When we talk about Analytics and statistics, the Dashboard is the place where you would be able to see a macro overview of the performance of Releva’s elements compared to the other mediums and sources you may be using.
That way you will always be on top of the revenue, where it comes from so you can make an informed desicion on your best source of revenue [not sure about the last part, maybe it’ll be better to change it].
Now, the first thing I want to do is go over to your website.
And let’s check
how we and analytics are recording data. Before
we go
into anything.
so these are the
cookies.
currently,
you don’t have the Google Analytics cookie,
but you have the relevant cookies.
OK, OK, so
even if I only if I say that
I accept the cookies.
You’re going to see the Google Analytics
data here, which means that in analytics,
you only see the users that have accepted the cookies. OK,
in the
relevant, we have more data than analytics has. OK,
OK,
now
that’s
that. Let’s
jump over to the dashboard.
Now, the first thing in the dashboard is that you have the option to choose the time frame. OK,
so we can
check,
for example,
may I have my
own statistics to.
OK,
for me.
OK,
this
is me.
OK,
now,
here we
have the different
channels,
OK, and if you
add these numbers,
OK,
they’re likely going to be higher than this number. So which
number
which from the
over here in the circle, you have that level contributed. OK,
OK,
this is without any duplication.
OK, I will explain that in a sec. So it’s not there anymore.
OK,
when a customer comes from any kind of traffic,
be it
Facebook,
email or whatever,
OK,
they
come to a product page. This can be Google as well.
They come to a product page,
right?
Yeah.
OK,
and they add one
product to their
cart, the one they
have landed
on, they added to the cart and now the
cart has one product.
Now, on that
same page, they
see a product block
and in that product block,
they see one product and they open it and they add
it to the cart.
Now,
their cart has two products. Now, when this customer completes this particular purchase, the amount of both
products is going to be attributed to the channel and only the amount of the product
that came
through a product block will be attributed to the product block.
Does that
make sense?
Yeah.
OK, so this one product is going
to be attributed to two channels, but which you can
see here, OK,
eventually
when we talk about the entire revenue, OK, we’re going to remove any duplications and
each purchase is going to only be counted once. Does that make
sense?
Yeah.
Yeah, OK,
so the sums up here.
So, may I ask you something here? So, as I understand this 4,268 Euro means
that our customers added
this product from Releva block.
Yes. Am I true? Yes.
OK,
you mean that they clicked this product
from the product block of Releva and they added them to their cart and they completed the purchase?
Yes.
OK.
OK,
let me just show
you
a little something. OK,
so
these are the cart
checkout
success events.
So, these are the completed
purchases, OK, and on here you will see this is the content of the cart.
OK,
have products, products, all of these, you see a product and on here you see a recommender.
You see,
OK,
here you
have the recommender, which means that the above mentioned product
has been added through a product block of Releva.
So,
from the entire
cart, which is
38 Euro,
OK, only the amount of this particular product is
counted towards
the product blocks, not
the entire cart.
Can we see here at the event, can we have a period check, let’s say a month?
We can input, I think, the date. No, we can add the dates. OK, oh, that’s fine. OK, OK, no, no, no, that’s fine. I will check them. I didn’t know this part of the event. I know Irena showed it, but I didn’t focus on this part. OK, no
problem.
Yeah, you have the option to do the time frame.
OK, and you also have the option to export it.
OK, this
is going
to create an Excel,
and it’s going to show you the order ID as well.
And it
also shows whether it was from a product block or it was from an email campaign when we’re talking about the Releva.
OK.
So you
do have the
option to export this.
Back to the dashboard. So on the
graph here, you have the dynamic between the different channels within Releva. OK, so in
here,
if you have text messages or Viber, you will have another line on here
showing the dynamics between the different channels.
OK.
OK, going
down, you have
the option to see the revenue by
traffic source.
OK, and on here
you can see the top three sources.
Hopefully
next week they’re going to start showing the top ten sources.
OK.
OK, so this is by
source and this is by medium.
OK, if we’re talking about source Releva, in the mediums you have the recommender, which is the product block, you have email as well, you have push notifications and so on and so forth. OK, and going down, you also have the average order value, again, by source and
by medium, and you have the graph about it.
So on the graph here by medium, you can see what
exactly is.
So you have a push notification that is bringing more
value to you here.
OK,
email, product blocks, and you can see the average order value by each of the channels.
OK,
this is UTM from an influencer.
OK, yes. So on here, the
system does
count the UTMs,
it can read them and it can show them in here for you to be able to compare. OK,
this is
about the revenue.
OK, the
other part of the
revenue is the dynamic.
Before going to engagement, can you go back to the revenue? Yes.
For example,
I have noticed
for me. Yeah,
I keep
statistics from Releva stats and I’ve named them my fatigue stats, by meaning my stats is from analytics.
As I see,
when I am talking
about email revenue, this is the part that I am interested in much more.
I am checking that Releva has… Wait a minute, I have to open a calculator because there is a way that I… Yeah,
the number is 2,000… 493. Yeah, I have for Releva 2,076,
because I am getting the stats from coupon also.
But
when I am calculating them from analytics,
the number is 1,900.
The part that I am interested
in… May I share my screen?
Absolutely.
So you can understand?
Mm-hmm. But I don’t know, it doesn’t show a report, it won’t show the report that I am
having here. How can I do it?
In the middle of your screen, you have a smiley face.
Wait a minute, if I do it like this
and
save it as a photo.
May I share here a photo?
No.
No, what? You can open the picture and show your screen anyway.
Really?
Mm-hmm. So, where is the smile, OK? To the
right of the smiley face, you have a little box with an arrow going up.
Click on it.
Yeah.
OK, then
select the first option, present your entire screen. Entire screen, OK.
Cool.
Now, yes, OK, you
have to click
on the picture.
Lovely.
OK, yes, we can see your screen.
You
can see.
Now, do you see this one?
It’s a little bit small. Can you zoom in a little bit? No,
wait a minute. Is
it OK
now?
Yes, thank you. The part that I am interested in is this,
automates.
OK.
And I
haven’t calculated for June yet, but as I see, the difference is that with RelevaStats, as you see, this is calculated only the automates without the welcome mail. OK.
Here are the mails that are sent by us, and here is the push notification.
RelevaStats is this, 1,600.
And the real stats from Analytics is this.
It is a big difference.
OK, the same here, you see.
That’s why I started the conversation
with
showing you that Analytics cookie does not load
unless you accept the cookies.
OK.
I can continue browsing on your website
until that bar sits
there.
Only Releva sees the user.
Google Analytics does not see it.
OK, so you can continue. So, the explanation is that I am keeping this, not so I can explain this to my colleagues also, is that the Analytics, you have to accept the cookies. -OK. -Yes.
In order for Analytics to see that information, you need to accept the cookies. If you have received the email,
and you open it on your mobile, OK,
and you
continue browsing, and on. your
mobile, we can attribute to that
particular user because
we know who received the email.
But if the user does not accept the cookies, Analytics is never going to see it. OK.
-If you want– -The same thing is happening, I think, with WooCommerce also, because the Analytics stats are close to the WooCommerce stats. What I mean the orders that came from the UTM using Releva is close to Analytics stats, not the stats that Releva is showing to us. -Was I clear, or can I repeat it? -Yes. -OK. -No, no, no. -I understand what you mean. -OK. I understand what you mean. I don’t know how WooCommerce tracks the purchases, OK? Therefore, I cannot have an opinion on that one. But about Google Analytics, unfortunately, with the new implementation of Consent Mode 2, they do miss a lot of data. OK. I can see OK. So we discussed the revenue. Now, this revenue is consisted of a number of purchases. OK? For the previous period, which I believe was not a complete month, OK, there were 242 purchases, OK? Then this… Sorry. So for the month of May, OK, the overall cart creates were 3,859. OK? But you had 1,200 purchases. Compared to the previous month, where you had more carts, but less purchases completed. So the conversion rate in May is better than the conversion rate in April. OK. OK? Down here, this is new, OK? And you’ll be able to see it. This is the overall conversion rate. 4.6% is quite good, actually. OK. This is the overall conversion rate. This is the traffic that interacts with relevant elements, and this is the traffic that does not interact with relevant elements. The percentage is 46%? No, 4.6%. -4.6%, OK. -Yes. 4.6%. So four and a half out of every hundred people that come to the website actually complete a purchase. OK. So, that’s that. So in here, we can see that the conversion rate is improving. It went up to 4.6% when it was 4.1% in the previous period. -OK. -So for April. So in here, you can also track that information. This is the, when you say, I beg your pardon. No problem. Can you scroll up, please? Here,
when it says 447 purchases from product block,
it means that
447 people
purchased,
completed their purchase, and they have added
maybe only
one product from product block.
Yes.
Yeah, OK.
mean, if someone has added
five products, and one of the product is coming from product block purchase, so it counted as one purchase from product block purchase. -Am I right? -Yes.
OK.
The same is for banner purchases. If he has clicked a banner and he completed a purchase,
so the assisted purchase, let’s say, is 242.
Yes.
May it be combined?
I mean, if someone added a product from block purchase, also he has clicked a banner purchase, so it
will count one and one?
Yes.
OK,
so this 242 isn’t clear from banner purchase. Also, it can
have also product block
purchases too.
Yes, the same way that it can be duplicated,
like
here.
Mm-hmm. OK, same way it can be. So this is a purchase after interaction with a product block or after interaction with the banners. OK, OK, it’s clear. Now you stated
it well,
OK.
OK.
Now,
the
other part of the equation is the traffic that comes to the website, And this particular traffic was a little bit more, so you have more page views
this month
compared to the previous.
5,000 more, but still more. Mm-hmm. OK.
Here, a little bit less
page views from relevant elements than the previous
period, but in general, you have an increase. Now,
on here, again, you see the dynamic between the traffic that goes through relevant elements and all the other
traffic and the dynamics on the graph as well.
OK.
So from what I can see, about half the traffic is going through relevant elements. Mm-hmm.
OK.
And now, down here, again, you have the
stats by UTM source and by UTM medium and the dynamics between the different sources
and
mediums.
So on here, this big one, this is Instagram that
has– Yeah, we had– –the biggest impact here. –we had influencers
in this day.
Mm-hmm. So you see,
again,
the different
channels.
And if you put the cursor
onto this, you can see the UTM
for the given medium.
OK.
This is traffic-wise. And how does
traffic– how does traffic
interact with the website?
OK.
You will see that you have 781 subscribes and almost the same number unsubscribes. OK.
Compared to the previous period, this is better
because the unsubscribes have gone down.
On the other hand, the subscribes have not increased substantially,
only 140 on top of this. So on
here,
I
would
say
that
you are
not currently subscribing the customers aggressively
enough.
But
this is your
own choice how to do it.
OK. So if we go down, you have the registered users, which, from what I see, do not come to us. You
are
on a custom– no, you are on WooCommerce here. This is no longer custom.
Yeah, WooCommerce. Reni, can you take a note to check why registered customers are
not coming in
through? OK.
OK.
And you can see the dynamic of the subscribers and the dynamic of the newly subscribed users and the unsubscribes.
So in general, you have more subscribes
per day than unsubscribes, which is good.
That’s clear. OK.
OK.
And then we go to the marketing channels.
And in here, you can see the dynamics within each of the marketing channels.
OK.
So you send 172,000 emails,
which is 60,000 more than previous
month.
And the push notifications have decreased a little bit.
The push notifications, they are a little bit particular because they
depend on the device.
So if my phone is switched off,
or for example,
you send a push notification, but I have accepted the permission to receive the push notification on
my computer in the
office, which is switched off over the weekend, I’m not going to receive that push notification. So that’s why here, you have less push notifications
compared to the previous month.
OK.
And going down, you can see the dynamics.
So this was Easter
over here.
And you can see that you have quite a lot of email opens here,
which is this
is
exactly the eighth.
Whoops.
And yeah,
this is the 8th of May.
And on here, you can see the dynamic of the send messages. So on the 8th, you actually send more emails. And here,
you
can see that most of your
emails are well-received during
these days.
So usually,
your weekly newsletter is sent on Wednesday.
And therefore, you have
the highest open
rate on Wednesday.
Then people still open your emails Thursday and Friday.
The weekend, not so much.
Yeah, because we have an automation that it sends every Tuesday and Wednesday. That’s why they are opening in these days, I suggest.
Also,
this is the
open rate by hours,
which is quite interesting for me because I presume you send the emails in the morning.
This is around 10.
And from then on, you have a pretty steady open rate
by hours.
That’s good or bad? Yes. No, no, it’s good. It’s good because
people see your emails
throughout
the day.
OK, so this is like a steady flow of interest towards you. Unlike
other websites that have a peak
around probably 5 to 6 PM or three hours after sending the
email, in your case, this is very steady.
And it’s very good. OK.
Here you can see the bounced
messages.
When an email cannot be delivered, depending on the reason why it could not be delivered,
it will either be a permanent bounce
or it will be a transient
bounce.
What this means is that the message could not be delivered because the email address does not exist,
for example.
And here,
potentially, the Gmail server had some issue
temporary and could not deliver the email.
But next week, the system is going to retry that user again. These permanent bounces, they are never going to be retried. And the transient bounces, they will be retried again.
here you
have the
dynamics of the
push notifications, the clicks, and this is how many were sent, actually.
OK.
So
from what
I
can see,
you
have– this is on the 14th,
which is here.
Maybe there I have sent a manual push notification. That’s why we have– there are 19
sent only.
Ah, OK. So that’s– Yeah. Likely, it’s not a manual. Likely, it’s, again, the abandoned cart and abandoned browse. Yeah, yeah, yeah. In June. In June. When was the Father’s Day? In June. In June, yeah. Yeah. If we go to June, you will see
that I have sent the manual.
Manual. Yes.
It has been sent here manually, and the rest of the days, they were between 10 and
sent. And that’s the automated ones.
And here at the very bottom, you have the web folks, which
you’re currently not using.
I think
that’s the entire
dashboard,
all the data that we currently have in the dashboard.
This is overall
statistics by channel.
Here,
if you go to the
campaigns,
you can see the statistics by campaign.
I’m going to put
it for
June, so we can see the– come
on– we can see the latest ones. So
you can see
the number of sent messages and the
number of clicks, purchases,
and all.
As I see, our open rate
is not so good. No,
the first one is good, 10%, as I see.
This was a manual.
Let me expand this a little bit more so we can see more data here. This
new.
It was– Yeah, we did discuss that with Reni, these two.
you see the
.5, let’s say,
OK,
10%, I think it is a good open rate. I mean, we
have sent near to 20,000 mails, and the open rate is just 2,000.
I mean, the open
rate is– as I know, when it is above 10%, it’s OK.
We have no big
rate,
but it is not also
so– Let’s take a look at this.
So I’m going to get
all the users that we have ever sent an email to.
And I’m going to only filter the ones that have opened an email. OK, that’s good.
And out of all the 20,000, only 30% have opened at least one
email.
So in general,
the
health of
this
list
is not much.
Not much, yeah?
Yeah,
so 30% is very little.
OK,
so what can we do for this?
Subscribe more users.
Users that want to communicate with
that are interested currently,
to boost this open
Because the remaining 18,000 users that you’re sending to
are not
responsive.
So the only way to increase the open rate is actually to increase the
new blood
in this
list.
What you can do also to
only address users that are
interested is, let’s say,
I’m going to
add users that have viewed the product. Oops. That
have
viewed the products,
or they have
viewed the page,
or they have
opened an email. OK,
and you have another
1,000 users
on here,
which have interacted
with the website.
Let me see if we add another rule here
to– let’s see how many of
actually have an
email.
OK,
so no,
you had
100 and something.
So about 10% of these have emails.
But you have
another
almost 5,000 that actually have
emails.
And you can
approaching
them if you
want.
What I mean by that is that, depending on how
the privacy
policy of your website is configured, what you state in your privacy policy,
all the users that have made a purchase,
you can also approach them.
Yeah.
Yes.
Once a month or once every two weeks, you can add those users that have purchased
to the list of subscribed users.
And you can send marketing communication to them
as well.
Although they haven’t consented to subscribe, let’s say.
Although they have not consented
explicitly.
But when they make a purchase– Do we have a
list with this?
I can pull out the list for you. I
don’t know
what I clicked,
actually.
No problem.
You haven’t
selected
the size.
If you select size– Uh-huh. OK.
Yeah.
Sorry, I didn’t
see it there.
OK. So when a customer
makes a purchase,
they are required
to agree
to your
policy.
If in there you
state that you are going to send the marketing communication and they have the right to unsubscribe anytime they want– OK.
–you can count those users as subscribed.
OK.
This will bring some new blood to this.
And because these people have
purchased, you just need to bridge the gap between the first and the second
purchase.
From then on, they are your regular customers.
OK.
So how we can get them to a list, let’s say?
Oops. So
this
is the
list.
And in here, you
have 4,200.
OK?
Out of these people, only a quarter,
only 25%, are actually subscribed currently for marketing.
OK.
What I’m going to do is I’m going to save this segment. OK.
And you can come in here.
And actually, Reni can do this afterwards.
She can export these users.
And we can subscribe
them.
Ah, we can export them and then– Yes.
You have the option to export them. And we add a subscription date on there. And we import them back. This
way,
users,
you’re also going to be able to use them for marketing. OK.
And they import– from where do we
import? That will be under
Profiles.
When you click on Profiles, on the far right, you have an Import Profiles button. So I have to export them and import them, the same
file?
The same file. We just need to add a date in the Subscription Date column. Reni can do this for you. Absolutely, no problem. OK, I will ask from Irena to do this.
First, I have
to
write something in the policy.
Yes.
So on here, these
are, again,
another 3,000 subscribers,
which are fresh.
And–
So, Irena, we have imported also subscribers from the previous
platform, from Contact Pigeon.
So as I see,
we have some– not some, 60% of subscribers are not interacting with us.
So do we have to delete
them?
If you want,
you can.
OK.
Or– You don’t have to. Or I have to do a segmentation, so to not to send them.
Yes, in general, you can exclude them from sending
in emails. If
there is– is there any– when we create a segmentation,
can this segmentation be dynamic?
It is dynamic. It is dynamic. So– It is dynamic. Each segment is calculated every
hour. Oh, so– Yes, I have the purchased users here. If someone purchases in five minutes, in an hour, they are going to be added to this list. So if it is dynamic, I mean,
as you saw, we calculated near 7,000 emails, active emails, OK?
So we have here other 3,000, as I see, or 3 and 1/2, let’s
say. So we have 10,000 active emails,
let’s say,
out of 25.
So I can create here a segmentation which says active users
and send the mails to these users.
In general, yes.
OK, that’s a good strategy. And for example,
only when you have particular campaigns,
you can send
to everyone.
Oh, OK. Like for Easter, for Father’s Day, for Christmas, Black Friday, or whatever.
Just when you have the big campaigns,
you can send to everyone,
just in case.
Because people are usually more active at that time, minding their email for changes and for this kind of communication.
And you can spike their interest, and you can bring
them
back as customers.
Another question is, although Irena tried to answer me,
we have a spike of active users
this month.
I mean, in April, we had 28,000.
In May, we had 29,000.
And now we
have 38,000.
OK, let’s see.
Uh,
that’s
April.
Because
you are billing this from active
users.
Mm-hmm.
OK,
so let’s go to
traffic.
OK. OK.
So this is
April,
May, June.
Mm-hmm. OK,
so
let’s go
to traffic.
Again,
traffic.
And here, traffic.
OK, so April,
182,000 page views.
May,
slightly more.
And here, you have 250,000 page views.
OK.
So you have a significant increase in the page views. That’s about 65,000.
OK.
Let’s go to
here.
Whoops.
OK. Um.
So this
is going to be for April and then
for
May.
And then for June.
OK.
You have
three
months.
Uh-huh. OK. Yeah.
Uh, I saw
zero,
and I’m like, what?
forget that this
is– Yeah, yeah, yeah. –that it changed.
OK.
Now,
calculator.
Let’s
fresh.
Now,
in April,
we
have 181,82920 divided by– this is April.
That’s 28,130.
28,130.
OK.
So you have 6.5 average
page views
here.
OK.
For May,
you have 100– let’s see if I can do this– divided by– this is for May,
29,000.
OK.
So here– no
dots.
OK.
Again,
6.5 page
views.
OK.
Here,
you
have traffic,
250,000.
Without the
comma.
Yes.
Divided
by 39.
Nope.
I don’t
want– OK.
You have 6.4.
But still, you
have the same number of page views,
pretty much,
average
page views per
account.
So what this means is that the proper
user– what this means is that this last month, you had more new, fresh traffic
that came to the website. New
users,
let’s say.
Yes.
OK.
So you
have more
traffic in general.
And a larger portion of this traffic was to new users, users
that have not been to your website
previously,
which is actually quite good. OK.
Does this make sense?
Yeah, it makes sense.
OK.
So whatever you’re doing– In general, we had the same,
as I see from analytics, let’s say,
the same number
of user, as I remember. I will check
this. But you are saying that the new users
is the difference here, the 10,000.
Yes.
These are new users which
have come to the website
that we have not previously known. OK. Even if these users come once, or if they come five times, we’re still going to count them as one user. OK. That’s
why– So you mean
that this month, for example, we do not have– no, this month. I suggest in August that we don’t have any influencers, et cetera.
The number of active profiles will be less.
I
mean– OK.
I don’t know what this is. Now,
if we
the number of users
that
Areleva
knows– so these are
your, say, 29,000 active
users in May.
In June, you have 39,000, which
encompasses a large portion of these, and
then some new users.
So these are all new users that
come to your website.
OK.
Whether these users realize purchases
or not,
it depends.
So what you have currently done is good
because you’re bringing in new
traffic.
But if the rate of purchases– so in here, if you go back to the engagement, this is May. This
June.
So in June,
you see you have a lot more cart creates.
In May, you have about
4,000. In June, you
have almost 2,500
more
cart creates.
So you’ve done something which has been
interesting for the customers.
You have
engaged more new customers.
And this has resulted in 600 more purchases– 500 more purchases, almost
6– compared to the previous
month. So this is
good.
The
rate
in which you
increase traffic–
so you increase traffic.
Eventually, the return is going to start to diminish.
This is the golden point, OK,
where you have the highest
return with the least amount
of
traffic.
So for
your own website,
you have done
well.
You have engaged new traffic. How good
that
traffic is, we can actually
calculate that.
OK, let’s see. In the engagement here, the conversion rate– this is for June– is 4.7% compared to 4.6% in May.
Yeah.
What this means is that your
conversion rate is increasing a little, and the traffic is increasing
more. So currently, you are kind
of approaching this point
here,
where you have the most return,
because the traffic has increased with
about 10,000
active users
or 65,000 page views.
But the conversion rate has increased with 0.1%. OK. So either that’s not the correct traffic, and
you
just
got
lucky,
because
the
overall traffic
is 4.7%. But if
you compare it to the previous month,
the conversion rate
for the new
traffic is only 0.01%. Yeah.
So this
traffic, although it’s good for exposure,
it’s not exactly the right traffic to convert
your products.
OK.
Does that make sense? So the conversion rate of this traffic is very, very low.
Very, very low. Yeah, very low. It’s very, very low compared to the average conversion rate of your traffic. So [INAUDIBLE] My question– I’m really sorry about
this. Boryana?
Why I am not hearing
you?
Boryana?
Yes.
OK. Can you hear me? OK. Sorry.
My question in
this part was about billing.
Let’s say now we have 39,000 active users.
This means that the next month, it will be again 39 plus new users, or it can be less users?
It can be less. It can be less users,
because for this month, you have these 39.
OK.
OK?
If these users come
back, they can
come back like this.
And this can
be 29.
OK.
This was my question. OK.
Yeah.
They do not only
grow.
Potentially,
the users are
people that have actually come to your
website.
They have engaged somehow with your
website. And with Releva?
Yes.
OK.
OK. So these users,
they
are counted on average when
they are coming.
OK?
And if they come twice,
it’s still the same
Yeah. That’s the thing. It’s the uniqueness of this user that we count.
OK. OK. OK. I get it.
Mm-hmm.
As I see, now I will check analytics here.
For example,
if I put
here custom,
and I have– I’m doing this for May.
Mm-hmm. OK,
I have 23k
users from
analytics.
OK.
And in June,
if I
put it again custom, and I select 1
30 June,
I have 27k users
as analytics calculates them. OK.
So for May, you have 23.
In Releva,
you have 29.
Yeah.
OK?
For June,
you have 27 in analytics. In Releva, you have 39. Yeah.
OK.
This is kind of consistent.
It is consistent because you do see the increase in analytics as well.
OK. OK?
And new users that come for the first time, they are also more likely not to accept the cookies.
OK.
So that’s why the gap between May
and–
so for the month
of May, the gap between analytics and Releva is smaller
than the gap
in June
because,
as I said, you have attracted new traffic,
completely new traffic,
which–
actually, this is
something because you use Instagram
to– and I presume Facebook as well.
Yeah.
Usually,
I
was– for another customer, I was researching the types of campaigns.
And they
were explaining how
the users– how the algorithm of Facebook works. And when the users
are
setting up campaigns for
traffic,
they are just increasing their page views,
but not necessarily the people are with the relevant interests.
Because
traffic for Facebook needs clicks, and they are going to show the ads to people that, in general,
click. A lot of times, it will be people that click randomly on stuff. On the
other hand,
when you target
your campaigns towards sales, these are people that Facebook knows
that have
executed a sale in this kind of– what is it
called– industry via Facebook. So
people who
are purchasing clothing
and
lingerie after interaction with that on Facebook.
So in general, the
traffic
campaigns– I don’t know how you have set it up,
but the traffic campaigns are kind of consistent with this
very, very, very tiny conversion
rate.
OK, I will discuss this with our performer. OK,
I think
it was a
good meeting.
I learned
a lot
about your stats and analytics.
So you have said that you have recorded
also this meeting.
So you can send us a link.
Yes, Irena is going to receive the recording, and she’s going to send it to you afterwards.