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Multi-Channel Attribution - Where do Leads Come From?
Gary Angel, President of Semphonic presented a keynote discussion to the 2010 AIM Conference on the topic of attributing value to leads when the advertiser knows that multiple lead sources contribute to the buying decision.
It’s Getting Harder<br />The number and diversity of marketing channels is growing making attribution even harder.<br />
Why it Matters<br />Fights over attribution are sometimes perceived as being largely political:<br />My TV ads drove 5 million in business<br />My PPC campaign drove 2.5 million in business<br />How come we only had 6 million in sales?<br />My Display Campaign drove 1 million in business<br />
Why it Matters<br />But you can’t optimize your overall Media Mix or your individual channel strategy unless you understand how each marketing channel works and how the overall program works together.<br />
Why it Matters<br />For Instance:<br />If Natural Search attracts early-stage buyers, it may seem to perform worse than Paid Search even though it drives more new customers.<br />If Paid Search is heavily dependent on branded traffic, it may only perform well in conjunction with Mass Media buys.<br />If Display creates awareness but doesn’t drive direct traffic it may only work in conjunction with heavy search buys.<br />
Common Methods of Attribution<br />Last (Most Recent): The last known campaign touchpoint gets the credit for a conversion.<br />First (Original): The earliest known campaign touchpoint gets the credit.<br />Equal: Credit is divided equally between all known touchpoints.<br />All: Full credit is given to every touchpoint.<br />Spoken: Credit is given to the touchpoint identified by the customer.<br />
Last (Most Recent)<br />The more your lead/sales environment is multi-touch – the less well this method works.<br />In this example, 35% of the visitors who clicked on a paid brand term had already clicked on another paid term in the SAME session!<br />
First (Original)<br />Especially problematic with longer sales-cycles.<br />For this logged-in site, 33% of the people who registered used a different cookie IN THE SAME MONTH. More than 50% used a different cookie within 3 months.<br />
Equal (Shares Credit)<br />Doesn’t really help with Marketing Mix calculations.<br />
All (Every Touchpoint full Credit)<br />Doesn’t really help with Marketing Mix calculations.<br /><ul><li>If you’ve siloed reporting, there’s a good chance this is your de facto strategy!</li></li></ul><li>Spoken (Customer id’s Touchpoint)<br />Customer testimony is heavily influenced by collection point and method and, even at best, can be quite unreliable. <br />Only 64% of the most dissatisfied visitors in an online survey had actually used the tool they were rating.<br />
This method will allow separate attribution studies to be made of internal vs. external without one type screening off the others.</li></li></ul><li>Web Analytics Techniques<br /><ul><li>Campaign-Stacking
Use a cookie to store all campaign values recorded for a visitor
Pass to a variable in your web analytics solution
Omniture has a plug-in for this</li></li></ul><li>Web Analytics Techniques<br /><ul><li>Use multiple variables to track different attribution periods at least until confident of your sales-cycle.
We suggest the following attribution strategies:
It’s not just campaigns<br /><ul><li>This analysis looked at attribution based on previous visits without campaign sourcing. </li></ul>For two campaigns to this site, almost 50% of their click-throughs had already used the site! <br />
Showing Multi-Attribution<br /><ul><li>This Report shows how often each campaign interacts with others and what the total conversion rate is. </li></li></ul><li>Showing Multi-Attribution<br /><ul><li>Here’s the same report with the biggest incremental lifts highlighted. </li></li></ul><li>Dark-Period Testing<br /><ul><li>Testing media mix by going dark and tracking to baseline is a consistently useful method.</li></ul>In this case, going dark showed that the client had to purchase 6 clicks from these terms to get a single incremental visit.<br />
Correlation Analysis<br /><ul><li>Using correlation models, you can match marketing efforts to outcomes (if you have enough clean data):</li></ul>For this home products company we correlated weekly TV, Radio and Print TRPs, Banner Impressions, Search plus econometric data on housing starts and prices by region with web site activity.<br />Media effects only correlated with a 1-2 month lag – TV was by far the most impactful.<br />
Comprehensive Reporting<br /><ul><li>This client chose to compare campaigns by pipeline stage:</li></li></ul><li>Comprehensive Reporting<br /><ul><li>Here’s an example using our 4 Stage terminology:</li></ul>Comparison by Type<br />Best Companion<br />Best Overall & Trend<br />
Key Take-Aways<br />Analyze Carefully<br />Segment by Attribution and Life-stage type<br />Look at attribution beyond just marketing campaigns (existing customers/visitors)<br />Use Dark-Periods to Baseline and Tune Media Mix<br />Use Correlation Models to track marketing impacts vs. econometric variables<br />