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1:00

ready, enjoy the show. Welcome

1:02

to episode 476 of

1:04

The Braney Business,

1:06

Understandingless

1:09

Psychology of Why People

1:11

Buy. Today's episode is

1:13

all about setting up

1:16

experiments. Ready? Let's

1:18

get started. You

1:24

are listening to the brainy

1:26

business podcast where we dig

1:28

into the psychology of why

1:30

people buy and help you

1:32

incorporate behavioral economics into your

1:34

business making it more brain-friendly.

1:36

Now here's your host, Molina

1:38

Palmer. Hello, hello everyone. My

1:40

name is Molina Palmer and I want

1:43

to welcome you to the Brainy Business

1:45

Podcast. I share a lot of tests

1:47

and experiments on this show, some of

1:49

which have been done in academia, some

1:51

in industry, and hopefully they have inspired

1:53

you to want to do your own

1:55

experiments. Of course, for the

1:58

academics listening, you are potentially...

2:00

already doing lots of these, which

2:02

is awesome, but in business real

2:04

experiments are not as common as

2:06

we all might like. Experiments matter

2:08

because they can help you to

2:10

see if what you're trying is

2:12

working without having to rely on

2:14

just instincts or gut feelings. It's

2:16

one thing to say, I think

2:18

that did better than we would

2:20

have before, and it's another to

2:22

say we saw a 38% increase

2:24

in sales when we changed the

2:26

word them to the number 18.

2:28

feels totally different. To be able

2:30

to have evidence like that, to

2:33

prove that your work is working,

2:35

or to find areas where it

2:37

isn't worth the resources you're investing

2:39

in a type of content that

2:41

isn't paying off or anything else,

2:43

to be able to know that,

2:45

to have that evidence, you need

2:47

to run some tests. If you

2:49

haven't done this before, it can

2:51

feel a bit overwhelming, but it

2:53

doesn't have to be. In this

2:55

episode, which originally aired way back

2:57

in August of 2019, I share

2:59

my top tips for conducting your

3:01

own experiments at work. Get ready,

3:03

we're going to jump right in,

3:05

but before we get to it,

3:07

just one last thing, don't forget

3:09

links for my top related past

3:11

episodes and books are waiting for

3:13

you in the shownotes for this

3:16

episode, which are found within the

3:18

app you're listening to, and at

3:20

the Brainy business.com/476. All right, let's

3:22

talk about experiments. Experimenting is so

3:24

important for any organization, but I

3:27

know it can feel intimidating if

3:29

you've never done it before. The

3:31

truth is you probably have done

3:33

experiments and not realized it because

3:36

they don't need to be big.

3:38

In reality, good experiments are incredibly

3:40

narrow in their focus because if

3:43

you test too many things at

3:45

once, you don't know what contributed

3:47

to the result or why it

3:49

came about. I remember my first

3:52

research paper, which was published in

3:54

the Association for Consumer Research back

3:56

in 2009. Interestingly, as I was

3:59

looking back for doing this episode,

4:01

I believe this is actually the

4:03

10-year anniversary of that publication as

4:06

it came out in volume 8.

4:08

Amazing how time flies and that

4:10

it ended up being exact down

4:12

pretty much to the month. There's

4:15

of course a link for you

4:17

in the show notes if you

4:19

want to check that out. That

4:22

paper was the result of my

4:24

senior thesis as an undergrad at

4:26

the University of Washington, which was

4:28

a requirement for me to graduate

4:31

from the Global Honors Program. So

4:33

I was actually the only undergraduate

4:35

business student on the whole campus

4:38

who did a thesis like this.

4:40

It was uncharted territory for me,

4:42

and in working with my advisor,

4:45

I had to present ideas for

4:47

what I wanted to research. This

4:49

probably isn't a big surprise to

4:51

anyone that's listening, but my style

4:54

and inclination in that process was

4:56

to solve gigantic problems, and so

4:58

all my ideas were far too

5:01

grandiose for what could be achieved

5:03

in a project like this. As

5:05

I was required to write a

5:08

15-20-20-page paper on the subject, I

5:10

figured it needed to be a

5:12

big topic, because how else could

5:14

you have enough content for that

5:17

many pages? Boy was I wrong.

5:19

So every time I presented ideas,

5:21

he would send me away saying

5:24

to narrow them down, make them

5:26

smaller, and more specific. Truth be

5:28

told, it was a little bit

5:30

frustrating over time, but eventually got

5:33

to the final paper and the

5:35

title ended up being Global Advertising

5:37

Standardization in Japan and the United

5:40

States, a closer examination of high

5:42

involvement products. Yes, it's a mouthful.

5:44

The basics of what I did

5:47

for that study was obtaining magazines

5:49

from both the US and Japan

5:51

from the same month and year

5:53

to ensure the ads would be

5:56

the same and separated them into

5:58

categories based on emotional processing and

6:00

mental... or cognitive processing to see

6:03

when the advertisers were more likely

6:05

to standardize and use the same

6:07

ads in these two very different

6:09

countries and when they would be

6:12

more likely to use different ads.

6:14

My sister who obtained her undergraduate

6:16

degree in Japanese linguistics was living

6:19

in Japan at the time of

6:21

my research project and was kind

6:23

enough to translate a giant pile

6:26

of ads for me. Thank you,

6:28

Sis. I'm sure I said thanks

6:30

then, but I'm going to say

6:32

thanks now again. The study found

6:35

that advertisements for low cognition products,

6:37

so ones that you have to

6:39

think less about, were twice as

6:42

likely to be standardized as high

6:44

cognition products like cars. Ads using

6:46

pictures were more than twice as

6:48

likely to be standardized than those

6:51

using a lot of text. At

6:53

the time, I didn't realize how

6:55

useful this information was or how

6:58

impressive the results were. I remember

7:00

when my advisor called to let

7:02

me know that the paper had

7:05

been accepted by ACR for publication

7:07

and I said, well, they must

7:09

pretty much accept everything right. Is

7:11

it pretty easy to get in?

7:14

He politely said, um, no. How

7:16

naive I was. In looking back

7:18

and reading my paper today, there

7:21

were so many variables and items

7:23

cross-reference just for a study that

7:25

looked at one month of magazine

7:28

ads. In my original pitches to

7:30

my advisor, I'm sure I would

7:32

have recommended all types of advertisements

7:34

and over a longer span of

7:37

time. I also believe I recommended

7:39

including a third country to make

7:41

it extra interesting. As it was,

7:44

I had to break everything into

7:46

categories and I remember having hundreds

7:48

of ads strewn around my apartment,

7:50

looking for brand matches across the

7:53

countries and then categorizing them and

7:55

using a 100-point scoring rubric for

7:57

each ad which I modified. from

8:00

an existing model. I'm so glad

8:02

I did this and I learned

8:04

so much from the experience and

8:07

I can see why my advisor

8:09

kept telling me to think smaller.

8:11

The study I ended up with,

8:13

which felt incredibly small to me

8:16

at the time, was actually a

8:18

huge undertaking with important results and

8:20

it was a true academic experiment.

8:23

An experiment like this is probably

8:26

something you would want to bring

8:28

in outside help for, especially if

8:30

you haven't been trained in the

8:32

space. When there's a lot weighing

8:35

on the outcome of the findings,

8:37

say you're deciding whether to launch

8:39

a new product or want to

8:41

test out different names in a

8:43

rebrand, it's worth bringing in experts.

8:46

However, there are tests you can

8:48

do on your own fairly easily,

8:50

which can still have a great

8:52

impact on your business. And the

8:55

nice thing about doing small tests,

8:57

it means you can be more

8:59

agile and adapt quickly, which is

9:01

very helpful in business these days.

9:03

My general tips, which I will

9:06

break down throughout the episode, are

9:08

to keep these three things in

9:10

mind when setting up your experiments.

9:12

Be thoughtful, keep it small, and

9:15

test as often as you can.

9:17

I've already told you a little

9:19

about keeping it small. In addition

9:21

to making it so you can

9:23

actually do the test on your

9:26

own, it also allows for you

9:28

to understand what contributed to the

9:30

result you're seeing. As I talked

9:32

about in the color theory episode,

9:35

there are a lot of sites

9:37

out there claiming to know what

9:39

the best color for buttons and

9:41

calls to action are. And yet,

9:43

when you dig into them, they

9:46

all claim to have a different

9:48

perfect color. One says red buttons

9:50

are always better. Another says orange

9:52

and this one says green. In

9:55

some of those cases, they went

9:57

from a link in the text

9:59

as their call to action to

10:01

adding a big red or orange

10:03

button with the call out and

10:06

then claimed that the color is

10:08

what made the difference. Was it

10:10

the color or the fact that

10:12

there was a button at all?

10:15

Or the placement of the button

10:17

or the font or the verbiage?

10:19

Those likely all changed when the

10:21

button was added, so it isn't

10:23

just color that impacted the result.

10:26

It was a whole myriad of

10:28

things. This should instead be separated

10:30

into multiple mini tests to determine

10:32

what is really best for the

10:34

piece. AB testing in emails or

10:37

on websites are really great for

10:39

this. And many systems are set

10:41

up to track all that for

10:43

you really, really simply. Let's say

10:46

you send a weekly email to

10:48

your list. In the first week,

10:50

you would test the link versus

10:52

the button. And that's it. All

10:54

other text and layout and colors

10:57

and everything are exactly the same.

10:59

Whatever the link says, the button

11:01

says. In the next week's email,

11:03

you can look at the color

11:06

of the button, and don't be

11:08

tempted to also integrate things like

11:10

different fonts or placement or size.

11:12

Everything, including the subject line and

11:14

imagery and verbiage, must be exactly

11:17

the same. The only difference between

11:19

the versions is the color of

11:21

the buttons themselves. If you have

11:23

a large list, You could try

11:26

multiple versions, say four different color

11:28

versions, as long as they all

11:30

send at the same time, because

11:32

time of day or day of

11:34

week could impact performance as well.

11:37

But if you have a relatively

11:39

small list, say under a thousand

11:41

people, just stick with two options.

11:43

Now, you may spend a few

11:46

months going through color tweaks to

11:48

see what's the best performing button,

11:50

and that's okay. As long as

11:52

you're tracking what you do and

11:54

what the results were, you're learning

11:57

at every step of the way.

11:59

Use my tips from that color

12:01

theory episode, which is linked for

12:03

you in the show notes, to

12:06

narrow it down to contrasting colors

12:08

that will work. in your specific

12:10

situation and branding. And if it

12:12

feels like a waste of time,

12:14

remember that Google tested out more

12:17

than 40 different shades of blue

12:19

to determine the perfect color for

12:21

their links. They've publicly said that

12:23

the shade of blue, not the

12:26

difference from red to blue or

12:28

orange to blue, but between greenish

12:30

blue, yellowish blue, or a purplish

12:32

blue, results in an extra $200

12:34

million in ad revenue for the

12:37

company every year. While your business

12:39

may not be as big as

12:41

Google, and the results may be

12:43

comparatively smaller, what if finding the

12:45

right color combination on your emails

12:48

generated an extra 25% in clicks?

12:50

Or if you could tweak one

12:52

item at a time and convert

12:54

10 more people a month on

12:57

your website? These small tweaks don't

12:59

need to take a ton of

13:01

your time, but they uncover small

13:03

changes that can make a big

13:05

difference. One of the studies I

13:08

share most often is the one

13:10

with the end cap displays for

13:12

Snickers bars. This study used anchoring

13:14

and adjustment and found when they

13:17

said by 18 for your freezer,

13:19

there was a 38% increase in

13:21

sales over saying by them for

13:23

your freezer. This is a huge

13:25

difference and most everyone is impressed

13:28

when they hear about the results.

13:30

The article I wrote for CU

13:32

Insight on this concept called One

13:34

Word that increased sales by 38%

13:37

resulted in tons of credit unions

13:39

and others reaching out to me

13:41

to ask questions or see about

13:43

working together. But if it wasn't

13:45

tracked... No one would have known

13:48

the real difference. We all get

13:50

hunches all the time, but behavioral

13:52

economics shows us those are often

13:54

wrong because they're based on logic,

13:57

not the true rules of the

13:59

subconscious brain. A perfectly

14:01

rational being would not be impacted

14:03

by color or font size or

14:05

framing, but we humans are. So

14:08

this all matters, and testing can

14:10

help you to figure out what

14:12

really makes a difference for your

14:14

audience. Speaking of framing, some other

14:17

things you could test would be

14:19

how your ads or emails or

14:21

direct mailers or website pages do

14:23

when you change a number frame.

14:26

say in one you put 78%

14:28

of clients by for me again

14:30

and the next says four out

14:32

of five clients by again and

14:35

another simply says most clients buy

14:37

from me again. I know I've

14:39

mentioned before when I worked with

14:41

a credit union on their advertising

14:44

for their checking account. And we

14:46

changed from focusing on the APR

14:48

that you would get to asking

14:50

the question, did your checking account

14:53

pay you $315 last year? That

14:55

their month-over-month checking account openings went

14:57

up 60%. Again, they wouldn't know

14:59

this if they hadn't been testing

15:02

and tracking the information on that

15:04

project we worked on together. You

15:06

can also do tests on blog

15:08

post headers or copy on social

15:11

media posts, images used on ads.

15:13

Really, the options are almost limitless.

15:15

And this leads us to the

15:17

second important thing to focus on

15:20

when you're doing experiments, and that

15:22

is to be thoughtful. You know

15:24

this is one of my favorite

15:26

things since I close all my

15:29

emails and podcast episodes with this

15:31

phrase, but what does it mean

15:33

for experiments for experiments? For one

15:35

thing, being thoughtful means looking outside

15:38

of what you always do or

15:40

what you know to be true.

15:42

Often, the things we take for

15:44

granted are those that present the

15:47

biggest opportunity for learning. Like in

15:49

that previous credit union example, it's

15:51

really common to advertise on APYs

15:53

or APRs rates of any kind,

15:56

and that's what every... everyone else

15:58

does, so you think it's the

16:00

best way to go. But behavioral

16:02

economics teaches us that humans do

16:05

not always act rationally or with

16:07

much forethought. Make sure you fight

16:09

the tendency to make assumptions about

16:11

people's behavior as you look for

16:14

opportunities to learn in your organization.

16:16

It also means being thoughtful and

16:18

taking the time to plan before

16:20

you jump into a test or

16:23

start testing absolutely everything. While these

16:25

are all small items being tested,

16:27

in bulk they could add up

16:29

to a lot of time and

16:32

just a volume of data that

16:34

you don't want to deal with.

16:36

Doing multiple versions of every email

16:38

post, website page, and mailer could

16:41

quickly become a full-time job for

16:43

a few people. and you also

16:45

have to analyze the data that

16:47

comes in. In some cases, it

16:50

could be easy, the number of

16:52

clicks on a button, but in

16:54

others, it can get more complex

16:56

and take a lot more time.

16:59

Instead of testing everything, test the

17:01

right things. Before you start building

17:03

a test, know what problem you're

17:05

trying to solve and why it

17:08

matters to solve it. What are

17:10

you trying to achieve, and why

17:12

does it matter for your business?

17:14

This is useful for a couple

17:17

of reasons. First, it can narrow

17:19

your focus so you aren't scattered.

17:21

That means you can be more

17:23

efficient with your time and dedicate

17:26

enough resources to implement what you

17:28

learn and continually get better. Anything

17:30

can be worth testing, but everything

17:32

can be a waste of time

17:35

if you don't have a clear

17:37

focus and goal. Second, It helps

17:39

communicate the why behind studies and

17:41

your organization in general. If your

17:44

company is about driving value, then

17:46

all your tests should be about

17:48

creating more value for your customers.

17:50

What allows you to spend less

17:53

on advertising so you can give

17:55

discounts to customers? customers. How can

17:57

you showcase the new products most

17:59

effectively? If your company is instead

18:02

focused on getting additional products in

18:04

the hands of existing customers, increasing

18:06

the efficiency of your emails, and

18:08

getting people to notice them is

18:11

important, as well as getting them

18:13

to click. If you have an

18:15

application process, do you know where

18:17

people get stuck or why? What

18:20

would get them all the way

18:22

through? Does a certain type of

18:24

customer get stuck or is it

18:26

everyone? It is important, of course,

18:29

to focus on items that are

18:31

driving revenue and value to your

18:33

company. Make sure the juice is

18:35

worth the squeeze so you aren't

18:38

putting a huge amount of time

18:40

and effort into something that will

18:42

never pay for itself. Being thoughtful

18:44

allows you to pick your battles.

18:47

And if you're thoughtful up front,

18:49

you're building things out with intention

18:51

and hopefully putting together a schedule

18:53

of what you're wanting to learn

18:56

and why it matters to the

18:58

business. When you test things, they

19:00

are inevitably going to be findings

19:02

that seem as though they can

19:05

impact other areas. It's possible that

19:07

they do, but it's important to

19:09

understand general liability. To put it

19:11

simply, the results of one test

19:14

will not necessarily hold true in

19:16

every situation or for every business.

19:18

Think back to the red buttons.

19:20

Because they have a lot of

19:22

contrast, red buttons would probably do

19:25

really well on Facebook where they're

19:27

surrounded by blue. But on Target's

19:29

website, maybe not. Being thoughtful when

19:31

you build your experiments will mean

19:34

you understand what you're looking for.

19:36

and the parameters so you can

19:38

know how you might be able

19:40

to extend the findings reasonably beyond

19:43

the single test. In addition to

19:45

being generalizable, it's important to know

19:47

whether the data you're collecting is

19:49

qualitative or quantitative and how each

19:52

can be applied. Conversations with people

19:54

are qualitative. Number of clicks are

19:56

quantitative. They're both important and should

19:58

be used in tandem in businesses,

20:01

but you should have at least

20:03

a basic understanding of the benefits

20:05

and limitations of each. I've linked

20:07

to a short YouTube video that

20:10

outlines some of those differences and

20:12

there's a ton of information at

20:14

your disposal if you want to

20:16

learn more about these two categories

20:19

of research. And when you do

20:21

find something, dig a little deeper

20:23

to see what else you can

20:25

learn. To use a financial institution

20:28

example, say you sent an email

20:30

to a thousand people who are

20:32

pre-qualified for an auto loan. 500

20:34

got one version and 500 got

20:37

another version where you were testing

20:39

button color. Let's say 50 clicked

20:41

on the button in test A

20:43

and 150 clicked in test B.

20:46

Great! You know this color seemed

20:48

to work well, but what else

20:50

can you learn from the test?

20:52

200 out of a thousand people

20:55

clicked on the button. How many

20:57

ended up getting a loan? What

20:59

is similar and different about them?

21:01

How long have they been using

21:04

the financial institution? How many products

21:06

do they have already? What type

21:08

of products? Are they in certain

21:10

age or income brackets? How does

21:13

this all differ from the 800

21:15

people who did not click? If

21:17

you follow up with the 800

21:19

people who didn't click, what did

21:22

they have in common with each

21:24

other and different from the 200

21:26

clickers that you could call out

21:28

and feature in a second email

21:31

as another test? This can help

21:33

you segment better in future campaigns.

21:35

Say all people with at least

21:37

two products and who have been

21:40

a member or customer for over

21:42

five years get this message and

21:44

those who have one product get

21:46

a different message, which is still

21:49

different from those who've only been

21:51

with you for six months or

21:53

less. Digging a little deeper and

21:55

asking questions is really useful. for

21:58

ongoing experiments and becoming more efficient

22:00

and knowledgeable in your business. But

22:02

you can't dig deeper on information

22:04

you didn't set up for in

22:07

advance. If you know you'll want

22:09

to dig into demographics and other

22:11

details, you probably need to build

22:13

that into your data pull up

22:16

front. So think and talk through

22:18

what you may want to know

22:20

and what could matter before building

22:22

out your tests, unless you want

22:25

an analyst who is definitely not

22:27

your friend. Of course, it's important

22:29

to combine this with keeping it

22:31

small, so you find the right

22:34

balance for your business. Don't get

22:36

so bogged down with all the

22:38

things you could do that you

22:40

don't do anything, but don't scale

22:43

back so much that the information

22:45

isn't usable. And my final tip

22:47

is to test early and often.

22:49

Smaller experiments, like I've been talking

22:52

about here, allow for frequent nimble

22:54

testing and ongoing quick improvements. My

22:56

research study that I get to

22:58

tell you about in a couple

23:01

of weeks, took six months of

23:03

data collection with much more time

23:05

to plan, analyze, and then write

23:07

out the results. It took two

23:10

years from pitching the idea until

23:12

publication. Actually, almost exactly another one

23:14

of these to the day. I

23:16

guess August is a really big

23:19

time for me. I don't know.

23:21

It's kind of funny how that

23:23

works out. Not every academic test

23:25

takes this long, and it was

23:28

more like a year from final

23:30

pitch to paper completion, but it

23:32

still takes a while. Small tests

23:34

let you act quickly. So the

23:37

more you test, the more you

23:39

learn. As you get into a

23:41

groove with experimenting, it does get

23:43

easier. And, as you learn a

23:46

little more each time and combine

23:48

results and ideas, the bigger, more

23:50

exciting findings start to emerge and

23:52

come together. You get a little

23:55

smarter each time, learning more about

23:57

your... and customers. Oh, and don't

23:59

get discouraged when you have a

24:01

non-finding. Say if you test a

24:04

bunch of button colors and nothing

24:06

gets people to click more, or

24:08

if you change up subject lines

24:10

and don't have a difference, no

24:13

result is still telling you something

24:15

very important. Maybe it means that

24:17

you don't have to worry so

24:19

much about what you put in

24:22

that picture in your email blast

24:24

because no matter what you do,

24:26

it doesn't seem to matter to

24:28

people. Maybe you don't need a

24:31

picture at all, and you can

24:33

reduce staff time searching for the

24:35

perfect photos. Findings tell you what

24:37

attracts attention or what matters to

24:40

your customers, but non-findings tell you

24:42

what they don't pay attention to

24:44

or care about. This can help

24:46

you further focus your attention, and

24:49

it's very valuable information as well,

24:51

so you can run leaner and

24:53

smarter than you would have without

24:55

having taken the time to test

24:58

and experiment. Now you have some

25:00

simple tips and guidelines for running

25:02

those tests and experiments that will

25:04

make your business stronger and more

25:07

efficient Remember to keep it small

25:09

be thoughtful and test often and

25:11

Don't get bogged down by analysis

25:13

paralysis. It's better to just start

25:16

and figure it out than to

25:18

hold up and wait until everything

25:20

is perfect and never get going

25:22

you'll get better as you go

25:26

So, what got your brain buzzing

25:28

as you learned about setting up

25:30

experiments today? For me, I really

25:32

love experiments and think they're so

25:34

valuable in business. And while I

25:36

know that we all get busy

25:38

and it can be easy to

25:40

let this slip, I encourage you

25:42

to invest in doing small tests

25:44

throughout the year. You don't have

25:46

to test everything. And as you

25:48

heard from my tip to be

25:50

thoughtful, you really shouldn't test everything

25:52

because it's a waste of resources.

25:54

And it doesn't have to be

25:56

huge. And again, they typically shouldn't

25:58

be so that you can keep

26:00

it small and test often. in

26:02

building a testing habit in your

26:04

organization. Learn a little bit on

26:06

a regular basis, and you can

26:08

continually be improving, which is a

26:10

way to help you always stay

26:12

ahead of your competition. Emails and

26:14

website pages are a great place

26:16

to start because they're easy to

26:18

track, but there are countless areas

26:20

where you can test on internal

26:22

communication and opt-ins from employees to

26:24

sales language to the way you

26:26

present packages. There are so many

26:28

options to test. It's awesome. So,

26:30

what are you going to test

26:32

first? Or what have you tested

26:34

already? I'd love to hear about

26:37

it. Please come share it with

26:39

me on social media. You'll find

26:41

me as The Braney Biz pretty

26:43

much everywhere and as Molina Palmer

26:45

on LinkedIn. And of course, if

26:47

it is a more sensitive test,

26:49

feel free to email me, Molina

26:51

at the Braney business.com. I can't

26:53

wait to hear from you and

26:55

learn how you're using testing in

26:57

your work. And who knows? Maybe

26:59

it'll get featured on an upcoming

27:01

episode of the podcast. If you

27:03

have really cool stuff that you're

27:05

doing that would make a great

27:07

case study to share here or

27:09

on LinkedIn or other places where

27:11

I write articles, you know, let

27:13

me know. I'd love to hear

27:15

about it. As we close out

27:17

the show, don't forget about those

27:19

show notes with links to my

27:21

top related past episodes and books

27:23

and more. It's all waiting for

27:25

you in the app you're listening

27:27

to and at the brainy business.com/476.

27:29

And just like that episode 476

27:31

on setting up experiments is done.

27:33

Join me Friday for a brand

27:35

new episode with Dr. David Daniels

27:37

to discuss whether or not investors

27:39

value gender diversity. It's going to

27:41

be a lot of fun. You

27:43

don't want to miss it. Until

27:45

then, thanks again for listening and

27:48

learning with me. And remember to

27:50

be thoughtful. Thank you for listening

27:52

to the Braney Business podcast. Molina

27:54

offers virtual strategy sessions, workshops, and

27:56

other services to help businesses be

27:58

more brain-friendly. For more

28:00

free resources, visit

28:02

the Braney .com.