- [Pavel] Hi, guys, this is Pavel for measureschool.com,
and today's topic is product performance Analytics.
Product performance data
is part of enhanced E-commerce data,
which GA allows us to collect.
Let's have a look today on what we can see
above what is in standard reporting.
So I'm in product performance report tab,
which is under conversions and E-commerce,
and this is where we are.
So if you've been using this report
only with this horizontal tab called summary,
you've always seen mostly business data,
which means product revenue, unique purchases,
quantity, and a couple of more metrics.
But where the magic happens
when using product performance data is in a different tab.
It requires to click the shopping behavior tab,
which is here
and then we start seeing completely different data.
I would call it,
we are able now to see the full product journey.
So let me show you and explain
what metrics are we able to see there.
So first of all, is Product List View.
What do we mean by that?
It's good to mention that all of the metrics,
which are available in this report are tied to product,
to particular one SKU,
which then can be grouped either to product category
or product brand.
So let's explain what Product List View is.
The information about product being viewed in a product list
is sent in exact moment of product being viewed
in product category page.
Right now I'm in a Google merchandise store
into which Google Analytics data we are looking at.
And if I go to any category,
which in this case is lifestyle and bags,
and I see the list of four product,
this is exactly the moment
when the shop is sending to Google Analytics
data that these four particular products
has been viewed in a product list.
So this is so-called a first product impression.
If I scroll down a bit at this particular moment,
we send information,
okay, these four products have been viewed
in a product list.
So this is the explanation of Product List View.
Then there is a product detail view.
This one is I guess a little bit more clear.
And we send this information to Google Analytics
in a moment that product detail page was viewed,
which is exactly right now.
I clicked there.
So this was the second metric available there
once we collect the data.
This is important to mention.
If you see the zeros here, it means that you don't have
implemented enhanced E-commerce data now so far.
So another metric is Product Adds to Basket.
This one is I guess pretty clear.
So every time we add a product to basket,
which can be, for example, right now,
we send information, okay, this product was added to basket.
Another step available there is removed from basket.
This one is, I guess, pretty clear.
Every time we remove product from basket,
the information is sent to Google Analytics.
Then there is a Product Checkouts.
This one might not be that clear.
In ideal way, the information about product
being in checkout
should be sent exactly at the moment of a customer journey
in which we are right now.
It should be sound in a moment where we normally,
or in the part of the website
where we normally inputting delivery details,
payment details, personal data, and so on.
So this is the moment where we should send the information
about product being in checkout.
So this is exactly the step.
And then there is a metric Unique Purchases.
Don't mismatch with this metric Unique Purchases
with quantity.
This is something that is available
in that default report summary.
So this is both unique purchases and quantity.
What's the difference between them?
Let's look on the example of product number one,
which is Nest Hello Doorbell-USA.
Let's assume that there is a one transaction
in which this product was purchased three times.
So it will be counted three times into quantity,
but only once in unique purchases.
So unique purchases is basically a volume of transactions
in which particular product was included.
So going back to shopping behavior,
it makes sense why we have it here
because it is then used
in the two upcoming calculated metrics.
First of them is Basket-to-Detail Rate,
which is a ratio between product adds to basket
and product detail views, which is 61% for this product.
It can be also named as add-to-cart rate,
it's still the same calculation.
Then there's a last metric,
which is called Buy-to-Detail rate
and it's the ratio of unique purchases
and product detail views.
This can be also named as product conversion rates.
So this is why we have here Unique Purchases as a metric.
So to sum it up for both of these two metric,
Basket-to-Detail rate and Buy-to-Detail rate,
we use product detail views as denominator,
and as nominator, we have Product Adds to Basket
or Unique Purchases.
Now, let's go to interpretation of these great metrics,
I really loved them.
Now we're able to see the full product funnel.
And what this metric tells us,
It can help us to identify
whether the product performance is like so-so,
which means somewhere in the middle
or it's great products in terms of basket-to detail rate
and buy-to-detail rate, and we should promote them more,
or the product isn't performing well at all.
Important to remember from this video
is that the data available here in this report,
it doesn't tell us what is the problem
with particular product, but where the problem is
in a customer journey.
So let's have a look on that.
I will sort this report by product detail views,
which tells me, "Okay, these are top viewed product."
And now where would I start?
I want to see how my top products
in terms of product detail views performed
following in the funnel.
So I'm looking on a basket-to-detail rate
and then buy-to-detail rate.
And exactly looking on the product number one,
I can see, okay, this is my top viewed product.
It has slightly below average basket-to-detail rate
but very low buy-to-detail rate.
And this tells me,
okay, there's probably something wrong with a product.
And when looking on that ratio numbers,
I can see that, okay, this is like so-so slightly below,
but this one is really, really low.
So there's probably something wrong
in checkout with a product.
There can be many reasons for that.
And as we said, this data doesn't tell us
what exactly the problem is, but where the problem is.
So checkout is the place
where we should start investigating
what can be wrong with the product.
Just a couple of examples,
what can go wrong with the product in their checkout?
It can be for example, very cheap
and then comparing to the product price,
it can be very expensive delivery price
or the product isn't shipped to a particular country
and so on and so forth.
So there can be many reasons for that.
Very similarly is the second product,
quite good or not that good.
There's even wrong basket-to-detail rate.
So if we find something with a high below-the-average
basket-to-detail rate,
the product itself isn't even attractive
for adding a product to cart, right?
So this is what that number tells us.
Again, as in the case of a low buy-to-detail rate,
there can be many reasons
for product not being added to cart.
It can be expensive.
So the price is the reason,
it can be wrong product description, missing important data,
it can be product pictures quality
depending on the product category.
For example, for a fashion that can be really a good reason
not to buy it if I can't see product properly on a website.
So again, this is probably something wrong
on a product detail page.
I would say either price or missing important information.
As we don't want to look only on a low performing products,
we also should try to look
for something that performs very, very well.
So if I would scroll down a little bit,
I can see that for example, line number eight,
which is Nest Hello Doorbell
has twice as a average basket-to-detail rate, 61%
and also buy-to-detail rate is very, very decent, 40%.
So this is something that we'll be interested in
and I would look for,
okay, what's so special about that product?
Again, there can be many reasons for that,
but it tells me,
okay, this product performs very, very well.
What can I do with that?
It's very simple actually, start to promote that product,
probably trying to put it on a homepage
or promote it more in your product performance budget,
spend more money on it and see
whether these important metrics will still keep that high,
or it will decrease in time,
but still will be above the average.
So this is how to work with this data.
Try to look for the very low-performing product
and try to investigate what to do with them,
what can be improved,
what can be the reason why they are performing so, so low.
On the other hand, when you find the product,
which are for example, very good with basket-to-detail rate
and very low buy-to-detail rate,
there's probably something wrong in a checkout.
If we find something with a very low basket-to-detail rate,
but decent traffic, there's probably something wrong,
even on a product detail page,
as we said, for example,
missing the important product information,
or if we find something
with very decent basket-to-detail rate
an very decent buy-to-detail rate,
try to promote these products more,
or at first place, try to understand why they are so great.
So that was it, guys.
I hope you enjoyed the lesson
and try to remember these data doesn't tell us
what exactly was wrong or great with the product,
but where in the product journey it is.
So hope you enjoyed it and see you next time.
- All right, Pavel, thanks for this great information.
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then check out this playlist right over there,
where we have many different topics waiting for you.
Now, from everybody here at MeasureSchool,