An attribution or look-back window is the period during which a factor tracked by a conversion or customer journey analytics model may be credited for a conversion. It’s a key part of multi-touch attribution and other marketing attribution models.
Advertising platforms use attribution windows to determine when an action or event on their platform should be linked to a conversion event.
Independent analytics tools also use attribution windows to identify the period in which a causal connection will be made between customer interactions or exposures and a conversion event.
When a reporting or attribution model uses an attribution window, factors such as interactions by a customer on a particular channel or platform or a specific touchpoint that occur outside the designated period won’t be acknowledged as responsible for or contributing to a conversion.
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Are attribution, lookback, and conversion windows the same?
The terms “lookback window” and “conversion window” are sometimes used interchangeably with the term attribution window. However, not every advertising platform or analytics tool applies the same definition to these terms.
For example, in the past, Meta (formerly Facebook) used “conversion windows” for tracking ad credit. However, the brand has since replaced this feature with “attribution setting.” Meta now uses the phrase “attribution setting” to refer to the “finite period of time during which conversions can be credited to your ad and used to inform campaign optimization.”
Google Ads defines the term “conversion window” as the period after an ad interaction during which a conversion is recorded in Google Ads.
This period is not the attribution period, though. On the Google Ads platform, the “lookback window” is the period during which a conversion ad is eligible for attribution credit. This variance in terminology distinguishes between the periods used for data collection and credit assignment.
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Why define an attribution window, and how does its size affect marketing analytics and reporting?
Marketing attribution is the method marketers and their advertising partners use to assign value to various marketing channels or tactics.
This value is based on the likelihood that a particular action contributed to a customer’s eventual conversion event.
Assigning credit is done using various models that may attribute all the credit for an event to one factor or assign fractional credits between several factors–a process called “multi-channel” or “multi-touch” attribution.
Marketers use attribution for two main purposes:
- To decide when an advertising partner should be credited (and paid) for a conversion event; and
- To identify those marketing channels and tactics that are most successful at producing conversion events.
Which of these purposes you’re pursuing will often guide which attribution model and attribution or conversion windows you’ll use.
In the first instance, when paying an ad platform for performance, a narrow attribution window may work to your benefit. A short lookback period ensures that your brand only pays for those impressions or click-throughs that are most proximate to the conversion event you’ve defined.
If a customer sees an ad on social media on Monday but doesn’t visit your website until Friday, Monday’s ad publisher doesn’t get credit for the ensuing action.
In the second instance when your goal is to gain actionable insights, though, a short attribution window may mean missing out on critical information that can help you improve your customer acquisition funnel and increase conversions.
Sure, you may not want to assign full credit to Monday’s ad–it didn’t even get a click-through! But isn’t it important to know that the customer saw Monday’s ad when you’re trying to figure out what made them convert on Friday?
Very few customer journeys today are limited to a single day, a single channel, or a single encounter with your brand. Your prospects are bouncing from platform to platform, switching devices, and getting their insights and inspiration for making purchasing decisions from all over the place.
The shorter your attribution window, the less you know about where they were before they made their decision.
But does that mean that you should look back through every interaction from the first moment you and your customer met to attribute credit for today’s conversion?
While the information might be useful–especially if you are trying to identify what makes your highest lifetime value customers stick around–looking back that far isn’t always the best use of your time. Data from years ago isn’t likely to offer much insight into which of this year’s marketing campaigns was most effective.
How, then, do you decide how far to look back when assigning credit for a specific conversion?
The attribution window you choose for your customer journey analytics will significantly impact the output you obtain, and, ultimately, you may decide that one window isn’t enough. Look at your business model, available resources, and objectives to guide your decision.
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Factors to consider when choosing an attribution window for your customer journey analytics model
Many platforms allow advertisers to choose from a fixed set of attribution periods. This limits the amount of data available from these sources.
However, within your analytics system you can combine that information with data from internal and other external sources to build a more comprehensive view of your journey tactics and performance.
Once your organization gathers conversion data from your advertising and other third-party attribution partners, normalizes and integrates the information, it can be analyzed using varying attribution windows to compare the results.
How to choose which time intervals to examine and compare?
Approach your decision by asking the following questions:
- What sources of attribution data are available to you?
Attribution lookback periods will be limited by the source of the information. Most advertising partners and aggregate attribution data providers define minimum and maximum attribution windows.
For example, Quora’s default attribution window for click-through ads is 28 days. For view-through (impression) ads, the default conversion window is 1 day. Publishers can adjust these windows to up to 90 days for click-through conversion credits and 30 days for impression.
In comparison, Google Analytics allows you to look back for up to 90 days. The default conversion window for search and display campaigns is 30 days.
- What is your average sales cycle?
To determine an effective attribution window, you’ll need to get granular and set an interval that’s relevant to the specific campaign being evaluated and your study objectives.
However, different businesses have vastly different sales cycles, so before you can narrow down your window size, you need to establish what’s within the realm of possibility.
An enterprise brand with a multi-month sales cycle will probably employ a much wider attribution window than a fast-fashion brand that relies on banner ads and impulse purchases.
Sales cycles within the B2B and B2C realms can vary widely, too. Someone purchasing a new home may take longer to arrive at a decision than someone looking for a place to order takeout.
Set some standard benchmarks based on your average sales cycle and the intervals between micro conversions before you choose the attribution window for a specific attribution model.
- What type of campaigns are you evaluating?
The channel and campaign type you’re using to achieve conversions will influence how long the attribution window should be. An awareness campaign may take longer to generate a conversion than a bottom-of-the-funnel push.
If you want to examine and compare the effectiveness of various awareness tactics, you’ll need to use a window that’s long enough to connect the dots between cause and effect.
- For what conversion event are you attributing credit?
Sales aren’t the only type of conversion event about which you may decide to gather data. Interim conversion steps on the way to your first sale and conversions after that first sale will have different cycles and be supported by different campaigns. These variances make a one-size-fits-all window inadequate for gaining useful information.
Use historical performance data to determine what the average conversion period is for the event you are tracking, whether it’s downloading a lead magnet, signing up for a demo, registering for a free trial, or becoming a repeat purchaser.
- What information are you hoping to gain?
When setting your attribution window, ask yourself what you want to know and if the window you’ve chosen will help you get that answer. If you’re evaluating and comparing various “Act now!” campaign, it doesn’t make sense to look back more than a few days.
If you’re seeking insights into which channels attract your highest-value customers, you may need a longer history of interactions from which to gain actionable insights.
Setting long or short attribution windows can assist you in evaluating different channels or advertising partners, too.
If you’re trying out a new advertising network and don’t want them to receive credit for your other network’s efforts, you can set a very narrow window. On the other hand, if you want to see how a new channel or network performs over time, you might set a long attribution window to give them a chance to gain momentum.
Wrapping up attribution windows
- An attribution or conversion window is the period in which an action such as an ad display, email click-through or other marketing effort will be given credit for the subsequent conversion.
- Advertisers use attribution to claim credit for generating conversions for a brand. Marketers and brands use attribution to assign credit to various advertisers, marketing channels and marketing or other sales tactics.
- How wide or narrow your attribution window is set will determine how many channels, touchpoints or tactics may be in line to receive credit for a conversion and how much credit each one receives.
- Setting a realistic window will improve the quality and actionability of your attribution analytics.