Who else thinks is cool ?

How would you translate your company’s data and analytics
into a step-by-step plan to grow the business? Where is your company’s most
significant conversion opportunity? Can you detect any intriguing patterns in
your company’s metrics?

To help you organize your data, pinpoint funnel leaks and increase conversion, MarketingExperiments held a live, interactive coaching session with Flint McGlaughlin, CEO and Managing Director, MECLABS Institute.

This first-ever coaching session from MarketingExperiments focused on practical application of a methodology to help you get more value from your data. Participants from around the globe interacted with MECLABS Institute’s CEO and Managing Director Flint McGlaughlin, Director of Research Services Matthew Klein and Director of Hypotheses Development Danitza Dragovic to discuss specific data challenges, ask questions about the lessons taught in The Marketer as Philosopher Episode 2, and get direct help in using the free Data Pattern Analysis Tool to increase conversion.

See below for specific questions that were addressed, along with time stamps in the video for those questions, if you would like to jump to a specific topic that addresses your immediate needs.

  • 00:20 What you will get in this series
  • 00:44 How can I simplify the way I view my data?
  • 3:33 Can I really use the DPA to drive major conversion increases?
  • 5:25 How many numbers do I need before I can detect a pattern?
  • 6:22 What period of time should I use for data analysis?
  • 8:47 How can I recognize a meaningful pattern?
  • 9:25 How can I get my data out of Google and into the DPA tool?
  • 10:15 How do I ensure that the data is accurate?
  • 13:42 Why do you insist on visualizing the conversion journey?
  • 14:47 Marketing is missing its way…

Watch the edited, condensed replay of the coaching session now to simplify the way you view and use your company’s data.

Related Resources

If you need help filling out the Data Pattern Analysis Tool or would like to have a MECLABS Scientist certify your data, email our sciences team directly with this link: Have a MECLABS Scientist Certify My Data

The Marketer as Philosopher Episode 2 — The Data Pattern Analysis: 3 ways to turn info into insight

MECLABS Data Pattern Analysis Template

How To Model Your Customer’s Mind Toolkit

Google Analytics Solution — MECLABS Simplified Data Pattern Analysis Template

Transcript

This transcript provided by GoTranscript:

Flint McGlaughlin: In this series, we’re going to give you a complete set of tools that
we’ve developed in our research program over the last 20 years. For those of
you that are new, we conducted 20,000 experiments. We invested $130
million-plus into a research program to answer a single question. “Why do
people say yes?”

Karen asked such a good question. I want to share something that I’ll
be teaching in future episodes, but this is a coaching session. All of you
should think about your conversion and your data by using a tool we call the
discovery triad. When you as a leader or your boss comes in and ask a
“how” question, for instance, “How can I get more sales? How can
we increase revenue? How can we get more subscribers? How can we generate more
leads?” That’s what bosses ask. They ask “how” questions and
what they’re really implying is, “Go fix this.”

Never let your mind stop at “how”, but instead think of this
as a triangle. At the top of the triangle is “how” and then I’m going
to move over here to the other side of the triangle, and that question is,
let’s say, “How can I get more leads?” Here’s the “what”
question. “What does the data tell me about customer behavior?” That
is the primary question that you apply to your metrics program. When you apply
that to your metrics program, it’s going to put a lens on so that you can
suddenly see into your data something more important which is the customer
patterns.

For instance, let’s suppose you notice that people are getting on this
page, but they’re not completing the form. Now, I’m oversimplifying. Let’s
suppose you see, “I’ve got great clickthrough from the ads. It looks like
they’re engaging with the page,” but when I get to the form, many of them
start, but don’t complete it. Let’s suppose your data showed you that. You went
from “how” to “what”. “What does the data tell us
about behavior?” That leads you to a “why” question now, and
that completes the triad. The “why” question is, “Why are people
behaving that way?” That typically leads you into the psychology of the
offer.

For these almost 30 years, I’ve been asking, “Why do people say
yes?” To get to the answer, I had to ask a more profound question, and
that is, “Why do people say no?” Because you get a lot of nos before
you get a yes. If I can understand the nos, I can move people up the micro
“yes-chain” to the ultimate “yes” that turns them into a
customer. Always think in terms of– Right now is your website, your
challenges, all your “how” questions.

Listen, as Peter Drucker, my favorite business philosopher said,
“The purpose of a business is to create a customer, and it’s the job of
every single person in the company and it’s the number one job of the
CEO.” The number one way you accomplish that is by crafting a strong value
proposition. The only way you can craft a strong value proposition is to take
the “how”. “How can I create a customer?” And complement it
with a “what” question and then with the “why” question.

This is a big company. This is Aetna’s HealthSpire. If you look on your
left, something happened that changed the control’s performance. Do you see the
treatment? It represents something we call a signal set. You would call it a
web page, but we view it as a signal set. It’s not a page, it’s not a web, it’s
zeros and ones turning on twos in the mind. Look at the results, 638%.

Here’s another. We’re going to move on to another, 166%. This is
another organization. That’s Toll Brothers, huge nationwide builder. That’s
166% conversion rate and that results in 167% increase in leads. Here’s
another, 96%. That’s Fluke by the way. Defense contractor, big organization.
This is another. 1600% increase. Oh, by the way, that’s The New York Times.
These are all part of the research program at MECLABS. PR Newswire, 202%.
Here’s another piece, CBS Sports, 44.5%.

Whether your business is big or small, it is possible to see
exponential impacts if we can understand customer behavior. We can understand
customer behavior if we can get into their behavioral traces. I like to think
of them as brain tracts. Beneath those results, was a deep-dive into the data
to understand how people were thinking and thus how they were behaving. With
that in mind, I’m going to talk with you about a tool that we applied in those
situations to get an increase. That tool was the subject of Episode 2 in our
new series, The Marketer as Philosopher.

In the spreadsheet tool that we downloaded, you’ll see that we’ve found
in one line, a break in patterns. All you need to establish a pattern is a
majority. When I say majority, I mean critical mass occurs in the pattern. This
is pure philosophy. When you’ve reached enough nodes that you can see anything
weighted one direction or another. It’s hard with two, it’s easy with three.
Sometimes three numbers can give me a pattern, but the more numbers, the more
reliable our understanding of that pattern can be.

Look for the broadest threshold you can bring into your pattern
recognition piece. Look over a year instead of over a week. A month is better
than a week. This accounts for seasonality also. That’s a technical answer to a
technical question, but I’m going to keep trying.

Matt, just go into your experience and tell us what you think about
that.

Matthew Klein: We’ve
done data analysis as short as just a few weeks even. We’ve done data analysis
as much as three years. It’s somewhat contingent on the organization. Generally
speaking, if you do experience any type of monthly seasonality, it would be
helpful to have more than one year’s worth of data. 12 months of data is a
really good starting place. You also have to account for– This is a really
important consideration for any kind of timeline amount of data. You have to
consider for any significant changes that may have happened either in your
organization, with your ideal prospect, or within your website.

Let’s just say I take 12 months of data, but six months ago, I
redesigned my website. I’m only going to have really six months’ worth of
relevant data to inform how customers are behaving or interacting with my
current website. There’s no golden rule in terms of the amount of data. It’s
really contingent on how the uniqueness of your business as well as the things
that you may have done, which may have caused changes in your data.

What you’re really trying to capture in your data analysis is a
representative sample of customer behavior over time so that you can start to
predict if based on what I’m seeing in the data, this is how my customer is
behaving with my website right now. You want to be able to analyze that over,
let’s just say periods of seasonality, whether that be weekly seasonality,
monthly seasonality, et cetera. Does that make sense?

Flint: I
think it’s a great answer. Philosophically, the foundation of data analysis
comes from one sort of thinking skill, that is comparison. If you’re comparing
future performance with previous performance, any of those different items
you’re comparing these elements, they determine really how long that data needs
to be. That’s the philosophical answer. Matt gave you the very practical
answer, and I hope that helps you with that question.

We’re going to charge double, and double times nothing is nothing
Michael, but still, [chuckles] that’s probably what the advice is worth.

[laughter]

Michael: Really,
you clarified the fact because I had seen some other people had asked questions
about if you have a minimal amount of traffic, what constitutes a pattern as
opposed to just a new one?

Flint: Good.
It’s a great question, Michael. If you see Episode 2, you’ll actually see us.
We will highlight the numbers and we’ll show you the pattern and then we show
you where we found the missing money. Hopefully, that will help.

Dani, go ahead. Take over.

Danitza Dragovic: We actually do have a version of the tool that’s a bit more simplified
that you can download from Google Analytics solution gallery. It’s under
marketing experiments. For some of the more simpler data polls, you can just
download that tool. You don’t have to actually plugin manually. There’s some
instances where there’s some more difficulty if you’re making custom funnels and
things like that where you would actually want to go into GA and make custom
segments for those. For the funnel itself, that won’t be automatic but most of
the pages can be.

Flint: Dani
thus is telling you, she’s created a template sort of tool inside of GA that
you can use to pull your data automatically.

“Do I have a concern about the quality of data?” I run two
metrics programs. Somebody asked that question. Matt, what do you think people
should do to make certain the quality of their data is right? We can certify it
for you if you need extra help and you want our scientist to– If you want to
use the tool and say, “Did I get it right?” you can talk to us about
that, but other than that, I’m going to ask Dani or Matt to answer that. Which
one wants to go first to answer that question?

Matthew: Sure,
I can answer it.

Flint: Okay,
Matt. Go ahead.

Matthew: The
first thing that I would do if I was looking at a data platform for quality is,
this is incredibly basic, but does it pass the sniff test? Is there something
in there that is just either completely implausible or highly unlikely? That
would hint to a potential quality issue. I do believe that, as Flint mentioned,
having a second tool is often very helpful to do so. You can also potentially–
If you do have a testing tool, you can also run what we call dual control tests
that may be able to validate or invalidate that your metrics are tracking
correctly.

Flint: Matt,
can I jump in there?

Matthew: Absolutely.

Flint: I
want to point out what Matt has said is very important. Everybody should do
this. If you have a testing tool, run a “A versus B” test but keep
the pages the same. Watch and see if you see a big disparity in conversion.
When he says a dual control, just to be clear to everyone here, that means
testing the same page against itself. You have an A and you have a B and at the
end of the test, you’re looking without saying, “Well, that number should
be very close or there’s something wrong with your metric set up.” Matt,
do you want to add to that anything or Dani? Add to that anything? Nope?

Danitza: I
completely agree. Always having a second platform is enormously helpful just so
you can see it. Usually, there is going to be a little bit of discrepancy, but
if there’s a gap, you know there’s something wrong right away.

Flint: Dani,
what is the average discrepancy you see? When you say a second platform, maybe
you have an expensive– Maybe you’re using one of the Adobe. It doesn’t hurt to
have Google running on the side especially an expensive version where you can
compare page metrics and key metrics and see how close are they. What do we say
on average is a disparity when we run two tools? Dani, I have a number in my
head, but I want to hear what you say.

Danitza: If
there going to be a big disparity and then you know there’s something wrong,
but a small disparity would probably be– A regular one would probably be about
5%.

Flint: Yes,
about 5%. The same number I have. All right. If you’re in 5%, you’re probably
in the right zone. Now, I’m out of time. Matt, you want to say something?

Matthew: Yes.
Sorry, I was just going to– One final thing related to quality of data. You
can also audit your digital data with comparable metrics offline as well. If
you’re driving let’s just say leads and you’re capturing leads in a CRM, audit
what you’re seeing in your CRM with what you’re getting in your analytics
platform to make sure that your conversion metric is accurate. Phone calls or
any number of data as well, orders even, if you’re an e-commerce store.

Flint: I’m
going to show you what you should be doing on your wall. Everybody, learn from
this. See the funnel? It’s not just numbers. It’s written here. See it’s in the
spreadsheet. You want to take those screenshots and put them in there. Now, if
I were running your business or you said, “Can you help us with our
organization?” I would put poster-size versions of that on my wall and I
would write the conversion rate on there every day or every week depending on
how much you see change in fluctuation and on each step through the funnel and
then final conversion. When it change, forget all this fancy technology.

Go up there with your pen, mark through the number, write the change on
there, and note the difference. You should be monitoring that number always. By
monitoring that number, you’re able to adapt and adjust to changes. Candidly, a
marketing department should be living around that number because that’s going
to drive results for them. Make your walls talk. Don’t underestimate the power
of big visuals.

Marketing is missing its way. Right now, understanding how to get the
data right, and then understanding how to get the message right, and then
understanding the value proposition, that’s all coming up in this series. It’s
an opportunity for us not just to learn but we can come alongside of Teresa and
rescue 3,500 small businesses.

The post Data Pattern Analysis: Learn from a coaching session with Flint McGlaughlin appeared first on MarketingExperiments.

More stuff on please

How would you translate your company’s data and analytics
into a step-by-step plan to grow the business? Where is your company’s most
significant conversion opportunity? Can you detect any intriguing patterns in
your company’s metrics?

To help you organize your data, pinpoint funnel leaks and increase conversion, MarketingExperiments held a live, interactive coaching session with Flint McGlaughlin, CEO and Managing Director, MECLABS Institute.

This first-ever coaching session from MarketingExperiments focused on practical application of a methodology to help you get more value from your data. Participants from around the globe interacted with MECLABS Institute’s CEO and Managing Director Flint McGlaughlin, Director of Research Services Matthew Klein and Director of Hypotheses Development Danitza Dragovic to discuss specific data challenges, ask questions about the lessons taught in The Marketer as Philosopher Episode 2, and get direct help in using the free Data Pattern Analysis Tool to increase conversion.

See below for specific questions that were addressed, along with time stamps in the video for those questions, if you would like to jump to a specific topic that addresses your immediate needs.

  • 00:20 What you will get in this series
  • 00:44 How can I simplify the way I view my data?
  • 3:33 Can I really use the DPA to drive major conversion increases?
  • 5:25 How many numbers do I need before I can detect a pattern?
  • 6:22 What period of time should I use for data analysis?
  • 8:47 How can I recognize a meaningful pattern?
  • 9:25 How can I get my data out of Google and into the DPA tool?
  • 10:15 How do I ensure that the data is accurate?
  • 13:42 Why do you insist on visualizing the conversion journey?
  • 14:47 Marketing is missing its way…

Watch the edited, condensed replay of the coaching session now to simplify the way you view and use your company’s data.

Related Resources

If you need help filling out the Data Pattern Analysis Tool or would like to have a MECLABS Scientist certify your data, email our sciences team directly with this link: Have a MECLABS Scientist Certify My Data

The Marketer as Philosopher Episode 2 — The Data Pattern Analysis: 3 ways to turn info into insight

MECLABS Data Pattern Analysis Template

How To Model Your Customer’s Mind Toolkit

Google Analytics Solution — MECLABS Simplified Data Pattern Analysis Template

Transcript

This transcript provided by GoTranscript:

Flint McGlaughlin: In this series, we’re going to give you a complete set of tools that
we’ve developed in our research program over the last 20 years. For those of
you that are new, we conducted 20,000 experiments. We invested $130
million-plus into a research program to answer a single question. “Why do
people say yes?”

Karen asked such a good question. I want to share something that I’ll
be teaching in future episodes, but this is a coaching session. All of you
should think about your conversion and your data by using a tool we call the
discovery triad. When you as a leader or your boss comes in and ask a
“how” question, for instance, “How can I get more sales? How can
we increase revenue? How can we get more subscribers? How can we generate more
leads?” That’s what bosses ask. They ask “how” questions and
what they’re really implying is, “Go fix this.”

Never let your mind stop at “how”, but instead think of this
as a triangle. At the top of the triangle is “how” and then I’m going
to move over here to the other side of the triangle, and that question is,
let’s say, “How can I get more leads?” Here’s the “what”
question. “What does the data tell me about customer behavior?” That
is the primary question that you apply to your metrics program. When you apply
that to your metrics program, it’s going to put a lens on so that you can
suddenly see into your data something more important which is the customer
patterns.

For instance, let’s suppose you notice that people are getting on this
page, but they’re not completing the form. Now, I’m oversimplifying. Let’s
suppose you see, “I’ve got great clickthrough from the ads. It looks like
they’re engaging with the page,” but when I get to the form, many of them
start, but don’t complete it. Let’s suppose your data showed you that. You went
from “how” to “what”. “What does the data tell us
about behavior?” That leads you to a “why” question now, and
that completes the triad. The “why” question is, “Why are people
behaving that way?” That typically leads you into the psychology of the
offer.

For these almost 30 years, I’ve been asking, “Why do people say
yes?” To get to the answer, I had to ask a more profound question, and
that is, “Why do people say no?” Because you get a lot of nos before
you get a yes. If I can understand the nos, I can move people up the micro
“yes-chain” to the ultimate “yes” that turns them into a
customer. Always think in terms of– Right now is your website, your
challenges, all your “how” questions.

Listen, as Peter Drucker, my favorite business philosopher said,
“The purpose of a business is to create a customer, and it’s the job of
every single person in the company and it’s the number one job of the
CEO.” The number one way you accomplish that is by crafting a strong value
proposition. The only way you can craft a strong value proposition is to take
the “how”. “How can I create a customer?” And complement it
with a “what” question and then with the “why” question.

This is a big company. This is Aetna’s HealthSpire. If you look on your
left, something happened that changed the control’s performance. Do you see the
treatment? It represents something we call a signal set. You would call it a
web page, but we view it as a signal set. It’s not a page, it’s not a web, it’s
zeros and ones turning on twos in the mind. Look at the results, 638%.

Here’s another. We’re going to move on to another, 166%. This is
another organization. That’s Toll Brothers, huge nationwide builder. That’s
166% conversion rate and that results in 167% increase in leads. Here’s
another, 96%. That’s Fluke by the way. Defense contractor, big organization.
This is another. 1600% increase. Oh, by the way, that’s The New York Times.
These are all part of the research program at MECLABS. PR Newswire, 202%.
Here’s another piece, CBS Sports, 44.5%.

Whether your business is big or small, it is possible to see
exponential impacts if we can understand customer behavior. We can understand
customer behavior if we can get into their behavioral traces. I like to think
of them as brain tracts. Beneath those results, was a deep-dive into the data
to understand how people were thinking and thus how they were behaving. With
that in mind, I’m going to talk with you about a tool that we applied in those
situations to get an increase. That tool was the subject of Episode 2 in our
new series, The Marketer as Philosopher.

In the spreadsheet tool that we downloaded, you’ll see that we’ve found
in one line, a break in patterns. All you need to establish a pattern is a
majority. When I say majority, I mean critical mass occurs in the pattern. This
is pure philosophy. When you’ve reached enough nodes that you can see anything
weighted one direction or another. It’s hard with two, it’s easy with three.
Sometimes three numbers can give me a pattern, but the more numbers, the more
reliable our understanding of that pattern can be.

Look for the broadest threshold you can bring into your pattern
recognition piece. Look over a year instead of over a week. A month is better
than a week. This accounts for seasonality also. That’s a technical answer to a
technical question, but I’m going to keep trying.

Matt, just go into your experience and tell us what you think about
that.

Matthew Klein: We’ve
done data analysis as short as just a few weeks even. We’ve done data analysis
as much as three years. It’s somewhat contingent on the organization. Generally
speaking, if you do experience any type of monthly seasonality, it would be
helpful to have more than one year’s worth of data. 12 months of data is a
really good starting place. You also have to account for– This is a really
important consideration for any kind of timeline amount of data. You have to
consider for any significant changes that may have happened either in your
organization, with your ideal prospect, or within your website.

Let’s just say I take 12 months of data, but six months ago, I
redesigned my website. I’m only going to have really six months’ worth of
relevant data to inform how customers are behaving or interacting with my
current website. There’s no golden rule in terms of the amount of data. It’s
really contingent on how the uniqueness of your business as well as the things
that you may have done, which may have caused changes in your data.

What you’re really trying to capture in your data analysis is a
representative sample of customer behavior over time so that you can start to
predict if based on what I’m seeing in the data, this is how my customer is
behaving with my website right now. You want to be able to analyze that over,
let’s just say periods of seasonality, whether that be weekly seasonality,
monthly seasonality, et cetera. Does that make sense?

Flint: I
think it’s a great answer. Philosophically, the foundation of data analysis
comes from one sort of thinking skill, that is comparison. If you’re comparing
future performance with previous performance, any of those different items
you’re comparing these elements, they determine really how long that data needs
to be. That’s the philosophical answer. Matt gave you the very practical
answer, and I hope that helps you with that question.

We’re going to charge double, and double times nothing is nothing
Michael, but still, [chuckles] that’s probably what the advice is worth.

[laughter]

Michael: Really,
you clarified the fact because I had seen some other people had asked questions
about if you have a minimal amount of traffic, what constitutes a pattern as
opposed to just a new one?

Flint: Good.
It’s a great question, Michael. If you see Episode 2, you’ll actually see us.
We will highlight the numbers and we’ll show you the pattern and then we show
you where we found the missing money. Hopefully, that will help.

Dani, go ahead. Take over.

Danitza Dragovic: We actually do have a version of the tool that’s a bit more simplified
that you can download from Google Analytics solution gallery. It’s under
marketing experiments. For some of the more simpler data polls, you can just
download that tool. You don’t have to actually plugin manually. There’s some
instances where there’s some more difficulty if you’re making custom funnels and
things like that where you would actually want to go into GA and make custom
segments for those. For the funnel itself, that won’t be automatic but most of
the pages can be.

Flint: Dani
thus is telling you, she’s created a template sort of tool inside of GA that
you can use to pull your data automatically.

“Do I have a concern about the quality of data?” I run two
metrics programs. Somebody asked that question. Matt, what do you think people
should do to make certain the quality of their data is right? We can certify it
for you if you need extra help and you want our scientist to– If you want to
use the tool and say, “Did I get it right?” you can talk to us about
that, but other than that, I’m going to ask Dani or Matt to answer that. Which
one wants to go first to answer that question?

Matthew: Sure,
I can answer it.

Flint: Okay,
Matt. Go ahead.

Matthew: The
first thing that I would do if I was looking at a data platform for quality is,
this is incredibly basic, but does it pass the sniff test? Is there something
in there that is just either completely implausible or highly unlikely? That
would hint to a potential quality issue. I do believe that, as Flint mentioned,
having a second tool is often very helpful to do so. You can also potentially–
If you do have a testing tool, you can also run what we call dual control tests
that may be able to validate or invalidate that your metrics are tracking
correctly.

Flint: Matt,
can I jump in there?

Matthew: Absolutely.

Flint: I
want to point out what Matt has said is very important. Everybody should do
this. If you have a testing tool, run a “A versus B” test but keep
the pages the same. Watch and see if you see a big disparity in conversion.
When he says a dual control, just to be clear to everyone here, that means
testing the same page against itself. You have an A and you have a B and at the
end of the test, you’re looking without saying, “Well, that number should
be very close or there’s something wrong with your metric set up.” Matt,
do you want to add to that anything or Dani? Add to that anything? Nope?

Danitza: I
completely agree. Always having a second platform is enormously helpful just so
you can see it. Usually, there is going to be a little bit of discrepancy, but
if there’s a gap, you know there’s something wrong right away.

Flint: Dani,
what is the average discrepancy you see? When you say a second platform, maybe
you have an expensive– Maybe you’re using one of the Adobe. It doesn’t hurt to
have Google running on the side especially an expensive version where you can
compare page metrics and key metrics and see how close are they. What do we say
on average is a disparity when we run two tools? Dani, I have a number in my
head, but I want to hear what you say.

Danitza: If
there going to be a big disparity and then you know there’s something wrong,
but a small disparity would probably be– A regular one would probably be about
5%.

Flint: Yes,
about 5%. The same number I have. All right. If you’re in 5%, you’re probably
in the right zone. Now, I’m out of time. Matt, you want to say something?

Matthew: Yes.
Sorry, I was just going to– One final thing related to quality of data. You
can also audit your digital data with comparable metrics offline as well. If
you’re driving let’s just say leads and you’re capturing leads in a CRM, audit
what you’re seeing in your CRM with what you’re getting in your analytics
platform to make sure that your conversion metric is accurate. Phone calls or
any number of data as well, orders even, if you’re an e-commerce store.

Flint: I’m
going to show you what you should be doing on your wall. Everybody, learn from
this. See the funnel? It’s not just numbers. It’s written here. See it’s in the
spreadsheet. You want to take those screenshots and put them in there. Now, if
I were running your business or you said, “Can you help us with our
organization?” I would put poster-size versions of that on my wall and I
would write the conversion rate on there every day or every week depending on
how much you see change in fluctuation and on each step through the funnel and
then final conversion. When it change, forget all this fancy technology.

Go up there with your pen, mark through the number, write the change on
there, and note the difference. You should be monitoring that number always. By
monitoring that number, you’re able to adapt and adjust to changes. Candidly, a
marketing department should be living around that number because that’s going
to drive results for them. Make your walls talk. Don’t underestimate the power
of big visuals.

Marketing is missing its way. Right now, understanding how to get the
data right, and then understanding how to get the message right, and then
understanding the value proposition, that’s all coming up in this series. It’s
an opportunity for us not just to learn but we can come alongside of Teresa and
rescue 3,500 small businesses.

The post Data Pattern Analysis: Learn from a coaching session with Flint McGlaughlin appeared first on MarketingExperiments.

Who else loves

How would you translate your company’s data and analytics
into a step-by-step plan to grow the business? Where is your company’s most
significant conversion opportunity? Can you detect any intriguing patterns in
your company’s metrics?

To help you organize your data, pinpoint funnel leaks and increase conversion, MarketingExperiments held a live, interactive coaching session with Flint McGlaughlin, CEO and Managing Director, MECLABS Institute.

This first-ever coaching session from MarketingExperiments focused on practical application of a methodology to help you get more value from your data. Participants from around the globe interacted with MECLABS Institute’s CEO and Managing Director Flint McGlaughlin, Director of Research Services Matthew Klein and Director of Hypotheses Development Danitza Dragovic to discuss specific data challenges, ask questions about the lessons taught in The Marketer as Philosopher Episode 2, and get direct help in using the free Data Pattern Analysis Tool to increase conversion.

See below for specific questions that were addressed, along with time stamps in the video for those questions, if you would like to jump to a specific topic that addresses your immediate needs.

  • 00:20 What you will get in this series
  • 00:44 How can I simplify the way I view my data?
  • 3:33 Can I really use the DPA to drive major conversion increases?
  • 5:25 How many numbers do I need before I can detect a pattern?
  • 6:22 What period of time should I use for data analysis?
  • 8:47 How can I recognize a meaningful pattern?
  • 9:25 How can I get my data out of Google and into the DPA tool?
  • 10:15 How do I ensure that the data is accurate?
  • 13:42 Why do you insist on visualizing the conversion journey?
  • 14:47 Marketing is missing its way…

Watch the edited, condensed replay of the coaching session now to simplify the way you view and use your company’s data.

Related Resources

If you need help filling out the Data Pattern Analysis Tool or would like to have a MECLABS Scientist certify your data, email our sciences team directly with this link: Have a MECLABS Scientist Certify My Data

The Marketer as Philosopher Episode 2 — The Data Pattern Analysis: 3 ways to turn info into insight

MECLABS Data Pattern Analysis Template

How To Model Your Customer’s Mind Toolkit

Google Analytics Solution — MECLABS Simplified Data Pattern Analysis Template

Transcript

This transcript provided by GoTranscript:

Flint McGlaughlin: In this series, we’re going to give you a complete set of tools that
we’ve developed in our research program over the last 20 years. For those of
you that are new, we conducted 20,000 experiments. We invested $130
million-plus into a research program to answer a single question. “Why do
people say yes?”

Karen asked such a good question. I want to share something that I’ll
be teaching in future episodes, but this is a coaching session. All of you
should think about your conversion and your data by using a tool we call the
discovery triad. When you as a leader or your boss comes in and ask a
“how” question, for instance, “How can I get more sales? How can
we increase revenue? How can we get more subscribers? How can we generate more
leads?” That’s what bosses ask. They ask “how” questions and
what they’re really implying is, “Go fix this.”

Never let your mind stop at “how”, but instead think of this
as a triangle. At the top of the triangle is “how” and then I’m going
to move over here to the other side of the triangle, and that question is,
let’s say, “How can I get more leads?” Here’s the “what”
question. “What does the data tell me about customer behavior?” That
is the primary question that you apply to your metrics program. When you apply
that to your metrics program, it’s going to put a lens on so that you can
suddenly see into your data something more important which is the customer
patterns.

For instance, let’s suppose you notice that people are getting on this
page, but they’re not completing the form. Now, I’m oversimplifying. Let’s
suppose you see, “I’ve got great clickthrough from the ads. It looks like
they’re engaging with the page,” but when I get to the form, many of them
start, but don’t complete it. Let’s suppose your data showed you that. You went
from “how” to “what”. “What does the data tell us
about behavior?” That leads you to a “why” question now, and
that completes the triad. The “why” question is, “Why are people
behaving that way?” That typically leads you into the psychology of the
offer.

For these almost 30 years, I’ve been asking, “Why do people say
yes?” To get to the answer, I had to ask a more profound question, and
that is, “Why do people say no?” Because you get a lot of nos before
you get a yes. If I can understand the nos, I can move people up the micro
“yes-chain” to the ultimate “yes” that turns them into a
customer. Always think in terms of– Right now is your website, your
challenges, all your “how” questions.

Listen, as Peter Drucker, my favorite business philosopher said,
“The purpose of a business is to create a customer, and it’s the job of
every single person in the company and it’s the number one job of the
CEO.” The number one way you accomplish that is by crafting a strong value
proposition. The only way you can craft a strong value proposition is to take
the “how”. “How can I create a customer?” And complement it
with a “what” question and then with the “why” question.

This is a big company. This is Aetna’s HealthSpire. If you look on your
left, something happened that changed the control’s performance. Do you see the
treatment? It represents something we call a signal set. You would call it a
web page, but we view it as a signal set. It’s not a page, it’s not a web, it’s
zeros and ones turning on twos in the mind. Look at the results, 638%.

Here’s another. We’re going to move on to another, 166%. This is
another organization. That’s Toll Brothers, huge nationwide builder. That’s
166% conversion rate and that results in 167% increase in leads. Here’s
another, 96%. That’s Fluke by the way. Defense contractor, big organization.
This is another. 1600% increase. Oh, by the way, that’s The New York Times.
These are all part of the research program at MECLABS. PR Newswire, 202%.
Here’s another piece, CBS Sports, 44.5%.

Whether your business is big or small, it is possible to see
exponential impacts if we can understand customer behavior. We can understand
customer behavior if we can get into their behavioral traces. I like to think
of them as brain tracts. Beneath those results, was a deep-dive into the data
to understand how people were thinking and thus how they were behaving. With
that in mind, I’m going to talk with you about a tool that we applied in those
situations to get an increase. That tool was the subject of Episode 2 in our
new series, The Marketer as Philosopher.

In the spreadsheet tool that we downloaded, you’ll see that we’ve found
in one line, a break in patterns. All you need to establish a pattern is a
majority. When I say majority, I mean critical mass occurs in the pattern. This
is pure philosophy. When you’ve reached enough nodes that you can see anything
weighted one direction or another. It’s hard with two, it’s easy with three.
Sometimes three numbers can give me a pattern, but the more numbers, the more
reliable our understanding of that pattern can be.

Look for the broadest threshold you can bring into your pattern
recognition piece. Look over a year instead of over a week. A month is better
than a week. This accounts for seasonality also. That’s a technical answer to a
technical question, but I’m going to keep trying.

Matt, just go into your experience and tell us what you think about
that.

Matthew Klein: We’ve
done data analysis as short as just a few weeks even. We’ve done data analysis
as much as three years. It’s somewhat contingent on the organization. Generally
speaking, if you do experience any type of monthly seasonality, it would be
helpful to have more than one year’s worth of data. 12 months of data is a
really good starting place. You also have to account for– This is a really
important consideration for any kind of timeline amount of data. You have to
consider for any significant changes that may have happened either in your
organization, with your ideal prospect, or within your website.

Let’s just say I take 12 months of data, but six months ago, I
redesigned my website. I’m only going to have really six months’ worth of
relevant data to inform how customers are behaving or interacting with my
current website. There’s no golden rule in terms of the amount of data. It’s
really contingent on how the uniqueness of your business as well as the things
that you may have done, which may have caused changes in your data.

What you’re really trying to capture in your data analysis is a
representative sample of customer behavior over time so that you can start to
predict if based on what I’m seeing in the data, this is how my customer is
behaving with my website right now. You want to be able to analyze that over,
let’s just say periods of seasonality, whether that be weekly seasonality,
monthly seasonality, et cetera. Does that make sense?

Flint: I
think it’s a great answer. Philosophically, the foundation of data analysis
comes from one sort of thinking skill, that is comparison. If you’re comparing
future performance with previous performance, any of those different items
you’re comparing these elements, they determine really how long that data needs
to be. That’s the philosophical answer. Matt gave you the very practical
answer, and I hope that helps you with that question.

We’re going to charge double, and double times nothing is nothing
Michael, but still, [chuckles] that’s probably what the advice is worth.

[laughter]

Michael: Really,
you clarified the fact because I had seen some other people had asked questions
about if you have a minimal amount of traffic, what constitutes a pattern as
opposed to just a new one?

Flint: Good.
It’s a great question, Michael. If you see Episode 2, you’ll actually see us.
We will highlight the numbers and we’ll show you the pattern and then we show
you where we found the missing money. Hopefully, that will help.

Dani, go ahead. Take over.

Danitza Dragovic: We actually do have a version of the tool that’s a bit more simplified
that you can download from Google Analytics solution gallery. It’s under
marketing experiments. For some of the more simpler data polls, you can just
download that tool. You don’t have to actually plugin manually. There’s some
instances where there’s some more difficulty if you’re making custom funnels and
things like that where you would actually want to go into GA and make custom
segments for those. For the funnel itself, that won’t be automatic but most of
the pages can be.

Flint: Dani
thus is telling you, she’s created a template sort of tool inside of GA that
you can use to pull your data automatically.

“Do I have a concern about the quality of data?” I run two
metrics programs. Somebody asked that question. Matt, what do you think people
should do to make certain the quality of their data is right? We can certify it
for you if you need extra help and you want our scientist to– If you want to
use the tool and say, “Did I get it right?” you can talk to us about
that, but other than that, I’m going to ask Dani or Matt to answer that. Which
one wants to go first to answer that question?

Matthew: Sure,
I can answer it.

Flint: Okay,
Matt. Go ahead.

Matthew: The
first thing that I would do if I was looking at a data platform for quality is,
this is incredibly basic, but does it pass the sniff test? Is there something
in there that is just either completely implausible or highly unlikely? That
would hint to a potential quality issue. I do believe that, as Flint mentioned,
having a second tool is often very helpful to do so. You can also potentially–
If you do have a testing tool, you can also run what we call dual control tests
that may be able to validate or invalidate that your metrics are tracking
correctly.

Flint: Matt,
can I jump in there?

Matthew: Absolutely.

Flint: I
want to point out what Matt has said is very important. Everybody should do
this. If you have a testing tool, run a “A versus B” test but keep
the pages the same. Watch and see if you see a big disparity in conversion.
When he says a dual control, just to be clear to everyone here, that means
testing the same page against itself. You have an A and you have a B and at the
end of the test, you’re looking without saying, “Well, that number should
be very close or there’s something wrong with your metric set up.” Matt,
do you want to add to that anything or Dani? Add to that anything? Nope?

Danitza: I
completely agree. Always having a second platform is enormously helpful just so
you can see it. Usually, there is going to be a little bit of discrepancy, but
if there’s a gap, you know there’s something wrong right away.

Flint: Dani,
what is the average discrepancy you see? When you say a second platform, maybe
you have an expensive– Maybe you’re using one of the Adobe. It doesn’t hurt to
have Google running on the side especially an expensive version where you can
compare page metrics and key metrics and see how close are they. What do we say
on average is a disparity when we run two tools? Dani, I have a number in my
head, but I want to hear what you say.

Danitza: If
there going to be a big disparity and then you know there’s something wrong,
but a small disparity would probably be– A regular one would probably be about
5%.

Flint: Yes,
about 5%. The same number I have. All right. If you’re in 5%, you’re probably
in the right zone. Now, I’m out of time. Matt, you want to say something?

Matthew: Yes.
Sorry, I was just going to– One final thing related to quality of data. You
can also audit your digital data with comparable metrics offline as well. If
you’re driving let’s just say leads and you’re capturing leads in a CRM, audit
what you’re seeing in your CRM with what you’re getting in your analytics
platform to make sure that your conversion metric is accurate. Phone calls or
any number of data as well, orders even, if you’re an e-commerce store.

Flint: I’m
going to show you what you should be doing on your wall. Everybody, learn from
this. See the funnel? It’s not just numbers. It’s written here. See it’s in the
spreadsheet. You want to take those screenshots and put them in there. Now, if
I were running your business or you said, “Can you help us with our
organization?” I would put poster-size versions of that on my wall and I
would write the conversion rate on there every day or every week depending on
how much you see change in fluctuation and on each step through the funnel and
then final conversion. When it change, forget all this fancy technology.

Go up there with your pen, mark through the number, write the change on
there, and note the difference. You should be monitoring that number always. By
monitoring that number, you’re able to adapt and adjust to changes. Candidly, a
marketing department should be living around that number because that’s going
to drive results for them. Make your walls talk. Don’t underestimate the power
of big visuals.

Marketing is missing its way. Right now, understanding how to get the
data right, and then understanding how to get the message right, and then
understanding the value proposition, that’s all coming up in this series. It’s
an opportunity for us not just to learn but we can come alongside of Teresa and
rescue 3,500 small businesses.

The post Data Pattern Analysis: Learn from a coaching session with Flint McGlaughlin appeared first on MarketingExperiments.

love the post

1 – 2 p.m. EDT
Thursday, August 20th
Zoom

How would you translate your company’s data and analytics
into a step-by-step plan to grow the business? Where is your company’s most
significant conversion opportunity? Can you detect any intriguing patterns in
your company’s metrics?

To help you organize your data, pinpoint funnel leaks and increase conversion, MarketingExperiments will be holding a live, interactive coaching session with Flint McGlaughlin, CEO and Managing Director, MECLABS Institute.

This first-ever coaching session from MarketingExperiments focuses on practical application of a methodology to help you get more value from your data. You have the opportunity to interact with McGlaughlin and a MECLABS data scientist to discuss your specific data challenges, ask questions about the lessons taught in The Marketer as Philosopher: Episode 2, and get direct help in using the free Data Pattern Analysis Tool to increase your company’s conversion.

In this question-and-answer session, you will learn how to:

  • Set up and use the Data Pattern Analysis Tool
  • Simplify your data with three key dials
  • Apply the principles of The Marketer as Philosopher: Episode 2 to your own company

Due to the intimate, interactive nature of this live
coaching, this session is limited to the first 30 attendees.

There is no charge to attend. To receive your Zoom
invitation, simply use the form on this page to register for this Q&A
session and receive helpful content from MarketingExperiments.

The post Live Coaching Session with Flint McGlaughlin: The Data Pattern Analysis, 3 ways to turn info into insight appeared first on MarketingExperiments.

anyone like as much as us

Data-driven marketing has become an increasingly popular topic in the marketing industry. But it’s as easy to be overwhelmed by data as it is to utilize it to drive your marketing.

In Episode 2 of The Marketer as Philosopher: Become a Force for the Good, Flint McGlaughlin teaches how you can transform your data into wisdom. The CEO and Managing Director of MECLABS Institute (parent organization of MarketingExperiments) teaches viewers how to

  • Use a simple but powerful spreadsheet tool that will help you tame your metrics (click here to download your free Data Pattern Analysis tool)
  • Simplify your marketing goals with just three ratios that any marketer can understand
  • Treat these ratios as dials you can turn in the right combination and order to unlock transformational results

McGlaughlin uses real-world data from TenbyThree© — a unique nonprofit that sells products — to illustrate these points with a specific example. Since the organization is a nonprofit, it has allowed transparent sharing of its journey to increase sales. While engaging with the show, any insights you add that help to increase sales for Ten by Three will also do good by helping to reduce poverty for artisans throughout the world.

Here are some key points in the video:

  • 3:47 An explanation of the math equation that powers the DPA tool
  • 8:34 Four ways to tame your data
  • 15:23 Maximize your ROI with this heuristic. Notice the importance of the ORDER of activities.
  • 16:47 How to extract the predictive power of your data
  • 20:04 Real-world Example: MECLABS analysts determined where revenue is being lost in TenbyThree’s nonprofit business using the DPA tool. Hint: We detected a problem in the psychology of the messaging on the product tags.
  • 20:59 Now that the location of a major funnel leak has been identified, in the next episode we invite you to participate with us in optimizing the product tag to help plug the leak.
  • 23:55 Three ways you can help…

Related Resources

Data Pattern Analysis Tool — Free spreadsheet tool to help you tame your metrics

Infographic – Visual summary of the teachings from this
video will be available soon

The
Marketer as Philosopher, Episode 1: Become a Force for the Good

5
Marketing Lessons From a Unique Nonprofit That Sells Products (and why the
world needs marketers today more than ever)

The Marketer as Philosopher: 40 Brief Reflections on the Power of Your Value Proposition

How to Model Your Customer’s Mind: 60 pages of essential
tools and charts

– Download this free tool to see how you can leverage data to better understand
and serve your customer so you can achieve better results.

Examples
of Using Data to Become a Force for the Good

Get
Your Free Test Discovery Tool to Help Log all the Results and Discoveries from
Your Company’s Marketing Tests

What
is Data? A discussion about getting value from your marketing analytics

Ecommerce
Research Chart: The value of analytics and data

What
You Can Learn about Automated Personalization from Google’s Hilarious Mistake

A
Simple Guide for the Busy Marketer: Using data from online marketing and web
analytics tools

Data
Analysis 101: How a nonprofit used data to secure a critical business decision
and help find 125 missing children

The
Behind-the-scenes Story of How We Optimized Outdoor Advertising That Was
Featured in a USA Today Article

MECLABS
Conversion Sequence Heuristic
– Review the conversion heuristic to prepare
for Episode 3


Sign up for the free MarketingExperiments newsletter to get notified when each episode goes live.

Transcript

This transcript provided by GoTranscript:

Flint McGlaughlin: How would you translate this data into a step-by-step plan to grow the
business? Do you see any clues in this column? Where is the most significant
conversion opportunity? Can you detect any intriguing patterns? What about this
product tag? If the goal is to get you to visit the website how would you
improve its performance? How do these three numbers connect?

[music]

Flint: That
number is absurdly low.

Dani: You and I both.

Flint: The
answer to how is why.

[laughter]

Flint: We would achieve a triple win; high traffic, higher conversion, higher average customer spend. Marketer how can you transform your data into wisdom? How do we keep from being overwhelmed by the deluge of information flowing into our analytics program? Could there be powerful practical insights hiding in the undetected patterns of our silos reports. My name is Flint. This is episode two of our new series The Marketer as Philosopher, Become a force for the good.

In episode two we’re going to learn how to discover hidden opportunity
within our data. First, we’re going to give you, at no cost, a simple but
powerful spreadsheet tool that will help you tame your metrics. Next, you’re
going to learn to simplify your marketing with just three ratios. We call them
the three data dials. By the way, you don’t have to be a mathematician to
understand or use it. Three, you’re going to learn how to turn these dials in
the right combination and in the right order to unlock transformation results.

This requires us to reflect on three powerful insights. Let’s begin
with insight one. In data analysis, the way forward is back. It is 4:00 PM on a
Monday afternoon. The world is in crisis and so like many others, our meetings
are being conducted via video conference. It’s important to get to that
simplicity on the other side of complexity.

Dani: You and I both. [laughs] …

[laughter]

Theresa: All of the orders backed up. All of these just came in …

[laughter]

Flint: You’re muted Dani. You’re muted. Analysts from the MECLABS team are meeting with Theresa Carrington, the founder of Ten by Three. We are discussing the first in a series of tools that will be applied to Theresa’s challenge. This is the data pattern analysis, the DPA. It consists of at least a dozen tabs derived from data within Theresa’s metrics platform. All of this data was automatically imported from Google Analytics. There are a number of tabs but the two most important are the Funnel Analysis and the Three Data Dials. Marketer to help Theresa you’re going to learn how to think about your craft like a philosopher beneath your assumptions in reverse order from your revenue target back through your customer data then even further back into the heart of your message.

Speaker 3: We
engage past purchasers and get people to return to the site.

Dani: These are initially some of the pages that we’ll look at for initial testing.

Flint: If we
can turn these dials we can turn up your sales. We must capture the clarity of
the three data dials. Before we show you the dials in action we need to show
you a very simple math equation that powers their insights. You’ll notice RV=SU
x CR x AOV. RV is revenue. SU is select users, that’s the number of people who
encounter the opportunity. That definition is important when we test. CR is the
conversion rate, that’s the number of people who say yes. Average order value
that is the average customer spend.

The best way to learn the raw power of this simple equation is to push
it to extremes. Here’s a very simple example. If our revenue target is $50,000
then one person visits our site and they purchase a product for $50,000. You
can see that our conversion rate’s 100%. Our SU is 1 and our AOV is $50,000.
Now we all know that this scenario is unlikely so let’s take it further. By the
way, if you’re a mathematician and you say, “I’m bored with this. I know
about this,” stay with me. Before this episode is over we’re going to be
delving the data deeply for patterns.

Here is another example. If you had two people visit and your average
order value remained at $50,000. What would you need for a conversion rate? If
both people who visit and said yes you would have $100,000. That’s two times
your goal. It would only take one of those two people to buy. Only one of those
two people to say yes. The answer is 50%.

Here’s one more scenario. What if you had an average order value of $50
and a conversion rate of 10%. How many visits would you need? We’re solving for
SU. To get to $50,000 total with an average order value of 50 you would need
1,000 yeses. That’s 1,000 times 50. If 1 out of 10 people who encounter the
opportunity say yes, that’s 10% then you would need 10,000 users.

By the way, the three data dial does all of this calculation for you
and it helps you chart a critical path. Keep in mind that while we’ve used this
tool in very simple situations with startups we’ve used it with Fortune 10
companies. I’ve used it with one organization whose revenue was $138 billion.
We prioritized and exceeded our budget goals by carefully following the logic
that’s implied, that’s built-in to the simplicity of this tool. Stay with me.

Here is how it works. There are three dials. You should already be
familiar with the SU, the CR, and the AOV. Select users, conversion rate, and
average order. However, any change here is reflected in the incremental revenue
gains that you see at the top both annually and monthly. This is powerful
because it allows you to move those three ratios in combination to achieve the
most likely and most profitable way forward.

There is a basic calculation here for overall conversion and then for
more advanced work, there’s a calculation for step by step conversion. That is
improvements in each stage of the funnel. We’ve seen how the DPA works but how
can we use it to solve the financial challenges of Ten by Three? What does it
look like in practical application? How can we use it to prioritize our work
over the next several episodes?

These questions bring us to the next insight. Insight two: opportunity
is discovered through limitations. What am I saying? This statement seems
counterintuitive. What does it mean? The answer will become clear in the next
five minutes. Let’s look at this DPA with the actual Ten by Three numbers. We
know our goal is $100,000 but we’ve left that blank. We’re going to exceed that
by spinning the dials. We know that the current monthly traffic is 1,351,
that’s SU. We know that conversion rate is 1.27%. We know the average order
value is $112. Now, we understand these basic numbers, our task is to find the
optimal path forward. This task demands relentless prioritization. This
prioritization requires perspicuous clarity. This clarity requires a four-step
analysis.

Throughout this series, we’re going to be helping Theresa and then teaching you transferable principles. Here are four that you should be applying right now to your own data. First of all, define the practical range of your dials, that is, separate the improbable from the possible. Number three, adjust your goals to the optimal settings. You’re going to see that power very soon. It’s remarkable. Number four, sequence your improvements for the highest impact. Now let’s apply principles one and two. What is the practical range of the three dials? How can we separate the improbable from the possible?

Average order value is $112. We have tested more than 20,000
treatments. From that experience, I’m going to suggest that it’s not likely
that this number could increase by more than 50% without changing the business
model. Achieving that gain would be difficult but what is the impact if we did?
This is where the DPA becomes so valuable. We plug in an increase. The range is
from $112 to $168 but we can see the maximum impact is only $11,000. We need
$100,000.

Let’s look at conversion. Conversion is 1.27%. Once again, experience
suggests that for an e-commerce site one would rarely see this number increase
by more than 100% and that would be a remarkable success. What is the impact if
we did? Again, in the DPA, we can see our range is from 1.27% to 2.54% but the
total impact, that’s if we maximize the dial is only $23,216. It’s not enough.
SU is 1,351. That’s 1,351 visits per month. Very low. This number could grow
exponentially. It could grow a hundredfold. It could grow more. It would be
hard but it would be possible.

Let’s follow the impact with the tool. We turn that dial. Our range is
1,351 to 14,858. What is the impact? $232,000 plus. Marketer, something should
start to emerge in your mind. What can we learn from this? Which of the three
ratios is holding us back? Which dial do we turn the most? If you answered
select users, traffic, then you are correct. You have separated the improbable
from the possible. With a big enough budget, you could buy a tenfold traffic
increase, and we don’t have that budget. Yet all the money in the world might
not be able to buy a tenfold conversion increase. Does this mean conversion is
important? It is incredibly important. We’re going to see. It does suggest that
we need to be realistic about how we turn the dials, how we set them for the
right combination. We need to be realistic so that we can chart the best path
forward. I’m going to share with you that optimal setting but before I do, I
want to take a break from the math.

It’s important to me that every marketer, whether you specialize in the
creative or you specialize in the analysis, that every marketer who wants to
make a difference can follow along and see how their talent can be applied.
Right now, I can tell you that before this episode is over, we’re going to
discover why the question I’m asking next could make all the difference for
thousands of families. There is.

I’m holding up a basket in my hand. Attached to is a product tag, a
label. Let’s assume the goal of this tag is to get people to visit the website
and connect with the artists. Marketer, what would you do to improve the
performance of this tag? Would you change the photograph? Would you change the
color? Would you change something about the call to action? Let’s go back to
three dials. How should we adjust our goals in view of the optimal settings?
Now, this is where we establish a framework to guide all of your marketing
activities. I’m going to take a very conserved approach. I’m going to suggest
that we only improve Average Order Value by 20% and Conversion by 25%. I
believe that number can be higher. Traffic is set for 500%. If that seems high,
remember the traffic is very low, so it doesn’t take very much to create a
boost there.

In the right combination, we can see the impact on the financial
picture. Look at it. This puts us on track to exceed our goal of $100,000 by
$85,000. That is a healthy margin of error and more, if we fall short we can
spin one of the other dials to make up for it. For example, if we couldn’t
increase Average Order Value but we could increase Conversion, you might see
this. We hit the same number by simply adjusting the mix of the dials. As
simple as this might be for those of you that are experienced marketers in big
organizations, its clarity can guide every aspect of your resource planning.

We have to do it now so that we can guide our resources and plan the
next several weeks together so that we can help Theresa rescue these 3,500
small businesses. Watch us do it and help us do it. Not only will you learn,
but you’ll be making a major difference all over the world. In this way, you
adjust your ratios to dialing your marketing performance despite the inevitable
surprises that are sell any plan. It brings us to the fourth principle.

This fourth principle I can only touch lightly but it’s very important.
We learned it after doing an 18-month study. Sequence your improvements for the
highest impact. Now there’s a difference between the urgent and the important.
We have identified what’s important using steps one through three but step four
is about urgency, doing what must be done now. To do that, we can discipline
our activity to produce the highest return if we keep in mind the following
heuristic. Optimize the product in the presentation and in the channel.

Ultimately, you will make more money if you begin by optimizing the
value proposition of the offer, then optimizing the message in your marketing
collateral, and finally, optimizing the spend in your channels. If you do it in
a different order, you’re going to leave a great deal of money on the table.
We’re going to teach you much more about this in upcoming episodes. For now,
let’s admit that while approaching your data with these dials can produce a
central clarity, it does not produce actual sales. How can we translate this
clarity into rewarding results? Are there any hidden patterns in the Ten by
Three data that we could leverage immediately to sell more baskets?

These questions bring us to our final insight in today’s episode. Insight
three, the value of data is limited to its predictive power. It’s now time to
think about how to use other tabs within the DPA to produce impact. While there
are many ways we can achieve an increase in visits and some ways to achieve an
increase in Conversion, there may be a powerful solution for both just hiding
in the data. Challenge yourself with a riddle. Take a look at this table. Where
is the greatest opportunity and why?

Let me give you three principles that will help you extract the
predictive power of the data. Number one, do not seek to optimize webpages;
seek to optimize the sequence of thought. Number two, do not think of data as
digital bits; think of data as behavioral traces, as mind tracks. Number three,
do not look for numbers; look for dissonance in patterns. Please, marketer,
don’t let your attention fade just yet. We’re on the edge of a discovery that
could help rescue 3,500 small businesses. The families that depend upon them
are depending upon us. This is the moment where your powers, your craft can
truly make a difference. We’re about to be surprised. Carefully study the next
clip from Ten by Three. Think about the table we just reviewed and try to find
the connection to elements in this short video.

Theresa: When
you watch the exchanges, they’re quite powerful. To see that human-to-human
connection, it’s getting to know one another on a human level. It’s how the
world change us.

African Woman 1: I was filled with so much love and beauty. [foreign language] I had to
purchase it.

Theresa: Oh,
you have a beautiful smile.

African Woman 2: [chuckles]

Theresa: When
the women get their picture taken, it is also a very remarkable and very moving
moment because, in many cases, it is the first time their picture has ever been
taken. It’s the first time that they’ve ever seen a digital image of
themselves.

Flint: Now,
consider these numbers from the DPA. Remember, we’re looking for dissonance.
For the 15-month period analyzed in the DPA, total website traffic is 20,261.
Total number of units sold through all channels is 59,817. Hold on a moment.
Something should already be puzzling you. Pay close attention, we’re close to
breakthrough insights. Total number of units sold on the website is just 1,280.
It is when you look on the top pages tab of the DPA that we can start to detect
dissonance in the patterns. In just two minutes of math, we’re going to find
something that could transform this entire operation. Stay close now. Pay close
attention.

The total number of visits to the artisan-lookup is 1,059. Can you
detect the dissonance? The answer to how is why? How can we drive more traffic?
How can we improve Conversion? How can we improve Average Customer Spend? Let’s
start with the why. Why is that number so low? Why are people behaving in that
way? Think about it. Here’s a simple subtraction problem to help clarify.
59,817, that’s total baskets sold, minus 1,280, that’s total basket sold on the
website. The answer is 58,537. Wait a second. Ten by Three sold 58,537 units
through their network of stores. That is 58,537 product tags that could be used
to get people to visit the website to look up the artists and who created the
product and interact and connect. Yet, wait for it, here’s the hidden
opportunity. Only 1,059 people visited the artisan-lookup page. That number is
absurdly low. Why is this so important? Because it’s also an absurdly rich
opportunity for you and I to make a difference.

If we start with this pattern dissonance and follow the mind tracks
back to the customer, we can detect the problem in the psychology of the
message. That can be fixed. Our lab has developed specific heuristics for
discerning the underlying psychology of a message. We’re going to teach those
to you in the next episode. We’re going to help you analyze this message, but
if we could optimize these labels to achieve a higher conversion rate we could
find a major source of free traffic and we could increase average customer
value because some of these people would place additional orders. Moreover, Ten
by Three would win a direct relationship with the customer something they don’t
have when the product’s purchased in a store. We would achieve a triple win.
High traffic, higher conversion, higher average customer spend.

This single insight could help us achieve our goal for Ten by Three. In
fact, you can see the power in these last two or three numbers we need to
review. If we could optimize the product tags so that 20% of the in-store
buyers came to the website and ordered again, we would drive $1,311,329 in new
sales. That’s a lot more than our goal of $100,000. But you say, “I don’t
know if 20% is practical. Let’s cut the number in half.” If we could
optimize the product tag so that 10% of the in-store buyers came to the website
and ordered again, we would drive $656,000 in new sales. You say, “That
seems pretty high,” it doesn’t to me. I’ve done this before, and I’ve
achieved much higher numbers. Let’s go to 5%. If we could optimize the product
tags so that 5% came back and purchased, we would still drive an additional
$327,000 in new sales. In one powerful move, we could solve the Ten by Three
financial challenge. We would achieve a triple lift; conversion, traffic,
average customer spend, and all without investing $1 more in marketing or
advertising.

This is powerful. Marketer, this is where you can truly help. If we
stand together, we can win this revenue for Ten by Three. This is a way for you
to do something meaningful with your special skills. You have more power than
you realize. As we learn together through this series, your power to help
others only grows. As I have said from the beginning, you can learn and you can
help. Here’s what you can do now. We need to optimize this product tag. The
best way to do that is with the MECLABS Conversion Heuristic.

In the next episode, we will teach you step-by-step how to use this
tool, then we’re going to host a live YouTube session where you can share with
us your best thinking. In the meantime, three ways to help. One, we need to
reach critical mass with this program. With that, we’ll have enough people to
solve larger and larger problems, not just for Ten by Three but for other
groups. Please invite at least 10 like-minded marketers to watch the first two
episodes and join this new community. Two, visit this link to learn how to
apply the MECLABS Conversion Heuristic. This will help prepare you to make a
significant contribution during the next episode. It is, of course, free.
Three, visit Ten by Three. Purchase an authentic handcrafted product. Some of
you are already doing so. Theresa called me and said she noticed a small spike
in sales. Let’s give her a big spike in sales. The money will help us meet our
goal and the experience will help you make useful recommendations for improving
the checkout proceeds.

Remember, we are open to any of your ideas on how to drive traffic for
improved performance. Feel free to contact me at my personal email, I read
every one. flint.mcglaughlin@meclabs.com. Here’s what you can learn from this
episode. Download the simplified MECLABS data pattern analysis so that you can
use it to grow your own organization. It is free. It’s distributed under a
Creative Commons Licence. In addition, we have built a large infographic poster
that summarises everything I taught today. You can download it and use it to
keep these principles at the forefront of your thinking.

My name is Flint. Thank you for your trust. We’ll be back with more.

The post <b>The Marketer as Philosopher Episode 2</b><br>The Data Pattern Analysis: 3 ways to turn info into insight appeared first on MarketingExperiments.

anyone love this as much as we do

Data-driven marketing has become an increasingly popular topic in the marketing industry. But it’s as easy to be overwhelmed by data as it is to utilize it to drive your marketing.

In Episode 2 of The Marketer as Philosopher: Become a Force for the Good, Flint McGlaughlin teaches how you can transform your data into wisdom. The CEO and Managing Director of MECLABS Institute (parent organization of MarketingExperiments) teaches viewers how to

  • Use a simple but powerful spreadsheet tool that will help you tame your metrics (click here to download your free Data Pattern Analysis tool)
  • Simplify your marketing goals with just three ratios that any marketer can understand
  • Treat these ratios as dials you can turn in the right combination and order to unlock transformational results

McGlaughlin uses real-world data from TenbyThree© — a unique nonprofit that sells products — to illustrate these points with a specific example. Since the organization is a nonprofit, it has allowed transparent sharing of its journey to increase sales. And since the organization is a nonprofit, any insights you add while engaging with this show that help to increases sales for Ten by Three will also do good by helping to reduce poverty for artisans throughout the world.

Related Resources

Data Pattern Analysis Tool — Free spreadsheet tool to help you tame your metrics

Infographic – Visual summary of the teachings from this
video will be available soon

The
Marketer as Philosopher, Episode 1: Become a Force for the Good

5
Marketing Lessons From a Unique Nonprofit That Sells Products (and why the
world needs marketers today more than ever)

The Marketer as Philosopher: 40 Brief Reflections on the Power of Your Value Proposition

How to Model Your Customer’s Mind: 60 pages of essential
tools and charts

– Download this free tool to see how you can leverage data to better understand
and serve your customer so you can achieve better results.

Examples
of Using Data to Become a Force for the Good

Get
Your Free Test Discovery Tool to Help Log all the Results and Discoveries from
Your Company’s Marketing Tests

What
is Data? A discussion about getting value from your marketing analytics

Ecommerce
Research Chart: The value of analytics and data

What
You Can Learn about Automated Personalization from Google’s Hilarious Mistake

A
Simple Guide for the Busy Marketer: Using data from online marketing and web
analytics tools

Data
Analysis 101: How a nonprofit used data to secure a critical business decision
and help find 125 missing children

The
Behind-the-scenes Story of How We Optimized Outdoor Advertising That Was
Featured in a USA Today Article

MECLABS
Conversion Sequence Heuristic
– Review the conversion heuristic to prepare
for Episode 3


Sign up for the free MarketingExperiments newsletter to get notified when each episode goes live.

The post <b>The Marketer as Philosopher Episode 2</b><br>The Data Pattern Analysis: 3 ways to turn info into insight appeared first on MarketingExperiments.