How to Report on Multi-Touch Attribution
A Multi-Touch attribution model assumes that all touch points in the customer journey have an influence on conversion. There are three main types of Multi-Touch attribution models: Even-Weighted (each touch gets equal value), U-Shaped (weights first and last touch higher), W-Shaped (weights first-touch, touch-prior-to-conversion, and touch prior to deal higher), and Time Decay (touches near the beginning or end of the customer journey are weighted more).
Why You'd Use This Model
Customers interact with many different events during the buying journey, and multi-touch attribution models are helpful in gaining insight into the different touch points along said journey and how each impacts conversion. Multi-touch models paint a more holistic picture than Single Touch models for marketers looking to better understand the right combination of channels and messages used to achieve higher ROI for their marketing programs. They are also helpful for marketers looking to shorten their sales cycle by engaging customers with fewer but more impactful marketing messages.
WHO THIS is valuable for
Depending on the size of your organization, you may have different stakeholders. If you're a small business or midsize enterprise, this data will be valuable for:
- Demand Generation teams
- Marketing Analysts
- VPs of Marketing
- Chief Marketing Officers
- AVPs, VPs of Sales, Chief Revenue Officers
If you're an Enterprise organization, you can expect this data to be valuable for all of the above roles, aside from AVPs, VPs of Sales, and Chief Revenue Officers.
DATA You Need
- Any data that represents a “touch”. Lead Source, UTM, Salesforce campaign, event attendee list, etc.
- Opportunity data (Opened, Closed Won, Closed Lost) and/or the conversion event data you wish to measure.
- Agreed upon “time-bound.” For longer sales cycles, you may wish to look back 180 days or even 365 days prior-- relative to the conversion date. This sets the stage to how far back should data be counted.
data sources required
The more [clean] “event” data set you can add in, the more robust the resulting model will be. For example, a log of website visits + email clicks + form submits + sales activity is better than just having one of those sources. This includes any marketing or sales activity involving an interaction with the customer. This dataset will become the source data for attribution. These events (or touches) are all eligible to get the credit for the conversion
- Marketing Automation Platform (Marketo, Hubspot, Eloqua, Pardot, etc)
- CRM (Salesforce, SAP, etc)
- AnalyticsJS / product behavior
- Web Analytics (Google, Adobe)
- Ad Platforms (Google Ads, LinkedIn, Facebook)
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