How to delegate (without dropping the ball)

 

There's a difference between delegating and dumping.(Hint: it's not what you think)

It comes down to 5 letters.

The HANDS method gives you a simple way to pass
things on without losing trust.

Here's what each step can look like in practice:

✦ H — Here's what done looks like
↳ Get aligned on the finish line before anyone starts

✦ A — Agree on when to check in
↳ Set the rhythm before the work begins

✦ N — Name who decides what
↳ Ambiguity is where ownership quietly disappears

✦ D — Decide what to do if it's not right
↳ A plan for imperfection makes it safe to try

✦ S — Sit down and talk about how it went
↳ Where you both learn what to do differently next time

The more you use it, the more you might notice:

⭐ Problems surface early
⭐ Your team comes to you with answers
⭐ Each time, they own a little more of the process

5 letters, each with its own step.

That's where it starts.

Maybe you use all five in order.

Maybe you lean into the one or two your team needs
most right now.

There's no single right way to delegate.

But in my experience, an effective way is the one that helps
your people take real ownership.

Credits to Amy Gibson, make sure to follow!

https://tinyurl.com/4uzsw24s

7 Rules for Building Wealth

 

Many people think wealth is about luck
or the ability to “buy the right stock at the right time.”

It isn’t.

Wealth isn’t built on willpower.
It’s built on systems that work
when you don’t feel like being disciplined.

I’ve seen many high-income professionals
end up with zero net worth.

Not because they didn’t earn enough.
But because their lifestyle grew faster than their income.

The problem isn’t how much you earn.
The problem is how you manage the gap
between income and expenses.

In the infographic below, I break down 7 rules
that turn financial chaos
into a predictable system.

My personal Top 3 from this list:

1. The Automation Rule (Rule 2)
If you have to decide every month to save money,
you’ve already lost.

Wealth runs on processes, not discipline.
Set up automatic transfers on payday.
Make saving invisible.

2. The Pause Rule (Rule 4)
Most impulse purchases are just
attempts to get a quick dopamine hit.

Wait:
• 24 hours for purchases under $500
• 7 days for bigger ones

If the desire fades,
you didn’t need the thing, you needed the emotion.

3. The Rule of 72 (Rule 3)
The most powerful force in finance is time.

Divide 72 by your expected return
to see how many years it takes
for your money to double.

The earlier you start,
the less heavy lifting your money has to do later.

Financial freedom doesn’t start with
what you buy,
but with who you become.

The best ROI will always come from Rule 7
investing in yourself.

Skills are the only asset
inflation can’t take away.

Credit to Natan Mohart follow for more impactful content.

https://tinyurl.com/3uw84vbe

The rooms where people speak

 

People do not stop having ideas.

They stop paying the price of raising them.

That price is set in the room, and it is usually set in the first ninety seconds.

Watch for it. Someone starts with "this might be a stupid question." Someone else gets interrupted at the halfway point of their sentence and does not go back to finish it. The most senior person in the room states a position before anyone else has spoken, and everything that follows is now a response to it rather than a contribution.

Then the real conversation happens in the corridor, and you never hear it.

Psychological safety is not a feeling you generate. It is a structure you design.

Which is where most executive teams get stuck. They try to solve it with warmth. More reassurance, more encouragement, more "there are no bad ideas here." Warmth helps, but it is personality-dependent, so it disappears the moment that leader is not in the room.

Structure does not.

Structure looks like deciding, deliberately, who speaks first, and making it the person with the least positional power. It looks like separating the meeting where ideas are generated from the meeting where they are judged, because the two cannot share a room and both survive. It looks like the leader stating their view last, on purpose, every time.

None of that requires anyone to be braver. That is the point. You should not be running an organisation that needs its junior people to be brave in order for you to hear the truth.

The one change worth making this week is the smallest one. In your next leadership meeting, speak last. Not as a technique. As a standing rule.

What is the last good idea your organisation did not hear, and where in the room did it die?

https://tinyurl.com/2t8knmf9

The SNAP Selling Framework

 

Every buyer makes 3 decisions before they buy.

This framework helps you influence all 3:

SNAP Selling is a great method to adopt.

Jill Konrath developed it for a world where buyers are busy, overloaded and balancing competing priorities.

That feels even more relevant today...

Because before anyone commits to your solution,
they're making three smaller decisions:

1. Will I give you my attention?
2. Is this worth changing for?
3. Can I justify this internally?

The 4 SNAP principles help buyers move through each stage with confidence.

1️⃣ KEEP IT SIMPLE

Make your message easy to understand.
Focus on the problem you solve and the next logical step

2️⃣ BE INVALUABLE

Bring insights that help buyers think differently.
The best conversations leave people feeling smarter than when they joined.

3️⃣ ALWAYS ALIGN

Connect your solution to the goals, priorities, and pressures your buyer is already managing.
Relevance creates momentum.

4️⃣ RAISE PRIORITIES

Help buyers understand why acting now supports their business objectives.
Timing becomes much clearer when the value is clear.

One of the reasons I like this framework is how closely it aligns with great positioning.

When your positioning is clear:

✅ Buyers understand your value faster
✅ Sales conversations become more focused
✅ Internal buy-in becomes easier
✅ Decision-making accelerates

Positioning creates the foundation.
Frameworks like SNAP help your commercial teams build on it.

That's a combination worth investing in!

https://tinyurl.com/3bz7r857

How Marcus Frind built a $800M company with 100 people

You built an $800 million company.

You did it without a single venture dollar.

At the time of sale, you had 100 employees.

Markus Frind didn't get lucky. He just refused to run his company the way everyone told him to.

Here are the five lessons that made the difference:

𝟏. 𝐇𝐢𝐫𝐞 𝐩𝐞𝐨𝐩𝐥𝐞 𝐰𝐡𝐨 𝐚𝐬𝐤 𝐰𝐡𝐲
Frind uses two interview questions. "What is your spirit animal?" and "If someone who likes you, someone who doesn't, and someone neutral each described you in one word, what would they say?"

Half of candidates go blank.

"They're trained for every question under the sun but not for what is your spirit animal."

If someone freezes in a low-stakes interview, they will freeze when it matters.

𝟐. 𝐌𝐨𝐫𝐞 𝐡𝐞𝐚𝐝𝐜𝐨𝐮𝐧𝐭 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐦𝐞𝐚𝐧𝐬 𝐦𝐨𝐫𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬
When you over-hire into specialisms, nobody sees the whole picture. Nobody can kill something that is not working. The team owns the problem instead of the individual, and ownership disappears.

"Headcount is not synonymous with success. It's usually the opposite."

Hiring more people to fix a problem is often just a way of hiding it.

𝟑. 𝐅𝐢𝐯𝐞 𝐭𝐡𝐢𝐧𝐠𝐬 𝐰𝐢𝐥𝐥 𝐦𝐨𝐯𝐞 𝐭𝐡𝐞 𝐧𝐞𝐞𝐝𝐥𝐞 𝐭𝐡𝐢𝐬 𝐲𝐞𝐚𝐫. 𝐓𝐡𝐞 𝐫𝐞𝐬𝐭 𝐢𝐬 𝐧𝐨𝐢𝐬𝐞.
"There's always only five things a year that move the needle. In hindsight they're usually pretty obvious."

List everything you could build. Estimate the gain, estimate the time, rank it, start from the top.

The biggest change Frind ever made took five minutes and generated $50 million. Multi-year engineering projects rarely came close.

𝟒. 𝐘𝐨𝐮𝐫 𝐭𝐞𝐚𝐦 𝐢𝐬 𝐩𝐫𝐨𝐛𝐚𝐛𝐥𝐲 𝐫𝐞𝐩𝐨𝐫𝐭-𝐝𝐫𝐢𝐯𝐞𝐧, 𝐧𝐨𝐭 𝐝𝐚𝐭𝐚-𝐝𝐫𝐢𝐯𝐞𝐧.
Most companies build 200 dashboards and call it analytics. Real data culture means answering a specific question within two hours. A 0.5% drop in engagement traced to the exact minute a deployment went live.

"It's being data-driven, not report-driven. The vast majority of companies are actually report-driven."

𝟓. 𝐏𝐢𝐜𝐤 𝐨𝐧𝐞 𝐦𝐞𝐭𝐫𝐢𝐜 𝐚𝐧𝐝 𝐛𝐮𝐢𝐥𝐝 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐚𝐫𝐨𝐮𝐧𝐝 𝐢𝐭.
From week one, Frind logged one number nightly. Not traffic. Not signups. Distinct senders and receivers of messages per day.

"Distinct senders and receivers was the absolute core metric. I focused the entire product around it."

By acquisition, over a billion messages a month. Started with a manual log in week one.

Most founders track too many things and optimise for none of them.


In 2008, Frind was offered hundreds of millions to sell. He turned it down because he had not yet learned how to lead a team.

He wanted to earn the exit, not just take it.

Most founders would have taken the money.

Source: Markus Frind on A New Wave of Entrepreneurship podcast.

https://tinyurl.com/46cpmhvj

How to set creative constraints

 

Michelangelo carved David from a reject marble block.

Smart builders set tight constraints, not bigger goals.

As creatives, setting constraints can free you up to do your most creative work.

They ask you to step up to the challenge of working within limitations.

🟢 Dr. Seuss wrote Green Eggs and Ham on a bet that he couldn't do it in 50 words.

🛸 George Lucas invented Star Wars because he couldn't get the rights to Flash Gordon.

🎨 Michelangelo had to paint before the fresco medium dried in the Sistine Chapel.

Three constraint ideas you can use today:
1/ Write the press release first
Jump a year ahead. Write the press release you'd want to send when it ships. That's your bounding box.

2/ Pitch three, not one
Pixar's rule: never pitch a single idea. Always pitch three. Your first idea is almost never your best idea.

3/ Cook with three ingredients
If you can cook any meal, you'll cook something you already know. If you can only cook with three ingredients, you'll invent something new.

Constraints feel like the enemy of creativity.
They're the engine of it.

Without them, you explore.
With them, you ship.

One of my constraints in half-year two is fear!
If I'm afraid to do it, then I NEED to do it.
If it doesn't scare me, I don't do it.

That's why I have some big goals to be putting more amazing products in front of my audience.

https://tinyurl.com/27ue8jyz

9 brain tricks marketers use

 

You think you make rational buying decisions.

You don't.

Every price you see.
Every option you compare.
Every "free" gift you accept.

Your brain is being guided.
One quiet decision at a time.

The best marketers know this.
So they build for how people actually think.

Here are the 9 concepts they use to do it:

PERCEPTION

1. The Framing Effect
↳ How you phrase something changes how people perceive it.

2. The Affordability Illusion
↳ Breaking a large number into smaller amounts makes it feel more reasonable.

3. Anchoring Bias
↳ The first price you show will always influence perceived value.

DECISION

4. The Rule of 3
↳ People almost never choose the cheapest option when given a choice of 3.

5. The Contrast Effect
↳ People perceive something as better value when placed next to a more expensive alternative.

6. The Paradox of Choice
↳ Too many options overwhelm buyers and lead to indecision.

OWNERSHIP

7. The IKEA Effect
↳ People value things more when they contribute effort.

8. The Power of Free
↳ People overvalue things that are free, even if they don't need them.

9. The Endowment Effect
↳ People value things more once they own them (or feel ownership).

These are the concepts that turn browsers into buyers.

Not by tricking people.
By making the right choice feel like the natural one.

Learn them once.
And you'll spot them everywhere.

Which of these are you already using?

https://tinyurl.com/36xd9jpe

Tips for Great Product Ideas

 

Great product ideas rarely appear out of nowhere.

They usually come from paying closer attention:

Most people think they need to wait for inspiration before they can build something worth selling.

The opposite is usually true.

The best ideas come from following a repeatable process.

Not from hoping for a lucky breakthrough.

Start by getting every idea out of your head.

Pick one topic.

Set a timer for two minutes.

Write continuously without judging or editing.

Quantity matters first.

Quality comes later.

Next, combine what you already know.

List three skills you have.

Three problems people regularly face.

Three formats you could create.

Mix them together.

Suddenly one idea becomes dozens of possibilities.

Before getting attached to any idea, validate it.

Search for it.

Type it into Google with words like "how to."

Notice what people are asking.

The more questions you find, the stronger the demand often is.

Another simple exercise is reading reviews.

Visit a product or book people already buy.

Look for repeated complaints.

Every complaint is a potential opportunity.

If many people struggle with the same thing, solving it becomes much easier.

Don't stop after finding your first idea.

Write ten.

Then score each one.

Ask yourself two simple questions:

How excited are we to create it?

How valuable would it be for someone else?

The highest combined score deserves your attention.

Sometimes the best ideas sound strange at first.

Give yourself permission to explore unusual combinations.

Many successful products started as ideas that looked unconventional until someone tested them.

When you've collected enough possibilities, group similar ideas together.

Patterns begin to appear.

You'll usually notice one concept that keeps standing out.

That's often the one worth building first.

Before moving forward, simplify your offer into one clear sentence.

If you can't explain it simply, your audience probably won't understand it either.

A useful formula is:

We help [who] go from [current situation] to [desired result].

Simple always wins.

The biggest mistake isn't having bad ideas.

It's building the first one that comes to mind without checking whether people actually want it.

Strong products aren't built on inspiration alone.

They're built on curiosity, testing, and refinement.

The good news?

You don't need one perfect idea.
You just need one idea that solves one real problem for one specific group of people.

https://tinyurl.com/2s3uh8dj

Respond, don't react

 

90% of the things that hurt your feelings

had nothing to do with you:

Someone snaps at you in a meeting.
A friend goes quiet out of nowhere.
Your boss gives feedback that stings.

And your first thought is, "What did I do wrong?"

Probably nothing.

That person was stressed. Tired. Carrying something you know nothing about.

But you took it home with you.

Replayed it.
Lost sleep over it.
Made it yours when it never was.

I used to do this constantly.

One sideways comment and I would carry it for days.

Not because I was weak.

Because I had no system for deciding what was mine to carry and what was not.

So I started running everything through six questions before I respond to anything that feels personal.

1. Can I separate myself from this?
2. Am I hearing or reacting?
3. What was their actual intent?
4. Is this really about me?
5. Can I release this?
6. What response serves me best?

That is my SHIELD method in the infographic.

And it works because it slows you down just enough to choose.

The goal is not to stop feeling.

The goal is to stop letting someone else's bad morning become your bad afternoon (and sometimes bad week when we let it).

The strongest people I know are not the ones who always have the perfect comeback.

They are the ones who never needed one.

https://tinyurl.com/ycxnp6vp

12 Habits to Build a Growth Mindset

 

Not just another motivational post.
It’s 12 ways to grow without changing who you are.

A growth mindset isn’t just a trait.
It’s a daily practice.

It’s how you respond when you’re challenged or rejected.
And it’s built one habit at a time.

Here are 12 habits to strengthen your growth mindset:
(With one action you can take immediately)

1. Let feedback guide you, not define you
☞ Feedback is not judgment. Its direction.
✅ Ask one person you trust: “What’s one thing I can do better?”

2. Add “yet” to your vocabulary
☞ You’re not bad at it. You’re just not good yet.
✅ Next time you fail, reframe: “I am not done yet.”

3. Set goals that stretch you
☞ Comfort zones keep you small. Growth zones push your limits.
✅ Write down one bold goal you’ve been avoiding and take step one.

4. Seek out real challenges
☞ Growth hides in what scares you.
✅ Say yes to one task others avoid.

5. Chase progress, not perfection
☞ Perfection keeps you stuck. Progress builds momentum.
✅ Celebrate 1 small improvement you made today.

6. Change your perspective on failure
☞ Failure is not the end. It’s the data for your next attempt.
✅ Write down what the last failure taught you.

7. Celebrate effort, not just results
☞ Hard work trains your mindset more than outcomes.
✅ Share a recent effort you’re proud of regardless of the outcome.

8. Be patient with yourself
☞ Self-growth isn’t a race. It’s a journey.
✅ Pause today and say: “I’m not behind. I’m becoming.”

9. Be a continuous learner
☞ Mindset grows with knowledge, not noise.
✅ Read 2 pages of a book that grows your perspective.

10. Surround yourself with people ahead of you
☞ What feels impossible to you is normal to them.
✅ Reach out to one person who’s doing what you want to do.

11. Learn from diverse network
☞ Different perspectives stretch your thinking.
✅ Follow 1 person outside your field who challenges your views.

12. Find a mentor who’s walked the path
☞ You don’t need 100 opinions, just one guide.

You don’t grow all at once.
You grow one mindset shift at a time.

https://tinyurl.com/mwtnw7yv

The Leadership Colour Wheel

 

Can your favourite colour reveal your leadership style?

Research shows that your favourite colours reveal leadership insights.

Here's how. Here’s a breakdown of what different colours say about your leadership style!

Red: The Bold Leader
↳ Passionate, energetic, and decisive. You thrive in fast-paced environments and inspire others with your enthusiasm.

Blue: The Trustworthy Leader
↳ Calm, reliable, and analytical. You create a stable environment where team members feel secure and valued.

Green: The Nurturing Leader
↳ Compassionate, growth-oriented, and supportive. You focus on developing your team’s potential and fostering collaboration.

Yellow: The Creative Leader
↳ Optimistic, innovative, and open-minded. You encourage out-of-the-box thinking and inspire creativity in your team.

Purple: The Visionary Leader
↳ Imaginative, strategic, and inspirational. You have a clear vision and motivate others to work toward the future.

Orange: The Dynamic Leader
↳ Enthusiastic, sociable, and adventurous. You bring energy to the team and encourage a fun, engaging workplace culture.

Have you ever noticed how your energy shifts in the workplace? Your leadership colour might be influencing how others see you!

What’s your leadership colour?

Credits to Chris March, follow for more insightful content

https://tinyurl.com/mw68r37a

How to lead with empathy

 

Raises can reward.
Promotions can motivate.
But only empathy builds real belonging.

I’ve noticed something in the teams that work best.

People feel safe.
They speak up.
They stay.

And when I look closer, the leaders in those rooms tend
to share a few habits.

Nothing dramatic.
Just small ways of being present that add up over time.

I think of them as the 7 letters of E.M.P.A.T.H.Y:

E – Engage Fully
↳ Put the phone down. Close the laptop.
↳ Let them feel heard.

M – Mirror Emotions
↳ “It sounds like you’re feeling...”
↳ This alone can shift a whole talk.

P – Pause Before Responding
↳ A breath can change your reply.
↳ It gives space for what they said to land.

A – Ask, Don’t Assume
↳ “Help me know more” beats “I think I know.”
↳ Get curious first.

T – Trust Their Perspective
↳ Their view is real to them.
↳ You don’t have to fix it to honor it.

H – Hold Space
↳ Sometimes people need a person.
↳ Not a plan.

Y – Yield the Spotlight
↳ Wait for the whole thought.
↳ Your turn will come.

Empathy takes practice.
It’s a skill, not a trait.

And honestly, some days you’ll get it right.
Other days you won’t. That’s okay.

The point isn’t to be perfect at all seven.

It’s to keep showing up and trying one or two when it
matters most.

Your version of empathy might look different from mine.

That’s the beauty of it.
There’s no single way to make someone feel seen.

But the teams that feel it?
They give it back tenfold.

https://tinyurl.com/mrywy6xy

The Buyers's Pyramid in 2026

 

The B2B sales framework that worked for 30 years still holds in 2026.
The playbook for using it does not.

Chet Holmes mapped the Buyer's Pyramid in the 90s. 3% of your market is actively buying. 7% is thinking about it. 90% is not on the radar.

Those numbers have not moved in three decades. They describe something structural about markets, not something specific to any era.

But the playbook for working each layer has changed completely.

The 3% used to be the obvious target. Now it is the noisiest, most expensive segment in the history of B2B sales.

Every vendor with a tool subscription is pointing AI-personalised outreach at the same prospects. Sender reputations are burning. Reply rates are collapsing. Costs are climbing every quarter.

You can still win in the 3%. It just costs more than it ever has.

The 7% is the most under-served segment in 2026.

These prospects have identified the problem. They are exploring solutions. They are not yet on competitor radars because they have not surfaced as "actively buying."

A conversation with a 7% prospect lands differently. They are problem-aware. The relationship you build now has a realistic conversion horizon, months not years.

Whoever owns the 7% today owns the 3% in six months.

The 90% has not changed in composition. They are not thinking about buying right now. What has changed is how you reach them.

Inbound used to do the work. Content marketing. Email lists. SEO. They found you when they were ready.

Not anymore. AI search is bypassing your funnel. Organic discovery is fragmenting. Email lists are harder to grow and harder to land in.

Outbound, done right, is one of the few reliable ways left to reach the market majority.

The teams winning in 2026 are not the ones with the most tools. Everyone has the same tools.

The teams winning are the ones doing the thinking the tools cannot do. The research. The personalisation that goes beyond first name and job title. The consultant-mindset that makes a prospect feel understood rather than targeted.

The pyramid still holds. The percentages have not moved. The strategy has to.

TLDR: The framework still works. The playbook has not. Whoever owns the 7% today owns the 3% in six months.

https://tinyurl.com/yvzbdj9r

Principles of Marketing. 6. Marketing Research and Market Intelligence. Part 1-3.

 

Figure 6.1 Marketing research provides companies with data-driven insights that allow for deep understanding of their customers in order to develop products and services that meet those customers’ needs. (credit: modification of work “Workshop: Biodiversity Data Mobilization - Day 3” by Maheva Bagard Laursen/GBIF/flickr, CC BY 2.0)

In the Spotlight

When you think of LEGO, you may imagine a child building a spaceship or castle, but LEGO wanted to learn more about how children are encouraged or discouraged to play with its bricks. In 2021, LEGO launched a research study of close to 7,000 parents and children aged 6 to 14 years old in seven countries to determine how gender stereotypes influence play in creative activities.

During this study, LEGO learned that girls are more open to bending gender roles than boys but that parents have learned to stereotype some careers as being gender-specific. Additionally, parents are more likely to encourage girls to play dress-up (83 percent for girls, 17 percent for boys), dance (81 percent for girls, 15 percent for boys), and bake (80 percent for girls, 20 percent for boys), while they suggest computer coding (71 percent for boys, 29 percent for girls) and sports for boys (76 percent for boys, 24 percent for girls). Due to these findings, LEGO initiated its “Ready for Girls” campaign.

The data compiled in this study allowed LEGO to take a step forward in helping to break down some gender norms when it comes to its product. On October 11, 2021, the International Day of the Girl, LEGO announced a new program to encourage girls to show their creativity. “Get the World Ready for Me” was launched with a 10-step guide to collect information about how girls are engaging with LEGO. Due to this program, LEGO has launched a campaign of stories about how girls are involved with imagination and creativity.

Through this campaign, LEGO identified a way to encourage girls to challenge worldwide views of gender norms (see Figure 6.2). The background necessary for this campaign was researched and used in a way that would help the company stand out. For LEGO and many other companies and organizations, research is its competitive advantage.1

Figure 6.2 Through the use of marketing research, LEGO was able to gain data-driven insights into gender stereotypes and launch a campaign that encouraged girls to challenge views on gender norms. (credit: “LEGO Shuttle Expedition and City Spaceport Comparison” by Adam Purves (S3ISOR)/flickr, CC BY 2.0)

6.1 Marketing Research and Big Data

Learning Outcomes

By the end of this section, you will be able to:

• 1 Define marketing research.
• 2 Explain how marketing information provides an understanding of the customer and the marketplace.
• 3 Explain the role of big data and the marketing information system.

What Is Marketing Research?

Oftentimes people think of marketing as the process of communicating with a target market—sharing messages, products, and value with customers. However, marketers know that understanding customers, learning about their wants and needs, and developing a relationship with them is essential for success. Marketing research allows marketers to listen and assess the needs of the market, to understand what’s missing and how to reduce those gaps from their customers, target markets, and prospective clients. Managers need marketing information in order to make data-driven decisions rather than make assumptions about consumers. In this chapter we’re going to investigate the importance of marketing research, some strategies employed in the field, and how to complete the marketing research process.

Marketing research is the work to gather information and data about customers and markets. Let’s look at the definition, why it’s important, and the influx of big data.

Marketing Research Defined

According to the American Marketing Association (AMA), marketing research “is the function that links the consumer, customer, and public to the marketer through information.”2 Marketing research presents information gained through various sources as a resource for managers to make data-driven business decisions. Additionally, the AMA states that “marketing research specifies the information required to address these issues, designs the method for collecting information, manages and implements the data collection process, analyzes the results, and communicates the findings and their implications.”3

The Importance of Marketing Information

Marketing information, also known as business intelligence, competitive intelligence, or marketing intelligence, is information about the market that helps to identify opportunities in the market. This information helps to determine a company’s strengths and weaknesses while also evaluating the external environment’s opportunities and threats. Ideas generated through analysis of marketing information support business decision-making from a long-term strategic approach to smaller issues at a tactical level.

Marketing information is essential for a company or organization to stay competitive and also meet the customer’s needs. As referenced above, LEGO used marketing research to gather information about how children use its product but also how parents felt about opportunities for their children. Universities and colleges use information gathered through marketing research to build next year’s recruitment materials by asking students their perceptions of the previous year’s items. Additionally, a fast-food restaurant might conduct an analysis of the time of day each of its items are more likely to be purchased. Obvious to most, coffee would probably be an item more likely ordered earlier in the day. Other items might not be as evident but could require different preparation times. By accounting for when each of these items is most likely to be ordered, the restaurant can plan its inventory and schedule of employees more efficiently.

Big Data and the Marketing Information System (MIS)

The amount of data currently available is not only vast but is growing at an exponential level every day, which describes the concept of big data. Big data is the countless number of records that continues in an increasing capacity and at a faster rate. Because of the constantly changing landscape of data, it’s difficult for companies to develop an approach for analyzing it. Big data is often described through the use of the three Vs: volume, velocity, and variety. The amount of data, or volume, is more than we have ever witnessed. Additionally, it is growing at a fast rate; the velocity is also ever increasing. We expect that the velocity of data will continue to surge exponentially as each day more users are contributing to the data available. Finally, there is the variety of data that is part of this enormous data set—because each user is contributing to the cache of data available, the diversity of data is just as unique as its creators.

Link to Learning

What Is Big Data?

Big data is massive amounts of data. But what does that mean? Think of all the data a smartphone generates with texts, searches, emails, photos, etc. Now consider how many smartphone users there are in the world. Watch this video and learn how much data is generated on the internet each day and how it can be classified through the three Vs concept.

“Big data has become one of the most valuable assets held by enterprises, and virtually every large organization is making investments in big data initiatives.”4 This statement was based on a 2021 NewVantage Partners survey of senior C-level executives at Fortune 1000 companies regarding their perceptions of big data and their utilization of its resources. NewVantage Partners learned that many companies are already pursuing this data, with 96 percent reporting that their companies have already had success using big data and artificial intelligence programs. Additionally, 99 percent of the executives surveyed are pursuing either new or existing big data programs. Why are companies so keen to invest in this source? It is estimated that the world creates approximately 2.5 quintillion bytes of data daily. This vast accumulation of data can be collected through various methods, such as point-of-sale databases, connected devices through the Internet of Things (IoT), third-party marketing research firms, social media, location data from mobile devices, or surveys.5 Tapping into the resource generators is helpful for companies to understand their customers, employees, or others.

So, who are these data generators? They are everyone, like you and your friends, who post content on social media, engage with web content through streaming services, and share stories through web applications. In addition, businesses are contributing to the massive amount of content available. Extra data (volume), at a faster rate (velocity), and from a more widely diverse set of people (variety) explain why it is called “big” data.6 So how do businesses and individuals capitalize on this vast data world?

In order to be able to utilize and make the most of the availability of business data, businesses use a marketing information system to collect, analyze, and report interesting findings from internal and external data of the company. This system is an ever-changing database of content that is used to support the company or organization’s marketing efforts. The marketing information system is the collection of data and requires actions taken by marketers to utilize the data saved.

Careers In Marketing

Market Research Analysts

Market research analysts are needed in numerous industries, and according to the US Bureau of Labor and Statistics, the job outlook has a much higher rate of growth than average. Read about the skills needed, typical pay, education requirements, and career outlook in this article and watch this video about the various types of jobs available as a market research analyst.

Knowledge Check

It’s time to check your knowledge on the concepts presented in this section. Refer to the Answer Key at the end of the book for feedback.

1.

Anaya is collecting information from a variety of sources to make a decision on where to market her new line of designer scarves. Anaya is conducting ________.

1. market intelligence
2. big data
3. management information system
4. marketing research

2.

The collection of data the company has gathered over time and used to make marketing decisions on a regular basis is called its ________.

1. big data
2. marketing information system
3. marketing research
4. survey data

3.

Ryan and Christie are uploading their recent pictures to Instagram, tagging the photographer and the venue. What is this content adding to?

1. Market intelligence
2. Big data
3. Management information system
4. Marketing research

4.

Which of the following is not a reason why marketing research is important for the success of a business?

1. It provides a guarantee of customer satisfaction.
2. It identifies opportunities in the market to explore.
3. It helps to quantify customer perceptions.
4. It uncovers weaknesses within a company.

5.

Which of the following would not be considered marketing research?

1. Analyzing the product purchases of current customers
2. Measuring the number of reactions to a social media post
3. Examining a competitor’s database of information
4. Surveying potential employees about why they are interested in working for a company

6.2 Sources of Marketing Information

Learning Outcomes

By the end of this section, you will be able to:

• 1 Identify sources of marketing information.
• 2 Describe the different categories of marketing information.

Identify Sources of Marketing Information

Data, as mentioned in the first section of this chapter, comes from a variety of sources. In this section, we’ll investigate the sources of important marketing information and how these resources can be accessed to meet the needs of the institution. Online resources such as company websites, journal databases, and e-commerce locations could provide valuable resources to someone opening a new business. For instance, if a new product is to be sold, some companies will review competitors’ websites to glean information about comparable pricing before setting their price. The sources identified are closely aligned with the category of information and are described below.

Describe the Different Categories of Marketing Information

Marketing information can be derived from many sources. We will review three types in this section—internal data, external data, and competitive intelligence—and further explain other types of data in the next section. External and internal data both have unique qualities that make them essential for businesses to utilize. Additionally, competitive intelligence refer to specific types of data that must be examined to further the company or organization’s continued success and effectiveness.

External Data and Databases

External data is data that originates from outside the organization. Examples of external data would be information gleaned from customers through a customer service survey or reviews of a competitor’s website. Previously we learned about big data and the volume of information that is available daily. These data pieces would also be considered external data. Competitive and market intelligence is often gathered through these external sources of material. Data sources can include any interested parties of the business or a competitor’s business, social media mentions, news articles, journal publications, and others. The only limitation of collecting external data is financial. Not all sources of information are free, and the time spent to collect these insights is also a valuable commodity as “time is money.” Once external information is collected and available for those within the institution, it can be considered internal data.

Internal Data and Databases

Critical marketing intelligence can be data that already exists in the company’s databases. This data is called internal data and gives the company a historic view of what has worked in the past as well as identifies times when the company did not meet its goals. Internal data includes sales, promotional effectiveness, pricing, product launch information, research and development, and logistics information. Examples of internal data include the percentage of coupons redeemed, the sales volume at specific prices, the highest-grossing motion picture for a production company, and even the most-missed question on last unit’s marketing exam.

Businesses, organizations, nonprofits, and even colleges and universities use these types of data sources to make day-to-day and more comprehensive decisions. A database is a collection of related data. For instance, at the school you are currently attending, there are multiple databases—one for current students, one for alumni, and still another for faculty. Within each of these databases, there is information about that specific population. The current student database will be a list of all students who are enrolled in courses this term, with additional information such as what courses they are enrolled in, any past enrollments, grades earned, major, hometown, and academic advisor’s name.

Competitive Intelligence

Marketing research can be conducted on every aspect of business and marketing. Understanding the competition and its strengths and weaknesses through an analysis of the industry and competing forces gives a company a competitive edge. Competitive intelligence is the collection of that information from the marketplace. A company’s position must be examined to determine if it matches with the needs of the customers.

This competitive intelligence may be related to any of the marketing mix elements: product, price, distribution, or promotion. Checking prices of competitors’ products to make sure a company’s pricing is competitive, conducting a promotional audit to verify reach of the messages, or examining the competitive industry’s distribution channels may allow the company to identify a new location, and all help to make the company more educated on future decisions. When in a competitive space, why do customers choose the competitor over the company’s products? Marketing research can come in many forms and helps managers to make data-driven decisions. Once this data is collected, it becomes part of the business or organization’s internal data cache.

Knowledge Check

It’s time to check your knowledge on the concepts presented in this section. Refer to the Answer Key at the end of the book for feedback.

1.

Which of the following is a source for external information?

1. Sales receipts of your company’s most popular product
2. Employee salaries
3. Comments received from a customer service survey
4. Company’s website content

2.

Xin wants to determine the best price for a new product. What source of data would be the most appropriate to use?

1. Price of a competitor’s products
2. Inventory expenses
3. Journal articles
4. Online news site

3.

Which of the following is not a source of marketing information?

1. Journal articles
2. Social media posts
3. Experiments
4. Marketing information systems

4.

Which of the following would be a good source of competitive intelligence?

1. Experiments
2. Product sales of a company’s products
3. Consumer responses to a poll on a company’s new products
4. Competitor’s website

5.

Critical data that already exists within a company’s databases is called ________.

1. big data
2. internal data
3. external data
4. competitive data

6.3 Steps in a Successful Marketing Research Plan

Learning Outcomes

By the end of this section, you will be able to:

• 1 Identify and describe the steps in a marketing research plan.
• 2 Discuss the different types of data research.
• 3 Explain how data is analyzed.
• 4 Discuss the importance of effective research reports.

Define the Problem

There are seven steps to a successful marketing research project (see Figure 6.3). Each step will be explained as we investigate how a marketing research project is conducted.

Figure 6.3 The Marketing Research Plan (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

The first step, defining the problem, is often a realization that more information is needed in order to make a data-driven decision. Problem definition is the realization that there is an issue that needs to be addressed. An entrepreneur may be interested in opening a small business but must first define the problem that is to be investigated. A marketing research problem in this example is to discover the needs of the community and also to identify a potentially successful business venture.

Many times, researchers define a research question or objectives in this first step. Objectives of this research study could include: identify a new business that would be successful in the community in question, determine the size and composition of a target market for the business venture, and collect any relevant primary and secondary data that would support such a venture. At this point, the definition of the problem may be “Why are cat owners not buying our new cat toy subscription service?”

Additionally, during this first step we would want to investigate our target population for research. This is similar to a target market, as it is the group that comprises the population of interest for the study. In order to have a successful research outcome, the researcher should start with an understanding of the problem in the current situational environment.

Develop the Research Plan

Step two is to develop the research plan. What type of research is necessary to meet the established objectives of the first step? How will this data be collected? Additionally, what is the time frame of the research and budget to consider? If you must have information in the next week, a different plan would be implemented than in a situation where several months were allowed. These are issues that a researcher should address in order to meet the needs identified.

Research is often classified as coming from one of two types of data: primary and secondary. Primary data is unique information that is collected by the specific researcher with the current project in mind. This type of research doesn’t currently exist until it is pulled together for the project. Examples of primary data collection include survey, observation, experiment, or focus group data that is gathered for the current project.

Secondary data is any research that was completed for another purpose but can be used to help inform the research process. Secondary data comes in many forms and includes census data, journal articles, previously collected survey or focus group data of related topics, and compiled company data. Secondary data may be internal, such as the company’s sales records for a previous quarter, or external, such as an industry report of all related product sales. Syndicated data, a type of external secondary data, is available through subscription services and is utilized by many marketers. As you can see in Table 6.1, primary and secondary data features are often opposite—the positive aspects of primary data are the negative side of secondary data.

	Strengths	Weaknesses
Primary Data	Can be structured to be exactly what is needed Under complete control of researchers Timely, current data	Expensive to implement Takes time to compile May not be generalizable beyond specific research question
Secondary Data	Generally inexpensive or free Can be accessed quickly Available through a variety of sources	May not match required parameters Can be outdated Same data accessible by competitors

Table 6.1 The Strengths and Weaknesses of Primary and Secondary Data

There are four research types that can be used: exploratory, descriptive, experimental, and ethnographic research designs (see Figure 6.4). Each type has specific formats of data that can be collected. Qualitative research can be shared through words, descriptions, and open-ended comments. Qualitative data gives context but cannot be reduced to a statistic. Qualitative data examples are categorical and include case studies, diary accounts, interviews, focus groups, and open-ended surveys. By comparison, quantitative data is data that can be reduced to number of responses. The number of responses to each answer on a multiple-choice question is quantitative data. Quantitative data is numerical and includes things like age, income, group size, and height.

Figure 6.4 Four Research Types (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

Exploratory research is usually used when additional general information in desired about a topic. When in the initial steps of a new project, understanding the landscape is essential, so exploratory research helps the researcher to learn more about the general nature of the industry. Exploratory research can be collected through focus groups, interviews, and review of secondary data. When examining an exploratory research design, the best use is when your company hopes to collect data that is generally qualitative in nature.7

For instance, if a company is considering a new service for registered users but is not quite sure how well the new service will be received or wants to gain clarity of exactly how customers may use a future service, the company can host a focus group. Focus groups and interviews will be examined later in the chapter. The insights collected during the focus group can assist the company when designing the service, help to inform promotional campaign options, and verify that the service is going to be a viable option for the company.

Descriptive research design takes a bigger step into collection of data through primary research complemented by secondary data. Descriptive research helps explain the market situation and define an “opinion, attitude, or behavior” of a group of consumers, employees, or other interested groups.8 The most common method of deploying a descriptive research design is through the use of a survey. Several types of surveys will be defined later in this chapter. Descriptive data is quantitative in nature, meaning the data can be distilled into a statistic, such as in a table or chart.

Again, descriptive data is helpful in explaining the current situation. In the opening example of LEGO, the company wanted to describe the situation regarding children’s use of its product. In order to gather a large group of opinions, a survey was created. The data that was collected through this survey allowed the company to measure the existing perceptions of parents so that alterations could be made to future plans for the company.

Experimental research, also known as causal research, helps to define a cause-and-effect relationship between two or more factors. This type of research goes beyond a correlation to determine which feature caused the reaction. Researchers generally use some type of experimental design to determine a causal relationship. An example is A/B testing, a situation where one group of research participants, group A, is exposed to one treatment and then compared to the group B participants, who experience a different situation. An example might be showing two different television commercials to a panel of consumers and then measuring the difference in perception of the product. Another example would be to have two separate packaging options available in different markets. This research would answer the question “Does one design sell better than the other?” Comparing that to the sales in each market would be part of a causal research study.9

The final method of collecting data is through an ethnographic design. Ethnographic research is conducted in the field by watching people interact in their natural environment. For marketing research, ethnographic designs help to identify how a product is used, what actions are included in a selection, or how the consumer interacts with the product.10

Examples of ethnographic research would be to observe how a consumer uses a particular product, such as baking soda. Although many people buy baking soda, its uses are vast. So are they using it as a refrigerator deodorizer, a toothpaste, to polish a belt buckle, or to use in baking a cake?

Select the Data Collection Method

Data collection is the systematic gathering of information that addresses the identified problem. What is the best method to do that? Picking the right method of collecting data requires that the researcher understand the target population and the design picked in the previous step. There is no perfect method; each method has both advantages and disadvantages, so it’s essential that the researcher understand the target population of the research and the research objectives in order to pick the best option.

Sometimes the data desired is best collected by watching the actions of consumers. For instance, how many cars pass a specific billboard in a day? What website led a potential customer to the company’s website? When are consumers most likely to use the snack vending machines at work? What time of day has the highest traffic on a social media post? What is the most streamed television program this week? Observational research is the collecting of data based on actions taken by those observed. Many data observations do not require the researched individuals to participate in the data collection effort to be highly valuable. Some observation requires an individual to watch and record the activities of the target population through personal observations.

Unobtrusive observation happens when those being observed aren’t aware that they are being watched. An example of an unobtrusive observation would be to watch how shoppers interact with a new stuffed animal display by using a one-way mirror. Marketers can identify which products were handled more often while also determining which were ignored.

Other methods can use technology to collect the data instead. Instances of mechanical observation include the use of vehicle recorders, which count the number of vehicles that pass a specific location. Computers can also assess the number of shoppers who enter a store, the most popular entry point for train station commuters, or the peak time for cars to park in a parking garage.

When you want to get a more in-depth response from research participants, one method is to complete a one-on-one interview. One-on-one interviews allow the researcher to ask specific questions that match the respondent’s unique perspective as well as follow-up questions that piggyback on responses already completed. An interview allows the researcher to have a deeper understanding of the needs of the respondent, which is another strength of this type of data collection. The downside of personal interviews it that a discussion can be very time-consuming and results in only one respondent’s answers. Therefore, in order to get a large sample of respondents, the interview method may not be the most efficient method.

Taking the benefits of an interview and applying them to a small group of people is the design of a focus group. A focus group is a small number of people, usually 8 to 12, who meet the sample requirements. These individuals together are asked a series of questions where they are encouraged to build upon each other’s responses, either by agreeing or disagreeing with the other group members. Focus groups are similar to interviews in that they allow the researcher, through a moderator, to get more detailed information from a small group of potential customers (see Figure 6.5).

Link to Learning

Focus Groups

Focus groups are a common method for gathering insights into consumer thinking and habits. Companies will use this information to develop or shift their initiatives. The best way to understand a focus group is to watch a few examples or explanations. TED-Ed has this video that explains how focus groups work.

You might be asking when it is best to use a focus group or a survey. Learn the differences, the pros and cons of each, and the specific types of questions you ask in both situations in this article.

Preparing for a focus group is critical to success. It requires knowing the material and questions while also managing the group of people. Watch this video to learn more about how to prepare for a focus group and the types of things to be aware of.

One of the benefits of a focus group over individual interviews is that synergy can be generated when a participant builds on another’s ideas. Additionally, for the same amount of time, a researcher can hear from multiple respondents instead of just one.11 Of course, as with every method of data collection, there are downsides to a focus group as well. Focus groups have the potential to be overwhelmed by one or two aggressive personalities, and the format can discourage more reserved individuals from speaking up. Finally, like interviews, the responses in a focus group are qualitative in nature and are difficult to distill into an easy statistic or two.

Figure 6.5 A focus group is a research method for collecting customer data that involves a moderator asking questions of a small group of people who represent the target market. (credit: “Meeting” by UBC Learning Commons/flickr, CC BY 2.0)

Combining a variety of questions on one instrument is called a survey or questionnaire. Collecting primary data is commonly done through surveys due to their versatility. A survey allows the researcher to ask the same set of questions of a large group of respondents. Response rates of surveys are calculated by dividing the number of surveys completed by the total number attempted. Surveys are flexible and can collect a variety of quantitative and qualitative data. Questions can include simplified yes or no questions, select all that apply, questions that are on a scale, or a variety of open-ended types of questions. There are four types of surveys (see Table 6.2) we will cover, each with strengths and weaknesses defined.

	Strengths	Weaknesses
Mailed Surveys	Ability to reach large population Convenience of respondent	Time delays Expensive
Phone Surveys	Respondent can ask questions Collection in real time	Time intensive People don’t answer calls from numbers they don’t know
In-Person Surveys	Respondent can ask questions Follow-up questions can be asked based on answers	Time intensive People avoid talking with strangers
Electronic Surveys	Less time intensive than other methods Less expensive	Identification as spam Low response rate

Table 6.2 The Four Survey Method Options

Let’s start off with mailed surveys—surveys that are sent to potential respondents through a mail service. Mailed surveys used to be more commonly used due to the ability to reach every household. In some instances, a mailed survey is still the best way to collect data. For example, every 10 years the United States conducts a census of its population (see Figure 6.6). The first step in that data collection is to send every household a survey through the US Postal Service (USPS). The benefit is that respondents can complete and return the survey at their convenience. The downside of mailed surveys are expense and timeliness of responses. A mailed survey requires postage, both when it is sent to the recipient and when it is returned. That, along with the cost of printing, paper, and both sending and return envelopes, adds up quickly. Additionally, physically mailing surveys takes time. One method of reducing cost is to send with bulk-rate postage, but that slows down the delivery of the survey. Also, because of the convenience to the respondent, completed surveys may be returned several weeks after being sent. Finally, some mailed survey data must be manually entered into the analysis software, which can cause delays or issues due to entry errors.

Figure 6.6 A mailed survey, like the US Census, is a research method for collecting customer data that utilizes the mail, which provides companies with a way to reach a large number of households. (credit: “Census” by KSRE Photo/flickr, CC BY 2.0)

Phone surveys are completed during a phone conversation with the respondent. Although the traditional phone survey requires a data collector to talk with the participant, current technology allows for computer-assisted voice surveys or surveys to be completed by asking the respondent to push a specific button for each potential answer. Phone surveys are time intensive but allow the respondent to ask questions and the surveyor to request additional information or clarification on a question if warranted. Phone surveys require the respondent to complete the survey simultaneously with the collector, which is a limitation as there are restrictions for when phone calls are allowed. According to Telephone Consumer Protection Act, approved by Congress in 1991, no calls can be made prior to 8:00 a.m. or after 9:00 p.m. in the recipient’s time zone.12 Many restrictions are outlined in this original legislation and have been added to since due to ever-changing technology.

In-person surveys are when the respondent and data collector are physically in the same location. In-person surveys allow the respondent to share specific information, ask questions of the surveyor, and follow up on previous answers. Surveys collected through this method can take place in a variety of ways: through door-to-door collection, in a public location, or at a person’s workplace. Although in-person surveys are time intensive and require more labor to collect data than some other methods, in some cases it’s the best way to collect the required data. In-person surveys conducted through a door-to-door method is the follow-up used for the census if respondents do not complete the mailed survey. One of the downsides of in-person surveys is the reluctance of potential respondents to stop their current activity and answer questions. Furthermore, people may not feel comfortable sharing private or personal information during a face-to-face conversation.

Electronic surveys are sent or collected through digital means and is an opportunity that can be added to any of the above methods as well as some new delivery options. Surveys can be sent through email, and respondents can either reply to the email or open a hyperlink to an online survey (see Figure 6.7). Additionally, a letter can be mailed that asks members of the survey sample to log in to a website rather than to return a mailed response. Many marketers now use links, QR codes, or electronic devices to easily connect to a survey. Digitally collected data has the benefit of being less time intensive and is often a more economical way to gather and input responses than more manual methods. A survey that could take months to collect through the mail can be completed within a week through digital means.

Figure 6.7 Online Survey Example (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

Design the Sample

Although you might want to include every possible person who matches your target market in your research, it’s often not a feasible option, nor is it of value. If you did decide to include everyone, you would be completing a census of the population. Getting everyone to participate would be time-consuming and highly expensive, so instead marketers use a sample, whereby a portion of the whole is included in the research. It’s similar to the samples you might receive at the grocery store or ice cream shop; it isn’t a full serving, but it does give you a good taste of what the whole would be like.

So how do you know who should be included in the sample? Researchers identify parameters for their studies, called sample frames. A sample frame for one study may be college students who live on campus; for another study, it may be retired people in Dallas, Texas, or small-business owners who have fewer than 10 employees. The individual entities within the sampling frame would be considered a sampling unit. A sampling unit is each individual respondent that would be considered as matching the sample frame established by the research. If a researcher wants businesses to participate in a study, then businesses would be the sampling unit in that case.

The number of sampling units included in the research is the sample size. Many calculations can be conducted to indicate what the correct size of the sample should be. Issues to consider are the size of the population, the confidence level that the data represents the entire population, the ease of accessing the units in the frame, and the budget allocated for the research.

There are two main categories of samples: probability and nonprobability (see Figure 6.8). Probability samples are those in which every member of the sample has an identified likelihood of being selected. Several probability sample methods can be utilized. One probability sampling technique is called a simple random sample, where not only does every person have an identified likelihood of being selected to be in the sample, but every person also has an equal chance of exclusion. An example of a simple random sample would be to put the names of all members of a group into a hat and simply draw out a specific number to be included. You could say a raffle would be a good example of a simple random sample.

Figure 6.8 Type of Samples (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

Another probability sample type is a stratified random sample, where the population is divided into groups by category and then a random sample of each category is selected to participate. For instance, if you were conducting a study of college students from your school and wanted to make sure you had all grade levels included, you might take the names of all students and split them into different groups by grade level—freshman, sophomore, junior, and senior. Then, from those categories, you would draw names out of each of the pools, or strata.

A nonprobability sample is a situation in which each potential member of the sample has an unknown likelihood of being selected in the sample. Research findings that are from a nonprobability sample cannot be applied beyond the sample. Several examples of nonprobability sampling are available to researchers and include two that we will look at more closely: convenience sampling and judgment sampling.

The first nonprobability sampling technique is a convenience sample. Just like it sounds, a convenience sample is when the researcher finds a group through a nonscientific method by picking potential research participants in a convenient manner. An example might be to ask other students in a class you are taking to complete a survey that you are doing for a class assignment or passing out surveys at a basketball game or theater performance.

A judgment sample is a type of nonprobability sample that allows the researcher to determine if they believe the individual meets the criteria set for the sample frame to complete the research. For instance, you may be interested in researching mothers, so you sit outside a toy store and ask an individual who is carrying a baby to participate.

Collect the Data

Now that all the plans have been established, the instrument has been created, and the group of participants has been identified, it is time to start collecting data. As explained earlier in this chapter, data collection is the process of gathering information from a variety of sources that will satisfy the research objectives defined in step one. Data collection can be as simple as sending out an email with a survey link enclosed or as complex as an experiment with hundreds of consumers. The method of collection directly influences the length of this process. Conducting personal interviews or completing an experiment, as previously mentioned, can add weeks or months to the research process, whereas sending out an electronic survey may allow a researcher to collect the necessary data in a few days.13

Analyze and Interpret the Data

Once the data has been collected, the process of analyzing it may begin. Data analysis is the distillation of the information into a more understandable and actionable format. The analysis itself can take many forms, from the use of basic statistics to a more comprehensive data visualization process. First, let’s discuss some basic statistics that can be used to represent data.

The first is the mean of quantitative data. A mean is often defined as the arithmetic average of values. The formula is:

$$$$

A common use of the mean calculation is with exam scores. Say, for example, you have earned the following scores on your marketing exams: 72, 85, 68, and 77. To find the mean, you would add up the four scores for a total of 302. Then, in order to generate a mean, that number needs to be divided by the number of exam scores included, which is 4. The mean would be 302 divided by 4, for a mean test score of 75.5. Understanding the mean can help to determine, with one number, the weight of a particular value.

Another commonly used statistic is median. The median is often referred to as the middle number. To generate a median, all the numeric answers are placed in order, and the middle number is the median. Median is a common statistic when identifying the income level of a specific geographic region.14 For instance, the median household income for Albuquerque, New Mexico, between 2015 and 2019 was $52,911.15 In this case, there are just as many people with an income above the amount as there are below.

Mode is another statistic that is used to represent data of all types, as it can be used with quantitative or qualitative data and represents the most frequent answer. Eye color, hair color, and vehicle color can all be presented with a mode statistic. Additionally, some researchers expand on the concept of mode and present the frequency of all responses, not just identifying the most common response. Data such as this can easily be presented in a frequency graph,16 such as the one in Figure 6.9.

Figure 6.9 Frequency Graph (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

Additionally, researchers use other analyses to represent the data rather than to present the entirety of each response. For example, maybe the relationship between two values is important to understand. In this case, the researcher may share the data as a cross tabulation (see Figure 6.10). Below is the same data as above regarding social media use cross tabulated with gender—as you can see, the data is more descriptive when you can distinguish between the gender identifiers and how much time is spent per day on social media.

Figure 6.10 Cross Tabulation (attribution: Copyright Rice University, OpenStax, under CC BY NC-SA 4.0 license)

Not all data can be presented in a graphical format due to the nature of the information. Sometimes with qualitative methods of data collection, the responses cannot be distilled into a simple statistic or graph. In that case, the use of quotations, otherwise known as verbatims, can be used. These are direct statements presented by the respondents. Often you will see a verbatim statement when reading a movie or book review. The critic’s statements are used in part or in whole to represent their feelings about the newly released item.

Prepare the Research Report

The marketing research process concludes by sharing the generated data and makes recommendations for future actions. What starts as simple data must be interpreted into an analysis. All information gathered should be conveyed in order to make decisions for future marketing actions. One item that is often part of the final step is to discuss areas that may have been missed with the current project or any area of further study identified while completing it. Without the final step of the marketing research project, the first six steps are without value. It is only after the information is shared, through a formal presentation or report, that those recommendations can be implemented and improvements made. The first six steps are used to generate information, while the last is to initiate action. During this last step is also when an evaluation of the process is conducted. If this research were to be completed again, how would we do it differently? Did the right questions get answered with the survey questions posed to the respondents? Follow-up on some of these key questions can lead to additional research, a different study, or further analysis of data collected.

Methods of Quantifying Marketing Research

One of the ways of sharing information gained through marketing research is to quantify the research. Quantifying the research means to take a variety of data and compile into a quantity that is more easily understood. This is a simple process if you want to know how many people attended a basketball game, but if you want to quantify the number of students who made a positive comment on a questionnaire, it can be a little more complicated. Researchers have a variety of methods to collect and then share these different scores. Below are some of the most common types used in business.

Awareness

Is a customer aware of a product, brand, or company? What is meant by awareness? Awareness in the context of marketing research is when a consumer is familiar with the product, brand, or company. It does not assume that the consumer has tried the product or has purchased it. Consumers are just aware. That is a measure that many businesses find valuable. There are several ways to measure awareness. For instance, the first type of awareness is unaided awareness. This type of awareness is when no prompts for a product, brand, or company are given. If you were collecting information on fast-food restaurants, you might ask a respondent to list all the fast-food restaurants that serve a chicken sandwich. Aided awareness would be providing a list of products, brands, or companies and the respondent selects from the list. For instance, if you give a respondent a list of fast-food restaurants and ask them to mark all the locations with a chicken sandwich, you are collecting data through an aided method. Collecting these answers helps a company determine how the business location compares to those of its competitors.17

Customer Satisfaction (CSAT)

Have you ever been asked to complete a survey at the end of a purchase? Many businesses complete research on buying, returning, or other customer service processes. A customer satisfaction score, also known as CSAT, is a measure of how satisfied customers are with the product, brand, or service. A CSAT score is usually on a scale of 0 to 100 percent.18 But what constitutes a “good” CSAT score? Although what is identified as good can vary by industry, normally anything in the range from 75 to 85 would be considered good. Of course, a number higher than 85 would be considered exceptional.19

Customer Acquisition Cost (CAC) and Customer Effort Score (CES)

Other metrics often used are a customer acquisition cost (CAC) and customer effort score (CES). How much does it cost a company to gain customers? That’s the purpose of calculating the customer acquisition cost. To calculate the customer acquisition cost, a company would need to total all expenses that were accrued to gain new customers. This would include any advertising, public relations, social media postings, etc. When a total cost is determined, it is divided by the number of new customers gained through this campaign.

The final score to discuss is the customer effort score, also known as a CES. The CES is a “survey used to measure the ease of service experience with an organization.”20 Companies that are easy to work with have a better CES than a company that is notorious for being difficult. An example would be to ask a consumer about the ease of making a purchase online by incorporating a one-question survey after a purchase is confirmed. If a number of responses come back negative or slightly negative, the company will realize that it needs to investigate and develop a more user-friendly process.

Knowledge Check

It’s time to check your knowledge on the concepts presented in this section. Refer to the Answer Key at the end of the book for feedback.

1.

Sagar is completing a marketing research project and is at the stage where he must decide who will be sent the survey. What stage of the marketing research plan is Sagar currently on?

1. Defining the problem
2. Developing the research plan
3. Selecting a data collection method
4. Designing the sample

2.

A strength of mailing a survey is that ________.

1. you are able to send it to all households in an area
2. it is inexpensive
3. responses are automatically loaded into the software
4. the data comes in quickly

3.

Bartlett is considering the different types of data that can be pulled together for a research project. Currently they have collected journal articles, survey data, and syndicated data and completed a focus group. What type(s) of data have they collected?

1. Primary data
2. Secondary data
3. Secondary and primary data
4. Professional data

4.

Which statistic can be used to show how many people responded to a survey question with “strongly agree”?

1. Mean
2. Median
3. Mode
4. Frequency

5.

Why would a researcher want to use a cross tabulation?

1. It shows how respondents answered two variables in relation to each other and can help determine patterns by different groups of respondents.
2. By presenting the data in the form of a picture, the information is easier for the reader to understand.
3. It is an easy way to see how often one answer is selected by the respondents.
4. This analysis can used to present interview or focus group data.

https://tinyurl.com/3dkp2jpx