Google Analytics is out with a new nifty tool that allows you to explore the complexity of the customer journey for different industries.
Disclaimer: I was hired by Google as an adviser on this report.
I want you to specifically look at the media vertical. As you can see, most sale requires several days of decision making, compared to the other industries where most sale happens on the first day.
What is really interesting about this study is just how big a difference there is between verticals.
Consumer packaged goods, travel and finance are almost exclusively based on instant sale. And this is where you need to understand the purchasing funnel. People don't just buy financial services on impulse. Instead, it's far more likely that what we are seeing here is that people are researching what to buy before they go to their bank or other financial service.
The same with travel. People don't just buy a trip to Taiwan. Instead they spend a long time deciding if they want to go, and then once they have decided what to do, they go to the travel site, find a good offer, and take it.
On the other hand, people probably don't think too much about what groceries to buy. They check their kitchen before they leave and buy what they need as quick as possible. You don't need to spend four days of interactions to decide what milk to buy.
BTW: In the future this is likely to change. Once people start to buy groceries online, many will add products to their shopping cart as their run out (instead of managing shopping lists), and by the end of the week they will order all the products in the cart.
With media products, however, people do spend a lot of time going to the store contemplating if they should or should not buy that new tablet or TV.
This study helps you see these patterns. But it's up to you to figure out why people are behaving in one way with one type of products and another way with another type of products.
We also see that average order value goes up with longer purchasing paths. There can be several reasons for this. It might simply be that people buy more expensive products and because of that take longer to decide.
We can't really tell from this data, but it's something that you as a brand should look into. Why do some people take longer to buy some products? Is there a correlation between the time spent and the cost of the product? Is there a correlation between time spent and the type of products?
You need to answer 'why' ... because the data can only tell you 'what'.
But it's a very interesting study, and it's part of the shift to the next generation analytics where 'multi' is the new normal.
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