INBOX INSIGHTS, May 5, 2021: Attribution Models, Third Party Data, Predictive Analytics - Trust Insights Marketing Analytics Consulting

Attribution Models, Third Party Data, Predictive Analytics

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How Important is Attribution Modeling?

One of the questions we’re asked most often is about how to build effective attribution models. What’s the best model type? What kind of model should you build? What gives you the most actionable data?

The answer to this question depends very much on your audience and purchase process, as well as your data. Some businesses have very shallow paths to conversion; it’s rare for a conversion to require more than one or two touches. Those businesses are highly transactional; they tend to have little or no actual relationship with their customers, and there’s little risk in the purchase. Someone buying a pack of gum or a video game online would be examples. As such, their attribution models can remain relatively simple.

Other businesses have very deep paths to conversion, requiring dozens of touchpoints. Typically, these are businesses with big commitments from the buyer – and big risks if the purchase doesn’t work out. Think about a college education, a mortgage, IT hardware in your datacenter, or choosing an insurance provider for your business. The paths to conversion can be a tangled hairball. As a result, the attribution model for these kinds of businesses requires significant multi-touch analysis, and likely needs sophisticated techniques like machine learning and AI.

Take a look even in something like Google Analytics. For example, here’s the Trust Insights touches to conversions, which for us are filling out any form on the website:

You can see clearly that we have a 3.24 touches to conversion average; we definitely benefit from a multi-touch attribution model because there’s a lot of potential variation in how people find us and indicate their intent.

Compare that with this model from my personal website, which tracks form fills and book purchases:

This is a much more transactional site; the conversion path length is 1.63 and 85% of the conversions are 1 touch. This site could likely use first or last touch attribution and still get decent results – but it indicates a bigger potential problem – less of a relationship with customers, fewer ways for them to come back to the site. That could mean marketing channel problems.

So, which attribution model should you use?

If your touchpoints to conversion hover around 1.0, you can use any model and get decent results – and then focus on deepening your relationship with your customers.

If your touchpoints to conversion are greater than 2.0, consider a multi-touch model.

If your touchpoints to conversion are greater than 3.0, you definitely need a multi-touch model because you don’t know what’s happening in the middle of the buyer’s journey.

And if you have no idea how to do any of this or you just don’t want to do it… drop us a line.

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In this week’s episode of In-Ear Insights, Katie and Chris bring on special guest Brooke Sellas of BSquared.media to talk about third party data, iOS 14.5, and what marketers should be thinking about and doing to adapt to data loss now and in the future.

Watch/listen to this episode of In-Ear Insights here »

Last week on So What? The Marketing Analytics and Insights Live Show, we looked at how to make use of content marketing forecasts to plan your marketing calendar.

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This Thursday at 1 PM Eastern, we’re going to look at identifying influential podcasts using their digital footprints.

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Data Diaries - Interesting Data We Found

This week, we look at Instagram’s engagement rate for brands on unpaid content. The big question everyone’s had with the updates to iOS 14.5 is, will Facebook accommodate brands by boosting engagement as a way to keep the ad dollars flowing on their media properties?

The quick answer, of course, is that it’s too early to tell still. Many brands have gone through and made the required changes to keep their ads running; however, in terms of unpaid engagement on Facebook’s properties – like Instagram – there isn’t a clear signal yet, but early indicators suggest the answer is no.

We see that the rate of decline for brand engagement has started to accelerate a bit in mid-April; at the start of the month it was ~0.27% and by month’s end it was 0.25%, a 7% decline within the month. Since the beginning of the calendar year, we’ve seen a decline of 30.5% for brand unpaid content on Instagram.

What’s the key takeaway here? Facebook isn’t planning on doing your brand any favors when it comes to organic engagement on Instagram. There’s been no bump, no boost in unpaid social media engagement. What should you do about it? If Instagram is a core part of your strategy, look to influencers to fill the organic engagement gap and garner new audiences if you don’t feel like putting money directly in Mark Zuckerberg’s wallet. Either way, expect to pay for access to audiences on Instagram – and then do your best to get them off Instagram and onto a property you own as fast as possible.

Methodology: Trust Insights used Facebook’s Crowdtangle software to extract 497,578 posts from 3,890. Brands were identified by both Facebook and Trust Insights. The timeframe of the data is January 1 – May 3, 2021. The date of study is May 5, 2021. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors, and declares no competing interests.

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In the newly revised Third Edition of AI for Marketers book, you’ll get the answers you’ve been looking for. With all-new practical examples, you’ll learn:

Key marketing problems AI solves, such as:
- Attribution modeling
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Where can you find us in person?

ECommerce Marketing Summit, May 2021, virtual
AAF/Women in Analytics, May 13, 2021, virtual
ContentTech Summit, June 2021, virtual
MarketingProfs B2B Forum, October 2021, virtual

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