Tag Archives: conversion optimization

The Four Types of Traffic to Your Home Page

Every founder’s favorite project is redesigning their home page. It’s the introduction of your company, brand, mission, and hopes and dreams to all of your customers. At least, you think it is. When you analyze your actual business, you might find the majority of new customers don’t actually start on your home page. If you’re doing paid acquisition, they might land on specific landing pages designed for those ads. If you’re growing via social traffic or SEO, most people are landing on specific pieces of content. The typical growth team’s response to this urge is that the home page is not a high priority, and that they should work on landing pages or content pages This is correct. But the home page for some businesses is still a major source of traffic. You have to learn what type of traffic that is in order for a redesign of it not be a complete waste of time. I’ll talk about what those types of traffic are, how to identify them, and what types of designs you might pursue based on your mix of traffic.

Traffic Type #1: People who want to login
On sites with a lot of engagement, a lot of the traffic to a home page is from people who are already customers and want to login. In this case, your goal is to just make logging iin as easily as possible or auto-log them in via something like Google Smart Lock. Better yet, if you can make sure you never logout your customers, then they never see this page and get right back into the product. Facebook, Pinterest, and Tumblr are good examples of this.

While Facebook has sign up front and center, it has a top navigation bar for login, and that is where the cursor begins.

Pinterest has a unified sign up and login field with a friendly call to action that just says continue. It also has a dedicated Login button for those searching for it.

Tumblr has a login button front and center equal to the signup button.

The metric when you are optimizing for logins is login conversion rate. This may be harder to calculate than you think. Let’s do an example. Let’s say you have 10,000 people visit your home page. 2,000 login. Let’s say another 500 sign up on this page. Your login conversion rate is 2,000 / (10,000 – 500) = ~21%. You don’t actually know if the remaining 7,500 who did not login or sign up were there to sign up or login. If you have cookie data, you can check to see if they had ever logged in, and that may give a clue on how to segment them. If you don’t have that data, you assume they were there to login. If at all possible, you should never log people out. The best way to help them login is to keep them logged in. Tools like Google SmartLock are also effective.

Traffic Type #2: People who want to sign up
Someone coming to your home page directly is not doing so because they randomly type it into a browser. They already have some context. A friend told them about it, they read an article about, or something similar. Many of those people are already convinced and want to sign up, and the job of the home page is to get out of their way and make that as easy as possible. Generally, sites do this by putting a sign up form front and center, and making that form really easy to fill out. You can see how Facebook and Pinterest do this really well. If you look at the images above, Facebook’s signup formis right aligned, and Pinterest’s is front and center. There isn’t much to distract you from signing up.

The metric when you are optimizing for signups is signup conversion rate. It is similar to login conversion rate, just with signup as the numerator instead of logins, and logins are subtracted by the numerator. Given the same number from above, your signup conversion rate is 500 / (10,000 – 2,000) = ~6%. You still don’t actually know if the remaining 7,500 who did not login or sign up were there to sign up or login. So, to be conservative, you assume they were there to sign up.

Traffic Type #3: People who want to learn more
There can be a wide discrepancy between the people who come to your home page directly, and are not existing users. Some may want to sign up quickly like above, but others just want to learn more. Preferably, they would not like to have to give you their information before they understand if the site is for them. The ideal scenario for these these users is to see a free preview. If personal information is required to show a convincing product, then the home page sells the value instead of shows it, or asks for filtering criteria without asking for personal information. Tumblr, Pinterest, and Facebook all address this type of user in different ways. Facebook, as seen in the example above, left aligns the explanation of Facebook on the page. Pinterest and Tumblr create a separate call to action to learn more that triggers a dedicated “learn more” experience. Pinterst has a red call out with a How It Works button, and Tumblr has a clickable green bar at the bottom of the page asking “What is Tumblr?”. Both clicks result in scrolling explanations of what you can use these products for.
Tumblr:


Pinterest:

Traffic Type #4: People who are skeptical
There is a fourth type of new user that visits your home page. This is the person who heard about it, but is very skeptical. The best way to engage this user is to let them have free usage of the product for as long as possible. You usually encounter these users with very well penetrated products that are reaching the very late majority or laggards. Google is a good example of a site that lets you experience the product value without signing up.

You can see from the above examples that companies try to address multiples of these audiences at the same time on the page. In some cases, based on activity of the page, they will be able to bucket you into one of these groups definitively. Gibson Biddle has a great post on how Netflix evolved their design with regards to these different types of users and these users’ understanding of their brand over time.


As you’re working on your home page, you should first make sure it is the most important page to work. For many sites, their landing pages are where a lot more people get introduced to the product. When you do work on your home page, think about these four audiences, which one you really need to optimize for, and if you easily segment and address the other groups that are not your primary focus. Also, be sure to revisit thes decisions over time as audiences and brand awareness changes.

Currently listening to Mind Bokeh by Bibio.

Align Revenue to the Value You Create

“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.

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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 Brian Erwin.

Currently listening to Shape the Future by Nightmares on Wax.

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

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.

B2B Growth Podcast with Naomi Ionita

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.