to the avg number of activities for a Won deal.

2. Future Activities: Number of scheduled activities (selected activity types) for a specific deal in the coming 14 days.

3. Recent Activities: Number of activities (selected activity types) for a specific deal in the last 7 days.

4. Deal Length: This feature assesses an opportunity's deal length, calculated from its creation date to the present, against the 12-month rolling average length of won deals. Optimal scores are achieved when the deal's length is close to this average.

5. Deal Probability: The current deal probability %. If deal probability does not exists, stage probability is used. This is the only variable that a salesperson directly influences themselves.

6. Time in Stage: Compares how long the deal has been in its current stage vs the 12m rolling average for how long won deals have spent in that stage. The closer to the average for won deals, the better the score for this variable.

7. Close Date Changes: This metric assesses how often a deal's close date has changed compared to the 12-month rolling average of close date changes for deals that were successfully won. A deal's score improves as it aligns more closely with the average for won deals.

8. Deal Size: This metric assesses a deal's proximity to the 12-month rolling average deal size for won deals. A deal scores lower if it deviates significantly from this average, whether it's an overly optimistic/inflated value or a deal that is unusually small, reflecting a departure from typical sales.

9. Overdue Days: This metric assesses whether a deal is overdue. A lower score indicates a more overdue deal, suggesting it may have been neglected or lacks a confirmed close date.

10. Deal Value Changes: This metric assesses the frequency of deal value modifications against the 12-month rolling average for successful deals. The closer a won deal's value changes are to this average, the more favorable the score.

Activity Types:

You have the flexibility to select specific activity types for your Deal Score's activity variables. For instance, you might choose to incorporate only customer-facing activities like calls and meetings, while excluding internal activities such as notes and tasks. This customization depends on how your sales team utilizes the CRM for activity tracking and what suits your organisation best.