Table of Contents

Custom Attribution Configuration - Custom Weighting

Custom Attribution Configuration - Custom Weights

Custom Attribution - Purpose

Frequently, customers want to have the option of creating their own Custom Attribution Models. The Attribution Configuration feature allows users to create logic that weights attribution based on custom settings. This allows users to adjust the scoring of the attribution models based on their business goals and objectives, giving them more control over their analytics data.

Custom Attribution - Assumptions

What the Custom Attribution Scoring Models does apply to:
  • Only considers campaign variables (i.e. base it on channel or campaign type or campaign name or program.)
  • Inbound touches
Inbound touch definition
Prospects and customers can reach your company via inbound touches to ask questions, seek advice, or provide feedback. Websites, landing pages, Drift Chat, Demo requests, document downloads, webinar registrations, webinar attendance, listening to podcast, filling out forms, opening emails, clicking links, are all examples of inbound touches.
  • Applies to a multi-touch model
Multi-touch attribution scoring model definition
A multi-touch attribution model assumes that all touch points in the customer journey have an influence on conversion. An example of multi-touch attribution is to assign fractional credit to all touch points on the consumer journey, so that a marketer can find out how much influence each channel has on a particular sale. This allows marketers to measure the impact of each touchpoint on the overall conversion rate and allocate budget more effectively.
The Custom Attribution Scoring Model does NOT apply to:
  • Chain-Based or machine learning models
Chain-based or Machine learning attribution scoring model (CBA) definition
(CBA) - works backwards from Closed opportunities to analyze the complete chain of events and computes the contribution of each marketing channel to revenue. Using machine learning, CBA is always listening and improving the model over time. CBA calculates the actual contribution of each channel along the conversion path using your account's conversion data. A comparison of conversion paths between accounts that convert and those that don't determines what is truly important and what isn't.
  • Single-touch scoring models
Single touch attribution scoring model definition
An attribution model that assigns 100% of conversion credit to one marketing touchpoint is known as single-touch attribution. In a scenario in which a customer saw 20 advertisements before converting, single-touch attribution will determine only one is responsible for the conversion. Due to their simplicity, single-touch attribution models are easy to implement. This is because single-touch attribution models do not take into account the customer journey before making a conversion. Instead, they focus solely on the single touchpoint that is deemed to have caused the conversion and ignore all other factors. This makes single-touch attribution models easier to set up and use, but it also limits their ability to accurately measure and analyze the entire customer journey.
  • Attribution weights do NOT impact your lead or account scoring models. It does not impact the amount of credit a touch gets based on what kind of account or person associated with the lead. This is NOT lead scoring.
What is lead scoring?
Marketers and sales teams use lead scoring to determine how likely their leads are to buy. Your leads are given a score (often 1-100). Lead scores indicate a lead's probability of making a purchase. They're more likely to purchase if their score is higher. Lead scores are determined by various attributes – which include email unsubscribes, web site visits, job titles, and industries, to name a few.

Custom Attribution Configuration - Use Case Scenario and Analysis

Q: Why would I want to create a custom attribution model in CaliberMind?

CaliberMind Customer Attribution Model
A: Configuring a custom attribution model in CaliberMind allows you to influence where credit is given. For example, if you know that a tradeshow meeting is more influential than a content download, you can use attribution configuration to adjust the amount of credit or points each of those touches gets.

When customizing attribution, it's also beneficial to exclude low-value touch points. The filter mechanism lets us remove tactics that can bloat marketing's reported impact on pipeline and bookings, which dillutes our return on advertising spend calculations. By keeping the bar for attribution higher than a web visit or email open, we're only reporting the most influential interactions.

How to Configure a Custom Attribution Model

How to Configure a Custom Attribution Model - PDF Version

Using the "Otherwise" Statement
  • Once you have configured the desired individual values, you may want to add a catch-all statement to allocate some or zero points to the remaining/unspecified categories. To do that, click the button at the bottom labeled “Add Otherwise.”
CaliberMind Otherwise Statement
  • Here you can see that the user wants everything else to be awarded 0 attribution dollars. This means any campaign type not listed above will receive $0 of opportunity value.
CaliberMind custom attribution model

Attribution Timeframe Tab

The Attribution Timeframes tab allows the user to select if attribution should only include activities before the opportunity was created or if the opportunity should continue to allocate dollars to touches that happen after the opportunity is opened. This section of the setup screen also allows you to select how far back attribution should look (we recommend using at least as many days as it takes to open and close-win an opportunity)

CaliberMiind Attribution Timeframe Tab
Attribution Timeframe Discussion

Definition - Attribution timeframe is the span of time touches are considered for attribution. Some models look at first-touch to opportunity close while some models only look at "source" information, or what happens prior to opportunity create. This second view is useful if you want to lock in values as soon as the opportunity is created and aren't as interested in demonstrating the value of campaigns that are helpful in propelling in-flight opportunities forward.

Why should I have the Attribution Timeframe Toggle button on? - A lot of campaigns that are high cost are used by the sales team to engage existing opportunities. Examples of this include trade shows, in-person meetings, and webinars. By not looking at the dollars or opportunities that are propelled forward, we're not reporting the full value of these tactics and may cut spend on an event that is actually very productive.

Attribution Lookback Discussion

Definition - A look-back window is a the number of days prior to opportunity create that are considered influential in opening the opportunity. For example, if an average won opportunity takes three to six months to close, it may make sense to look back as far as 365 days to figure out how the prospect first heard of our brand and what they did as they researched what to buy. If our sales cycle is less than a month, it makes sense to only look back 90-180 days.

Why should I use the Attribution Lookback feature? Using a lookback window helps other departments feel comfortable with the time frame you're considering. If you select a very long lookback period, sales may get the impression that marketing is trying to get more "credit" for pipeline and bookings than they think is fair.

How do you calculate a lookback window? - We recommend looking back at least as many days back as the average amount of days it takes from opportunity creation to close (the "sales life cycle").

As an example - If your sales team averages 12 months from opportunity open to close-won, 365 days or more is a good lookback period.

Attribution Filter Tab

The Filter tab is the most efficient way to exclude certain campaigns, campaign types, or other campaign indicators from your attribution model.

CaliberMind Attribution Filter Tab
Attribution Filter Discussion

Why should I use the Attribution Filter for my custom model? - With filtering, you can eliminate things that happen too frequently or have a very low barrier to entry. For example, we know that if someone takes the time to reply to an email, fill out a form, or some other "hand raise," the normal expectation would be that the sales team will follow up. If we stay focused on the most influential touchpoints, other departments won't feel like marketing is "cheating" and claiming too much credit, and our return on investment calculations will be much more in line with reality.

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