The focus for most firms is to get their customer to convert. Whether it’s a visit, a click, or a purchase, conversions come in many different forms but they are the ultimate goal. Sometimes this conversion can take weeks. Other times the conversion can be immediate. Conversions are just like falling in love. There are some that fall in love at first sight. Others can take many months. Everyone is different.
|(Source: Inviting Smiles)|
In love, there is no secret love potion to cause two people to love each other. There is no Cupid flying around shooting arrows causing people to love. The same goes for conversions. There isn’t a magic potion that unlocks the secret of how to convert people. Almost everyone is converted differently. As such, in creating a marketing strategy, several different campaigns have to be implemented. This is called multitouch or multi-channel funnels; there are multiple touches by the user before they are converted or there are multiple channels through which they arrive at conversion.
For example, a user might take a path similar to this in his/her process to conversion:
- Day 1
- See a banner ad for the first impression but didn’t click
- Day 7
- Do a organic Google search for the product
- Visit the site and sign up for email promotions from the company
- Day 14
- See the product featured on a friend’s Facebook news feed
- Day 21
- See a sponsored tweet from the company while surfing Twitter’s timeline and click on the link that leads to a YouTube video about the product
- Watch the YouTube video and take no further action
- Day 28
- Receive email promotion directly from the company
- Day 35
- See a banner ad on Yahoo
- Click on the banner ad and visit the website
- Make purchase and become a converted customer
As we can see, the process can be very lengthy. It can be almost impossible to determine exactly when the customer finally fell in love and converted. They could have been converted on Day 7 but didn’t pull the trigger until Day 35. Or it could have taken them the full 5 weeks to finally become a paying customer. For companies, it becomes very important to diversify their strategy, as it is not clear through which channel their customers will come. They must also determine which of the many channels is the most successful in conversions so that they can best allocate their marketing dollars.
Who gets the credit?
We all want to take the credit. These multiple touches and channels lead to the issue of attribution. The attribution problem is knowing who deserves the credit for the conversion. Just like George, Google, Yahoo, Facebook, Twitter, and the actual company itself can all claim to deserve at least some of the credit in the conversion in the example above. They all possibly contributed in the user falling in love and as a result, feel like they deserve some of the revenue.
The most common and standard model to an attribution problem is Last-Click Credit. In the example above Yahoo would receive the credit for the customer’s conversion, as they were the last click. Even though there were several other impressions and touches before the Yahoo banner ad, the last channel receives the revenue credit.
As web analytics develops in 2013, there are more and more tools that are available to help better distribute credit among different channels. Now that Google Analytics is available to everyone, more and more website owners have the ability to better track credit and solve the problem of attribution. Google Analytics gives users the ability to choose the model that best fits their situation and allows them to allocate their budget accordingly. Here are a few of Google’s models that give users something more than just the Last-Click Credit model:
This is just the beginning. Attribution modeling that addresses the multiple channel issue is just part of the story. Going forward there are other issues that will arise. Mike Shaw from comScore pinpoints the challenge of web analytics. “Analytics providers need to adapt to this changing digital world to become a trusted resource for understanding cross-platform consumer behavior and enabling multi-platform unification of all data” (Source: The Drum). As analysts try to understand the true value to each little piece of content on the web through the many interconnected channels, it will become more and more important to unify that data. The current attribution models still don’t paint the whole picture and can’t tell us how users are falling in love but it's definitely a start.
- Kaushik, A. (2010), Web Analytics 2.0, Indianapolis, IN: Wiley Publishing, Inc.