Dutch language

How to pronounce apis in Dutch?

Full Transcript

um
um
so that's it for now um uh
alexi you can hear me because i have my
phone open
so we use an old school method so
connected to finland
the floor is yours so i'm going to leave
now
let you present
the idea and what you can do with the
product and the demonstration of the
product
and afterwards i come back and we handle
the questions of the audience the floor
is yours
perfect thanks a million peter
um and super nice to be
that i got this opportunity and it it
was really great that there was so many
of you who
who joined today um and
and of course it's it's super
interesting topic
very very timely topic as such
so i'm extremely happy that you were
also really interested in it
i said uh i will now
kind of like present you the idea of
customer um what we do
be with who we are and then go through
customer cases and then actually in the
demo itself show
kind of like a logic how how you can
reveal and reach the customers behind
the data
and and what that means in in real life
what does it mean marketing and
communication wise
and of course the whole whole idea in
the
in in customer as a platform is that a
cdp
which custom customer is a customer data
platform with marketing automations in
it
how that can be used to combine all the
customer related data from different
sources and then how you can use it to
improve your
customer experience for for the
consumers and of course
get more sales with that um
first of all the things i will go
through a brief introduction to customer
as a company
um then what can you actually do with
with customer with the tool what's the
idea in it
um then i will present you a kind of
like a timeline view
of the unified customer profile because
that
gives you a really good picture of what
it actually means
to have all data connected um and then
usable for
automations targeted campaigns and all
of that
um then i will continue with some
customer cases
after the first one let's actually jump
into the demo itself because
then you have an idea of what what it is
in actuality and then i show
how how it how it works in the tool um
and then i will follow up that with a
couple of other cases if
if we hopefully have time and um then of
course key take
takeaways after that but i'm alexi monda
and i'm the head of business development
at customer um
before this i was doing crm consultancy
then i was a controller for the menswear
online at h
m so the clothing retailer from from
sweden and now i've been
running running the sales for customer
for the last four years
and and then about customer well we are
the nordic's leading customer data
platform
and marketing automation system for for
retail
um we were founded in 2004 and the
original idea actually for the tool
came from our earlier or the founders
earlier
earlier retail customers so they had the
request of
creating a system which combines all the
customer related data from e-commerce
newsletters tools
um pos or erp system so that it's
actually usable
for marketing and communications um
like like peter said we're from finland
and i'm now physically sitting in
finland like we are
all sitting physically somewhere um
it would have been great to do it on
site but not with you with this
um but but but we're actually like
really international so we have
customers in
in 14 different countries um good
example
is actually tilroy and the integration
we have with them
um so so through these kind of partners
we've been able to extend our customer
base in
in europe and of course in belgium we we
already have
several customers um which which is
great
um then what customer actually does so
it can be divided into
two three parts so so on the left
um first is collecting data
so we have ready-made integrations and
and open apis
so so we get all the customer related
data from different systems into
customer
so of course usually the subscribers
um e-commerce customers so people who
buy from e-commerce
customers um who buy from physical
stores
um especially when there's a kind of
like a loyalty program and there's a
customer id identification for the
in-store sales that's of course required
there um
if if you have an app we have also
several customers who
who send the data from apps to customers
well
which also of course works the other way
then then there's possibility to also
integrate um
customer service tools for example
senders zendesk or freshtest
desk so the tickets from those systems
are also combined
to the customer profile um and naturally
there's also a
cookie cookie which is like first party
cookie on your site which then
gathers the browsing data for example
from the e-commerce what
what products the customer has have been
browsing and if there's an app like
similar similar kind of like
browse events can be also sent from
there or or
actually any other interesting events as
well like basket ads
wishlist ads and those so the first part
is that
collecting the data and then putting
that together so creating a 360 view
like a full view of every individual
customer who they are what kind of
marketing permissions they have
what they usually buy from which stores
how good customers they are money-wise
um and basically all of these parts i
will also show in the system itself
um and then the important next step is
of course how that data is used
well all of the data which comes to
customer can be
used for creating um dynamic audiences
um and triggers for
what is marketing automations and and
flows like that
so so basically you have the data then
you select
what are the interesting target groups
what are for example
how you want to activate the passive
customers is it after three months
is it after a half a year and and then
the data basically works for you
then the third part is that after you
have an idea of
of the audiences um then then reach out
to the customers
and customer supports a lot of different
um
channels so there's of course emails
and sms you can even take out address
list for physical post
in in germany and and um and finland for
example already now
there's possibility to do physical
sendings
through this local post postal service
then you can send push notifications or
messages to apps
so actually targeted targeted push
notifications or or messages
and then of course really importantly
nowadays
is of course the display channels so for
example
uh google ads or facebook ads so
as we're moving towards the time when
third party cookies
are not supported um and and basically
here i'm referring to the facebook and
google pixels
then your own customer data in your cdp
is basically a data which you can and
have to use to target
also the marketing um in the display
channels
so that's also covered and most
importantly
of course is that as customer
knows the customers who got the campaign
or automation
and we also get the sales data so
from all the different campaign types
whether it's
online buying or like loyal customers
buying from physical stores so they buy
an
identified way you know the actual
conversion of the campaigns who bought
and what and when but but more about
that in the
in the demo itself but this was a brief
run-through
then bit of a visualization of the
basically the timeline of the
customership how
what what it means in a visual way of of
collecting all the data
so this is the base for knowing your
customers
and then then the marketing actions
segmented campaigns
automations follow with it um
so this is a customer journey example uh
it takes into account e-com app
and and stores you can only have one on
you can you
you can have all of these or you can
have even more more channels
as such where the data comes from and
the example
just like the demo environment which you
will see is about uh
omni channel uh bookstore uh bookstore
chain
so that's kind of like the setting for
you
okay so first of all the customer comes
to the e-commerce page
and and they register there or or they
um subscribe to your new newsletter so
customer gets customer gets the email
subscribe um
event and then the customer is created
at that point of time we know the email
address and and we get the
um email permission
then when we go forward then right away
there's a welcome
email which is triggered to the new
customer which is right away sent from
customer to the client um
then of course we see that the customer
opened the email
then the next part is that through the
link they go to the
site um the the cookie is saved
so right from there we start to get also
the browsing data and we can see that
this
this customer she was browsing science
fiction
what happens next is that the customer
is identified as a
as a science fiction lover they haven't
yet bought so we have to use the
browsing information to
to kind of like start building the
profile so
they're identified as uh as interested
in sci-fi
and then the first campaign is sent via
email
and then there's also automation to
create a google
google and about that category for for
her
and of course the more data we get more
different data we get the more channels
are of course
also available for the marketing okay
now the customer bought a science
fiction book book
followed by the campaign that's of
course visible in the campaign
conversion
what happens next we get an event from
the e-commerce systems or the
or the like the erp system back-end
um and then we send the order
confirmation email to the customer
everything is done automatically and
as the customer did the purchase we also
get the address and address data and
phone number which is then updated to
the
updated to the customer profile so as
you can see the customer profile is
building through that
or being built
now that the customer has also bought
cos custom bar
updates the customer's lifetime value
which can be once again used for
segmentation
and also the position in the rfm matrix
which i will show you later
um is updated so extremely important
metrics when we think about the
entirety of marketing and data driven
marketing
and also of course they're identified as
one-time buyers
next we get an event pick and collect
um from the from the back end what
happens then that customer sensor or
they're ready for pickup sms to the
customer
and it informs in which stores and um
and
from which store and when when they can
pick up the order
now in this case they the the customer
would also have an app
so so we send also or try to send a push
notification to the customer
um about the same order or the ready
status
then when we continue um the customer
comes to the store to pick up the order
and while the store the store employee
can ask the customer
are they registered to the loyalty
program
um in this case they weren't so
the the client of the clerk at the desk
puts in the information
and right away an sms is sent to the
customer
to to ask them to install the app as
as they haven't had the app before
and and that's then done the app is
installed and
and then the next uh push type there is
that there's automation that now as they
are a science fiction
science fiction interested there's a
there's also a push
push notification going to the customer
about new books in in science fiction
category which which might interest her
then when we go forward um this data can
of course be
like the segment data can be exported to
ecom platform or apps back-end
and in that case for example if there
would be an app
the segment science fiction fan can be
used to also cater the content
or products in the app
now the customer continues the brown
science fiction and related products
um they buy the science fiction book and
now as they got the push
notification um then the sales is
attributed to
to that campaign um and
then we also know because before they
were like one-time buyer
but now they are um identified as a
returning customer so
now they have two now she has two
purchases
so once again the lifetime value and the
rfm matrix is
updated or the position in the rfm
matrix is updated based on this
so that was just a kind of like quick
run-through and visualization of
what can it actually look when when all
the data comes to
comes to one tool and when it's used for
um
targeted communications and and
automations
then an interesting customer case from a
from a great finnish customer of ours um
and this is
basically a prelude before we go into
the demo itself
so not maybe the easiest name for
for you guys um even actually for finn
it's uh
it's a strange name it means like a
small ember
like ember in in the fire um
but the company is it's actually quite
old so it was founded in 1957
um they only started with um actually
one retail store
but then they've grow they've grown to
uh nine physical stores
and online stores so omnichannel
clothing retailer
in in essence um online store in
in good good way um they have a loyalty
program a loyalty card so they also um
also identify the buying the in the
stores
and they've always been really um data
driven
uh before they started with costa bar i
think
about three three years ago they were
really adamant that the
being data driven and doing marketing in
a data driven way
that's the key to to their success
because that's how they can know their
customers
and keep keep ahead of the competition
so before they had paid a scattered in
different system
so erp system e-commerce systems
differently
they had an old email tool with limited
analytics
only one channel basically none of the
none of the social media google ads sms
channels to use
no way of actually um segmenting the
customers
and they wanted to combine all of that
data analyze the
uh campaign and automate automation
results
um and see the actual conversion not
only from online sales but offline sales
um and um of course to add also
other channels besides email was super
important for them
so customer was the solution so so we we
get the data from
product data from their pim system um
other data from the erp and e-commerce
system
so we get all of the uh identified
customers so learn the program customers
online and offline buyers newsletter
subscribers
so we really create the unified customer
profile for them
and targeted campaigns and automations
are run with customer
customer and um emails sms display
social media and they actually use the
nps survey so customer satisfaction
survey
which is built in in customers so they
also can
see the customer satisfaction for the
different stores
based on the customer satisfaction
surveys which are automated from costa
bar
and and then interesting case which they
had so
they had a case they wanted to um
bring in a new uh men's clothing brand
into their stores
so they wanted to start it off with the
with the omni channel and data driven
campaign
um and this clothing brand was quite
similar to
tommy hilfiger or hugo boss so sharp
suits kind of like business attires
um and and then they wanted to it only
went
i think to two of their stores or one of
their stores in the beginning
um so they really wanted to have a
targeted campaign and see
do they get traction from their customer
base
as it was men's clothing first of all
they started with a
gender search so every everybody who had
identified themselves as
male or had been buying um men's
clothing
i think it was more than three thousand
three times
um then the other part was that people
who've also
bought similar brands so that's a and
search on top
so people who had bought similar brands
tommy hilfiger polo
hugo boss or others
then on top of that they also added a
search bought from a targeted area
because it was only in the in the one
store where they had it first
so they they needed to get people who
are close to the store who would
actually come there and and
and check the launch launch out so so
they selected also
people who have only bought from from
two certain stores which are close to
the one store where they had the new
offering
um then on top of that they also took
customers who've only bought online
but are from a selected zip code area
so the postal code area which is close
to the store
so that's what that's actually a good
way that they were also
able to get customers who haven't
actually bought from the stores but also
introduced the store concept to the
to the online buyers
so this was the setting and this was the
search um
what happened then was that
there was thousand customers in the
audiences and
and for the first week of sales they got
9400 euro revenue
from only these customers
so it was a huge success so this sweet
little triangle
um which which was found through these
these
searches um gave gave them a good launch
for the new product line
and of course very rare verification of
potential to sell it also in
in other stores um and this was
this was the first case and now let's
jump to the
live demo itself um because here i can
show you the
segmentation as well hopefully it's not
um
too small i i wish you wish that you can
see it but this is actual
um the customer environment so
here we have customers then a bit later
after we've looked at the segmentation
i'll i'll show you the campaigns the
campaign results how that's created
um but let's first start with the
with the 360 view like
view of the individual customers so you
can actually search out customers by
by their name as well phone number
anything like that
and there's also actually in-store ui
for the
for the physical physical stores as well
um actually i'll actually move
or maybe i cannot i'll put it there like
that
yes sorry um so this is the 360 view of
a
individual customer so this is she's
bessie watson
um on the left side there's the basic
information
and this is basically only part which is
fixed so we can see that
she's made 12 purchases um she lives in
haringey in in uk
um you can see the different um data
that she's left
the different uh marketing permissions
that she has what tag she has
and then the rest of this data can be
actually catered
based on what data you bring into the
system in this bookstore demo example
it's how many times they they've bought
how much
revenue they've generated if if she
would have given her birthday that can
be shown here
um if if if the customer
has a for example a loyalty point system
or loyalty levels those can be displayed
here
you see what product categories what
product types
she likes to buy from which specific
stores
customer also calculates which is one of
our add-ons we also calculate product
recommendations
based on all of the omni channel sales
and uh also browsing data
these can be of course used as dynamic
content in the in the emails
but this can also be used um in the 360
view so for example having this view
um in customer service like like some of
our customers has
um first of all it shows you who the
customer
is what are they interested in and then
the product recommendations of course
bring
an extra idea of like what are the
things that you could right away offer
to the customer
what they might find interesting
then of course the product customer data
can be edited here
but the great thing here is that the
customer view layout so you can actually
define the different user roles um
what kind of data you want to show
actually on a
on a field level so if we take that away
you can you can decide what
what actual fields um you're showing
here
so no need for for admin stuff like that
so any data which comes in about the
customer that can be displayed here
so super easy and handy and quick way of
getting getting grasp of a
individual customer then when we go down
here's the timeline and this is
basically the one like a similar one
which i showed you in the presentation
so every touch point with the customer
this is demo data so there's quite a lot
of demo events in the beginning
so of course there's like different kind
of automated campaigns
there are the newsletters that the
customer has gotten
um here's the nps survey so customer
satisfaction score
um like answer that she has given
so the rating and of course the written
feedback would be visible here as well
then when we go down um we can for
example see that she has
created a zendesk ticket um delivery
problem there's
there's a url which takes you to the
zendesk ticket itself
so once again super helpful in in
customer service
but also something that can be used for
for segmentation naturally
and then browsing data from the site
what are the pages what are the products
that they've been proud
or she's been browsing and then the
sales
what are the products that she bought
from which stores
and when and like said
this is the essence for the segmentation
for the for the automations all of this
data can be used
for for that um and then of course there
might be some people of you who are
who are interested and know a lot about
gdpr there's
for example if the customer asked to get
the data exported that's possible here
to to get a csv out and and send it to
them if they
so have asked or remove the customer
naturally if they ask that as well but
this was 360 view so basically the
unified customer profile which is the
base for
base for everything then when we go to
the segmentation part
here's audiences so this can be
basically anything what you want them to
be for example for a for a bookstore so
these are dynamic customer groups
groups that you communicate too often or
are just interested to see them and
follow them up
for a bookstore chain for example
fiction lovers biography readers these
kind of um
buying personas super important people
who only buy from offline
um it can be people from
specific geographical areas which
many of our customers actually use it to
people who buy from specific stores
anything like that um and then we can
just start building a
new search from from here or new
audience from here
so kind of like as having the
clothing clothing example in the in the
background
like so the product launch so we start
with the board of products
so customers who bought a specific brand
specific category
um specific like products themselves
when they've bought from which store
let's go with a bit more general one
people who've bought comics
so we had the whole customer base there
100 137
000 customers now there's a bit under 5
000
we can right away see in which marketing
channels how many permissions these have
and then when you scroll down um
here you can actually see quite a lot of
interesting
data about these customer groups for
example the customer lifetime value
do these customers mainly uh fall into
the west
10 group customer lifetime value-wise or
do are they part of the best 10
and this can of course be used as
segmentation um criteria as well
when they've been less active when did
they buy the last time
how many times they've bought do they
usually buy online or offline
and which from which specific stores do
they buy
from which cds are they from which
product categories they usually buy
which brands they buy
so so trying to offer you as much
information
about the group that you've selected as
as possible
then when we go up here um we can
continue by adding for example customers
who've also been browsing
this this product category so
let's put comics there as well um
so customers and here so one year so now
we have
all search so the customer base
increased
people who've been buying comics or have
been browsing comics
during the last year then for example we
can add a
cd search on top so
let's take a ring and old ham
so let's say that we have a stores
around there so
we add a and search there so now we have
customers who
have been um have been buying comics and
are from hovering or oldham or have been
browsing comics
and then we could also add a zip code
range here
um let's say that because i know that
this
is uh this is like
uh uk data so the the they have a bit
different
like way of using the postal code so
let's do that
all of the post postal got codes which
start
start with bx and then let's add it
on the browsing side so with everybody
who's been buying comics
are from these cities or have been just
browsing them
and are from this zip code range we have
152 customers
um 62 of them have email marketing
permission
so quite small group but i i think you
get the picture and of course
here's an exclude part as well
so for example we could add let's make a
copy of this
add it there so people who have been
let's
exclude people who've been um
have already bought from this um
category so fables so now we have 77
people so you can also really easily
exclude certain
certain customers from here then you can
of course save the audience so then it's
visible in the timeline
in the dashboard in the front view which
i showed and then it can be also pinned
to the email editor so then you can have
dynamic content for them
but let's run through the campaign
creation as well here so you see how
easy that is
so email sms external campaign push
notifications so you have the actual
pushes to
to apps their google and facebook ads
but let's
let's go with the email now and of
course the automations as well but let's
go with the email now because there's
quite a lot of
different uh possibilities there um then
there's of course folders there
let's go forward select a template so
different language version different
brand looks
um templates can be created here
now we selected the english template so
um
it's it's a module based um email
template tool so you can add
and at different modules based on your
wishes
um i'll just add a few here so
first of all there's a there's a
marketing image library
so they can be imported there on the
media library or selected from the
computer
and of course if you have text you can
have placeholders so for example in
automations hi first name last name
those kinds of things um great thing
here is that
the product data comes with the
integration so so from the backend
system or e-commerce
so in this case from tilroy so
you can search out products with with
name product code
you just drag them here you get the
pictures links to the stores
um okay this isn't finished but yeah
anyways
prices discount prices all of that is
visible there
then a great thing is that then you can
also if you use the product
recommendations for customer
you can define for example different
product categories brands or types
from which you want to get the product
recommendations from
so in this case there's fiction and
non-fiction um
so let's add the fiction product
recommendations here so this means that
for every customer who opens the or gets
the message
it's they get calculated products which
they are most likely to
to buy next so that's like super
personalized content
in the in the message itself
then which is also something that our
customers love you can select
any of these modules so now we selected
this
last product module and you can select
the module visibility
so you can select if everybody can see
it or if you only
show it to specific audience or hide it
from our audience
so now let's select fiction lovers here
so this is the idea or test the idea
behind it that
you can have different content in your
messages which is hidden or shown to
specific audiences
for example if you have a regional thing
going in one city then you can only show
information about that event to to
customers who live in that town or
usually go to
to that specific store or it can be that
you only show certain content for your
best customers or anything like that
um but let's say that we're now happy
with the
happy with this message then when we go
forward
um and there's a lot of lot more things
also even
actually only even the email editor
which i would love to show to you but
there's not not enough time
unfortunately um
but then there's of course the um like
sending criteria
for example you can attach coupon codes
so personalize coupon codes
with placeholders so every customer gets
their personalized coupon
but when we scroll down um
we see a preview of the message and as
you can see it only has the
two modules so the hero image and then
the
product module here but then so that's
for everyone
then when we go to the fiction lovers
as you can see that these people they
also get the product recommendations
there
so great way of having dynamic content
for
for specific audiences
and then we activate it oh we should
duel it or then if it's an automation
you have different criteria there and
then that's basically done then you can
of course choose the audience or define
the audience more you can go back to
editing the content but that's basically
it
but most importantly um what happens
when the campaign is activated the
campaign is sent
of course the result what actually
happened
so now this is um one email
newsletter campaign um and the stats are
interesting
of course you see the audience in in
emails you see it delivered you see the
opens and clicks
but most importantly you see the
conversion
how many customers actually bought
from the campaign 37 000 customers got
it 77 bought
so sales conversion of 0. 0.5
you see how many orders you got how much
revenue it created
uh did they buy from online or offline
from which specific stores did they buy
and how was the distribution
of the sales to different stores
then of course you have click maps um
like a heat map of
where did the customers click what was
the most interesting stuff
and then products what products did the
customers buy who were part of this
campaign and bought something
did they buy the products which were
like selected to the campaign
or did they buy something else so
very interesting data when you want to
improve your campaigns and marketing and
think about what worked and what didn't
so and and of course same same for the
store side sales actually one of our
customers they share
these numbers about the different
campaigns um
weekly to the store managers because
before the store managers was
they were always quite hesitant on or
they had the feeling that the
the marketing was taking the customers
to online but after this they have
been able to show that actually like
this campaign gave
gave 10 or 15 000 euros to your specific
store
so it can be actually also really good
in internal communications
and then the campaign results can also
be looked from uh
like perspective of a defined customer
group for example the fiction libraries
so if you had dynamic content there for
only specific customer group or you want
to see the results
for your best customer groups um
that's that's something that can be can
be absolutely done
then one more thing um in the demo which
i want to show you because that's a
it's a like a thing which is a
sweetheart
sweetheart of our customers and this is
the rfm matrix
so so inability in the system um it
comes from the word
recency so when was the customer last
active so this
line here where they're active in 30
days 30 to 90 days
or haven't they been active in a year
frequency how many times they've bought
zero times one time more than ten times
um or are they um
so so basically you get a picture of who
are new customers
they haven't bought or bought one time
have been active recently
um at risk customers so with them you
didn't even have that good of a
relationship with um the vip customers
so basically the best of the best
they buy a lot and often from you and
then passive vip customers
so these like of course the idea is that
you want to grow the new customers back
to vip customers
get something like some some kind of an
action from the at risk customers to get
them also here into the
um buying step activate the passive vips
um to get them back here um and the
great thing is that
if you select one cell or several cells
the percentage here and here it shows
the size
of that cell or the selection in
customer base so we have 3.7
of the customer base it brings 14
of the revenue so you right away see
who are your best customers to who you
should focus on
who are the customers who bring bring
you the most money
and if we think about the concrete case
you want to activate
passive vip customers what do you do you
select them
you create action and create a email
automation so win back campaign to these
customers so right away when a vip
customer
drops so hasn't been buying in 180 days
they can for example get the message um
then if they buy
they come back here um and then the
cycle continues
so it's not actually only an analysis
tool but the idea is that it's
it's easy to take action based on the
based on the data
and naturally now we were looking at it
on a on a whole
like on an overall level of all
customers but you can also use it for
for specific audiences as well
this was the this was the part of the
demo
so let's and i'm more than happy and
people from children are of course happy
to also tell you more and show you more
but
um then one more actually two more
examples from our customers
what what they've been doing um
so this is actually a brilliant case so
australia is a
homeless equipment and horse like
food or company from from northern
germany they have a store and um
warehouse and then a web shop super old
company they started from a meal
um but now the current owner
and the part of the like the founding
family
he decided or he understood the power of
customer data
he realized that only if they can use
the customer data effectively
they can actually compete in the market
and grow to the scale that they've been
able to grow
so combining all data
from from different customer touch
points of course with customer
and the best idea was that they had this
kind of calculator on their site
where you could give give your horses
breed uh
what hobbies what what what were the
things that you did with them
the horse's birthday um then the
allergies
when you put it to the tool itself then
then i think you got some kind of uh
what kind of food your horse should eat
but all of that data was then sent to
costa bar
so then they got this full profile not
only of the customer
but of course the customer's host which
is the kind of like end client here
so what happened there that they used
this data
to create a lot of different automations
and they were also using it with with
the rfm matrix
so for example um birthday notification
to the horse
um they were targeting the allergy foods
for the horses with different allergies
they were able to target the campaigns
based on the activities that the horse
horses were doing um and
the results were amazing so they gained
a 62
increase in the year over year
repurchase rate
um like compared to the time
time before they weren't using costa bar
so great example of how you can really
use your data to
to drive sales then
then one more case this is also from the
clothing retailer
but this is once again totally different
angle but but pretty interesting
so um what happened there is that
they used to send this catalog to to
basically all of their customers
um and of course catalogs i know it's
from h
m i think a lot of you also know that
they drive sales but it's expensive
um it's not always um desirable for
internet savvy customers we use
emails we go to the site we use
instagram all of that
um and it's also difficult to measure in
terms of effect in
effectiveness compared to online
campaigns so what revenue actually came
from the campaign
um what they did was that they did
it's simple when you say it like that
but they did a targeted catalog sending
so they included everybody who has made
a purchase within two years
so customer has been reasonably active
they have a permission to send physical
mail and they
excluded people who have recently bought
something it might have been
maybe three months so they didn't need
any or even less like they didn't need
any activation
um they excluded also people who only
buy
from online because they they know where
to shop
um most likely they're not even
interested in the catalog itself
and then they excluded everybody who
would openly clicked an email recently
so they were already kind of like
inactive collaboration with the brand
so what happened well this happened
the sales was great um interestingly
you can see that how the sales was
divided between the different channels
online and offline
20 000 customers in the audience
7.2 conversion of the campaign
you can only imagine what it what it
means in money but in the end
what they said was that with the 20
smaller target audience
which means 20 lower cost for the
catalog sending
they were able to make 20 more in sales
and and to top it off um they were also
able to
learn something about their customers so
build their customer understanding
and and they saw from the data that 98.9
of the customers bought from physical
stores who were part of this campaign
so there's a big big part of the
customers who like
physical stores they they like catalog
they like physical stores they're not
maybe that internet savvy they don't
like online shopping
so then they they kind of like they
understood that this is also a customer
group
which they need to take care of
um that was
that was basically it oh actually yeah
there was just like couple of um
a couple of note notes which i wanted to
kind of like key takeaways which i
wanted to summarize to you
um at least like hopefully it also came
came to you clearly clearly from the
examples
that your customer data is a source of
competitive
advantage um that's
that that's it there's no better way of
saying it
um and as cd p or customer data platform
like customer unifiles all
customer related data it also makes
possible to do targeted campaigns and
automations which is super important
um and going forward of course
like like these guys did they tested
different kind of
channels emails sms google facebook ads
um even the physical mails testing it
and trying out what works
in the best case you get more sales and
then also you learn something about your
customers
um and of course with with customer they
were
they were able to get full analytics and
the actual conversion of all of these
campaigns so they can actually see how
it works
why it works and then take action also
for the
for the future
but um yeah this was this was my part um
happy to answer questions now and of
course also
connect with you and help you with with
next next steps
if if if you want to continue the
discussion
okay alexi uh thank you for this uh
presentation always
uh admire the the ease of use
and and the the enormous amount of data
that
that that you can use it that you see
and that you can use in a fast way
and certainly to combine the the offline
in the online
things so i'm just going to call
uh alexi because he cannot hear us
so and then here is
okay yes
okay uh i have some uh some questions so
i
can mute you and then then you can uh
talk again um so there's a question
about
uh the tracking of the campaigns uh
towards the the turnover so you had some
great results from a campaign
but how do you track the turnover
related
uh to the campaign
super good question so how
how it works is that um it's um
so customer we know the customers who
were part of the campaign
and and what we do is that um
then we get the sales from online and
offline
to to customer so and then you define
a conversion window for every campaign
so ten thousand customers you have a
conversion
window of seven days during that time if
some of the customers buy
um then that sales is linked to the
to the conversion of the campaign um and
of course this is the great thing
because it works for facebook google
because we know people who are part of
the campaign same from physical mailings
um and then of course related to this
for the physical
stores you need to have you have to have
a way of identifying the customers from
there
so if it's a loyalty card you ask um
email or phone number on the till
anything like that
that's enough to basically identify the
customer and then add it to the
add it to the time
nice um i have another uh question
uh that i can answer um so that is
uh how do we get the data into crystal
bar
um now if you use tilde you're lucky
because
it's integrated so it's just activating
the
the link with crystalbar and that's no
development it's just a setup
that we need to do from the data for the
sales there's also a plugin
in the website and it depends on your
theme
to trace all the online activities
towards a
customer alexis there's a question about
is this tool also used in a in a b2b
context
so now we see b2c but what do you think
about the b2b
customers
once again a good question then question
we get quite a lot
honestly we are really focused on b2
b2c then again there's always a but
but we also have some customers who use
costa bar for b2b
it's not a crm solution absolutely not
for b2b
but it can be used for
b2b sales which is really similar to to
b2c
so a lot of customers a lot of a lot of
interactions with them
usually you have to have an online
channel where the customers buy
um but to to be honest mainly for b2c
in specific cases of course it works for
b2b as well
but that's something that we can
hopefully discuss more more later
okay um another question
can the system help you to to identify
customer groups customer journeys that
are
a good idea to target
so
the basically we don't
have we have an ai partner called
houston analytics which can basically
crack
all of the numbers and we have an
integration from costa bar so they can
basically do
a lot of predictive analysis on the data
and create that kind of groups
then again as all of the for example rfm
matrix
that's already i think a really like
tangible
way of identifying those groups and
one thing more is that as all of the
audiences which i showed
are dynamic so for example buying
personas one-time buyers returning
customers
those are things which we actually in
the setup phase we can save them with
you
or or we can show them how how they're
done and then those of course follow you
going forward
and then in our automation um build of
the flow tool there's kind of like some
templates for
for kind of like ready-made automations
which can be used
to to basically make those kind of
things even simpler
thank you um yet to conclude i think
there
are a lot of things that you showed in
the in the demo um
but the time is limited we wanted to be
around one hour
um but interesting to know uh for
everyone that
there's also a lot of automation
possible so
reaction of email campaigns based on an
event
for example if there's a birthday or
somewhere
someone abandoned basket emails all
these kind of uh
of events are certainly also possible
okay um alexey uh thank you
um for the presentation uh i hope we
were able to inspire the customers and
the viewers
so if anyone has uh questions afterwards
uh how to get started with it uh
possibilities
just let us know we
can send you an answer of course
together with alexi from
from crystalbar so uh happy to help you
with
any idea that that you have to uh
to connect to your customers
okay um also
sorry also thank you from from my part
it was a pleasure
um first of all in finland if we would
have had the same kind of event
there would have been no questions so i
really appreciate that you were so
active and um
it was a true true pleasure um there's a
couple of
uh questions about the pricing um so
actually this
we can get back to you with with peter
if you
get in touch with us and we we see your
name so we'll we'll send you the
kind of like the slides about the
pricing but on a
on a broad level um if you go to
costabar.com pricing
there you can see like the pricing for
our
kind of like the customer which you can
take into use through the online
online site so so that's one part but
but we'll also get in touch with you
with the specific pricing absolutely
okay great
um we will also send uh the presentation
uh you will get an automatic email with
the registration with a recording
uh of all this uh so i will you keep you
informed of
evolutions and uh and new plans
thanks for being uh online um
we are we were nearly with 100 people so
it's really it indicates that there's a
lot of interest
in connecting to our customers and i
think that's a that's a very good
good step thank you for participation

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apis::noun | Spocien Dictionary

apis

noun

/'eɪpɪs/

type genus of the Apidae: honeybees

Type	Words
Synonyms	genus apis
Type of	arthropod genus

How to pronounce apis in Dutch?

apis::noun | Spocien Dictionary

abandonment

Related words

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