Discover the various attribution and attribution modeling tools that can help your organization.
- [Voiceover] If you've been working in digital marketing lately, you've probably been hearing all the buzz about attribution and for good reason. it's not a new problem but with all of this data, we now have some really interesting and effective new ways of tackling this problem. So let's take a brief look at what it is and then we'll dive into some of the tools you can add to your technology stack to help. A great analogy to attribution within marketing is the dating process. You're probably not going to propose marriage on the very first date. And by the same logic, marketers shouldn't expect a consumer's first interaction with your brand to immediately result in a lifetime of happy purchases.
There is a process to acquiring a customer. And just like dating, there are different contexts and scenarios as you move from date to date or marketing touch point to marketing touch point. Attribution is the art and science of attributing value to each one of those touch points on that path to purchase. And it has always been a pretty hard thing to do. So let's take a quick example. Say you sent out an email newsletter with a specific promotion and someone received that email, clicked on it and then purchased something worth $100.00 to you.
In a really simplistic model, you might attribute $100.00 to that email marketing channel and that specific email newsletter campaign. But let's think through that a little bit more. How did they get to be an email subscriber in the first place? Well, they probably responded to some other marketing initiatives prior to being made aware of the brand and eventually convinced that they should sign up for that newsletter. It might have been an upper funnel branding initiative, like a television ad or a display ad. They might have used a search engine to dig in a little deeper.
And your SEO efforts got them to click on your organic results. They might have interacted with you on social media, eventually done another search and then clicked on one of your paid search ads. And then they signed up for that newsletter. Now this is a pretty simple example, but you can see just how easy it is for lots and lots of interactions to take place prior to a purchase or some kind of larger macro conversion event. So there's the big question, should that email campaign really have taken a hundred percent of the credit for the sale? The answer is a little more gray than just yes or no.
And the reality is, it depends. Attribution modeling allows us to use a number of different filters to look at and attribute value to the path to purchase in different ways. And none are right or wrong. They just offer us a different way of evaluating the contributions of each of our marketing channels so that we can make better decisions around how we allocate our budgets. There are some really common models out there that are worth taking a look at. First, that's what's known as last click or last touch attribution.
In that model, the last interaction point, in our case that would be the email campaign, would get all the credit. Now there's also a first touch model where exactly the opposite is true. That TV spot or the display ad in our example would get all the credit because, hey, if it wasn't for that ad they would have never found out about us. Now there's also a lot of models where credit is shared across all the touch points. You've got linear models that break up the credit evenly among all the touch points. Decay models that may weigh touch points higher the closer the get to that final conversion and of course there are many more.
And there's lots and lots of custom models that can be built to reflect your own organizations situation and that's really the point. Models are created to help us understand more about complex situations and ultimately they help us make better decisions. So how do we actually do this? Well, as you probably guessed there are plenty of tools out there that can integrate into the marketing technology stack to help us out. First, it's worth mentioning that enterprise level analytics tools worth their salt will have at least some functionality in this space.
At the very least, they'll let you see your data in the context of a first or last touch model. And many allow you to make all kinds of customizations to explore a little deeper. But if you're serious about attribution modeling you'll likely end up considering a tool that's focused on that specific job. There are a number of vendors out there with solutions and it's important to note that just about all of them are aimed at larger enterprises. As you can imagine, there's a certain threshold of data that has to be there before these begin to make sense.
But if you're in that range, you've got options like Google's Adometry, Verizon and AOL's Convertro, Visual IQ, Neustar's Marketshare, Ebay Enterprise, which used to be Clear Saleing and many, many more. Once implemented these tools can monitor all of the digital touch points you've got and they allow you to create, tweak and explore models that attribute the value being created by your cross channel marketing activities. Many are focused on the digital channels but there are others that can ingest data around your offline campaigns like television and add them into the mix as well.
If you're managing lots of different channels with big budgets, you'll no doubt want to know how your mix is performing and even more you'll want to know where to put that next marketing dollar. Adding attribution to your marketing technology stack can be a great strategy for getting those kinds of insights that will make sure that you're spending your money wisely.
NOTE: While specific software and platforms aren't endorsed, you will see how tools like a customer relationship management system and web analytics work in a successful marketing mix.
- What is digital marketing?
- Understanding the marketing data being generated
- Reaching customers via digital channels like social, search, and display
- Working with digital experiences
- Selling online with ecommerce
- Going mobile
- Measuring and optimizing with testing and analytics
- Running and operating a business with technology
- Storing and extracting data
- Learning and predicting with data exploration and modeling