Table of Contents:
- Chapter 1: A simple mantra: no data, no scale
- Chapter 2: (The right) data is critical to scale
- Chapter 3: To pursue an opportunity… in coconuts
- Chapter 4: Unintended outcomes? Make a change
- Chapter 5: Getting the right information in the right ways
- Chapter 6: Solve a need that you yourself know inside and out
- Chapter 7: Asking smart people about your idea is the best deal on data you’ll ever get
- Chapter 8: The absolute centrality of data when it comes to scale
- Chapter 9: Gather the data with enough speed to be ahead of the competition
- Chapter 10: Who your customer is, and who your scale customer is, isn’t the same thing
- Chapter 11: The more users you get, the more information you have
- Chapter 12: Serve the chief household officer
- Chapter 13: In a people service business, caregivers are your product
- Chapter 14: The success of not-for-profits is measured less by earnings than by impact.
No data, no scale
Chapter 1: A simple mantra: no data, no scale
JAMISON KERR: We don’t ever say that it’s in the middle of nowhere. We always say it’s in the middle of everywhere.
We have a Main Street that 15 years ago was pretty much empty. It was dead like many, many other Main Streets across America.
And now you drive down Main Street, and it’s full of businesses that are bustling, and people are able to be patrons to the businesses but also find really beautiful green spaces to sit and eat a cone of ice cream.
HOFFMAN: That’s Jamison Kerr, and that place “in the middle of everywhere” is Lake City, South Carolina. Today, it’s a bustling small town of just under 6,000 people.
What changed? In 2013, the town got an unexpected champion.
An investor who had grown up in Lake City came back to found an organization that would help revive her hometown. But it wasn’t a new factory, or a new retail chain. So what was it?
KERR: ArtFields was set on changing the way that Southern artwork is presented.
HOFFMAN: ArtFields is an annual celebration of Southern visual art with paintings, sculptures, installations, and even a quilt or two. Jamison is now the organization’s director.
But ArtFields is more than an art show. It also boosts the small businesses of Lake City.
KERR: Rather than the artwork being in galleries, we have it in our businesses: barber shops and dress shops and restaurants.
HOFFMAN: When local businesses become the gallery spaces, visitors convert naturally to customers.
Of course, the art fair is just one piece of a larger economic puzzle. But its very existence has brought new tourism and commerce to Lake City. Even if they’ve had to overcome their share of doubters.
KERR: To say, “We’re going to do this with art.” I mean, a lot of people thought that we were crazy.
HOFFMAN: ArtFields wanted hard proof that they were genuinely contributing to Lake City’s renaissance. So they got just the right weapon to fight the skeptics: data.
KERR: In the very first year, we did an economic impact study that saw over 20,000 people come through and $5.4 million in return.
HOFFMAN: And since 2013, the fair’s impact has only grown. Gathering that data is a top priority for Jamison’s team.
KERR: We go around to each of the businesses and talk to them. “How did your sales compare to years past? How does it compare to a regular week for you?”
We feel a huge responsibility to these businesses and to this town, because we just want to deliver on what we’ve promised.
HOFFMAN: Collecting this kind of feedback doesn’t cost a lot. And it highlights just how valuable data can be if you’re measuring the right things, in the right way.
That’s why I believe in this simple mantra: no data, no scale. But not all data is created equal. So look for the most useful – and most cost effective – data you can, at each phase of growth.
Chapter 2: (The right) data is critical to scale
Here’s a hypothetical. Let’s say you’re a baker, and you’re trying to decide whether to open a bakery that only sells cake pops. You have a logo chosen, and a name – you’d call it the Pop Shop, naturally. You’ve perfected your recipe. But you want to know if the business is going to be viable.
So you reach out to some of your closest friends and family. It’s just a one-question survey: “If I made these cake pops, would you buy one?” Great news: every single person you talk to says yes! (Except your uncle, who says he’s watching his weight.) 9 out of 10 people think your cake pops will be bigger than gourmet donuts!
Well, sorry to burst your bubble, but that isn’t very useful data. Your friends and family may support you, but they’re not going to drive you to scale.
Okay, let’s try again. This time, you take the same question, and you survey 10 strangers. This time, every single person says no. You’re crushed until you learn that everyone you asked was a Type 1 diabetic.
This isn’t useful data either. Diabetics probably aren’t your intended audience. At least not until you perfect your low-sugar recipe.
All right, one more time. This time you’re really, really serious about gathering data. So you commission a survey of every single person in your city. No, the state! Let’s find out if they like cake pops!
I probably don’t have to tell you that that’s going to be a disaster. This time it’s too much data, expensive to gather … and a lot less practical than simply talking to another business owner who’s succeeded in this space.
The fact is: data is critical to scale. There’s really no path without it. But data can be expensive to gather and messy to interpret. So you need to gather information regularly, and strategically.
I wanted to talk to Sheila Lirio Marcelo about this because as the founder and former CEO of Care.com, Sheila scaled her business right past the competition by getting the right data at the right time.
Care.com is a two-sided marketplace connecting working families with care providers, from babysitters to nurse’s aides, tutors, petsitters, and house cleaners.
Sheila sees Care.com as a means to democratize childcare, and give women equal access to a career. But it wasn’t just a sense of purpose that drove Care.com to scale.
SHEILA MARCELO: I was very data-driven. It’s something I coach a lot of entrepreneurs, that you can have a great vision and idea, but start with a lot of data and testing.
Chapter 3: To pursue an opportunity… in coconuts
HOFFMAN: Sheila was born in the Philippines, the second-youngest of six. Her upbringing instilled in her some foundational principles – starting with one key data point.
MARCELO: What’s interesting about the Philippines, Reid, in the World Economic Forum report, is that it is the country with the narrowest gender gap in Asia. It has a very maternalistic culture. And my family reflected that.
HOFFMAN: Sheila’s parents were serial entrepreneurs. When she was just six years old, her family moved to Houston, Texas, to pursue an opportunity… in coconuts.
MARCELO: Coconut, as you know, in the Philippines is sort of our livelihood. We had plantations, we had trees, and just lots and lots of coconut. And so my dad said, “How do I extract oil from the coconut?” That led us to Houston in the 1970s, that there were expellers and technology there.
Well, we ended up staying. My parents fell in love with this country, and fell in love with entrepreneurship. They opened a lot of other businesses. But then later they sent us back to the province in the Philippines.
HOFFMAN: Why go back? Because the children, especially the two youngest, had gotten so accustomed to the U.S. that they had forgotten their first language.
MARCELO: One of the smartest things my parents did was send us back to the province to relearn the language, make sure that the culture was embedded in us as children.
Chapter 4: Unintended outcomes? Make a change
HOFFMAN: In this moment, Sheila’s mom and dad weren’t just acting like caring parents; they were also acting like entrepreneurs with new data. No matter how good their original mission was, once they saw the unintended outcomes of their decisions, they made a change. The data set was small, but decisive.
Sheila returned to the U.S. for college. There, she faced a decision that would shape her personal and professional mission… and give her a new data set to work from.
MARCELO: I went to a women’s college, and then I got pregnant between my sophomore and junior year. Mount Holyoke, the administration, and even my friends didn’t really know what to do with me as a young mom.
HOFFMAN: The way her professors and peers reacted to her decision foreshadowed the professional world she’d be entering as a young mother in the mid ’90s. Unlike in the Philippines, where it was quite typical for mothers to work outside the home, Sheila was looking at a playing field that was tilted against women who wanted both career and family. So when she interviewed for her first job as a strategy consultant, she adjusted.
MARCELO: I hid the fact, Reid, that I was a mom. I was too afraid to be judged and perceived as a young mother, because at that time, young fathers would be deemed responsible. Young mothers would appear distracted because there is the expectation we’re the primary caregiver. So I hid it. Of course that impacted my first job. I didn’t enjoy the environment because I couldn’t bring my whole self to work. That’s not a great feeling.
MARCELO: I joined a small company called Upromise, helping families save money for college. That’s where I got the vision of marketplaces and building them for families around what we call pain businesses. One of my mentors said, “Are you in building pleasure businesses like gaming companies, entertainment companies, or are you solving consumer pain?” I realized saving for college was not that fun, but yet it was a need.
HOFFMAN: At Upromise, Sheila learned a lot about getting data early, cheaply, and smart.
MARCELO: One of the things I learned at Upromise was this really light testing and multivariate testing.
Chapter 5: Getting the right information in the right ways
HOFFMAN: If you need a translation, that’s OK! Multivariate testing is a way to experiment with the layout and content of consumer interfaces, such as websites. It’s like A/B testing, with a few more letters mixed in. It lets you test more than one variable at a time, like mixing and matching which headline works best with which copy.
Light testing lets you gather information at relatively low cost, and a high ROI. All testing costs something, from collecting it to storing and analyzing it. So you want to be as active as you can in thinking about what data will help you at each next phase.
The Upromise experience taught her the value and practice of getting the right information in the right ways – by testing and iterating. And Sheila also learned something else. She loved helping build a company from the ground up.
MARCELO: I realized, wow, this is really fun. Company building is fun. But one of my mentors said, “You have to go learn again at another company before you become your own CEO.”
HOFFMAN: By now, Sheila and her husband had two young sons. They invited her father to move in and become the boys’ caretaker. But then, the family experienced a deeply personal setback.
MARCELO: My father fell ill when I was working at Upromise.
HOFFMAN: Besides being a scary time for Sheila and her family, her father’s illness meant that
MARCELO: In the care industry, we call this sandwiched, where you’re sandwiched between childcare and senior care.
Chapter 6: Solve a need that you yourself know inside and out
HOFFMAN: It was during this time that Sheila noticed something essential was missing in the care space.
MARCELO: I was challenged with finding great care using the yellow pages, but yet I was working at a tech company. Craigslist was just starting, and it wasn’t reliable. Newspaper classifieds were going away. Yellow pages were becoming non-existent. Where would you go? You’d get an 8.5 by 11 printed paper with those little fold things that you take out at the local library or YMCA or your church. And yet I was helping build a marketplace for college savings. I was like, yeah, there’s got to be a better solution.
HOFFMAN: With two young children, and an ailing father, Sheila was highly motivated to solve the sandwich problem.
And this drive to solve a personal struggle is actually common to many founders. It makes sense – if you’re going to start a company, why not have it solve a need that you yourself know inside and out. It means you’re highly motivated, and you understand the size and shape of the problem. You already have some data about the customer’s needs because that customer is you.
But be careful. This is also where a lot of entrepreneurs stumble. Because the next step is realizing that your experience isn’t universal. The customer might be you, but you aren’t the only customer. And you might not actually be the scale customer. Finding out who that scale customer is, is the job of data.
Sheila spent five years at Upromise, then briefly at a job marketplace site called The Ladders. Then, she was invited to become entrepreneur-in-residence at Matrix Partners. This would change everything.
MARCELO: I met our mutual friend, Nick Beim, who was on the board of The Ladders, who invited me to be an entrepreneur in residence at Matrix. I said, “What is that? I have no idea. Is that a role?”
Chapter 7: Asking smart people about your idea is the best deal on data you’ll ever get
HOFFMAN: Entrepreneur-in-residence is in fact a great role, and a great onramp to build a data-driven company.
MARCELO: There’s opportunities where they can help really pressure test the idea and help me with defining the total addressable market, was the business model sound, how do I think about the team building? So it was fantastic to get that level of support that I know a lot of entrepreneurs don’t. I felt a sense of privilege to have had that access and advice.
HOFFMAN: Notice what Sheila is saying here. Obviously, being in residence at a VC firm gave her access to capital, something so many entrepreneurs scramble to find. But she was equally grateful for the advice.
This is valuable data-gathering too. In fact, the one piece of advice I give most often to early-stage entrepreneurs is to go out and ask the smartest people you know, “What’s wrong with my idea? Why won’t it work?”
This response didn’t make me say, “OK, never mind.” Instead it showed me what my number-one obstacle was going to be. Asking smart people what’s wrong with your idea is the best deal on data you’ll ever get.
Sheila sought Nick Beim’s advice while she was at Matrix from the very beginning of her time there.
MARCELO: Before I accepted the job, I said, “So before I do this, I want you to know that I want to do something in the family healthcare space.”
HOFFMAN: Nick approved. And in 2006, Care.com was founded.
Sheila had her mission. She had the support of a venture firm. And she had insights into her customer, firsthand.
Now the real search for data would begin.
Chapter 8: The absolute centrality of data when it comes to scale
HOFFMAN: We’re back with Sheila Lirio Marcelo, founder of Care.com. If you’re enjoying this episode and want to share it with friends, send them the link: mastersofscale.com/marcelo. That’s M-A-R-C-E-L-O. And to hear my complete interview with Sheila, become a Masters of Scale member at mastersofscale.com/membership.
We’ve been talking about the absolute centrality of data when it comes to scale. Think of your company like a cake pop – and data as the baking powder that makes the dough rise.
But how do you get data when you’re first starting out, and you don’t have the instrumentation to gather large quantities of data? The answer is: look for useful and cost effective data that can be gathered by asking the right questions.
One question you’ll want to answer early is: what’s your total addressable market? And is that market ready for your product? Sheila set out to answer this quickly, and efficiently, by looking at what other people’s services were moving online.
MARCELO: I remember when Monster came out–
COMPUTER VOICE: Monster.com, a job search engine founded in 1999.
MARCELO: And everyone was suspicious. Would you ever post anything? I think your own creation of LinkedIn that you founded was another influence for us to say, “Wow, people are starting to be comfortable to do stuff online.”
Chapter 9: Gather the data with enough speed to be ahead of the competition
HOFFMAN: From observing these market trends, Sheila felt it was the right time for a care marketplace. But she wanted to see proof.
MARCELO: Sometimes you can come up with the best idea, but if the marketplace and the macro environment isn’t ready for it, even though the technology may be phenomenal, it’s just the consumer mindset. So I was following on the shoulders of amazing companies that had started to influence and change mindsets, that we were ready for a marketplace that was very personal.
HOFFMAN: But where can you go for the data that will help test your theory? And can you track it early enough to matter?
MARCELO: You can have a great vision and idea, but start with a lot of data and testing. And we were testing light.
HOFFMAN: Care.com was “testing light” partly out of necessity. Until you build your marketplace, you don’t have much access to user data. So Sheila also had her team do external data testing to find out which cities were most likely to have people source caregivers online.
MARCELO: So this is not that sexy and not super complicated technology. We hired 20 college interns and came in and analyzed Craigslist, honestly, and said, “Hey, where are the top 20 metros? What are the key care verticals? And educate us on supply and demand of both caregivers and families so that we have a thesis from the beginning.”
HOFFMAN: What I enjoy about this method is its simplicity. Hiring a small team of college students to study Craigslist is something you can stand up cheaply and fast – and get results fast too. It’s not just about getting data. It’s about getting data with enough speed to be ahead of the competition.
For this reason, marketplaces are tricky flywheels to get started – so you have to build them in places that are ready.
Once Sheila and her 20 interns had compiled their findings, they used it to determine which markets Care.com should pursue first.
MARCELO: We came together with a thesis. We picked 20 top metros from that analysis and testing.
We then built the algorithm across the country to grow the other areas that said, “When a certain ratio of caregivers came in, we would then turn on the payment platform, the pay side of credit card charging.”
So it was free for a period up until a certain ratio because one of the things we observed in the marketplace was the expectation of about 12 to 15 caregivers per family to result in a choice of interviews of three to four, that then they ultimately selected a caregiver. And understanding that data and that ratio in the marketplace was important.
Chapter 10: Who your customer is, and who your scale customer is, isn’t the same thing
HOFFMAN: There’s a lot of wisdom packed into these moves, so let’s break it down.
First, figuring out those first 20 metros and what the key care verticals were. There was a lot riding on that decision. A simple misjudgment could spell the death of the company. So not only was the data itself critical, but so was Sheila’s interpretation of it. Data gives you the tea leaves; it’s your job to read them.
And as Sheila says, she didn’t actually read all of them right.
MARCELO: I think we were too early for senior care. Certainly I saw it a decade later, but I had the thesis early, that we were ready. But childcare was definitely, I hit that one on the spot, but senior care I did not.
HOFFMAN: Yep. No, exactly. And one of the funny things about entrepreneurship is the general rule is ideally you’re two to three years in advance of the market.
MARCELO: That’s right.
HOFFMAN: You can survive five, and 10 is very, very difficult.
MARCELO: 10. Yeah. And thank goodness that we launched with numerous verticals. My thesis in senior care was amiss, but childcare really carried us through to actually then support senior care down the line.
HOFFMAN: Remember when we said that learning who your customer is and learning who your scale customer is isn’t the same thing?
Sheila had been all-in on senior care in part because it had been one of her own personal drivers in starting Care.com. But as it turns out, the scale market for senior care wasn’t ready, yet. Your user data is what gives you that snapshot. And the sooner that picture comes into focus, the sooner you’re able to pivot and direct resources elsewhere.
HOFFMAN: And with all the experience you have now, what would you have wanted to add into your founding moment, your initial strategy?
MARCELO: It was one that you challenged me on as an early investor, and I still get interviewed for this, and I share it. “Reid Hoffman really pushed me at the beginning to say: Should you charge or should you make it free in building marketplaces?” I do sometimes think if I could do it all over again per your advice, could we have just built the marketplace fast and then come back to the business model to even bigger liquidity?
And I wonder if that speed would have helped us, and just gathering the data and getting smarter faster.
Chapter 11: The more users you get, the more information you have
HOFFMAN: Anyone in the software business particularly will be familiar with this debate. Should your product be free? Or freemium? Or should you charge from the very beginning? But the same question applies to the intrepid cake pop founder. How many free samples can you afford to give away?
In software at least, I usually advocate for building your marketplace first. If your worries about getting to profitability means you start charging too soon, you may be cutting yourself off from future paying customers by missing the chance to win their love first. And, you’re cutting yourself off from data.
The more users you get, the more data you get about what your customer wants and doesn’t want. And the more information you now have to make critical decisions about the future.
But remember: that data often comes in messy, and incomplete. And even high volumes of data can miss spotting a challenge ahead.
Care.com launched in 2007 and had scaled massively by the time the company went public in 2014. But even with a high volume of users, split nearly evenly between caregivers and families, there was a change Sheila didn’t see coming.
MARCELO: I didn’t read mobile and on demand. And I know in talking to Sheryl Sandberg, this also surprised them at Facebook. But we were in a people service business, so my operations, we could not transition as quickly as a social media platform. So had I spent more time thinking through that, we would have changed a lot of things and not have gone public too early.
HOFFMAN: It is actually, in fact, one of the things that I think is a good general principle for entrepreneurs to say, “What are the macro trends?” Technology trends are a key one, mobile, Cloud, AI. And do they apply? And if we see those coming, what would that be? Actually, the world really sorted out between the people who really adjusted to mobile and didn’t, and it was a lot of tech companies–
MARCELO: That’s right.
HOFFMAN: Because the ones who did, great, and the ones who didn’t, had a lot of pain.
Chapter 12: Serve the chief household officer
HOFFMAN: Luckily, Care.com was able to weather the transition to mobile and on-demand. And, they made a point to scale safety features like advanced caregiver screenings to accompany the fast-paced nature of finding care on the fly.
But there was yet another metric that Sheila was tracking that mattered as much to her as any other.
HOFFMAN: I think you have been one of the leading voices and entrepreneurs on this topic, which is that businesses can be massive forces for social good, that aren’t just a function of, “Hey, we created a product or service,” or, “Hey, we create jobs,” which of course, those are social goods. But actually in fact, things that are fundamental to how society can become the way it should be, not just by economic productivity. And Care was a central part of that. The impact that you would expect from nonprofits, that’s the depth of impact, but with a scalable commercial model and with that all being driven to it.
Care was an economic imperative. I found that the definition of it for so many families is that if you had care, it would drive jobs and drive the economy. But yet we often describe it in the lens of something so soft, that care is love. And it’s often described as a gender problem, or it’s a female responsibility.
So I started to realize, wait a minute, I need to use my voice and my platform to redefine how care is deemed. So I started to talk really about Care driving jobs and that it was becoming an economic imperative.
HOFFMAN: Statistically, women are still more likely to be the primary caregivers in a household. So the more access to care they have, the more they can participate in the professional world, which drives the economy.
MARCELO: For me at Care, the engagement strategy was: the mom’s a chief household officer. What was going to help her achieve her aspirations? What were all the things that got in the way of her life that she needed to outsource? So that’s part of the reason we did pet care, we did senior care, we did tutoring, we did housekeeping.
HOFFMAN: But what became very apparent, very quickly, was that it would be important to consider the data on both sides of the care marketplace. Because if you empower one kind of working woman by leveraging another, that’s not only going to fail your social mission – it’s going to destroy one side of your business.
MARCELO: My mom called it out that the number one source of caregivers around the world that actually exports care is the Philippines.
Our culture is often described as very nurturing. So here I was saying, “Well, what am I doing to advocate also for caregivers, given who I am? So I started partnering as I researched this with an incredible friend of mine, Ai-jen Poo, with the National Domestic Workers Alliance, and started to realize, wow, we can use the platform of the company and my voice to advocate for caregivers too, not just for families to make care affordable and support them economically, and really enhance women as a contribution to society. But also, how do we serve the underserved? How do we make sure that the platform doesn’t accept any jobs below minimum wage?
Chapter 13: In a people service business, caregivers are your product
HOFFMAN: Once again, Sheila found a way to fact-find efficiently and strategically. By leveraging her partnership with Ai-jen Poo at the National Domestic Workers Alliance, Sheila was able to learn fast what steps she could take to serve the millions of caregivers in her marketplace. The problem had already been studied – so she could put solutions in place, fast. Not only wage protection, but something that had been missing in the freelance space for a long time.
MARCELO: Families could take a percentage of what they were paying Care and sweep it into Care money accounts that then could be used for groceries, pharmacy. We did this with MasterCard. We partnered with Noah at Stride Health and offered healthcare access.
We started to realize the vision of supporting the care infrastructure, in turn helped families and women drive jobs and ultimately drive the economy, which meant we were helping everybody.
HOFFMAN: What Sheila’s describing is the virtuous circle that’s in so many corporate mission statements. But marketplaces have a way of demonstrating with quantifiable data whether the vision is coming true.
HOFFMAN: Say a little bit more about paying attention to the creation of the marketplace, but as opposed to, as everyone who has an anticapitalist reflex kind of thinks, “Oh, you’re just trying to drive wages down and get labor cheaper.” No, no. We’re actually trying to create value and humanity across it.
MARCELO: They’re not diametrically opposed. If you really think long-term, and I’m talking to investors who are listening to this, creating a sustainable business where a gig economy, like care providers, have a true livable wage and a long-term profession means that the business will just continue to grow, the demand will just continue to increase, and the supply will be there to deliver on that demand.
Sometimes we think that investing extra, what they call extra, you could just cut it off and just drive profitability, is not too dissimilar in the analogies that I use in investing in a user experience that is focused on the long-term and not shortcuts. Sometimes I think that investment in other feature sets for the supply-side or the product is sort of deemed unnecessary because you’ve got to drive the short-term profit.
Sheila stepped down as CEO at the start of 2020, after Care.com’s sale to IAC.
Sheila is now a venture partner at NEA, investing in young companies that will need to learn all of these same data lessons. She was also named executive chair of The Wing, a startup membership organization with coworking spaces in major cities across the U.S. They were founded as a women-only network, but have since opened up to all genders.
And this year, Sheila helped form the inaugural board of The Asian American Foundation, or TAAF. You can hear our interview with the group’s founding President, Sonal Shah, on Masters of Scale Rapid Response. Go to mastersofscale.com/rapidresponse/shah. S-H-A-H.
TAAF formed this past spring in response to the spike in violence and harassment against the Asian American community – a spike, by the way, that you can see right in the data. Anti-Asian hate crimes rose nearly 150% in the U.S. in 2020, and in New York City, that number is 833%.
MARCELO: When I started Care, there was always a debate: Is it a nonprofit or a for-profit? Obviously I was trained in business, and I thought for-profit is really where it can make a broader impact. TAAF has really opened my eyes.
Chapter 14: The success of not-for-profits is measured less by earnings than by impact.
HOFFMAN: Just as we heard in the story of ArtFields at the top of the show, not-for-profits have to track data just as diligently as for-profits. Their success is measured less by earnings than by impact.
MARCELO: Just like Care.com, I thought about: how do I do things running a for-profit company with a social mission? This was actually the other direction, which was a nonprofit using for-profit principles to scale faster so that we can create impact for Asian Americans and Pacific Islanders.
We were like, “Hey, it’s a not-for-profit, but let’s use our entrepreneurial skills to be scrappy and get this off the ground.”
HOFFMAN: No one knows how to be scrappy better than entrepreneurs. But as Sheila and her cohorts build TAAF, they’ll need to keep relying on data to grow their mission.
Because no matter what type of organization you’re trying to build, there is no scale without data. So look for meaningful data wherever you can, at every step of your journey.
I’m Reid Hoffman. Thanks for listening.