How good is your team at solving for marketing's holy grail?
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The Marketing < > Analytics Intersect, by Avinash Kaushik
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A slightly esoteric topic today, but one that I hope strengthens your analytical thinking.

One of the business side effects of the pandemic is that it has put a very sharp light on Marketing budgets. This is a very good thing under all circumstances, but particularly beneficial in times when most companies are not doing so well financially.

There is a sharper focus on conversions. 

From there, it is a hop, skip, and a jump to, hey, am I crediting my conversions to the marketing tactics correctly (a la attribution!).

Right then and there, your VP of Finance steps in with a, hey, how many of these conversions that you are claiming are ones that we would not have gotten anyway (a la incrementality!).

Two of the holiest of holy grails in Marketing: Attribution, Incrementality.

Analysts have died in their quests to get to those two things. So much sand, so little water.

Hence, you can imagine how irritated I was when someone said: 

Yes, we know the incrementality of marketing. We are doing attribution analysis.


You did not just say that.

I’m not so much upset as I’m just disappointed. 

Attribution and Incrementality are not the same thing. Chalk and cheese.

Incrementality identifies the conversions that would not have occurred without various marketing tactics.

Attribution is simply the science (sometimes, wrongly, art) of distributing credit for conversions.

None of those conversions might have been incremental.

Attribution ≠ Incrementality.

An upcoming TMAI Premium will cover types of incrementality and how to measure it smartly (I have the first draft of it done!).

For now, let me take this chance to touch on attribution modeling, and how you might be doing it wrong.

When you open a report in any digital analytics tool, like Google Analytics, almost all the reports you look at attribute full credit for the conversion to the referrer associated with the last session where the conversion occurred.*

(*For the Analytics super nerds, my sisters and brothers: Strictly speaking Google Analytics reports are not last-click conversion, they are last-non-direct-conversion.)

In English, this means if someone clicked on a Paid Search ad on Bing and converted...
Last-click attribution to Bing paid search ads.
…Bing gets credit for that conversion in your Analytics reports.

For example, a report like this one…
Google Analytics last-click report.
This report is not an accurate representation of advertising’s performance because the last-click rarely represents the complete consumer journey.

The customer might have seen, or been forced to see :), other ads. The act of identifying all the touch-points (impressions and/or clicks) and their influence is what’s known as attribution analysis.

Many analytics tools come built with functionality to do this (including Google Analytics). 

What Marketers do, in particular the ones whose job descriptions include only Paid Media, is say ok fine, let us look at all the touch-points that led to conversions.

This picture might look something like this….
Attribution across paid media.
This sucks less.

But. Notice a pattern. They are all paid ads.

Paid Media Marketers (sometimes referred to as Direct Response Team or Performance Marketing) love doing the above analysis because they are taking credit for the conversion and only distributing it to paid channels.

This inflates the importance of paid advertising, at the expense of owned and earned tactics.

That of course suits the agenda of your Paid Media Marketers just fine. 

But. It is wrong.

Because the complete consumer journey to conversion in this instance looks like this…
Attribution: Owned, Earned, Paid Media
The advertising played a role in driving the conversion. Yes. Great.

So did owned media, Email, the second to last before conversion.

And, so did earned media, Organic Search.

As you do digital attribution analysis, watch out for Paid Marketers who say they do attribution analysis but only count paid media channels. Sometimes you might not have the power, but if you do then try to resist this strategy of inflating paid marketing’s value.

In an act of self-preservation, they will make excuses about tools, tracking, process, and the weather to resist moving to a more accurate attribution model.

Excuses are just that… Excuses.

Every decent web analytics tool now includes built-in attribution analysis across owned, earned, and paid across digital platforms.

Here’s how you can measure how sophisticated your attribution approach is:

If you are using the full power of the attribution modeling across owned, earned, and paid, you are at an industry average level of analytics sophistication.

If you have hooked up the owned, earned, and paid multi-channel attribution analysis results directly to platforms you are buying ads on to ensure smarter bidding, you are at an industry leading level of analytics sophistication. 

(In English: Attribution analysis will give proper credit to AdWords instead of an over/under-inflated value. This can be connected to AdWords. AdWords will lower/raise your bids to account for the credit it deserves. Nice.)

Now you understand why attribution is important, how your Paid Marketing team might potentially be inflating its value, and how to check how sophisticated your approach is.s…
Challenge #1. Which attribution model rocks?

If last-click and last-non-direct-click are not the best, which attribution model should you use?
Some people like to use first-click.

First click attribution is akin to giving my first girlfriend 100% of the credit for me marrying my wife.

Not that smart, right?

You can read about all digital attribution models in this post on Occam's Razor - it contains pretty pictures! If you don’t need the details, in the post I recommend not using last-click, first-click, linear, time decay, position-based, models. If you are a genius, you can use custom attribution modeling.

The one I recommend is data-driven attribution modeling

Don’t overthink it. You and I are not as smart as machine learning algorithms that can analyze insane complexity across terabytes of information from millions of customer interactions.

Trust the machines. There are more productive uses of your time.
Challenge #2. Wait, what about all my offline media?

This is not the complete picture for so many companies…

Attribution: Owned, Earned, Paid Media
The real world also exists!

For so many companies, the reality of their marketing efforts looks like this...

Online & Offline Attribution
So what do you do with your Google or Adobe web analytics tool?

Not much.

Sure every company will tell you that you can stand on one feet, curl three left toes, raise your right hand, close only one eye, stand under a shower of arctic-cold water, and fast for 27 days and then do some hard coding to jury rig some sort of signal gathering mechanism with JavaScript hacking and maybe get your offline media into your web analytics tool and maybe you have complete attribution modeling ability.

I just want to observe that their recommended solution is difficult to pull off.

If you want to do (new phrase for you) Marketing Portfolio Attribution Analysis, using advanced statistical modeling is the only way out.

These are custom built for each company, there is no off-the-shelf product worth its salt.
Some consulting companies will sell you media mix modeling solutions, from experience I’ve come to see them with suspicion due to data access issues, stretching math and data beyond a stretching point and so much more.

If you spend so much on marketing that Portfolio Attribution Analysis is worth it for you, you need to hire a small number of brilliant people and empower them.  It is the only way to ensure digital is not being over-credited for the conversions that are rightly being driven by offline channels - or vice versa.
Attribution is not Incrementality.

Now that you are so much smarter with a new level of appreciation of the nuances involved…

Let me close the circle, and end this newsletter where we started.

Let’s say we got 10 conversions this month (each worth $14 million :)).

When we do attribution analysis, whatever kind you like, what we are essentially doing is taking the credit for those 10 conversions and distributing it across identified activity...
Online & Offline Attribution
This is good.

When done right, it helps you identify how to invest your marketing budget across owned, earned, and paid media optimally (the last-wish of every CMO).

But above is not the full picture of reality. This one is
Cleaner picture of sales drivers
By existing as a company what I mean is that there is a whole bunch of activity that could cause people to buy your company product - that has nothing to do with any kind of marketing.

I’ve constantly recommended that you buy Patagonia products because it is a company for social good and I love them.
You might have seen me wearing my blue nano puff jacket and thought I looked snazzy in it and right there you decided to buy it.

Perhaps you read a review of Patagonia products by my friend Daniel and you decided to buy it.

(True story) You might have landed in Frankfurt on a really cold day without a jacket - because California is warm! - and you bought the first jacket you bumped into, and it happened to be Patagonia.

Your mom noticed something in your hiking pictures and decided to gift you a gorgeous Mellow Melon Atom Sling

I could keep going on.

The company will sell a whole bunch of products merely by existing, and apart from the work done by the marketing team.

This is true for your company as well.

The number 10 above, that you were crediting only to Marketing, is wrong.

It is more like this...
Attribution across all company activity.
Incrementality then is being able to identify how many of the 10 conversions would have happened anyway - even if you did no marketing.

I’ve done loads of incrementality analyses during my career across different types of companies.

Using the highest percentage incrementality the data has demonstrated, the answer as to how many of the 10 conversions are incremental would look something like this.... It is measuring what's known as True Incrementality...
True Incrementality
Your True Incrementality of Marketing might be 8% or 22%.

Stay with me for, one more super analytics nerd bit.

Real attribution analysis then is the distribution of the credit for 3 conversions across all your multi-channel marketing efforts (online and offline).

Faux-real attribution analysis would be distributing the credit for those 3 conversions across only your digital channels.

What you do will determine how smart your company’s marketing strategy will be.
Bottom line: Whatever you do, never say attribution is incrementality. It’ll hurt my feelings. You are behind the eight ball if you are not using your web analytics tool to do digital attribution modeling across owned, earned, paid tactics. And, don’t forget to hook it up to ad platforms that allow for auto-optimization.

Much love.


PS: Measuring incrementality is really hard. An upcoming TMAI will cover the types of incrementality analysis you should perform (will give you a common language to speak with your team and company leadership) and the high-level options to measure the same.

PPS: Bonus Link: I did an interview with Sabir yesterday. We covered analytics best practices, mistakes ecommerce Marketers commonly make, and live's pivot points. You can watch the recording here on YouTube.
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