Optimizing Marketing Spend Through Multi-Source Conversion Attribution

David Jenkins

Introduction

Key Questions What marketing activities impact a sale?How to allocate marketing budget optimally between these activities?

The Problems . . . and Solutions1. Tracking incomplete and inconsistent.2. Leading indicators misleading.3. Tracking too basic.

The OutcomeWhere we focused improvement … and the results

Unresolved IssuesQuestions

About BuildDirect

BuildDirect is an eCommerce platform servicing high volume purchasers of building materials.In business since 1999Around 50 employees, $50 million in salesSell to both business and residentialPrimarily finishing products: Flooring, Decking, Siding etcMajority of customers interact with website

BuildDirect’s Marketing Activities

Branding/ Traffic Based

ROI Based Activities

Issue #1: Tracking Incomplete and Inconsistent

The Problem in 2007

LeakageMany sales that should have been linked to Marketing activities were “leaking” out of the tracking system. Main Causes

• Large share of sales close offline• Multiple contacts involved in a B2B sale• Long sales cycle• Sole reliance on cookie-based tracking

Double Counting of SalesOnline sales being attributed in multiple tracking systems:

• PPC tracking tool• Shopping Engine tracking tool• Affiliate tracking tool

Some systems more robust than othersPPC included some offline salesWe had no way of evaluating PPC against other marketing initiatives

Quantifying the Leakage ProblemCustomer Feedback

Testing

Allocate tracked revenue to relevant source. Compare to total revenue.

Trackable Revenue Before New System Implemented

Trackable Revenue

43%

Untrackable Revenue57%

Trackable Revenue includes revenue that can be mapped to:- Direct Sales Activities- Paid Marketing Activities

- "Free" Marketing- Repeat Buyers

How we solved these issues

Data Warehouse

- Cookie Tracking- Unique 800#- Promote Sign in, email Capture, Sample Sale

- De-duplicate/ Household Data- Cookie aggregation based on house-holding- Match call and email detail to household data- Match sales to grouped cookie data- Attribute sales to relevant sources

Web AnalyticsData

Call DetailSales tracked in

3rd Party Systems

Email detail

CRM

The results . . .

We were in a better position to more effectively attribute revenueHowever, we did not feel we knew which sources were performing best . . .

Trackable Revenue After New System Implemented

Trackable Revenue

81%

Untrackable Revenue19%

Before New System Implemented

Trackable Revenue

43%

Untrackable Revenue57%

Issue #2: Leading Indicators Misleading

The Problem in 2007Lacked a good leading indicator to employ in bidding engines.

Long Sales Cycle• Very difficult to accurately tune bidding engines to react in the short term

Minimum order volumes• Unqualified visitors add noise to click through rates

Large Average Order Value • Results in lumpiness when monitoring ROAS

Click Through Rates Can be Misleading(4 keywords with similar cost per click, exposure and average position)

0%

2%

4%

6%

8%

10%

12%

14%

Click-Thru Rate Final Performance

Keyword 1 Keyword 2 Keyword 3 Keyword 4

The Solution: Quality Visit ScoreProxy values mapped for key short term actions

Phone calls assigned a $ value based on historic conversion rateSample sales assigned a $ value based on conversion rate

Developed Quality Score based on actions during visitDepth of visit impacts scoreViewing key pages impacts scoreKey actions impacts score (e.g. going to cart and calculating shipping)

Click Through Rates Can be Misleading

0%

2%

4%

6%

8%

10%

12%

14%

Click-Thru Rate Quality Rating Final Performance

Keyword 1 Keyword 2 Keyword 3 Keyword 4

Issue # 3: Tracking Too Basic

The Problems

Web metrics tool could only link a sale to one Marketing activity.

We knew there were interactions but could not quantify.

Needed to Analyze sales by click date, not sale dateWe wanted to factor in other issues

Outbound calls by salesLeads (samples, phone calls) Different treatment for repeat purchasersDifferent treatment for direct sales assigned accountsLifetime value of an acquisitionEnsure all costs included – even tracking costs

The Problem: How to attribute a sale to multiple activities

Which source gets the credit?First?

Last?

All Sources Get All Revenue?

Assist Model?

50% of our sales involve touches with > 1 marketing medium

Day 1 8 20 26 43 51Source/ Action

Yahoo Organic

Yahoo Organic

Google Shopping

Sample Purchase

Shopping Bizrate

Purchase

Product Line/

"Stone Siding"

"Porcelain Tile"

Porcelain Tile

Porcelain Tile

Porcelain Tile

Porcelain Tile

Day 1 13 18 21 21 26 42 42 42 42 43Source/ Action

Google Organic

Google Shopping

Google PPCGoogle

ShoppingSample

PurchaseNexttag

ShoppingNexttag

ShoppingGoogle

ShoppingGoogle

ShoppingShopping.com Shopping

Purchase

Product Line/

Keyword

"select cinnamon wide

plank maple flooring"

"American Cherry

Flooring"

"flooring maple"

"shiraz maple

flooring"

Maple Flooring/ Bamboo Flooring

"Bamboo Flooring"

"Hardwood Flooring"

"beauchene cherry spice"

"beauchene cherry

reviews"

"Hardwood Flooring"

Hardwood Flooring

Day 1 1 1 20 20 21

Source/ Action

Shopping Bizrate

Yahoo Organic

Sample Purchase

AffiliateGoogle Organic

Purchase

Product Line/

Keyword

Laminate Flooring

"Laminate Flooring"

Laminate Flooring

Laminate Flooring

"build direct"Laminate Flooring

First Source

Last Source

Is the attribution method really important?

Impact on Revenue Attribution Based on Method UsedFirst Source Assigned Revenue vs Last Source

0

20

40

60

80

100

120

140

PPC Organic Affiliate Shopping Email

First Source Last Source

Paid search looks 20% LESS effective if "Last Source" attribution is used.

Shopping Engines look 30% MORE effective if "Last Source" attribution is used.

Is attribution less important with a short sales cycle?

Impact of Revenue Attribution for Sample SalesWhen first source is used to attribute sales vs last source

0

20

40

60

80

100

120

140

PPC Shopping

First Source Last Source

Even short sales cycle products are impacted by this issue(over 50% of sample sales occur on the same day as the first click)

Shopping Engines look 25% MORE effective if "Last Source" attribution is used.

The Solution

All sources tracked in data warehouseSystem assigns sale to all sources and weights revenue and # orders based on assist model

Assist model25% of revenue automatically goes to first source

Remaining revenue assigned equally among all sources (including first source)

Day 1 15 20

Source/ Action

Google PPC Affiliate Purchase

Product Line/

Keyword

Laminate Flooring

Laminate Flooring

Laminate Flooring

Share of Revenue

25% + 75%/2 = 62.5%

75%/2 = 37.5%

Revenue Allocated

$1,563 $938 $2,500

Example: 2 Sources

Day 1 15 19 20

Source/ Action

Google PPC Affiliate email Purchase

Product Line/

Keyword

Laminate Flooring

Laminate Flooring

Laminate Flooring

Share of Revenue

25% + 75%/3 =

50%

75%/3 = 25%

75%/3 = 25%

Revenue Allocated

$1,250 $625 $625 $2,500

Example: 3 Sources

Other Issues To Consider When Evaluating Marketing Spend

Monitoring activity by click date not sale dateLeads (samples, phone calls)

Sales linked to these actions via house-holdingCost per lead useful metric

Factor in direct sales activityOutbound calls by sales treated as “assist” Different treatment for direct sales assigned accounts

Different treatment for repeat purchasersOnly a portion of repeat revenue attributed to marketing

Lifetime value of an acquisitionMonitored as secondary metricsRevenue from new buyers/ # new buyers monitored as secondary metric

Ensure all costs included in “ad spend”Cost of 3rd party tracking, Management of programsCost of sample program

Where we focused our improvement . . . and the results

Metrics

#1 – MOAS (Weighted Margin on Ad Spend)Replaced return on ad spend – more important as a low margin companyOnly took share of margin based on assist modelAd Spend includes all costs (Ad Spend, 3rd party management, monitoring tools)

Other key metricsClicks/ Click through rateQuality site visitsLeads

• Sample sales• Inbound calls/ emails

Cost per LeadTotal Margin Generated

• Need to be careful not to focus too much on MOAS

Where we focused our improvementsBalancing MOAS between marketing sources

Balancing MOAS by product line• Acted as a catalytic mechanism

Visits Cost (incl mgmt fees)

Cost Per Visit

# Calls # Samples # Orders Revenue Margin Cost/ Lead

Quality Rating

MOAS

Bamboo Flooring 2.1Cork Flooring 0.9Laminate Flooring 1.2Travertine Tile 1.8Marble Tile 1.9Kitchen & Bath 2Composite Decking 1.8Stone Siding 1.0Roofing 0.7Total 1.7

LeadsProduct Line SalesTraffic Summary Conversion

Visits Cost (incl mgmt fees)

Cost Per Visit

# Calls # Samples # Orders Revenue Margin Cost/ Lead

Quality Rating

MOAS

Affiliate 2.1Auction Sites 0.7Email 1.1PPC 1.7PPC-Tier 2 1.5Shopping 1.1Social 1.0Total 1.7

ConversionProduct Line Traffic Summary Leads Sales

The Results

Q4 2008 vs Q4 2007 - Change in Key Metrics

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

%Change in Cost %Change in Margin

Unresolved Issues

Unresolved Issues

Some leakage issues remainWe know leakage is not consistent across all sources.

• How can we quantify this?

Some sources are still problematic• Offline advertising

• Social media

• Advertising mediums that add long term branding value

We need to further refine our leading indicators• Use modeling to enhance quality visit metric

Still have some reliance on cookies

Conclusion

Removing gaps in tracking system helped us allocate our spend with more confidence (and success).

Building a short term proxy measure for quality visit generated more successful outcomes for initiatives driven by bidding engines.

Allocating revenue correctly across marketing sources changed our thinking.

Focusing our initiatives on a key metric helped to drive other efficiencies in the organization

Thank You

davidjenkins@builddirect.com