Walkthrough of how to track through the lead generation funnel and find efficiencies for accurate predictive modeling.

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Heather Cooan | @HeatherCooan
Manager, Paid Advertising | Infusionsoft
Advanced Excel Trickery: Account-Side
Efficiencies & Post-Transactional Analysis

2. The In-House View
Post-Transactional Analysis

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The Problem…

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The Problem…How Do You Tie Ad Dollars To Deals?
Source: Marketo Survey 2015

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The Problem…Just Compare Buckets?
• Compare Buckets in Time
Frame
• Find Funnel Conversion Rates
at Each Stage

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The Problem…How Do You Recognize Revenue?
Ad Conversion
Date
March
Customer
Transaction Date
April+

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The Problem…Advanced Session Stitching?
• Advanced tools stitch together
sessions user ID’s from web traffic
through CRM

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The Problem…

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In-Month vs. Rolling
Conversion Rates…

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Not cool enough to stitch or growing so fast you outgrow
systems…Excel to the rescue!
Source: ixlog.com

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First, pass through lead source information…
• We create a custom lead source parameter ls= using GAutm parameters
• We use all 5 utm’s to pass keyword, placement, ad creative variations, etc.
• We have lead source tracking scripts on all pages and forms that pass the ls=
parameter through to our CRM and attach to the lead and customer records
• We then use a dash boarding tool to parse and sort this info into categories and
sub-categories

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Dump Data Sets into individual tabs
• Create a new sheet for each level of your sales funnel
• Dump the raw data for each level into the appropriate tab in your workbook

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Make each data dump a table (this allows formulas to auto update)

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Vlookup the MQL date to the opportunity tab and the customer tab

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Vlookup the opportunity date to the customer tab

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Countifs formula = (range in data set, what criteria you want that range to
meet, repeat all criteria’s you want included) in this case >= current date – 30
and <= current date
• Count field on your summary tab

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Countifs formula = (range in data set, what criteria you want that range to meet,
repeat all criteria’s you want included) in this case >= current date – 30 and <=
current date for both MQL and Opp/Opp and Customer/MQL and Customer
• Count from last 30-days field on your summary tab

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The Difference…
Newest Origination Date: 3/20/2015 Month: March
MQL to Opp Last 30 Days MQL to Opp In-Month
MQL Count 9,058 MQL Count 6,211
Opportunity Count From
Last 30 Day MQLs 2,098
Opportunity Count
From March MQLs 1,308
Conversion Rate 23.2% Conversion Rate 21.1%
Opp to Customer Last 30 Days Opp to Customer In-Month
Opportunity Count 2,865 Opportunity Count 1,866
Customer Count From Last
30 Day Opportunities 441
Customer Count
From March
Opportunities 241
Conversion Rate 15.4% Conversion Rate 12.9%
MQL to Customer Last 30 Days MQL to Customer In-Month
MQL Count 9,058 MQL Count 6,211
Customer Count From Last
30 Day MQLs 299
Customer Count
From March MQLs 163
Conversion Rate 3.3% Conversion Rate 2.6%

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Why Do We Care? Now We Can SEE!
• More Accurate Forecasting – within .01%
• We know the latent conversion rates of
our activities by channel
• We know how many deals we can count
on from the previous month by channel
• More Accurate ROAS
• Appropriate Supplemental Marketing Activities
• Nurture Campaigns
• Retargeting
• Content Marketing

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Step By Step Summary & Sample Data Set
• Dump Data Sets into individual tabs
• Make each data dump a table (this allows formulas to auto update)
• Vlookup the MQL date to the opportunity tab and the customer tab
• Vlookup the opportunity date to the customer tab
• Countifs formula = (range in data set, what criteria you want that range to meet, repeat
all criteria’s you want included) in this case >= current date – 30 and <= current date
• Countifs formula = (range in data set, what criteria you want that range to meet, repeat
all criteria’s you want included) in this case >= current date – 30 and <= current date for
both MQL and Opp/Opp and Customer/MQL and Customer
• Sample data set:

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Thanks so much for having me!
Heather is head of Paid Advertising at
Infusionsoft and a regular writer and speaker
on topics spanning digital advertising,
measurement and strategy.
Heather contributes to many publications and
served as a Technical Editor of Google
AdWords – Managing Your Advertising
Program (O’Reilly Media, 2011).
@HeatherCooan LinkedIn.com/in/hcooan