Author: Franz Malten Buemann

Two months back, we launched Buffer’s AI Assistant. It’s one of the most popular features we’ve ever launched at Buffer. Since launching AI has assisted in creating over 31,500 posts for 8,100 users. That’s 2.5 million AI-generated words created in Buffer. So, you won’t be surprised to hear we’ve been hard at work making it both smarter and faster. From today, Buffer’s AI Assistant can: Rephrase your postsSummmarize long-form textExpand sentences into paragraphsGenerate personalized social media ideasPlus, it’s integrated with Canva’s AI image generator—helping you create the perfect picture for your post.Assistance right when you need itIf you’ve ever struggled to come up with fresh ideas for your social media content, Buffer’s AI Assistant can help. By answering questions about your brand and target audience, you can generate new ideas that are perfectly suited for your account.Ideas are one thing, but ultimately you need to tweak those ideas until they’re ready to publish.To help the AI Assistant also comes equipped with features that help you rephrase, summarize, and expand your posts. This means that you can take existing content and make it more engaging and effective without spending hours writing and rewriting.Lightning-fast content creationSo, how does this help you create better content for social media, faster?For starters, the idea generation feature saves you time and brainpower. Instead of wracking your brain for hours trying to come up with new ideas, you can let the AI do the heavy lifting.This frees up your time to focus on other aspects of your social media strategy, like crafting compelling visuals or engaging with your followers.The rephrasing, summarizing, and expanding features are also incredibly helpful. If you’re struggling to find the right words to convey your message, the AI Assistant can help you find a new way to phrase things. If you need to summarize a longer piece of content, the AI can help you distill the main points down to their essence. And if you need to expand on a particular topic, the AI can help you find new angles and fresh insights.How it stacks upWhen we launched Buffer’s AI Assistant back in February 2023, we were one of the first to market. Today, many tools like Buffer have some form of AI available. So what makes Buffer stand out? First up, our AI Assistant is available across every channel. This means you can use the AI Assistant to improve your content on every social media platform you use.Secondly, the AI-powered personalized social media ideas aren’t available elsewhere. Simply answer a few simple questions about your brand and target audience, and voila, you’ve got endless ideas to try. Plus, the AI Assistant is available directly in the Buffer composer. This means you can create, edit, and improve your content all in one place, without having to switch between different tools or windows.Let’s face it, the best way to learn is to test it out yourself. So, don’t wait around, try Buffer’s AI Assistant for free →

If you’re keeping up with conversations about generative AI, you’ve likely heard of Jasper.ai.

In this post, I’ll cover its top features, show how it works, and explain the pros and cons of using this software.

What is Jasper.ai?
Jasper.ai Features
How Jasper.ai Works
What are the pros and cons of Jasper.ai?
How much does Jasper.ai cost?

The tool offers hundreds of templates to choose from, responding to many scenarios – like if you want to write a long-form blog post or need the perfect response to a review. It takes the stress of a blank page right out of writing.
Currently, Jasper.ai is best for marketers, offering advantages to companies of any size.

Jasper.ai Features

Text and image AI generation
Integration with Grammarly and other Chrome extensions
Revision history
Auto-save
Document sharing
Multi-user login
Plagiarism checker
Brand voice customization

One additional feature worth checking out on Jasper.ai is the “Explain it To Me Like a 5th Grader” option. As the name suggests, this feature allows you to select the text that may be jargon-heavy and reword it to simplify it – enough for a fifth grader to understand it.
This is particularly helpful when writing about a complicated topic to an audience with limited knowledge. It helps you keep the essence of your sentence while increasing its accessibility.

How Jasper.ai Works

Choose a template.
Add your inputs.
View output.

How reliable is the output?
It depends on the content. I’ve found that Jasper.ai works well with tactical, step-based content that’s been well documented. It also does well with marketing copy, like social media captions and ads.
But if the topic is too niche – i.e. there’s not much documentation already out there – the information will likely be incomplete or could be wrong altogether.

What are the pros and cons of Jasper.ai?
Pros

Generates in seconds – Seeing content appear out of thin air truly never gets old with generative AI. After a few simple inputs, you can have a full page of content to work with.
Sounds natural, well-written, and accurate– What good is gen AI if the output isn’t good, right? Jasper.ai does a fantastic job of sounding natural and matching the tone you’ve requested while keeping it error-free.
Fleshes out ideas – If you’re struggling to put pen to paper, Jasper.ai can help spark new ideas, new angles for your content.
Affordable – Jasper.ai is a great option for a small business looking to scale up its content production with a limited budget. The first tier starts at $24/month for 20,000 words – enough to get most marketers started.

Cons

Lacks personality and voice – AI can’t provide the experience and personalization that a human can add to a piece. While it can mimic tone, the output is often generic.
Can require heavy editing – This con is only a con depending on what you’re creating and how you want to leverage AI. Some only want to use software like Jasper.ai for a rough first draft, so heavy edits aren’t a bad thing. For others who are looking for a more polished end product, you’ll get this more easily with shorter-form content.
Struggles with niche topics – Jasper.ai seems to perform best with straightforward content requests. For example, it will likely do better writing a post on deleting your Instagram account than upcoming short-form video trends.
No fact-checking – Jasper feeds you a compilation of what it finds online. So, if the information’s incorrect, guess what? Your output will be the same.

How much does Jasper.ai cost?
Jasper.ai offers 3 pricing tiers:

Free trial – Jasper offers a five-day free trial with 10,000 word credits.
Starter – Starts at $24/month for 10,000 words, over 50 templates, and is ideal for individuals and entrepreneurs.
Boss – Starts at $49/month for 50,000 words, over 50 templates, and is ideal for marketers and small businesses.
Business – This will require custom pricing and is ideal for teams and businesses looking to scale their content production.

Alternatives to Jasper.ai include HubSpot’s Content Assistant, Copy.ai, Writer, and Frase.

Welcome to HubSpot Marketing News! Tap in for campaign deep dives, the latest marketing industry news, and tried-and-true insights from HubSpot’s media team.
Come on Barbie, let’s go party.
Last week the trailer and cast posters for this summer’s anticipated film Barbie the Movie got social media buzzing.

The trailer itself is fairly vague. Outside of introducing the main characters of the film, the clip reveals few details about the actual plot to build intrigue among audiences.
A few hours before the trailer dropped, official images of the cast were released on Twitter. Each image features stylized graphics of each Barbie character and their occupation.

Meet our Barbies and Kens ✨#BarbieTheMovie pic.twitter.com/KO2pwszXNJ— Barbie Movie (@barbiethemovie)
April 4, 2023

Upon the release of the trailer and images, Warner Bros. launched the Barbie Selfie Generator, an AI-powered website that allows users to put their own photos along with a Barbie-style occupation in a graphic that resembles the cast images.  An accompanying TikTok filter was also created.
Almost immediately, social media feeds were flooded with AI-generated memes.
Social media users who are excited about the film quickly created and shared their own images, distributing valuable user-generated content that has the potential to get further reach than the initial trailer or official posters.
This UGC play touches on an important element of nostalgia for those who played with Barbie dolls as a child. Part of the fun of playing with Barbies was having the dolls act out real-life scenarios and gravitating towards Barbies who had occupations we were interested in.
In other words, many of us wanted to be Barbie and by making ourselves the subject of Barbie-inspired memes, we can be.
Elsewhere in Marketing
The latest marketing news and strategy insights.
Podcast company Acast just signed an advertising deal with the Obamas’ production company Higher Ground.
Spotify announced plans to sunset its live audio app Spotify Live.
April fools? Twitter backtracks on revoking legacy blue checkmarks (except for The New York Times).
For the ‘gram: why parents are reserving social media handles under their children’s names.
LinkedIn is rolling out new personalization features and enhanced search capabilities.
How to get more reach on Instagram: five key takeaways from an “Instagram University” attendee.
YouTube users can now create a dedicated tab for podcast episodes on their channel pages.
TikTok’s parent company ByteDance reported record profits, surpassing other top-earning tech companies in China.
Substack is facing a Twitter dilemma. Tweets that contain the word “Substack” or links to a Substack page are experiencing platform limitations.
How marketers can thrive in a recession: expert tips from HubSpot’s consumer, marketing, and leadership research.

AI-generated content is a fascinating development, and we’re seeing more and more articles, stories, and images created by AI tools. (Thanks, AI, for the intro sentence.)
But, the rise of advanced AI generation tools has exposed potential issues, from people being unable to detect the difference between AI and human generations to AI predictions and analysis being flat-out wrong.
This is where AI detection comes in, as it’s a way for people to uncover when text, images, and even videos are machine-generated, so they can make informed decisions on the content they consume. In this post, we’ll cover:

What is AI detection?
How to Detect AI-Generated Text
How to Detect AI-Generated Images and Videos
AI Detection Tools

What’s the best AI detection tool?

AI detection tools don’t know the meaning of words and use context to analyze text. To get more technical, tools use the context of what’s to the left of the following word to predict the likelihood of the word to the right.
The more predictable the word to the right is, the more likely the text is AI-generated. On the other hand, human-written sentences vary from predictable patterns and are more creative.
If you’re anything like me, a basic example might be helpful to understand this. Let’s break it down.
Say someone inputs the sentence, “Bunnies are so fluffy.”
The tool uses learned data and context of words to the left of “fluffy” to predict that “fluffy” is more likely to come next, more so than words like “cute” or “soft.”
Since the sentence follows a highly predictable pattern, the tool will likely classify the text as AI-generated.
AI detection tools work at a much larger scale with more complex sentences and paragraphs than “Bunnies are so fluffy” to make predictions and classifications, but this is a basic example and shows how the process works.
Some detection tools analyze images and videos and use pixel anomalies to determine if something is AI-generated.

How to Detect AI-Generated Text
There are no set rules or guidelines for identifying AI-generated text, but here are some things to look out for:

Repetition of words and phrases: AI knows what it’s talking about, but not to the extent human experts do. Its outputs might repeat the same keywords and phrases with little variation when discussing a topic.

Lack of depth: Generation tools lack depth and can’t go beyond basic facts to truly analyze a topic and develop unique insight. AI-generated text might read more robotic and prescriptive than creative and have a generic tone.

Inaccurate and outdated information: The facts that content generation tools have are typically correct, but since the tools make predictions, outputs can be incorrect or unrelated to true facts. In addition, information can be outdated, like how ChatGPT is limited to information pre-September of 2021.

Format and structure: Generation tools follow the same sentence structure as humans, but sentences can be shorter and lack the complexity, creativity, and varied sentence structure humans produce. Content can be streamlined and uniform with little variation.

Human-written text is also more likely to have typos and use informal and casual language and slag.
Roft.io is a fun game to test your detection skills and see how good you are at predicting when text is AI-generated.

How to Detect AI-Generated Images and Videos
Identifying AI generated images and videos can be a bit more challenging than detecting text. Some commonly discussed tells are:

Textured backgrounds, images that look airbrushed, random brush strokes throughout images
Overall image sharpness, or parts of images that are blurry while others are more clear
Noticeable text in the background of images
Asymmetry in human faces, teeth, and hands
Signs of artist watermarks or signatures (AI tools are trained from existing artwork)

Tools like DALL-E 2 place a watermark on image outputs, but they might not be easy to spot. OpenAI also allows people to remove a watermark. You can also reverse image search to see if there are any traces of an image on the web.
The challenge of detecting AI images and videos is why deepfakes are so dangerous, as videos and images that seem lifelike enough can rapidly spread misinformation.

AI Detection Tools
At the moment, it might be easier to tell if something is AI generated because it sounds robotic, or someone’s hand is missing two fingers in an image. If generation tools become more sophisticated, it might be harder for humans to find the key discrepancies.
Regardless of future progressions, detection tools can be more helpful than our own deduction abilities in classifying AI-generated content, and there are various options available.
Below we’ll go over some of them and rate their effectiveness using an AI-generated paragraph from HubSpot’s Content Assistant (which uses GPT). Here’s what it gave me when I asked it to write a paragraph about dogs:
“Dogs are simply amazing creatures. They are loyal, loving, and endlessly entertaining. Whether you need a furry friend to cuddle with on the couch or a loyal companion to explore the great outdoors with, dogs are always up for the task. They come in all shapes and sizes, from tiny teacup Chihuahuas to majestic Great Danes, but all dogs share one thing in common: a boundless capacity for love and affection. Whether you’re a lifelong dog lover or a newcomer to the world of canine companionship, there’s never been a better time to discover the joys of life with a furry friend by your side.”
Note that human writing can still trigger a tool if it follows a predictable pattern.
1. ZeroGPT

Price: Free or contact for custom API
Tests for: ChatGPT and Google Bard

ZeroGPT’s algorithm is trained on 10M+ articles and text to have a detection accuracy rate of 98%. It supports multilingual text and detects popular language generators like Chat GPT, GPT-4, and Google Bard. Outputs highlight sentences most likely to be written by AI.
I entered the AI-generated paragraph about dogs, and it predicted the text is 88.57% AI/GPT generated.

Best for: ZeroGPT was built for educators to test for AI-generated content, but it works for anyone looking to detect AI content.
2. Giant Language model Test Room

Price: Free
Tests for: Developed in 2019 for GPT-2 text, might be unreliable on other generators

MIT-IBM Watson AI lab and the Harvard NLP group created the Giant Language model Test Room to detect AI-generated text. It analyzes inputs based on how likely each word is to appear based on the word immediately to the left. The more predictable the word is, the more likely the text is written by AI.
This tool doesn’t give a percentage but color codes words based on their predictability, with green meaning the word is part of the top 10 most predictable words.
Most of my paragraph is highlighted green, so the words are part of the top 10 most predictable (based on context) and more likely to be AI-generated.

Best for: Testing GPT-2 and learning more about predictable writing through an in-depth probability analysis.
3. Originality.AI

Price: Free 50 credit trial, then $0.01/100 words (1 credit scans 100 words)
Tests for: ChatGPT, GPT-3, GPT-3.5, GPT-NEO, GPT-J

Originality.AI Chrome Extension, built by content marketing experts, detects multiple versions of GPT with 94% accuracy. It scores text on a scale of 0-100, with a higher score being a higher likelihood of being produced by AI. You can also use the tool to scan for plagiarism (beneficial for educators). It’s the most accurate with more than 50 words.
With my test, it said that the paragraph was 99% likely to have been written by AI.

Best for: The Chrome extension makes it perfect for anyone looking for a seamless and immediate detection process when writing and reading online. Writers, content marketers, and web publishers alike can leverage this tool; not for academics.
4. Content at Scale

Price: Free version, or contact for API pricing
Tests for: GPT

Content at Scale’s AI Detector uses 3 AI engines and natural language processing to detect ChatGPT, all versions of GPT, and other generators. You can use it to test SEO, educational, and marketing content. The tool needs at least 25 words for reliable results, and you can enter up to 25,000 characters.
My test results were inconclusive because the tool couldn’t say with certainty if the paragraph was AI-generated. It gave a human content score of 51% with 17% predictability. 

It did say with certainty that the last sentence is AI-generated.

Best for: SEO and marketing-focused content creators to get line-by-line text breakdowns and analyze longer pieces of content (up to 25,000 characters).
5. Writer AI

Price: Free version or contact for API pricing
Tests for: ChatGPT and other generators

Writer AI’s content detector estimates how much text is AI-generated. The free and paid versions have a 300-word limit (1,500 characters), and results give a prediction percentage for how much of the text is human-generated content.
It scored my paragraph as 87% human-generated, with a recommendation to edit the text until there’s less detectable AI content. 

Best for: B2B and enterprise and agencies looking to analyze and edit content before publishing.
6. Hive’s AI Detection Tools

Price: Free demo, contact sales for API pricing
Tests for: ChatGPT, GPT-3, DALL-E, Midjourney, Stable Diffusion

Hive offers a suite of AI detection tools for images, text, and deepfakes.
The text detection tool gives a confidence score for how likely something is AI-generated, and estimates which sections are most predictable. It also estimates which sections of text are more likely to be AI-generated. It works starting at 750 characters with a recommended length of 1500 characters.
I had to input extra words to reach the character limit, and it predicted the paragraph was 99.99% likely to contain AI-generated content.

The media recognition tool identifies AI-generated media, gives a classification (AI-generated or not), confidence score (≤ 1), and image generation source (like DALL-E). (Documentation, tool page)
The deepfake detection tool tests if images or videos are deepfakes through facial classification. (Documentation)
Best for: Screening work to detect AI content or for websites to detect and moderate AI-generated images and text.
7. Bonus: OpenAI’s Text Classifier

Price: Free (requires account)
Tests for: All versions of GPT

OpenAI’s Text Classifier can distinguish between AI-generated text and human-written text. It works best with more than 1,000 characters and English text.
OpenAI does note that it is not entirely reliable and only correctly identifies 26% of AI text and incorrectly labels human-written text as AI 9% of the time, but reliability increases for longer text. It recommends using the classifier as a complement to other testing methods.
Best for: Detecting GPT

What’s the best AI detection tool?
I outlined each tool’s individual test score above, but here’s a table comparing scores.

Tool
score

ZeroGPT
88.57% AI content

Giant Language Model Test Room
Probability only

Originality.AI
99% AI content

Content at Scale
49% AI content

Writer AI
13% AI content

Hive
99.99% AI content

Based on these rankings, 

First place is a tie between Originality.AI, GLTR, and Hive AI
Second place is ZeroGPT
Third place is Writer AI
Fourth place is Content at Scale

Over to You
AI detection makes it a lot easier to distinguish between machine and human-generated text. As AI tools become more and more accurate, AI detection will remain important in helping people determine the legitimacy of the content they consume. 

While many think quiet quitting is nothing more than setting healthy boundaries, others see it as a sign of poor work ethic.
We could debate whether quiet quitting is good or bad forever. But, are workplaces actually taking the time to understand why it happens and how they can effectively and supportively address it?
In this post, we analyze data from 500 marketing leaders to learn how leaders are keeping up with quiet quitting, why they think it happens, and how they plan to navigate it.

Quiet Quitting Fast Facts
Before diving into the why and how, here are a few fast-facts to keep in mind about the state of quiet quitting:

On average, leaders think 17% of their staff are quiet quitting — but 33% of full-time employees polled in our consumer trend survey admit to doing it.
64% of marketing leaders say quiet quitting is a reflection of poor work ethic, while one-third view it as setting healthy boundaries.
77% of marketing leaders admit that it’s their responsibility to prevent quiet quitting, and 63% say it’s a reflection of poor leadership.
73% of marketing leaders say the determining factor in whether employees quiet quit is the quality of their relationship with their supervisor.
77% of marketing leaders say quiet quitting is unacceptable, but over half of them say it’s happening in their organization.

Marketing Leaders Might Underestimate Quiet Quitting
More than half of the surveyed leaders say they’re concerned about quiet quitting.
And, although 77% of leaders also say quiet quitting is unacceptable, 57% admit it happens in their organization.

Although they rightly assume it happens. our research hints they’re still underestimating how often it happens. Marketing leaders say 17% of their staff are quiet quitting, and 80% think they’d know if someone was quiet quitting,
However, in our State of Consumer Trends Report, 33% of full-time employees admitted to quiet quitting in their current job. Since this data is self-reported, it’s likely even higher than that as some might worry about disclosing their quiet quitting status.

Regardless of how often it happens, 57% of marketing leaders are somewhat to very concerned, while many worry about how low productivity and effort could get out of hand.

With that said, 64% say quiet quitting is a reflection of an employee’s poor work ethic, while only 36% view it as setting healthy boundaries at work.

Why Marketing Leaders Think Employees Quiet Quit
When it comes to the cause of quiet quitting, marketing leaders point to a handful of issues that leaders can prevent or help resolve. Here are just a few:
Lack of Accountability
According to leadership, the top reason for quiet quitting is that employees think they can get away with doing the bare minimum. In other words, a lack of accountability.
Poor Incentives
Leaders also think employees quiet quit because workers see no benefit in going above and beyond, feel burnt out, and are unhappy with the company culture.

If you’re looking at the data above and thinking that these all reflect issues with company management rather than employees trying to skirt by, you would be right. And marketing leaders know this too.
Employee-to-Supervisor Relationship
Most marketing leaders agree that it’s their responsibility to prevent quiet quitting and that the trend is a reflection of poor leadership/management.

In fact, 73% of marketing leaders say the determining factor in whether employees quiet quit is the quality of their relationship with their supervisor.
How Marketing Leaders Navigate Quiet Quitting
A whopping 66% of marketing leaders say their leadership team has explicitly discussed how to address it.
But, what solutions are they discussing or trying?
While it might not always be possible, here are few potentially simple and thoughtful ways to make employees feel happier and fulfilled at their workplace, thus — feeling more connected to their job.
Marketing leaders say motivating employees with rewards, recognizing hard-work, and offering career development or leadership opportunities are some of the most effective strategies.

After COVID-19, we all took a look at how our workplaces care about our health, mental wellness, psychological safety, physical safety, and overall well-being. And, many employees chose to leave workplaces that couldn’t keep up.
So, it’s not shocking that marketing leaders encouraged supporting employee health and well-being, emphasizing work-life balance in company culture, and offering employees flexibility in their work schedules.
If you’re worried your workplace is primed for quiet quitting due to management, lack of accountability, or other reasons, read up on these resources with expert insights from great leaders, managers, and even psychologists:

18 Strategies to Increase Employee Retention
How to Cultivate Psychological Safety for Your Team, According to Harvard Professor Amy Edmondson
Establishing Employee Wellness at Work
Remote Work Loneliness: How to Protect Mental Health When Working Remotely
6 Secrets to Achieving Work-Life Balance, According to HubSpot Marketing Managers

What Marketers Should Think About Before Quiet Quitting
While you should make setting boundaries and workplace standards key parts of the conversations you have with your manager, be cautious when entering “quiet quitting” territory.
When setting healthy boundaries, you should continue meeting the expectations of your job description and keep your colleagues in mind so they don’t have to take on extra work themselves.
If you decide to disclose that you’re quiet quitting in the workplace, keep in mind that some managers will not be pleased, while others will want to support you in setting those boundaries. Regardless, know that many marketing jobs require you to exceed the expectations of the current role to earn raises, bonuses, or promotions. Because of this, long-term quiet quitting could make upward motion difficult at any company.
Ultimately, try to keep an open dialogue about how you’re feeling in your role, what goals you’d like to reach for, what your most effective working style is, what could be holding you back, and how your team can create a positive and psychologically safe environment.
The Marketing Executive’s Playbook
Whether you agree or disagree with marketing leaders on quiet quitting, it helps to get their perspective on major industry trends.
Check out our Marketing Executive’s Playbook as well as our Act Like a Leader, Think Like a Leader series, for insights from leaders on their goals for 2023, the top challenges they expect, how they’re preparing for a recession, how marketers can make the greatest impact in their roles to get promoted, and much more.

To understand human-centered design, let’s start with what it isn’t.
Imagine you work at a gaming design company, and one day your boss comes to you and says, “Teenagers these days — they need to get off their phones. Let’s design a crossword-puzzle board game for teenagers — they’d welcome the opportunity to get offline.”
Your boss has good intentions, but his intentions don’t match your consumer’s reality. His idea isn’t empathetic towards a teenager’s passions, and it isn’t a solution that fits their wants and needs.

Now, let’s look at a real example of human-centered design: meal subscription boxes.
Take HelloFresh, founded in 2011 by Dominik Richter, Thomas Griesel, and Jessica Nilsson. The company delivers a box of fresh food to your door, with easy recipes included. The founders recognized that people have trouble finding time to shop for groceries and struggle to create healthy, affordable meals — they came up with a solution to both problems.
Unlike your boss in the first example, the HelloFresh founders didn’t develop an idea unrelated to real consumer needs. Instead, they recognized a struggle someone was facing and then worked to invent a solution. In this way, it’s arguable that human-centered design is a safer and more trustworthy approach to problem-solving.
Whether your role requires you to pitch ideas in marketing meetings or design the products your company sells, it’s critical you know the process of human-centered design. By putting your consumer at the forefront of your creative process, you ensure each product you create and distribute is a true, long-term solution to your consumer’s needs. If done correctly, you’ll gain a much more reliable and loyal customer base.
Now that we’ve covered the importance of human-centered design, let’s dive into the various stages of a human-centered design process and look at some examples so you feel confident implementing the strategy for yourself.
Human-centered Design Process
IDEO — the global design firm behind Apple’s first computer mouse, the Palm Pilot, in 1998, and more — came up with three phases for the human-centered design process, which has helped them create such successful and long-lasting products.
The three phases of the human-centered design process are inspiration, ideation, and implementation.
Phase One: Inspiration.
The inspiration stage requires true on-the-ground research. You’ll need to engage directly with your target audience to understand their biggest problems and pain points. It’s important to research your target audience. You want to find out: what makes your consumer happy? What makes them frustrated? What do they do first in the morning? How do they devour content? What takes up most of their time?
Essentially, you want to see from their point of view.
There are a few different methods you could use to research your audience. For instance, you might send out surveys to customers via email or create a survey submission form on one of your web pages. If you find it difficult to get people to fill out the survey, you might offer incentives — 10% off their next purchase or a ticket for a raffle contest with a giveaway prize.
You could facilitate a focus group if you don’t feel comfortable with surveys.
If you often interact with consumers on the phone or email, you might hear about issues they’re having organically.
If you’re still unsure which direction to take, check out 19 Tools & Resources for Conducting Market Research for more ideas.
Once you’ve done your market research, list with your team all the trivial and major problems with which your consumer struggles (within your skill set or products, of course). Consider the biggest hassles your consumer faces and how your products could get better to solve those issues.
Phase Two: Ideation.
Like the HelloFresh founders, your team must envision a future that doesn’t exist yet. Now that you know what problems your consumer faces, what solutions could help them become better, happier, and more productive?
The ideation stage is your “no such thing as a bad idea” brainstorming session. It requires you and your colleagues to create and tweak a long list. Take good ideas, and make them better. Refine and tweak them. Imagine all the different ways you could solve a customer’s problem, big and small.
When you’re confident you have a realistic, human-centered idea to solve for a customer’s needs, you’ll need to envision how a product could solve that solution.
Let’s use our HelloFresh example to see this stage more clearly. In Phase Two, Ideation, you’ve already recognized that people don’t have time to grocery shop and want healthy meals (that was Phase One). In this step, you’ve made a long list of potential solutions, i.e., “YouTube tutorials to create healthy meals? Write a cookbook? Pay for someone to come into your home and cook for you? Pay for a truck to deliver healthy food to your door?”
Ultimately, your team has decided — aha! We’ll create a meal subscription service.
Now, you want to prototype and test this product on your ideal persona.
Remember, the whole premise behind human-centered design is digging into your consumer’s actual needs and providing a solution to those needs. If you receive feedback on limitations of your product, don’t get dejected — get inspired. That feedback is exactly what you need to ensure your product will gain long-term traction with your target consumer base.
Phase Three: Implementation.
So you’ve created and tested a prototype of your product, collected feedback, and seem ready for release to a wider audience.
Now, it’s time to market your product. Ultimately, you’ll want to imagine yourself in your consumer’s shoes and then market to them from that point of view: How would I like to learn about this product if I were them?
Since your product revolves around your consumer’s struggles, you’ll want to develop an effective marketing strategy to spread the word about your product as a long-term solution to a real struggle.
You also might want to consider partnering with other businesses who offer similar solutions or share an audience with similar problems. By partnering with a business, you’re able to offer the user more of an all-in-one solution.
Human-centered Design Examples
1. Colgate Toothbrush 
Colgate-Palmolive’s toothbrush, Acti-Brush, was innovative in the 1990s, but since then, competitor toothbrushes have surpassed Colgate’s on the market. Colgate-Palmolive hired Altitude, a design consulting firm focused on human-centered designs, to create a new toothbrush model.
The Altitude team extensively researched the audience and then developed the Motion, a new, slimmer, high-powered toothbrush with oscillating heads and an arcing neck. The entire product, from superficial features to performance, centered around one critical question: will this serve our user’s needs? Ultimately, the Motion successfully solved a user’s problem — needing a slender toothbrush that could still deliver on performance — the industry hadn’t previously addressed.
 
Image Source
2. Spotify
Remember the days of paying $1.99 for one song, or hanging around the aisles of Walmart, searching for your favorite album?
I’d argue that one of the most impressive displays of human-centered design is Spotify — a product that showed me my prior method for purchasing music was a problem before I even recognized it as one.
Spotify succeeded by empathizing with their users’ struggle to pay for music from disparate sources and created a solution we could all embrace. Thanks to Spotify, users can get all their music in one place for one monthly fee. I’m willing to pay more for that kind of tailored, customized, helpful service.

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3. Fitbit
Before handy fitness trackers, we’d have to estimate how many calories we burned in a day and find the inherent motivation to be more active (which, as we all know, is an untrustworthy source).
The invention of products like Fitbit is undeniably human-centered. The inventors of fitness trackers recognized people’s challenges with tracking and maintaining fitness goals and provided a useful long-term solution. The product works with the user in mind by telling the user how many calories she burned and urging her to exercise more.

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4. Venmo
Venmo is another example of a product that solved a problem before most people realized it was one. I personally didn’t see how cumbersome exchanging money was until Venmo provided a solution.
The founders of Venmo, Andrew Kortina and Iqram Magdon-Ismail, stumbled across the idea of Venmo only when they encountered the problem. They went to New York City, and Iqram forgot his wallet. Andrew paid for everything, and at the end of the trip, Iqram wrote him a check.
During that exchange of money, they thought, “Why is this still the best way of exchanging money? Why can’t we do this on our phones?”
The Venmo founders needed to solve a problem they encountered and build a solution from which other people could also benefit.

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Feeling Inspired?
Hopefully, these examples confirm the usefulness of human-centered design for creating long-lasting and innovative products. You’re now ready to tackle your creative process from a new angle — the human angle.