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Measuring Customer Satisfaction With Likert Scales in Tableau

by | Dec 15, 2022 | Uncategorized | 0 comments

Join our founder Peter Koebel as he walks you through a demo of using likert scales in Tableau.

Likert Scales in Tableau can be an extremely powerful tool for measuring and analyzing customer satisfaction, user sentiment, and many other phenomena.

Here’s the transcript of the video:

Hello, it’s Peter Keobel here from Data Sciencing Consultants.

In this video I’m going

to create Likert scales in Tableau using

restaurants satisfaction survey data the

categories were food cleanse less

waiting time reservation process

reception ad server and the respondents

ranked those categories one to four

highly des satisfied dissatisfied

satisfied and highly satisfied and here

is the average score as you can see

server reception was Gordon really low

and food and Clinton scored really high

sort of start a new worksheet here and

of course we’re going to bring the

categories and we’ll bring in the

answers into each Oh

all right we’ll change these marks here

from going back to the Gantt bar and

this entire view next I’ll bring in the

percent this is going to help us

fill up those bars you can see here

these are the different responses

compute using answer and you can see

here this is where it’s starting to form

our bars

numbering in deep percentage a laser

calculated fields and I very very

established percentage seen

oops she met your size there we go

dr. Bartis and to make sure this is

should be set yet such a competing with

answer you can see these are already

separated okay sting ourselves a little

judge answered the color right here

somebody shows up over you again and

change these colors just something else

for mister screening so we’ll try colors

this time go green satisfied this color

green and purple

just picking random colors are not

really so seeing them with anything

specifically this just helps me more so

hiya satisfied as dark green and then

dissatisfied the light green light

purple is satisfied and I read that dark

purple plus we can tell these two

results are related and these two

results and we don’t need this header

should warm up first

is one yes one

because we can kind of already tell

relation really ratio of satisfy to this

highly satisfied to satisfied satisfied

by they satisfied by the curse since we

got right up the header of the values

which can get rid of nice lines


there we go

all right don’t think lines now we will

fix this tool tip here so we hover we

don’t need all that information so you

know we can’t percent is so change this

to do percent category above answer yes

let’s give one other category first and

then answer yeah there we go

snowy hover you easily see categories

reception answers highly satisfied

percent let’s change that percent

percent too much force instead of

decimals over here go to over here size

format number percentage good alright

all right now we can see the percent

today – Destin places and it’s cleanest

let’s sort this by category and we can

see which ones are

so this actual actually probably to do

the average so aggregate by average so

we incorporate the average into this

church so let’s go from that

alright so bringing the average school

so here Savage so right-click some

thoughts up here game pic degradation

the house very carefully the average

they’re real alright this picked out the

separate than Buddy ISS fight satisfied

it’s basic coffee yeah Kent percent I

have the colors but we actually don’t to

do that because as we saw over here we

actually just wanted circles so you can

just see what specific average so

takeout answer and take a percent then

each 50 sometimes these that should they

have a score and those gamblers you want

circles and yeah label there you go

let’s change that to two decimal places

let’s see what’s here alignment of spins

middle let’s make them bigger

there we go that’s better

no I changed the signs of it’s easy to

see all right no no you’d see these are

there was these are the average scores

we need to change the tooltip let’s see

if we reset what that does

no there we go figured out what yeah I

want it uh let’s change the wording Ava

game Fiji score to average score alright

now we want these two accesses to mix so

we’ll right-click and Alexis and so you

don’t need to fix this so this is

actually the right spot

the average score of this for

cleanliness is three point one seven

this is where it is but this is access

we need to fix ID access

so these surveys went from one to four

there we go

and so now this lights up with Kent

percent we have down here so these are

in the right place now combining with

the gap percent bars don’t need these

headers anymore because this is kind of

self-explanatory this is this is where I

will sort these same score and so there

we go we have tapas food and cleansers

there wait time reservation process

reception server and let’s change these

sizings bars a little smaller change the

size of these circles make me a little

bit bigger now let’s go back and change

actual these smaller

actually change neal cassady of faded

there we go that’s pronounced because

the main focus of the chart is the

averages and we’re just wanted in

relation to the bars don’t need to know

specifically right away and yeah

depending on how thick you wanna make

the secret circles a lot bigger already

can make the bars a lot thinner but well

you look here for now and next look at

the demographics so we can check any

different how it was by age sex than

type of customers so I’m trying type of


these were casual frequent and one offs

so just someone first time going there

and can see here the circles again just

those were first of all just the typical

customer to bit more frequency according

to the restaurant I love do this one

manually because tableau or most

computer don’t understand difference

less we rank these which is this is just

a lot easier steps up frequent and then

casually less frequent in than one offs

and we can circles in support so we can

read them better there we go and this is

a dependent on you want to analyze dad

if you want to just look at food you

compare the

responses from your frequent casual and

one of customers or if we just like

customer on this side they’ll break it

down by by the potential customer first

so you can see the frequent customers

and see how they responded then casually

one-off Sophie wanted to focus prudence

in here restaurant on satisfy the

frequent customers so you could focus on

here in this situation they all seem to

ranking receptions server as the lowest

so if you focus on helping out here or

proving quality for your frequent

customers by improving the reception

server that will also then incidentally

help the responses from your casual and

one-off customers but again if you

wanted to focus here on which ones are

worse overall it’s the same situation

casual is a bit more ok with the server

quality but frequent and one-off

customers still below a little away

response or low satisfaction for the

servant and and also then you can reward

see huge reward food is talk to you work

the kitchen staff and cleansiness also

get the highest second highest marks

there so let’s do it over here break

things up and then again

if you want you can actually with these

bars little thicker for presentation

purposes this be easier to see and then

you can also check out here age I

already created bins it’s 220 years open

oh here’s my boy here’s my thing so

these are in groups of 20 age groups 20

40 and 60 so you can get focus on near

demographics up to 20 year 2000 was

twenty to forty forty to sixty seven

sixty plus and see who would be want to

mark it to and then also checked by is

sex of the customer so again look at

just food for male-female about the same

for food just a bit more disparity with

the pleasantness and very close to

satisfaction here with the reception

server thank you

sit around and look just female

customers and just milk customers and

again you can you know use that that you

probably want for marketing recruitments

and rewarding of your staff yes it’s

like art skill it’s quick easy you can

see the average and kinda specially here

you can get a get a good education of a

percent so eight percent of customers it

scans what customers he responded with

their highly satisfied with food and you

can tell easily averages if you need to

look quick visualization to figure out

where you need to make improvements as

such thank you for watching.

Likert Scales in Tableau

If you need help with your Tableau, I’m Peter Koebel the owner of Data Sciencing Consultants. You can reach me at 204-770-6437, or email me at, or fill out the form on our website  You can also check out our YouTube channel for more awesome Excel tips!

For more awesome Tableau and data viz tips, like this one about likert scales in Tableau, check out the Datasciencing Consultants blog.

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