Half-Blind Attribution Modelling
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How identity resolution connects your marketing so you can see what really works.
Marketing's shattered mirror
Here's a weird paradox:
Marketing has never been so measurable - The rise of digital and analytics means we can see the effect of everything we do, almost instantly.
Marketing has never been so hard to measure - With so many channels, no purchase journey is a straight line. So, while we can see what works in any one channel, we can’t connect them all to see what works across the whole mix.
Here's the problem
That paradox hurts. Because, with so many places to invest your marketing budget, it’s never been more important to figure out how an action in any one channel – or any combination – leads to a sale.
This is the central challenge for every marketing department in every company: figuring out what really works. And it’s why so many smart marketing teams are investing time, money and effort in building attribution models: representations of their multi-channel world that try to connect each purchase back to the interactions that drove it.
But here’s the problem: these attribution models can’t create a whole picture because they can’t connect activities across channels – especially (but not exclusively) across the offline/online divide.
Create a clearer picture
This ‘half-blind’ attribution modelling is not much better than no model at all. Because it can lead to badly misguided conclusions about where you should be spending your money.
This short eBook is about the only way to fix that. It’s all about connecting your channel and data silos back to real people – and many of the world’s best marketing teams are doing it to improve their attribution models and create a clear picture of what’s working.
How marketers build attribution models now
Marketers have always tried to figure out which activities lead to revenue. But with so many touchpoints in the typical purchase journey, this has become a major challenge. The simplest approaches are, unfortunately, still the most common...
'Last Click' Attribution
Whatever the user did just before buying gets the credit for the sale. So even if you spent millions on a TV campaign, Google gets all the credit if the user happened to type your name into the search bar to find your site and make the purchase. The result: you allocate too much of your budget to SEO but don’t increase your TV spend.
'First Click' Attribution
As the name implies, this model simply credits the sale to whatever interaction first put the user on your radar screen. Clearly, this is just as misleading as ‘Last Click’ attribution. As marketing teams have recognised the distorting effects of these simple models, they’ve started to build better ones – models that start to connect the dots a bit...
The next step: Connecting a few dots
Simple attribution models mislead marketing teams, making them over-invest in the wrong places and under-invest in the right ones. So marketers are starting to connect some of their channels – the online ones that allow it.
In this approach, the e-Commerce system may be linked to the CRM system. Or the ad-serving platform might integrate with the on-site product recommendation tool.
With a persistent user ID, you can start to understand customer preferences across these few linked channels – as long as the user signs in everywhere.
The result is a slightly better picture. And that can be even worse.
Because these early models are starting to look sophisticated, they lull marketers into a false sense of what’s working and what’s not.
The most glaring example of all is the case of offline behaviours.
90% of all retail purchases are still made OFFLINE
Why offline is so important
A lot of important customer interactions happen offline. In retailing, 90% of purchases are still in stores. In banking, branch interactions can be as valuable and insight-generating as anything that happens online.
So it’s pretty important to figure out which of your many online activities contributed to offline behaviours – whether that’s sales in stores, calls to call centres or mortgage applications in-branch. If these interactions are not in your attribution model, you’re trying to measure your marketing activities based on a very limited picture – it’s like trying to map an entire house by looking through the front door keyhole.
But you’ve got to find a way: if you knew that people who did A, B and C offline were 10 times more likely to buy D, E and F products in stores, you’d invest heavily in A, B and C.
Connecting activities across several digital channels is hard enough.
Trying to connect online activity to offline purchase can seem almost impossible.
Why cross-channel measurement is so hard
Measuring the effect of different activities in different channels is so hard because you can’t share cookies between different marketing applications, platforms and channel silos.
So here you are, sitting on a great database of people who bought from you in shops or visited you in a branch. You even have their email addresses (because they’re in your loyalty programme or use your credit card or opted in to your email newsletter or downloaded your mobile app).
So you know exactly who bought what products.
And you know where and when.
The problem: there’s no way to connect this data to what they did online.
What you don’t know is what activities in a given channel drove desired behaviour in another.
Or which audience segments were ultimately converted by which marketing.
There’s just no place where you can make these connections.
That’s where new techniques that connect data silos – like identity resolution, or connecting different digital channels – come in.
A holistic, people-based model
The idea is simple: connect data across your many marketing apps, platforms and channels back to real people. So you can create holistic, people-based attribution models and see what’s really working.
Fully connected
When you connect all your consumer data, you can start truly people-based measurement, instead of channel-based or device-based measurement.
Your ad retargeting activities can be connected to your Email Service Provider.
If someone sees an ad on his smartphone, then switches to a tablet to make the purchase – you can see that, too.
All without breaching any cookie protocols or sharing any personally identifiable information.
By now, you’re probably feeling what hundreds of the world’s most sophisticated marketers already know: this is huge.
Identity resolution powers enlightened attribution modelling
It lets you connect all the dots in your multi-channel purchase journeys.
Now you can see that Segment A saw ads 6,7 and 9 (online) and were twice as likely to buy products A, B and C (offline).
Or more people from Segment B visited your website, watched that funny video, then went on to buy Product Z.
Or Segment C is far more likely to click through from a PPC ad and ended up buying a car.
The Benefits:
Resolving identity lets marketers measure more accurately and more holistically. That means you can:
- Build more accurate attribution models
- Optimise your budgets to increase marketing efficiency
- Give the digital team credit for all sales they drive, not just online sales
- Connect all silos, not just across the offline/online divide
Those are major benefits for any marketing team that’s serious about increasing performance.
And they’re only delivered if you can truly resolve identities.
Conclusion: If attribution models matter,identity resolution matters
Marketing has never been so measurable.
At the same time, it’s never been so hard to connect all these siloed metrics into one, comprehensive attribution model.
That’s why identity resolution is growing so fast across the very best brands in every category.
The technology might seem complex but the benefit is simple: now you can connect your different marketing applications and channels so you can see what’s really driving revenue not just what seems to be driving it.
And that makes all the difference.
Beyond measurement
Measurement is one of the big use cases for identity resolution. You can also use it to target different segments when they’re not even on your site – and to optimise experiences when they are.
If that sounds interesting, do check out our website.
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We're LiveRamp.
technology platforms, and data owners work together to create truly people-based consumer experiences.
We do that with our identity resolution service. LiveRamp ties data back to living, breathing people, and makes it possible to onboard that data in targeted, personalised and measurable initiatives across all channels.
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