Congrats! You've made it to the point where MadKudu is set up and scores and segmentations are flowing into your systems. Now comes the real fun: driving strong business outcomes.

Dark Launch to overcome FUD

Changing MQL rules is always a source of Fear, Uncertainty and Doubt for operators. 

Introducing a complete new set of rules to the MQL logic has the potential to keep even the most intrepid of operators.

This is why we recommend using our Dark Launch methodology. As importantly, the Dark Launch allows to:

• minimize risk for MOps when launching MadKudu by allowing them to iterate/adjust before exposing sales to the new MQL

• provide a measured upside to pitch going live to executives and confirm that the initiative is on track for success

What is a Dark Launch?

A "dark launch" refers to a technique where a new feature or product is released to a small audience or internally, without any external promotion or marketing. The goal is to test and refine it before releasing it to the broader public. This allows for any issues or bugs to be identified and resolved before the feature or product is widely available.

By using a Dark Launch, you can run everything as if you were fully live without impacting your sales team. 

Implementation

Our team is here to help you and has done this many times. The details below are to give you a sense of what is typically done but you should feel free to contact your CSM to discuss running this play with the MadKudu team.

We will use the following terminology below: MKL or MadKudu Qualified Lead to describe a lead or contact that is assigned a lead grade of A or B. The definition may vary based on your volumes.

New fields

The following fields will need to be created in your CRM and MAP.

• mk_MKL_date__c: this field will store the first date at which the record matched the MKL criteria. It will be blank if the record hasn’t MKLed

  This field is generally calculated upon record update

• mk_MQL_reason__c: this field will store whether a record was MQLed, MKLed, both and remain blank otherwise. Values are MQL only, MKL only, MKL & MQL, NULL

  This can be calculated upon record update or it can be a calculated field. We recommend calculating upon update to keep things simple.

New Reports

1. MQL volume

• • In Salesforce, create a new Lead report

  • Title: MQL & MKL Volume 

  • Filter on

    • All leads

    • created since Dark Launch Go Live date

    • MK MQL Reason ≠ NULL

  • Group by row: created date
  • Group by column: MK MQL Reason 

	MQL Reason
Date	MQL only	MKL Only	MKL & MQL
week 1	1235	352	6783
week 2	1320	257	7064

• • Report Description: This report shows what incremental volume will be generated by incorporating MKLs into the workflow.

 

2. Expected Pipeline Upside Conversions

• In Salesforce, create a new Lead report
• Use the Lead and Converted Lead information report type
• Title: MQL & MKL expected pipeline 
• Filter on
  • All leads
  • Created since Dark Launch Go Live date
  • mk_MQL_reason__c = MKL & MQL
• Group by row: created date
• Group by column: Opp amount (Sum), count of leads

Date	Opp Amount	Lead #
week 1	$530,215	6,783
week 2	$662,378	7,064

• Report Description: This report shows what incremental volume will be generated by incorporating MKLs into the workflow.

Here it would be: => ($530,215 + $662,378) / (6783 + 7064) = $86 per MKL

Using the previous report we can expect to generate $30k of pipeline every week, or in other words $1.5M of additional pipeline annually.

=> using week 1:  $86*352 (MKL only) = $30k

 

3. Spot-check MKLs

• In Salesforce, create a new Lead report
• Title: MQL and MKL Sample
• Filter on
  • All leads
  • Created since Dark Launch Go Live date
  • mk_MQL_reason__c = MKL only & MQL only
• Create a detailed report with the following columns

Status	email	MK Lead Grade	MK Customer Fit Signals	MK Lead Engagement Signals

• Show examples filtering on MK MQL Reason = MKL only
  This report allows reviewing records that were not caught by your existing MQL flow. It gives you the ability to check for blindspots in the MK segmentation (specific industries needing to be excluded, competitors…)
• Show examples filtering on MK MQL Reason =MQL only
  This report helps check for blindspots in the MK segmentation (always promote VP Marketing…) based on the existing MQL flow

 

New Dashboard 

Add the three reports you just built into a new dashboard to have a global view of the Dark Launch. 
Title: MadKudu Dark Launch