Author Archives: Casey Winters

Align Revenue to the Value You Create

February 20th, 2018

“We want to create more value than we capture.”*

Tim Kendall, the former President of Pinterest, repeated those words at an all hands to describe our strategy for monetization a few years ago. My role as an advisor to Greylock’s portfolio companies allows me to work with many different types of businesses: consumer social, marketplaces, SaaS, etc. I’ve come to realize this saying describes an optimal strategy for a lot more than just an ad-supported revenue model. It should actually be the guiding light for most subscription software businesses.

Align Revenue To The Value You Create
One of the most common questions I receive from subscription businesses is when to ask for a signup and when to start charging customers. In freemium businesses, the slightly different question is how aggressively you upsell the paid product, and how good you make the free product. If you talk to entrepreneurs, you will get definitive answers from them, but they are frequently the opposite of each other. “You should never give away your product for free!” “You’ll never succeed without a free trial!” “Ask for credit card upfront! People won’t take the product seriously.” “Never ask for a credit card upfront! You’ll shoo too many people away.” The default answer I gave to entrepreneurs after hearing all of this feedback is that it depends on the business and needs to be tested.

As I researched more into the problem, these questions actually seemed to be the wrong questions to be asking. Harkening back to Tim Kendall’s advice, I started asking entrepreneurs, “What is the path to actually creating value from your service for your customers? How long does it take, and what actions need to be accomplished?” In other words, very similar advice to what is a successful onboarding? Once you learn that, you can determine how to capture some of the value you create.

Capture Value For The Business After Value Has Been Created For The Customer
When your product is subscription based, the prime time to ask for a subscription is after a successful onboarding occurs. It frequently is based on usage, not time. Dropbox is a famous example. The product is free up to a certain amount of storage. Once a user hits that amount of storage, they cannot add more files to Dropbox without paying. This storage amount also happens to be around the point where Dropbox becomes a habit, and represents real switching costs to find another way to share files across devices. So their conversion rates to paid are very high without any sort of time-based trial period. They don’t have a free product and a paid product; they have a free introduction to their paid product, and it becomes paid as soon as value has been created for the customer.

Your company may not have a long time to demonstrate value though, which may force your product to change to display (and capture) value more quickly. For startups based on search engine traffic, people reach your page with intent at that moment, and you frequently learn that this initial session is your only chance to convert them. So you push for a signup during that session after showing a preview of the value you can provide.

That is what we implemented at Pinterest, and it worked well, but it definitely created backlash from users for whom we had not yet created enough value. Once Pinterest was relevant on search engines for multiple topics, we saw people come back multiple times, and pulled back the signup walls on first visit. At that point, Pinterest was confident users would come back and thus focused on demonstrating more value before asking for signup.

Don’t Try To Capture Value In A Way That Reduces Value Created
It’s interesting to map the revenue growth of Dropbox to Evernote over the same time period. Evernote allows you to store an unlimited number of files and only makes you pay for advanced features like offline storage, storing large files, and (later) sharing on more than two devices. These features would have actually increased value created and switching costs if they were free, because Evernote’s value prop is about being able to access notes everywhere. If Evernote had instead mined their data and seen that people stick around after, say 50 notes, that would probably have had more effective monetization.

You only want to hide features from free users if they do not create habits or virality. Hiding sharing functionality before payment never makes sense because it introduces more people to the product for free. Hiding functionality that helps create retention also doesn’t make sense because you can always upsell retained users, but you can never upsell users who did not see the value and therefore don’t come back.

Decreasing Churn Is Long Term More Important Than Maximizing Conversion
Many people will decry that this strategy actually reduces revenue. In the short term, this sentiment is likely to be true. Decreasing churn might have a lower conversion rate upfront, but it aligns to long term successful retention. Churn rate is usually one of the biggest barriers to long term growth, so it’s worth thinking about this type of strategy even if it has a short-term decrease in revenue. It can be much harder to re-acquire someone after they have canceled, than charge someone for the first time who has been receiving regular value because you charged them for value you didn’t create.

What usually happens when a company captures more value than they create is they will have high revenue growth for a period of time (with a lot of investor enthusiasm), followed by a flattening of growth and then a steep revenue decline. This happens because revenue growth is a lagging indicator. Usage growth is the leading indicator. When usage lags revenue, this predicts churn. As you churn more and more users, it becomes harder and harder (and eventually impossible) to replace those churned users with new users to keep revenue metrics flat. Look at Blue Apron’s valuation to see this playing out currently as subscribers start to decrease for the first time year over year.

You Want Your Revenue Model To Align As Closely As Possible To The Value You Create
Lastly, as you start charging customers to capture value you create, you want your business model to align to the value that is being created. Email marketing tools have mastered this. Email marketing tools’ value is based on reaching customers with messages. Most email marketing tools charge on a CPM (i.e. a price for every thousand emails you send via their platform). As your email volume increases, they continue to drop the CPM. This make these companies more money because customers are sending a lot more email over time. But it actually becomes more valuable to the customer as well, because email is now cheaper on a per unit basis to send.

Compare this to Mixpanel, a product analytics tool. Mixpanel charges per event, and their value is delivering insights based on data from events being logged on your website or mobile app. The more events that are tracked in Mixpanel, the more insights the customer can receive, and the stickier the product. Since Mixpanel is charging per event though, a weird calculus emerges for the customer. The customer has to ask if tracking this event is worth the cost because not all events are created equal. Meaning the customer has to decide which data is important before they use the product. So, Mixpanel’s revenue model actually hurts its product value.

— 

It’s easy for subscription businesses to get attracted to the allure of short term revenue. The goal of your business is first to create value. The creation of that value and the understanding of how it’s created allow for more optimal and sustainable revenue generation opportunities. Don’t pursue short term revenue opportunities that prevent the customer from understanding the value your company creates. When you are generating revenue, you want to align that revenue model to how value is created for your customer. If you’re not sure, err on the side of creating more value than you capture rather than the opposite. This leads to long term retention and the maximization of revenue.

Naomi Ionita, General Partner at Menlo Ventures and former growth leader at Invoice2go and Evernote, and I talk more about this and other subscription growth problems in the Greymatter podcast.

*This quote I believe originally stems from Tim O’Reilly.

Currently listening to Shape the Future by Nightmares on Wax.

Getting Smart About Growth Podcast with Andrew Chen

February 5th, 2018

Andrew Chen recently wrote a blog post about how growth is getting harder. I invited Andrew to the Greymatter podcast to chat more about why growth is getting harder, and more importantly, what to do about it.

We talk about how viral growth is on the decline in consumer, but not in B2B, and how to leverage paid referrals effectively. We also walk through trends in paid acquisition, how to find your first channel of growth, and much more.

The iTunes link is here, and here is the Soundcloud link for email readers.

What Are Growth Teams For, and What Do They Work On?

January 2nd, 2018

This blog post was adapted from a presentation I did recently. Hence, slides. Don’t say I didn’t warn you.

I receive a lot of questions about growth teams. Naturally, there is a lot of confusion. Is this marketing being re-branded? Who does this team report to? What is the goal of it? What do they actually work on? When do I start a growth team for my business?

The purpose of growth is to scale the usage of a product that has product-market fit. You do this by building a playbook on how to scale the usage of a product. A playbook can also be called a growth model or a loop.

The first question you should ask before asking about growth is if you have product-market fit?

The traditional definition above is qualitative, and if you’re like me, you like to have data to answer questions. The best way to get that data for most businesses is to measure retention.

The best way to identify the key action is to find a metric that means the user must have received value from your product. The best way to understand the frequency on which you should measure that metric is how often people solved this problem before your product existed. Let’s look at some examples from my career.

For Pinterest, a Pinner receives value if we showed them something cool related to their interests. The best way to determine if the Pinner thought something we showed them was cool is that they saved it.

For Grubhub, this was even easier to determine. People only receive value if they order food, and when we surveyed people, they ordered food once or twice a month (except for New York).

Once you have a key metric and a designated frequency, you can graph a retention curve or a cohort curve. If it flattens out, that means some people are finding continual value in the product. But that is not enough.

Brian Balfour has a great post on this, which he calls product-channel fit.

If you’ve been around startups for a while, you might remember this tweet from Paul Graham. It talked about the fastest growing startup Y Combinator has ever funded. It is a graph of revenue growth from $0 to $350,000 per month in just 12 months.

The startup was Homejoy, an on demand cleaning service. Investors liked this graph, so they gave the company $38 million to expand.

20 months later Homejoy shut down. From a post-mortem of the company, I highlight the following quote.

If you discounted to get to product-market fit, you didn’t get to product-market fit. Product-market fit is not revenue growth, it’s not growth in users, it’s not being #1 in the App Store. Product-market fit is retention that allows for sustained growth.

So, I though product teams were in charge of creating a product people loved, and marketing teams were in charge of getting people to try the product. What changed?

What changed is an acknowledgement of what actually drives startup growth. There are three main levers. Phase I is simultaneously the most important and the least understood. In Phase I, you change the product to increase its growth rate. Some changes include improving onboarding, helping the product acquire more customers through activities like virality or SEO, incresing the conversion rate, et al.

These initiatives are “free” in that they don’t require an advertising budget. Their cost is the opportunity cost of a product team’s time. They are measurable in that you can create an experiment and understand the exact impact of the change. They are also scalable in that if you make a change that, say, improves your conversion rate, and it has a certain amount of impact, it likely will have that same impact tomorrow, weeks from now, and potentially even years from now.

The other two phases are what we traditionally think of as marketing. Performance marketing initiatives, like buying ads on Facebook or Google, are also measurable and scalable, but scale with an advertising budget. Brand marketing usually requires an even larger ad budget, and is harder to measure or scale. The time frame over which brand marketing works takes years, and can be hard to confirm. If you do create a PR campaign or a TV ad that seems to work on a more immediate time frame, it can be hard to scale. that is because brand marketing always requires new stories to keep people’s attention.

This is why marketing can’t be in charge of all growth initiatives. They don’t have access or capability to the most important ones. They might know they need to improve the site’s conversion rate or get more traffic from referrals, but they don’t have access to the product roadmap to get them prioritized appropriately, and if they do get engineering and design help, they don’t have the expertise in working with them to build the best solutions.

Perhaps what’s more important to understand in the difference between marketing and growth is how the traditional marketing funnel changes with startups. Above is the traditional marketing. This model is based on the old school model of product development before the internet in spending a lot of money to make people want things.

Startups by definition should be making things people already want. When you do that, you can invert the funnel and focus on people that already want the product or people that are already using it. This is more effective on a small (or no) budget.

When you translate that into tactics, you see how product-driven growth initiatives dominate the top of the list of priorities. It does not mean you won’t work on performance marketing or brand marketing, but that they usually become important later on in a product lifecycle as an accelerant to an already sustainably growing company.

So I spent a lot of time explaining why growth is different from marketing. How is different from product?

Growth teams don’t create value. They make sure people experience the value that’s already been created.

The most common examples to start a growth team to address are:

  • improving the logged out experience (for conversion or SEO)
  • sending better emails and/or notifications
  • increasing referrals or virality
  • improving onboarding

SEO and onboarding are harder places to start because their iteration cycles are much longer than the other areas.

Growth teams don’t start by finding mythical VP’s of Growth to come in and solve all of your problems. They are usually started by existing employees at a company (or founders) that really understand the company and what’s preventing it from growing faster. They report to their dedicated functions, but sit together to focus on problem solving.

To find out which area you work on after you have the team, you have to analyze the data. For example, at Pinterest, they originally wanted me and my team to work on SEO. What we saw was that while there was a lot of opportunity to get more traffic via SEO, a bigger issue was the conversion rate from that traffic. So we decided to work on conversion instead.

Then we had to figure out what to work on. Jean, an engineer on the team, had recently run an experiment that gave us a key insight. So, we said, we could use this same modal when people clicked on Pins. Clicking on a Pin could show enough interest in Pinterest for you to want to sign up.

The other thing people did when they liked what they saw scroll to see more. So, we decided to try stopping them where we stopped the Google crawler, and asking them to sign up then.

It took Jean two days of work to launch this experiment, and it resulted in a much bigger impact than expected.

So that’s an example of finding a conversion issue in you data, and putting together a really scrappy experiment to try to improve it. What else can growth teams work on? Here are some examples from my time at Pinterest, and some best practices we’ve learned.

Usually, the biggest area a growth team focuses on improving is retention. That’s right; growth teams are not just about acquisition. Retention comes from a maniacal focus on improving the core product, which I define as core product, not growth, work. Where growth comes in is reducing friction to experience that core product. Simplifying how the current product works usually has much more impact than adding new features. New features complicate the product, making it harder for new people to understand.

So how do you simplify the core product? Well, you have to have data to understand what people do, and pair it with qualitative research to understand why they do it. We spent countless hours at Pinterest putting laptops in front of non-users watching them sign up for the product to figure out why people didn’t activate.

At Grubhub, data pointed out that Grubhub was an S curve when it came to both conversion and retention. This graph is a (now very old) graph of conversion rate in Boston based on how many restaurants Grubhub returned when you searched your address. After 55 results, conversion rate essentially doubled for new and returning users.

Qualitative research gave us different insights. When we asked users why they didn’t use Grubhub more often, they would say, “it’s expensive.” We thought that was weird, because Grubhub wasn’t charging them anything. What they meant is that delivery was expensive due to minimums and delivery fees. So, we went back to our restaurants, convinced a few to try lowering their minimums and fees to see if increased volume could make up for lower margin. When it did, we creates case studies to help convince other restaurants.

At Pinterest, we simplified the signup and onboarding flow. What used to be a flow that required five steps was now three with one of them pre-filled and the other two optional. What we did do was introduce friction that we knew made it more likely a Pinner would find content they care about. This was asking them which topics interested them before showing them a feed of content.

We also realized that the more content people see, the more likely they will find something they like, which will lead to retention. So, we removed content around Pins that was non-critical, like who Pinned it to what board and how they described it. All of these increased activation rates.

We also contextually educated people on what to do next when they were onboarding. There is a common saying that if you need to add education to your design, it’s a bad design. It’s pithy and sounds smart, but it’s actually dangerous. My response is that a design with education is better than a design that doesn’t educate.

Search engine optimization has been a really great lever for organic growth for every company I’ve worked on in my career. It’s not for every business though. People need to already be searching for what you do. That alone isn’t enough though. You need to be an authority on the subject, which Google determines by relevant external links to your domain and your content. You also need to be relevant to what was just searched.

We worked on improving both of these at Grubhub. When Grubhub launched new market, by definition we weren’t locally relevant yet. So we would go to local blogs and press outlets and tell them we were launching there, and that we wanted to give their readers $10 off their first order. All they had to do was link to a page where the discount would auto-apply. After a while, that page would have enough local links so that even though the promotional discount was over, it would still rank #1 for the local delivery terms e.g. “san francisco food delivery”.

For relevance, Grubhub knew which restaurants delivered where, their menu data, and reviews from real people. So we aggregated them into landing pages for every locale + cuisine combination e.g. ‘nob hill chinese delivery”.

We applied the same landing page strategy at Pinterest. While Pinners had created boards on their favorite topics, it was one person’s opinion on what was relevant for a topic. Pinterest has repin data globally for every topic, so we knew what the best Pins were across the Pinterest community. So we created topic pages with the best Pins, and they performed better than individual boards on search engines and with search engine users.

We also worked a lot on emails and notifications on the Pinterest growth team. Emails are a key driver of retention. They won’t solve your retention problem, but they will certainly help if you do them right. At every company I have been at, people hated email and didn’t want to send them to their customers. When they finally did, they saw lifts. You are not your customer. You get more email than they do. Emails help them if they’re connected to the core value of why they use your product. Emails are not helpful if they’re pushing a marketing message.

At Pinterest, I made this mistake. I set up campaigns with emails that explained all of the things Pinterest could do. People don’t care about what Pinterest can do. They care about seeing cool content related to their interests. We needed to stop sending email like a marketer, and start sending email like a personal assistant. So we replaced those emails with popular content in topics of interest for each Pinner, and our retention increased.

Then, we built a system around it. Each Pinner likes different content, at different times, and different amount of it. So we learned for each Pinner what content they liked, when they liked to receive emails and notifications (based on when they opened them), and how much they liked to receive based on testing different volumes and seeing open rate impacts.

If you’re testing emails and notifications, you can test manually first, then automate and personalize. What I have learned at Pinterest and Grubhub is what seems to be worth testing. At Pinterest, one engineer tested 4,500 different subject lines, resulting in hundreds of thousands of additional weekly active users. Around the same time, we spent three months redesigning all of our emails, and it had no impact on usage.

A common issue I see with growth and marketing teams is they think that emails and notifications can only have positive impact. This is not true. You have to measure the lift in usage vs. the unsubscribes (and the impact of an unsubscribe) and app deletions. Those will impact usage, and you need to know how.

Growth teams have a clear purpose, and that purpose makes sense only if you have first found product-market fit. Once you have that, you will find traditional product and marketing lacking in their ability to help scale usage of your product. That’s where growth teams come in. Growth teams use data and qualitative research to help understand the frictions that prevent more people from finding the value in your product. That can mean acquisition, but it can also mean reducing friction in the core product, working on conversion or onboarding, or finding ways to remind existing users about the value you’re creating. If you have questions about growth teams, don’t hesitate to reach out to cwinters@greylock.com.

This presentation was made in conjunction with @omarseyal, who is awesome.

Currently listening to Everybody Works by Jay Som.

Four Strategies to Win Big with Low Frequency Marketplaces

November 16th, 2017


Frequency creates habit which creates loyalty which creates profit. Uber and Lyft are successful because consumers need to get from A to B multiple times a day, forming habits that lead to long (and high!) lifetime values. Grubhub similarly benefited from people eating more than once per day.

But there aren’t that many business opportunities that have daily — or even weekly — frequencies. And those spaces have become very competitive. For example, how many food delivery companies can you name? Now add in groceries or meal kit cooking companies. All that just for the “eating” use case.

What if the natural frequency of use for a transactional business is low, like buying a house, selling a car, or booking a trip? How do you create a successful business if ideal frequency is quarterly or yearly or even once every few years? You would be unlikely to create a habit or loyalty, much less get the customer to remember your brand name. That is usually the case. If you don’t create loyalty, then you usually have re-acquire consumers when the need eventually arises again. This hurts customer acquisition costs and lifetime value. This fact makes building a successful business with low frequency extremely difficult.

With a low frequency business, you usually need to have a high average selling price to make up for the lack of frequency. While an order on Grubhub may cost you only $25, the average transaction size on Airbnb is hundreds of dollars. But a high average selling price alone is not enough to become a massively successful business. I’ve seen four distinct strategies for how to thrive in low frequency marketplaces. They all revolve around being top of mind when the transactional need occurs, no matter how infrequent that need is. I’ll start by talking about the most common approach, and then lead into some that are actually more valuable and defensible.

The Expedia Model (AKA SEO)
Companies that pursue this model: Thumbtack, Expedia, Apartments.com, WebMD

My first job was at Apartments.com. We were a classic low frequency marketplace. People search for apartments at most once a year, and there isn’t a whole lot of value you can provide in between apartment searches. So what did we do at Apartments.com? If you do not create habits or loyalty with initial use, users go back to the original way they solved the problem last time. Where do people go where they are searching for help renting an apartment? Usually, Google. So, the Apartments.com strategy was to rank well organically on Google so when people did search again for an apartment, they’d be likely to see us and use us for their search again.

SEO can be a very successful strategy, but the entire company has to be geared around success on Google. This strategy is also susceptible to platform shifts, like Google algorithm changes or Google deciding to compete with you. It also tends to shift companies toward portfolio models at scale. This is why Expedia owns Hotels.com, Orbitz, Hotwire, Travelocity, and Trivago, and why Priceline owns Booking.com and Kayak. When you rank #1 for your main keywords, the only way to grow is to own the #2 and #3 spots as well.

The Airbnb Model (AKA Better, Cheaper)
Companies that pursue this model: Airbnb, Rent The Runway, Poshmark

Sarah Tavel wrote a post about products that are 10x better and cheaper than their alternatives. You can definitely pursue this strategy even if you have low frequency. Airbnb was significantly cheaper than hotels, and many people, once they experienced Airbnb, found it a better experience as well. It was a more unique listing, in a “more real” part of the city, and they had a connection to a local. So, even though people only travel once or twice a year on average, when they do, they remember the Airbnb experience and start there directly instead of on Google, competing with the SEO behemoths of Expedia and Priceline.

Finding this level of differentiation in different industries is not easy, but worth contemplating. Airbnb is not the only startup that has entered a crowded space and grown rapidly by figuring out how to be 10x better and cheaper. RentTheRunway allows you to access high quality fashion without the high price, and without storing it, because dressing up is increasingly a low frequency occurrence.

The HotelTonight Model (AKA Insurance)
Companies that pursue this model: HotelTonight, One Medical, Lifelock, 1Password

There are certain businesses that are needed infrequently, but when they are needed, they are needed with great urgency. Example spaces include urgent care, being stuck in a random city unexpectedly, and fraud alerts. The key here is that someone keeps the app or account live despite a lack of usage because the fear of when it might be needed is so great. This is a hard strategy to pursue, but once the value prop is established, these companies remain sticky despite their lack of frequency.

The Houzz Model (AKA Engagement)
Companies that pursue this model: Houzz, Zillow, CreditKarma

Contrary to what many might think, keeping users engaged in a low frequency business is indeed possible: the key is a non-transactional experience. Many of these approaches have a “set and forget” component to them where they reach out with pertinent information in a more frequent way. Zillow is the first example I can remember that utilized this strategy. Even when not actively looking for houses to buy, Zillow kept users engaged by valuing their existing homes via the zestimates. Even when not actively looking for houses to buy, Zillow kept users engaged by valuing their existing homes via the zestimates. CreditKarma reaches out with alerts and monthly credit check updates.

Houzz is a great example that is more recent. People remodel and redecorate their homes infrequently, but they are inspired more regularly. Houzz has a great product that shows home inspiration that can be saved and discussed, and when needed, but much more rarely, transacted.This is a product people engage directly with in instead of having to have content pushed to them

For this strategy to work, you essentially build a second product that enables frequent engagement — not a transactional product. Engagement strategies for low frequency marketplaces take advantage of an inherent human desire to stay up-to-date on things important to them. This won’t work for all industries. We actually tried this at Apartments.com, but were not successful because renters don’t care as much about investing in their living situation as homeowners.

A common confusion is that loyalty programs are an example of this. What loyalty programs usually do is increase frequency or target users that have high category frequency, like business travelers in the travel segment, rather than create loyalty from infrequent users. It is still a very valuable strategy, and I have blogged about loyalty programs if you want to learn more.

Of the four models I wrote about above, you will notice that not one of these is a brand model. Many of the sites listed in the SEO model have spent hundreds of millions of dollars building brands. Yet most travel searchers still start with Google. Brand is an extension of the Airbnb model, not its own strategy. If the product doesn’t deliver on a differentiated experience, brand building usually does not create loyalty.

So, if you’re building a low frequency business, do not dismay. There are many paths to still becoming a very large and differentiated business. These strategies are difficult but very rewarding if they are executed well.

Currently listening to Take Me Apart by Kelela.

Why Focus Is Critical to Growing Your Startup, Until It Isn’t

October 23rd, 2017

When I was a teenager, I told my dad about a friend and his dad and how they had seven businesses. He immediately replied, “And none of them make money.” I thought it was an extremely arrogant thing to say at the time, but later, I realized it might be the smartest piece of advice he ever gave me.

When I joined Grubhub, I quickly noticed the founders were incredibly good at staying focused. They said we were building a product for online ordering for food delivery — and only delivery — not pickup, not delivery of other items, not catering, and that’s all we would do for a long time. I remember thinking, “but there’s so much we could do in [XYZ]!” I was wrong. By staying focused on one thing, we were able to execute technically and operationally extremely well and grow the business both very successfully and efficiently. When we added pickup functionality four years later, it proved not to be a very valuable addition, and hurt our conversion rate on delivery.

If you have product/market fit in a large market, you should be disincentivized to work on anything outside of securing that market for a very long time. There is so much value in securing the market that any work on building new value propositions and new markets is destructive to securing the market you have already validated.

There is an interesting switch in the mindset of a startup that needs to occur when a startup hits product/market fit. This group of people that found product/market fit by creating something new now have to realize they should not work on any new value propositions for years. They now need to work on honing the current product value or getting more people to experience that value. Founders can easily hide from the issues of a startup by working on what they’re good at, and by definition, they’re usually good at creating new products. So that tends to be a founder’s solution to all problems. But it’s frequently destructive.

If a product team can work on innovation, iteration, or growth, they need to quickly shift on which of those they prioritize based on key milestones and value to the business. In this scenario, it’s important to define what innovation, iteration, and growth mean. In this context:

  • Innovation is defined as creating new value for customers or opening up value to new customers. This is Google creating Gmail.
  • Iteration is improving on the value proposition you already provide. This can range from small things like better filters for search results at Grubhub to large initiatives like UberPool. In both cases, they improve on the value proposition the company is already working on (making it easier to find food in the case of Grubhub, and being the most reliable and cheapest way to get from A to B in the case of Uber).
  • Growth is defined as anything that attempts to connect more people to the existing value of the service, like increasing a product’s virality or reducing its friction points.

I have graphed the rollercoaster of what that looks like below around the key milestone of product/market fit.

Market Saturation
The time to think about expanding into creating new value propositions or new markets is when you feel the pressure of market saturation. Depending on the size of the market, this may happen quickly or slowly over time. For Grubhub, expansion into new markets made sense after the company went public and had signed up most of the restaurants that performed delivery in the U.S. The only way the company could continue to grow was to expand more into cities that did not have a lot of delivery restaurants by doing the delivery themselves.

All markets are eventually saturated, and that means all growth will slow unless you create new products or open up new markets. But most entrepreneurs move to doing this too early because it’s how they created the initial value in the company. Timing when to work on iteration and growth and when to work on innovation are very important decisions for founders, and getting it right is the key difference to maximizing value and massively under-performing.

B2B Growth Podcast with Naomi Ionita

August 14th, 2017

Naomi Ionita, VP of Growth at Invoice2go and formerly Director of Growth at Evernote, joins me to discuss the growth B2B startups that grow more like consumer businesses. We discuss topics like how to monetize your product in general, converting new customers to paying customers, and preventing churn.

The iTunes link is here, and here is the Soundcloud link for email readers.

Why Onboarding is the Most Crucial Part of Your Growth Strategy

July 18th, 2017

When people talk about growth, they usually assume the discussion is about getting more people to your product. When we really dig into growth problems, we often see that enough people are actually coming to the products. The real growth problems start when people land… and leave. They don’t stick. This is an onboarding problem, and it’s often the biggest weakness for startups. It can also take the longest to make meaningful improvements when compared to other parts of the growth funnel.

In my role as Growth Advisor-in-Residence at Greylock, I talk to startups in the portfolio about getting new users to stick around. Through many failed experiments and long conversations poring over data and research, I have learned some fundamental truths about onboarding. I hope this can function as a guide for anyone tackling this problem at their company.

What is Successful Onboarding?
Before you can fix your onboarding efforts, you need to define what successful onboarding is to you. What does it mean to have someone habitually using your product? Only then can you measure how successful you are at onboarding them. To do so, you need to answer two questions:

  • What is your frequency target? (How often should we expect the user to receive value?)
  • What is your key action? (The action signifies the user is receiving enough value to remain engaged)

To benchmark frequency, look at offline analogs. At Grubhub, we determined how often people ordered delivery by calling restaurants. The answer was once or twice a month, so we used a “once a month” as a benchmark for normal frequency for Grubhub. At Pinterest, the analog was a little harder to determine, but using Pinterest was most like browsing a magazine, which people read weekly or monthly. So we started with monthly, and now they look at weekly metrics.

Identifying the key action can be easy or hard — it depends on your business. At Grubhub, it was pretty easy to determine. You only received value if you ordered food, so we looked at if you placed a second order. At Pinterest, this was a little harder to determine. People derive value from Pinterest in different ways, from browsing lots of images to saving images to clicking through to the source of content. Eventually, we settled on saving (pinning an image to your board), because, while people can get value from browsing or clicking through on something, we weren’t sure if it was satisfying. You only save things if you like them.

Once you know your key action and your frequency target, you have to track that target over time. You should be able to draw a line of all users who sign up during a specific period, and measure if they do the key action within the frequency target after signup. For products with product/market fit, the line flattens as a percentage of the users complete the key action every period:

If the line flattens rather quickly, your successful activation metric is people who are still doing [key action] at [set interval] at [this period after signup]. So, for Pinterest, that was weekly savers four weeks after signup. If your cohort takes a longer time to flatten, you measure a leading indicator. At Grubhub, the leading indicator was a second order within thirty days of first order.

How should you research onboarding?
You can break down cohort curve above into two sections. The part above where the curve flattens are people who “churn”, — or did not receive enough value to make the product a habit. The people below where the curve flattens have been successfully onboarded.

To research onboarding, talk to both groups of people to get their thoughts. I like to do a mix of surveys, phone calls, and qualitative research using the product. I usually start with phone calls to see what I can learn from churners and activators. Our partner Josh Elman talks about best practices to speaking with churners, or bouncebacks. If I am able to glean themes from those conversations, I can survey the broader group of churners and activators to quantify the reasons for success and failure to see which are most common. (Sidenote: You’ll need to incentivize both groups to share their thoughts with you. For those that didn’t successfully activate, give them something of value for their time, like an Amazon gift card or money. For those that did, you may be able to give them something free in your product.)

But it is not enough to just talk to people who already have activated or churned. You also want to watch the process as it’s happening to understand it deeper. In this case, at Pinterest, we brought in users and watched them sign up for the product and go through the initial experience. When we needed to learn about this internationally, we flew out to Brazil, France, Germany and other countries to watch people try to sign up for the product there. This was the most illuminating part of the research, because you see the struggle or success in real time and can probe it with questions. Seeing the friction of international users first hand allowed us to understand it deeper and focus our product efforts on removing that friction.

The principles of successful onboarding
#1: Get to product value as fast as possible — but not faster
A lot of companies have a “cold start problem” — that is, they start the user in an empty state where the product doesn’t work until the user does something. This frequently leaves users confused as to what to do. If we know a successful onboarding experience leads to the key action adopted at the target frequency, we can focus on best practices to maximize the number of people who reach that point.

The first principle we learned at Pinterest is that we should get people to the core product as fast as possible — but not faster. What that means is that you should only ask the user for the minimum amount of information you need to get them to the valuable experience. Grubhub needs to know your address. Pinterest needs to know what topics you care about so they can show you a full feed of ideas.

You should also reinforce this value outside the product. When we first started sending emails to new users at Pinterest, we sent them education on the features of Pinterest. When Trevor Pels took a deeper look at this area, he changed the emails to deliver on the value we promised in the first experience, instead of telling users what we thought was important about the product. This shift increased activation rates. And once the core value is reinforced, you can actually introduce more friction to deepen the value created. When web signups clicked on this content on their mobile devices, we asked them to get the app, and because they were now confident in the value, they did get the app. Conversely, sending an email asking users to get the app alone led to more unsubscribes than app downloads.
Many people will use this principle as a way to refute any attempts to add extra steps into the signup or onboarding process. This can be a mistake. If you make it clear to the user why you are asking them for a piece of information and why it will be valuable to them, you can actually increase activation rate because it increases confidence in the value to be delivered, and more actual value is delivered later on.

Principle #2: Remove all friction that distracts the user from experiencing product value
Retention is driven by a maniacal focus on the core product experience. That is more likely to mean reducing friction in the product than adding features to it. New users are not like existing users. They are trying to understand the basics of how to use a product and what to do next. You have built features for existing users that already understand the basics and now want more value. New users not only don’t need those yet; including them makes it harder to understand the basics. So, a key element of successful onboarding is removing everything but the basics of the product until those basics are understood. At Pinterest, this meant removing descriptions underneath Pins as well as who Pinned the item, because the core product value had to do with finding images you liked, and removing descriptions and social attribution allowed news users to see more images in the feed.

Principle #3: Don’t be afraid to educate contextually
There’s a quote popular in Silicon Valley that says if your design requires education, it’s a bad design. It sounds smart, but its actually dangerous. Product education frequently helps users understand how to get value out of a product and create long term engagement. While you should always be striving for a design that doesn’t need explanation, you should not be afraid to educate if it helps in this way.

There are right and wrong ways to educate users. The wrong way: show five or six screens when users open the app to explain how to do everything — or even worse, show a video. This is generally not very effective. The right way: contextually explain to the user what they could do next on the current screen. At Pinterest, when people landed on the home feed for the first time, we told them they could scroll to see more content. When they stopped, we told them they could click on content for a closer look. When they clicked on a piece of content, we told them they could save it or click through to the source of the content. All of it was only surfaced when it was contextually relevant.

Onboarding is both the most difficult and ultimately most rewarding part of the funnel to improve to increase a company’s growth. And it’s where most companies fall short. By focusing on your onboarding, you can delight users more often and be more confident exposing your product to more people. For more advice on onboarding, please read Scott Belsky’s excellent article on the first mile of product.

Currently listening to Easy Pieces by Latedeuster.

Starting and Scaling Marketplaces Podcast

July 10th, 2017

Brian Rothenberg, VP & GM at Eventbrite, and I discuss how to start and scale marketplaces. We discuss certain topics such as the chicken and egg problem, going horizontal vs. vertical at the beginning, and traditional and non-traditional growth tactics to grow marketplaces. You can check it out below or read the summary here.

The iTunes link is here, and here is the Soundcloud link for email readers.

The Right Way to Involve a Qualitative Research Team

June 12th, 2017

Most teams significantly under-invest in qualitative research. Growth teams especially are all about data, but they think that data can only come from experiments. This can make teams overly reliant on what they can learn from experiments and the quality of the data they have, and under-invest from what they can learn from talking to users. This problem is usually exacerbated by the fact that existing researchers at startups aren’t usually assigned directly to teams or work independently. I’ll talk about some of the problems I’ve seen, and the right way to invest in qualitative research for your growth team.

Learning and Applying from Research
Using the right type and method for your question is key. Of course, qualitative research is one component of the research stack along with quantitative research and market research. There is also different types of qualitative research depending on what you are trying to learn.

I remember when I was at Apartments.com and went to my first focus group, a common type of qualitative research. It was a mess for multiple reasons. The first reason was structure. Finding an apartment is not a large social behavior, so why were we talking with a group of ten strangers at once? As what I later learned usually happened, one or two participants volunteered the majority of the feedback, so while we paid for ten people’s opinions, we really only received two people’s opinions. So, I now only do research with multiple people in the room if it’s a social product, and it’s a group that would use it togethers e.g. friends or co-workers.

The second issue was delivering the feedback to people who weren’t there. I wrote up a long perspective on what the issues were with Apartments.com vs. our competitors. It primarily included product feedback on why we were getting crushed by Craigslist in major cities. I sent it to my VP and received a one sentence reply, “Don’t get ahead of yourself.” What a waste of time, I thought. We do all this research, generate real insights, and no one’s interested.

I’ve now learned that research teams inside companies feel this every day. At Pinterest, we had an amazing research team, but they were originally a functional team, which meant they had to determine their own roadmap of what to research. Depending on the stakeholders you listen to, this can be broad strategic projects like “What is the deal with men?” to specific projects like “Help us test this new search flow already built.” Research can add value at both stages, so the team worked on both.

What I think research found when they worked on the broader strategic issues was similar to my response at Apartments.com. “Cool, but not my roadmap!” say the product managers. Research then gets filed away never to be looked at again. Researchers get very frustrated. To be clear, this is a failure of leadership — not the product teams — if these areas aren’t prioritized. But it is common. On the flipside of working on something already built, success was more variable based on how well the product team defined what they wanted to learn. Frequently, what the product team wanted to learn was that they could ship it, so they selectively listened to feedback to things that indicated they were on the right path.

What I have learned suggests that qualitative research cannot be effective unless 1) its people are dedicated a cross-functional product team and 2) research is involved throughout the entire product development process, from initial research on market to determining a strategy to testing concepts to testing nearly finished products. The value of research accrues the more it is a part of each step in the process.

This approach solves for two main problems. One is that product teams will only pay attention to feedback that is directly related to their current product and on their own timeline. Without being part of the cross-functional team that includes product, engineering, and design, it is hard for research to to be on the same timeline. The second problem this solves is it helps research prevent the rest of the team from locking on assumptions that they may be wrong, so they are focused on the right solution to the problem with research, instead of confirmation bias at the end of a project. The Pinterest team has moved to this model, and for my teams, it made both sides much more successful.

When to Research and When to Experiment
For teams that rely too much on experiments and not enough on research, I tell them two things:

  • Experiments are great for understanding what people do and don’t do. Research helps you understand why they do or do not do those things
  • Experiments don’t help you understand the under-represented groups that might be the most important to learn from e.g. non-users or smaller segments of users

A great way to get started with research as a team is to answer why your experiment didn’t work. Sometimes, the answer is there in the experiment data, but frequently it is not. You have to talk to users to understand why they are doing what they are doing. The best way to do that is to ask them the context of them doing or not doing it.

There is also the middle ground of quantitative research that can be helpful (usually surveys). What I usually like to do is use qualitative research to understand the universe of reasons for something, and use quantitative research if I need to quantify the importance/commonality of those reasons.

Research also helps you isolate users you may not be able to isolate with your usage data. For example, at Grubhub, we were trying to understand how many people used Grubhub regularly for delivery, but not for every order. So, we asked. Then, we called those users to understand why they sometimes don’t use Grubhub, then sent another survey with those reasons to quantify which ones were most important to address. I outline that process more here.

But I Don’t Even Have a Research Team
At Grubhub, we didn’t have a research team for the first couple of years (or even a product team for that matter). So, when we needed to learn things, me, someone on my team, or our sole designer (hello Jack!) would do one of three things: 1) throw flows up on usertesting.com, 2) survey users on our email list, or 3) call users on the phone, and provide them with free food for their time.

You don’t need to be a professional researcher to do this, though they are better at it. You just need to determine what you’re trying to learn and who from. You want to watch people go through that situation if you can. If you can’t, ask them about the last time it happened and what they did and why. You will get better at it the more times you do it. Startups are starting to hire researchers earlier in their development because of the importance of understanding users beyond the data. So, you may be able to justify a full time role here earlier than you thought.

Thanks to Gabe Trionfi for reading early drafts of this and providing his feedback. HeHAH!

Currently listening to Beyond Serious by Bibio.