Have you ever felt that an advertiser is following you? It’s very common, specially after you show some kind of interest for a product. Say you are going on vacations to Berlin and at some moment you were looking for a place to stay in Airbnb. “Forgot it”, you think. “I found a cheaper hotel in Booking.com and I don’t need a place to stay anymore”. Nevertheless, Airbnb doesn’t know that happened and they will keep showing ads to everyone that at some moment got interested for a reservation. There is where the advertiser starts following you. Let’s see how this works.
A similar approach is used by social media and search advertisers. Just like GATC, Facebook has a Pixel code we can install so we know what happened during a visit to our website, which products did users visit, if they added a product to a cart and if they ended purchasing the product (or not).
And just like Facebook, Google and Twitter have quite similar products:
Facebook Pixel Helper
Twitter Pixel Helper
Or you may inspect the source code of the website you are currently and type ‘Google’, for example:
As you can see, we can be tracked by multiple actors involved in the user’s journey. Think that you don’t spend 100% of your time at Facebook. Probably you use Twitter and Pinterest as well, and when you are looking for information you go to Google Search. In addition, you may spend some of your time on mobile and the rest on desktop. And what if we are not online? Could we being tracked? Absolutely, but it becomes technically harder. See for example what Facebook says on offline conversions:
Our offline conversion measurement solution allows you to track when transactions occur in your physical retail store and other offline channels (ex: orders made over the phone) after people see or engage with your Facebook ad. By matching transaction data from your customer database or point-of-sale system to ads reporting, you can better understand the effectiveness of your advertising campaigns across all objectives on Facebook, Instagram, and Audience Network.
Continue reading in Get started with tracking offline conversions
In this case, offline conversions would work only to identify Facebook and Instagram users reached by an ad. But what then with Google, Twitter and other online platforms? And even if we don’t want to talk about offline conversions, but we just want to know if a Facebook user completed certain action in our website. We will never find a Facebook user in Google Analytics, for instance, simply because what a user is in Facebook is totally different for Google. Let’s see why.
Facebook users against Google users, are they the same?
Do you remember the first time you created a Facebook account? That time Facebook assigned you an ID associated to your email address and phone number. And then you created an Instagram account you connected with Facebook. That’s why Instagram keeps suggesting you new people to follow, because most of them are users you’ve probably engaged with on Facebook in the past. Considering both Facebook and Instagram belong to Facebook Inc. the problem starts when you have a different user account at Google, probably when you created a Gmail account. An this user has access to your Google Chrome and Android settings. Said this, for one single user may exist at least two different users: one for Google and one for Facebook.
In order for Google Analytics to determine which traffic belongs to which user, a unique identifier associated with each user is sent with each hit. This identifier can be a single, first-party cookie named _ga that stores a Google Analytics client ID, or you can use the User-ID feature in conjunction with the client ID to more accurately identify users across all the devices they use to access your site or app.
So in addition of being a Facebook, Google and Twitter user, you are also a cookie. and none of them knows each other may represent the same person. The question here is why is this a problem for advertisers?
Misleading conversion attribution
Very often, when sales are not going well, businesses will try to find out explanations on this atipical behavior, and if they have some online advertising actions running, they will try to get answers from here as well.
— Business owner: hey, sales are not going well this month.
— Marketing team: that’s weird. I’am seeing we got more sales this month coming from Facebook.
— Business owner: I’m saying we don’t. Actually Google Analytics is showing different numbers than yours.
This is a very common conversation when working with clients that depend on sales on a daily basis. Say retail and eCommerce. Only they will be able to know if things are going well (or not) and it doesn’t matter what some vanity metrics on an analytics tool say. What actually should we be concerned is by the sale, not the number of clicks, impressions or if CTR increased, and this is a huge challenge when working with businesses that never had the chance of measuring where could be clients coming from. Imagine a car dealer or a real estate business. OK, it’s great they are getting more leads at a better cost, but that won’t matter if they don’t convert leads into new clients, do they?
And here’s where having users and cookies separated becomes a problem. I want to create Facebook Ads, but I don’t know what users may be doing outside Facebook. How can I know the efectiveness of one of the channels if measurement solutions work separately to each other?
Actually, as you can see in the video above, there is a conversion attribution that means assigning credit for a conversion. Say that last click from a user that purchased our product occured in an ad in Google Search. Last interaction attribution will attribute 100% of the credit to that channel, and it will ignore social and organic channels in the contribution of this goal.
When working with this model we got two problems:
- You are ignoring all the journey of that user before clicking in your ad, and probably during that journey the user interacted with your business through different devices and different channels. Just because you are not seeing conversions coming from Twitter it doesn’t mean Twitter is not working. Probably this is a channel in which users discover your product, but they end up purchasing it later in the future by going directly to your website from a different device.
- You can’t use this model for all products. According to the Attribution modeling overview by Google Analytics Help, there are at least 7 models. How can you use the last interaction model in products whose conversions traditionally happen offline, such like retail, real estate or education? Actually, in some cases the decision of purchasing or not may take months. You don’t see a Facebook ad and purchase a product the next day, do you? Probably you will be exposed to more ads, you will do some research, ask friends and you will decide after a few weeks.
Recently ROI Hunter said Google Analytics can misattribute up to 21% of Facebook Clicks. Based on an analysis on 17.000 transactions, they concluded “Google does not track across the different devices (…) even when “users often use multiple devices” before purchasing a product. In addition, they said that “different attribution models used by both make it difficult to match conversion values”. For example, for Facebook “attribution window is set to 1-day view and 28-day click, which means you see actions that happened 1 day after someone viewed your ad and up to 28 days after someone clicked your ad”. Based on this, we can see that for both Facebook and Google a user is a different entity, and also both use a different methodoloy to count if a conversion happened (or not).
In short, when we talk about Google and Facebook measurement solutions, we have two different universes with different rules and entities. If in one universe we can find Facebook and Instagram users, in the other we will find cookies representing unique users. Since then, any action taken by both users should be viewed with different lens. If Google Analytics can’t track actions among different devices, but Facebook can, we should start by trying to understand separately how is our user behavior within each platform and analyze offline data.
If you are a real estate business and you’ve just sold a house, your client will be able to mention hundreds of reasons why he/she bought this house and not other one. Probably your ad made part of the decision, but also did it the price, the budget available for the purchase, the location, your brand and other reasons your analytics tool won’t be able to track. Because of this, start by paying attention to your online actions and how do you decide when buying a product, and stop attributing 100% of credit to individual channels.
Next time, when going to the supermarket, think why did you choose this brand or the other. If you installed an app, consider all the actors involved before taking that action. Did your friend mentioned it or you read a blog mentioning it? By doing this, you will better understand your users and how they behave with your business through different channels. While Google and Facebook are different universes, there are more universes out there, and probably you are not aware of them.
So, did you see an ad? Try to understand why are you seeing it.
Imagen: OnePoint Services