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 Solutions 1.Tracking incomplete and inconsistent. 2.Leading indicators misleading. 3.Tracking too basic. The Outcome Where we focused improvement … and the results Unresolved Issues Questions

About BuildDirect BuildDirect is an eCommerce platform servicing high volume purchasers of building materials. In business since 1999 Around 50 employees, $50 million in sales Sell to both business and residential Primarily finishing products: Flooring, Decking, Siding etc Majority 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 Leakage Many 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 Sales Online sales being attributed in multiple tracking systems: PPC tracking tool Shopping Engine tracking tool Affiliate tracking tool Some systems more robust than others PPC included some offline sales We had no way of evaluating PPC against other marketing initiatives

Quantifying the Leakage Problem Customer Feedback Testing Allocate tracked revenue to relevant source. Compare to total revenue.

How we solved these issues - Cookie Tracking - Unique 800# - Promote Sign in, Capture, Sample Sale - De-duplicate/ Household Data - Cookie aggregation based on house-holding - Match call and detail to household data - Match sales to grouped cookie data - Attribute sales to relevant sources

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

Issue #2: Leading Indicators Misleading

The Problem in 2007 Lacked 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

The Solution: Quality Visit Score Proxy values mapped for key short term actions Phone calls assigned a $ value based on historic conversion rate Sample sales assigned a $ value based on conversion rate Developed Quality Score based on actions during visit Depth of visit impacts score Viewing key pages impacts score Key actions impacts score (e.g. going to cart and calculating shipping)

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 date We wanted to factor in other issues Outbound calls by sales Leads (samples, phone calls) Different treatment for repeat purchasers Different treatment for direct sales assigned accounts Lifetime value of an acquisition Ensure 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 First Source Last Source

Is the attribution method really important? Paid search looks 20% LESS effective if "Last Source" attributio n is used. Shopping Engines look 30% MORE effective if "Last Source" attributio n is used.

Is attribution less important with a short sales cycle?

The Solution All sources tracked in data warehouse System assigns sale to all sources and weights revenue and # orders based on assist model Assist model 25% of revenue automatically goes to first source Remaining revenue assigned equally among all sources (including first source)

Other Issues To Consider When Evaluating Marketing Spend Monitoring activity by click date not sale date Leads (samples, phone calls) Sales linked to these actions via house-holding Cost per lead useful metric Factor in direct sales activity Outbound calls by sales treated as “assist” Different treatment for direct sales assigned accounts Different treatment for repeat purchasers Only a portion of repeat revenue attributed to marketing Lifetime value of an acquisition Monitored as secondary metrics Revenue from new buyers/ # new buyers monitored as secondary metric Ensure all costs included in “ad spend” Cost of 3 rd party tracking, Management of programs Cost 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 company Only took share of margin based on assist model Ad Spend includes all costs (Ad Spend, 3 rd party management, monitoring tools) Other key metrics Clicks/ Click through rate Quality site visits Leads Sample sales Inbound calls/ s Cost per Lead Total Margin Generated Need to be careful not to focus too much on MOAS

Where we focused our improvements Balancing MOAS between marketing sources Balancing MOAS by product line Acted as a catalytic mechanism

The Results

Unresolved Issues

Some leakage issues remain We 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