As a digital marketer, you have almost endless data at your fingertips. If impactful marketing attribution is your objective, you don’t need it all – just the right data: User Identifiers, Timestamps, Media Data, and Channel Data. Gather (and govern!) these four types of data to allow your attribution efforts to tell your story effectively.
-Alison Latimer Lohse, Co-Founder and Chief Strategy Officer, Conversion Logic
On August 1st, I had the pleasure of hosting Alison Latimer Lohse at eSage Group’s monthly L.A. Marketing Analytics Group event in Santa Monica, CA. Alison took us through the full continuum of marketing attribution from:
Why Do Attribution: The marketing ecosystem is comprised of billions of different possible permutations of target audience touchpoints due to available marketing channels and tactics. Following the customer journey across this vast ecosystem to the point of conversion is challenging.
Attribution Determining Causality: Marketing attribution is the equivalent of determining causality. Conversion Logic focuses on advanced attribution: holistically measures points across all media stimuli in order to give credit where credit is due.
Marketing Channels: On an average over 90% of marketers said they used three or more channels currently, and a significant 39% said they will use more channels in 2 years. 6 on an average, and the number of available channels is on the rise. The good news: the trend is towards portability and accountability.
Marketer’s Questions to Consider: Credit where credit is due, Cross-channel impact, Identify waste and opportunities for scale, Find customers more efficiently, and Simulate investment strategy
Available Methodologies:
- Last Touch: 100% credit to the last touchpoint leading to conversion
- Rules/Heuristics: Rules used to allocate credit to each channel for conversion based on sequence, weighting etc.
- Vendor Reporting: Publisher provides metrics on how media performed
- Statistical Model: Statistical approach to allocate credit to each channel / touch-point (linear or logistic regression)
- Machine Learning Predictive Ensemble: Ensemble methods use multiple algorithms to obtain better predictive performance.
Approaches to Marketing Measurement:
- Media Mix Modeling (MMM)
- Cross-Channel Modeling
- User Level Attribution
Assess Attribution Readiness:
- Identity: Know your objectives and align across the business
- Alignment: Executive Buy In, Cross functional Champions, Ownership
- Organize: Be conscious of how your mar-tech systems work together, make sure you can track all conversion data, create consistent taxonomy and data structure
Alison was only scratching the surface of the available innovations and successes of a well-thought marketing attribution plan. One of the key takeaways for me was the part of her talk that covered Attribution Readiness and the need for businesses to take an honest look at their available data around marketing channels to assess whether or not they are ready to launch into attribution. Some of the important assessment tests that were talked about, include a checklist of items to be aware of. I think they are important enough to leave you with them as parting food for thought. Enjoy!
Attribution Evaluation Checklist
Methodology
– Digital Fractional Attribution Methodology
– Cross-Channel Modelling (Online & Offline)
– Modelling Transparency and Validation
Data
– Data Alignment & Reliability
– On-boarding and ETL Support
Partner
– Customer Service Level
– Implementation Time
– Partnership Cost
Product
– Side-by-Side Comparison of Last Click & Attributed Value
– Path to Conversion Analysis
– Detailed Optimization Insights & Recommendations
– Mobile Insights
– Customizable, Granular and Actionable Front-End