Today I am starting my series about Adobe's new product: Adobe Customer Journey Analytics.
I also want to correct one wrong assumption. Customer Journey Analytics do not replace Adobe Analytics, it is Adobe Analytic’s new feature and its new product. It enhances your analytics capability but you will still collect your digital data with Adobe Analytics as usual. Customer Journey Analytics unite online and offline data for a complete customer journey view.
It is Adobe Analytics’ feature but it is also standalone product by itself on Adobe Experience Platform but you have to have Adobe Analytics to use it. It is basically an alternative to other Business Intelligence products like Tableau which brings all data online and offline in 1 place to unite all customer data.
Adobe Analytics have multiple solutions to achieve this.
Adobe Customer Journey Analytics is more developed version of Data Workbench.
Data Sources is lighter version of Data Workbench where you import some data into Adobe Analytics.
Data Feed is the method we use when we want to import raw Adobe Analytics data out of Adobe into our internal servers.
All of them are older platform products. For instance data feed is so old that some of the columns there are not used anymore but they are still there since we database infrastructure still based on Omniture and you know these things are hard to change.
Customer Journey Analytics is a new platform that is part of new Adobe Experience Platform. I said that Adobe Customer Journey Analytics is more developed version of Data Workbench but this relation is more about the technical side. Data Workbench is not much a place to do very complex business intelligence analysis. What we try to achieve with Adobe Customer Journey is similar when we use Data Feed option. I did big Data Feed projects with big clients who has lots of digital and offline customer behavior. Under this model I set up Data Feed and bring Adobe Analytics data in DWH and unite customer behavior online or offline with several ID’s customer ID, email, session ID visitor ID etc. In this case of course you need to set up SQL queries to get the data you need.
Customer Journey Analytics is trying to achieve this within Adobe Experience Platform. Instead of complex SQL queries, you are just using advanced processing features of Adobe Experience Platform and Adobe Analytics together.
This is a must product if you have serious online and offline presence like banks, telecoms or retail stores. You will get most benefit if your customers have to login to use your digital services, that way you will have less anonymous visitors and you can connect all offline and online data together.
At the moment most of the customer journey data you are collecting is broken. Many software companies try to solve this issue. It is a very hard problem to solve even for tech giants like Amazon and Google. We can interact with a brand through their website and app, through their call center and then through their branch, but this is not the only issue. People can also interact with brand through their mobile phones or through different web browsers on their phone. I do it all the time.
Look at this scenario:
-I click an ad and go to a retailer website but do not complete purchase because I need more time to look at products. I am also not logged in, because at this point there is no reason for me to login
- In the evening I remembered the ad and decided to buy on my mobile phone
Here we have 1 visitor but there is no way to stitch these visits. Your analytics will tell you that his visitor came to your site directly and will credit purchase to direct channel and mobile device, although credit needs to go to the ad. But there is no way to do this 100%. We just try to get close so that we can see the trend. At the end web analytics is not about raw exact numbers, it is about trends. For instance if you track only 10% of your visitors journey , your data trend will not be correct. If you can increase this rate more than 50% then we can see some insightful trends.
For this reason I always encouraged my clients to do user stitching in their database for cross channel analytics. This has never been a possibility in Adobe Analytics because this stitching requires to access Session or Visitor IDs which is only accessible through raw data. You don't have access to this data on the interface because it is crazy amount of data and there is no way you can do anything with that data under Adobe Analytics. So we need SQL to explore this kind of big data.
If your customers logs in, it is very easier to stitch their digital behavior with offline. But what about anonymous visits. Most companies ignore anonymous visits and they don't think they can get anything out of it. But this is not correct. Anonymous visitors can login anytime. If that happens we can actually combine user’s past anonymous behavior by using some kind of session, user, device or cookie ID. I achieved this stitching exercise with one my clients because they had a very good DWH BI experts.We imported raw Adobe Analytics data into their servers by data feed, and used session or visitor ID to stitch users. But not every company has so many dedicated or expert people. With one of my clients, we even had an issue sending data feed to DWH. This client's DWH team just could not do it!! For that reason Adobe Customer Analytics is a very good solution if you don't have a talent in this area.
One of the things Adobe Customer Analytics brings is Stitched User ID. This is the ID I talked above. Adobe has a column for Customer ID and also column for Cookie ID. Stitch ID is basically combination of these IDs. That way, when you analyze, you don’t have to choose between anonymous visitor and logged in visitor. You can use them both. We do this because at some point your anonymous visitor going to become identified and its history will also be part of our data.
If we have to do this in-house we have to do very sophisticated queries to join data together. Adobe Customer Journey Analytics is trying to bring data together and enables you to analyze data much faster.
You will find Adobe Analytics data process speed very impressive especially if you have an experience with SQL queries.When you write SQL query, you might need to wait for sometime if you need to pull complex data for a longer time frame involving many JOINS. Then you might not even get the correct data you need, you need to tweak your query try again. Then not everybody can write those complex SQL queries so you have to go to BI department but they also have their own work, so in some cases you need to wait couple days. But marketing needs speed so waiting that long is not always ideal.
Yes there are some BI software tools with an interface where you can create queries without knowing SQL. But for me those interface was always worse and limited so I always preferred my own SQL code.
I want to end my first article about Adobe Customer Journey Analytics here and will start to add more details in my next article.
If you want to get most out of your Adobe Analytics implementation you can contact me on Linkedin for consulting or training. We both provide implementation services and business analysis and training services. I have 14 years experience to implement and use Adobe Analytics with big brands like Expedia, American Airlines, Best Western International, ING Bank, Vodafone, Buhler Group. Unfortunately many Adobe Analytics experts out there only tool analysts, they do not have significant product development experience. I have been developing digital products since 1999. Adobe Analytics has become my biggest support for an insight and that's why I learned it very well. I am certified Adobe Analytics architect.