Tag Archives: strategy

First to Product-Market Scale

I like to think of this blog as balancing between business school theory and startup execution. While there are many places they don’t add up, usually the combination of the two provides an insightful truth that is hard to see without the theory plus the experience of trying to implement it. One area where I struggled for a while between my experience and the theory was the first mover disadvantage as it relates to barriers to entry.

The first mover disadvantage states that, while being the first firm in a market to do something has its advantages in terms of brand recognition and speed to market, the firm bares an even greater cost of R&D, education, etc. that second movers do not. These second movers can fast follow without all of these additional costs the first mover had to deal with and quickly compete. See HBR for details. In my Chicago Booth studies, both Eric Lefkofsky (CEO of Groupon who taught Building Internet Startups) and up and coming economist Matthew Gentzkow (who taught Competitive Strategy) argued about how potent the first mover disadvantage would be for Groupon, and that now that everyone knew how profitable the Groupon model was, it would be copied as there was no competitive advantage.

In a case study about Groupon in Gentzkow’s class, I did a one man filibuster against this argument. I looked at the data. During the time of the class, Facebook and OpenTable were winding down their Groupon clones, Yelp called theirs “not a priority” six months after shifting almost their entire team to work on it. Living Social started having financial issues. Groupon was winning despite the first mover disadvantage. The question was not would Groupon win, it what the prize was going to be for being first. Why was that the case when economics would argue against it?

I saw this same phenomenon in my own work at GrubHub. Online ordering was not a hard technology to clone, and once we had educated restaurants on the value of online ordering and shown them the additional business we could bring them, a competitor would have a much easier time with their pitch. Yet, we were still winning in every market except New York and college towns, where competitors had entered well before us. After acquiring those competitors, we talked candidly about competing with each other. The folks at Seamless (the New York competitor) talked repeatedly about feeling boxed out due to GrubHub’s first mover advantage in the rest of the country, even though we weren’t first in many of those areas.

Having taken two classes emphasizing first mover disadvantage before hearing this, I knew something wasn’t right, but couldn’t quite nail the hidden truth. Last year, I read Andy Rachleff’s post on first to product market fit. Andy argued it’s not about first mover advantage, it’s about first to product-market fit. It felt warmer, but not quite right either. GrubHub was not first to product-market fit in many of the markets it entered and later dominated.

If we tweak Andy’s definition slightly from fit to scale, the model fits better. One thing about GrubHub is that everything we thought about we thought about at scale and with velocity. We would systematically try to grow every market we entered with the same focus and the same process. If we achieved this, we would overtake successful players that were already in the market. It also didn’t matter who entered the market and tried the same after that. We had already won. Product-market fit implies a product that works with a small product, and the next step in the company’s evolution should be scale. So, the target for startups or large firms entering new markets in order to be successful should not just be product-market fit, but product-market scale. If you achieve that, you dominate markets and cannot seem to be usurped no matter how few barriers to entry you have.

Value Trade Offs in Online Food Delivery

If you’ve been following the online food delivery space, now is a pretty exciting time. Multiple services are starting up, competing on different value propositions, and many corporations are theoretically launching businesses here as well. There is one clear giant, and it is unclear if any of the upstarts will challenge them. But what is so interesting is how large companies entering the space and new startups alike are confronting the different value trade offs in online food delivery. I’ll first describe the different types of services, their different components, and then their trade offs.

Types of Services

Marketplaces
Services: GrubHub, Seamless, Eat24
Marketplaces aggregates delivery restaurants and allow diners to search for restaurants that deliver to them. The restaurants do their own delivery.

Delivery Services
Services: Postmates, DoorDash, Caviar, Uber Eats
Delivery services offer delivery from restaurants that don’t do their own delivery and deliver the food themselves.

Delivery Only Restaurants
Services: Sprig, Spoonrocket, Maple
Delivery only restaurants have no storefront. They just make food that is available for delivery and deliver the food themselves.

Delivery Only Restaurants that Require Prep
Services: Munchery, Gobble
These restaurant services require some prep work ranging from microwave to stove or oven, but usually it’s only a few minutes of prep required.

Delivery of Ingredients/Recipe Only
Services: Blue Apron, Plated
These services deliver the ingredients and the recipe required to make a meal, but the diner has to cook it themselves.

Delivery of Groceries
Services: Instacart, Fresh Direct
These services deliver whatever items you want from a grocery store.

I won’t go into corporate focused services in this post.

Value Propositions

Variety
People rarely agree on what food they like, let alone on which food they want to eat at a specific time. While GrubHub is currently unmatched in its variety nationally with over 35,000 restaurants, different companies are tackling variety on both sides of the spectrum. Postmates will theoretically offer the most variety as it will pick up food from any establishment. Online food companies like Sprig, Munchery, and Spoonrocket limit options considerably each day. Doordash, Uber Eats and Caviar have the most confusing approach here, as their ability to use their own delivery network does not restrict them to restaurants who already offer delivery, but they curate the list to provide supposedly only great options. GrubHub works with every restaurant that does delivery already, and has expanded the market by convincing many restaurants to start delivery because they see how well other restaurants do by offering that option with GrubHub.

Prep
Convenience has two components: how much work you have to do to eat (prep), and how quickly the food arrives (time). Marketplaces, delivery only restaurants and delivery services deliver ready-to-eat food. Then, there are some that require a little prep, some that require full cooking, and some that require figuring out what to cook and cooking it.

Time
The other convenience layer is time. Delivery only restaurants target 10 minute delivery times by pre-pepping meals and loading them into the cars of their drivers, whereas GrubHub and Eat24 are closer to 45 minutes to an hour depending on the restaurant’s location and type of food. Delivery services tend to take over an hour as they require extra coordination with restaurants. I believe Uber Eats is attempting a hybrid of the delivery service model and the delivery only restaurant model, but I can’t confirm. None of the other services deliver food ready to eat, but they range on how much work is required. The some prep restaurants are more like 10 minutes to heat, and ingredient/recipe services require typically cook time of over 30 minutes to an hour.

Price
Price varies for all of these services. Delivery only restaurants target less than $15 everything included. While that is possible in some cities with marketplaces, it is not in others. Ingredient/recipe delivery services have plans that are under $10 per person. Delivery services tend to charge a fee for delivery or mark up restaurant prices, so they are typically more at $20 and above per person. This incentivizes group order to spread the delivery cost around to multiple people. This is why most delivery services end up focusing on corporate catering instead of consumers over time. Prep delivery only restaurants have different plans to entice regular ordering.

Quality
In marketplaces, the quality options are set by the market, and the diner chooses how good they want their food to be. Delivery services have the same option with perhaps a higher end than marketplaces as the very best restaurants tend not to deliver. The delivery only restaurants tend to be cheap and low quality so far. Whether you had a hand in making it yourself can also be considered a quality parameter, as some people to tend to prefer things they cook themselves.

Planning
With food delivery, one typically does not need to plan in advance to use it, but with new grocery delivery and ingredient/recipe prep services, diners need to plan ahead of time to use the service.

Trade Offs

As you start playing with these value propositions, you recognize some additional constraints. I don’t need to lecture you in price vs. quality. That’s pretty obvious. But what may not be obvious is the trade off between time and quality. Even if you are delivering food from an amazing restaurant, if it takes a long time to get to a diner, it’s typically not very amazing by the time it gets there due to the food being cold. The other interesting trade off is quality vs. variety. At GrubHub, our stance was akin to the saying “quantity is a quality all its own.” In that, if you organized all of the supply, even if you had many amazing restaurants and many not so good ones, the good ones quickly emerged to the top due to ratings and reviews and overall quality of the service improved. So, all GrubHub worried about was variety and convenience, with convenience mostly limited to the ordering and customer service experience. Price and quality were set by the market, but presumably, variety solved quality, with a cap on the high end.

What these new services are doing is taking constants in the marketplace equation and making them variables: prep, time, price, and quality. It is way too early to tell if changing the equation is valuable to the broader market as GrubHub does way more orders in a day than the rest of these services combined. But it will be interesting to watch.

Why Everyone Link Builds, or Why You Sometimes Do Things When You Don’t Know If They Work

I was talking to an analyst about how SEO works, and we inevitably got to the authority side of SEO. I started talking to him about how many companies spend a lot of effort trying to get external links to their site to build authority. It’s not something we have to worry about at Pinterest as our authority is super high naturally, but most companies do not have that luxury. The analyst, being a good analyst, asked how you track effectiveness of link building as a program. My answer surprised him: most of the time, you don’t.

Sure, sometimes you can see a correlation between link building and average weighted rank improvement, and maybe you didn’t make any improvements on the relevance side during that time. But, while you can experiment with SEO in relevance changes, it is pretty much impossible to experiment with link building as it works at both a domain and page level, its impact is felt over such a long period of time, and there are almost always so many other factors one can’t control, namely from competitors for those same search results.

So, he then asked, how do we know it works? The answer is: we usually don’t. So, the next question of course is, if it’s a pain to do and we don’t know it works, why do we do it? This question can be generalized to almost any competitive question via game theory. To really hammer the point home though, I actually used the climate change example.

In climate change, their are four scenarios and two dimensions. The first dimension is whether or not it is actually happening (or whether it’s man made), and the second dimension is whether we do something about it.

Next, you examine the outcome of each scenario to determine the outcome if that’s the box you pick.

As you can see here, in every box you are fine, except for the upper left. Sure, you might have wasted quite a bit of money and slowed the growth of some businesses, but none of that compares to possible catastrophe. Even if you think it’s a waste of time, the risk is so great if you’re wrong, and the answer reveals itself over such a long period of time, the obvious answer becomes to assume it is true and invest in fixing it.

Now, let’s apply this to a much less risky scenario of link building.

While we aren’t saving the world when we work on SEO, from a business perspective, the risk is just as great. In one belief, you lose, and in all other scenarios you don’t. If your competitors are smart, they all do this exact analysis and come to the same conclusion: to invest in link building. This cannot be a prisoner’s dilemma either, as one company always outranks another, and links occur organically that presumably change the rankings.

The Three Stages of Online Marketplaces

Prior to Pinterest, I worked on two sided network businesses my entire career, for apartment rentals (Apartments.com), real estate (Homefinder.com), and food delivery (GrubHub). As a result, I’ve admittedly become somewhat of a marketplace geek. And today is a very exciting time for online marketplaces. Marketplaces are evolving online. It’s hard to keep up with the innovation, but I’ll describe the three phases I am seeing, and why certain ones may prevail in different industries.

Phase 1: Connect buyers and sellers
This is the basic requirement of a marketplace. Early marketplace businesses like Ebay allowed you find people looking for your service if you were a seller, or find people selling what you were interested in if you were a buyer. To make this work, companies need to get past the chicken and egg scenario and build trust through their network. Things like ratings and reviews and guarantees make buyers trust they would get what they paid for, and sellers knew they would get paid if they delivered the service. Marketplaces in this scenario also had to find a way to get paid, using taking a lead generation or transaction fee for increasing the seller’s volume of sales. This phase is still in use with successful marketplaces like Airbnb, GrubHub, OpenTable, and others, but almost all are desperately trying to migrate into phase two or three right now, as you’ll see in the following paragraphs.

Phase 2: Own the delivery network
More recent marketplaces, not content to just facilitate a transaction, are actually working to implement the transaction by owning the element of bringing the service to the buyer. Marketplaces know that if they don’t control more of the experience, a great experience can be ruined by things outside of their control, supply side fault or not. Startups like Instacart don’t just allow you buy groceries online, but their workers deliver the groceries to you. Postmates and Doordash do the same for delivery food, picking up food from restaurants that don’t deliver and deliver it using their own workers. While this model is not new (restaurant delivery services have been around since before the internet), companies are now trying to build delivery networks at scale.

This is risky, as delivery networks all rely on the same pool of drivers. So, on the delivery side, marketplaces in different industries compete for delivery drivers. In a zero sum game there, it’s most likely the marketplace with the most demand wins (at this point, that’s undoubtedly Uber).

GrubHub, for example, bought two delivery services in Q4. OpenTable is moving into payments at restaurants. Airbnb is working on concierge services to improve the stay of guests. The companies starting in phase 1 see this as owning more of service blueprint, injecting their brand into the blueprint wherever possible.

Phase 3: Own supply
An even newer trend than owning the delivery network for an online marketplace is to vertically integrate the supply side of the business. Now, you may ask, what makes this a marketplace? In reality, it’s not, but from every other element, the business is designed or is mimicking an existing marketplace. Sprig and Spoonrocket do this with food delivery. They are delivery only restaurants that make their own food and have their own delivery drivers. MakeSpace and Boxbee, instead of just building a marketplace to help you find storage space, built their own storage spaces and will pick up your items and deliver them to storage and deliver them back for retrieval if needed. Margins are very different for their businesses.

The question for me becomes how far up the pyramid can you build a successful business. In many cases, owning supply will be victorious, but in many others, owning the delivery network is the best option. In other, a traditional marketplace is the best option. It will be interesting to watch almost every vertical determine the best model for customer satisfaction, scale, and profitability over the next decade.

The Perils and Benefits of AB Testing

Bob, our head of product design at Pinterest, asked me to write up a post on the perils and benefits of AB testing after reading my post on building cross-functional teams. This is me obliging.

One thing it is never difficult to do is to convince an engineer to do an experiment. In general, this is a good thing. Famous engineer W. Edwards Deming said, “In God we trust, all others bring data.” AB experiments generate data, and data settles arguments. AB experiments have helped us move from product decisions made by HIPPO (highest paid person’s opinion) to those made by effectiveness. We build better products as a result that delight more people.

An AB experiment culture can also have a dark side though. Once people figure out that AB experiments can settle disputes where multiple viewpoints are valid, that fact can lead people to not make any decisions at all and test everything. I liken this type of approach to being in a dark room and feeling around for a door. If you blindly experiment, you might find the way out. But turning the light on would make it way easier. Rabid AB testing can be an excuse for not searching for those light bulbs. It can be thought of as easier to experiment than to actually talk to your users or develop a strategy or vision for a product. Here are some perils and benefits of AB testing to think about as you experiment in your organization.

Benefits
1) Quantifying Impact
This one is pretty obvious. AB experiments tell you exactly what the lift or decrease a treatment causes versus a control. So, you can always answer the question of what an investment in Project X did for the company.

2) Limiting Effort on Bad Ideas
Another great benefit of AB testing is that you can receive feedback on an idea before committing a ton of effort into it. Not sure if an investment in a new project is worth it from a design and engineering perspective? Whip up a quick prototype and put it in front of people. If they don’t like it, then you didn’t waste a lot of time on it.

3) Limiting Negative Impact of Projects
Most additions to a product hurt performance. AB testing allows you to test on only a segment of an audience and receive feedback without it affecting all users. Obviously, the larger the company, the smaller the percentage you can trigger an experiment on to get a solid read.

4) Learning What Makes Something Work
In AB experiments, you isolate one variable at a time, so you know exactly what causes a change in metrics. You don’t have to debate about whether it was a headline or background color or the logo size anymore.

Perils
1) Not Building a Strategy or Vision
Many places convince themselves that testing is a strategy in and of itself. While AB testing can inform a strategy or vision, it is not one in and of itself. What happens in these cases is that companies do tons of random experiments in totally different directions, and their failure rate is very high because they have no unifying vision on what they are trying to do.

2) Wasting Time
AB testing can slow companies down when they convince themselves that every single thing needs to be tested thoroughly. Everyone knows of the anecdote from Google where they tested 41 shades of blue.

3) Optimizing for the Wrong Metric
AB experiments are designed to measure the impact of a change on a metric. If you don’t pick the right metric or do not evaluate all of the important ones, you can be making tradeoffs in your product you do not realize. For example, revenue over user engagement.

4) Hitting A Local Maxima
AB experiments do a very good job at helping optimize a design. They do not do as well as helping to identify bold new designs that may one day beat current designs. This leads many companies to stay stuck in a design rut where their current experience is so well optimized, they can’t change anything. You need to be able to challenge assumptions and invest in a new designs that may need quite a bit of time to beat control. This is why most travels sites look like they were last re-designed in 2003.

So, I’d prefer to optimize Deming’s quote to “When the goal is quantified and the ROI is worth it, run an AB experiment. All others bring vision.” It doesn’t have quite the same ring to it.

Currently listening to Forsyth Gardens by Prefuse 73.

The Startup Marketing Funnel

Quite a few startups have asked me how to approach their marketing plan. They hear that it’s important to do specific things, but that list eventually grows long, and they don’t have a plan of attack or a prioritization. While my post on three phases of startup marketing helps, it doesn’t go into enough detail on the framework behind that prioritization, and what to do with a new idea not represented there. Well, the good news is there is a framework you can apply to evaluate a list of ideas and prioritize them, and it’s not too different from the traditional marketing world. It just may be a bit inverted.

You may have seen a marketing funnel like this before (everyone calls the stages different things, but it’s generally something like this):

Startup marketing is a bit different. Instead of products being driven top down as in the above diagram, startups have to work bottom up due to budgets and what will be effective. Also, startups need to focus more on the inverted funnel post-use not seen in the above. So, your startup marketing funnel looks like this:

Now, instead of working top down here, startups need to work inside out. You work on the on site experience to make sure the few users who come convert and have a great experience. Then, you get them to come back and have another great experience. Once they are hooked, you ask them to invite friends. At this time, you also target those who came and didn’t convert. Then, you target those with a need for your product that haven’t tried. Then, you can define your core audience well from those using the product and do core audience targeting to find more like them. After saturating all of those methods, you finally work on general awareness.

Now, how does that translate to tactics. Well, let’s have a look:

Making sure people convert is all about conversion rate optimization. Email and push can help trials turn into repeat purchases, but the big winner there is an engaging product experience or a community. To get those who checked the product out but didn’t convert, you use use retargeting. To find others in need of the product, you focus on search (paid or organic). To find more people like your current audience, you can use Facebook lookalike targeting or interest targeting (thousands of other options here as well, of course). to pursue general awareness, that’s typically when you work on larger spend initiatives like TV, radio, outdoor, and sometimes PR.

Follow this funnel, focusing on each step until it saturates, and you can be sure you’re always working on the most effective and impactful projects to grow your business. Conversion, product, and community never tend to saturate, so you’ll almost always have dedicated people working on that even as you move further up the funnel.

Currently listening to Sonnet by BenoƮt Pioulard.

A Primer on Startup SEO

As I advise startups on growth, one of the most common questions I receive is “should we be working on SEO?”. At this point, I tend to remind them of the three phases of scaling startup marketing or show them Andrew Chen’s great post on the few ways to scale user growth. In today’s mobile-first landscape, with the limited scale of the App Store/Google Play, the answer is actually a bit more nuanced. So I created a guideline on how to answer this question for any startup.

Step 1: Keyword Research
The first question to answer when thinking about SEO for your business is “what should my business show up for?”, which really is asking the question, “what is my business about?”. Unlike branding, where the point is to synthesize that answer into as few clear words as possible, keyword research is about generating as many answers to that question as possible. These will be your potential keywords. I like to use the framework: who, what, when, where, how to answer this question. Let’s take the example of GrubHub:

Who: GrubHub, restaurant names we represent
What: food, delivery, menus, pizza, thai, indian, chinese
When: breakfast, lunch, dinner, late night
Where: every city, neighborhood, zip code, college covered
How: online ordering, mobile app, iphone app, android app

Take these words, combine them all into new keyword combinations in Excel e.g. “late night pizza delivery berkeley”, and check to see how much search volume they have. To do that, use the Google Adwords Keyword Planner. Click “Get search volume for a list of keywords”. Take the keywords from the exercise above and paste them in. Click “Get search volume”. Click on Keyword Ideas tab. You can also do this process again to find new keywords by clicking “Search for new keyword and ad group ideas” at the beginning.

You can now see how much search volume is closely related to your business. Search volume determines how much your prioritize SEO for your business. Now, there is no hard and fast rule for how much search volume there needs to be for you to get excited about it as an opportunity. It depends on purchase size, how much you want to grow, etc. Generally, I recommend taking all of those keyword’s search volume, assuming you can get a very small percentage of it to your site e.g. 1%, and seeing if that would make an impact on your business.

Now that you have an idea of the search volume for your business, you need to know how competitive that real estate is. Fortunately, Google estimates how competitive they think each keyword is next to the search volume estimate. It lacks the granularity I’d like, but it’s a good starting point. What I do in addition to looking at this gauge is do some spot searches and see what the results look like. Here, I’m looking for two things:
1) Are the results primarily businesses you would consider competitors or blogs?
2) Are the pages that are showing up well optimized for the keywords you searched or not? Are they dedicated landing pages or home pages?
(I’ll go into more detail on how to measure this a little later in this post)

Step 2: Picking an SEO Strategy
Now, you should have an answer to two questions:
1) Do my keywords have a lot of search volume?
2) Are those keywords competitive or not?

This creates four scenarios:

High Search Volume/Low Competition: Make Priority
This is a rare opportunity, and you can build a great business just off of SEO here. You should make SEO a priority and one of your primary growth strategies.

High search volume/High Competition: Play for Long Term/Make Core Competency
This means the ROI is there with SEO in the long run, but it will be hard to get it as a startup. You will need to organize the entire company around SEO to win, by making SEO a core competency of the company.

Low Search Volume/Low Competition: Content Marketing
This is common with startups that are creating new products or product categories, especially in mobile apps. They do not have enough demand yet. The general approach here is to expand your keyword target to the broader industry that does have high search volume, and pursue a content marketing strategy around those keywords that mentions your product/service occasionally in them.

Low Search Volume/High Competition: Ignore
Feel free to ignore SEO as a strategy here unless something changes.

This allows us to build a 2×2 to express SEO strategy options:

Step 3: Actually Working on SEO

Assuming you’re not in the low search volume/high competition bucket, you’ll want to start figuring out how to work on SEO. To do that, it’s helpful to make sure we define what we’re doing. Search engine optimization is the process sites use to appear in the organic results of search engines. To have a process, you need to understand what search engines do.

1) Search engines use crawlers to discover pages across the web.
2) They read any content they can find (mostly text)

So, in order to succeed, you need to be discoverable and readable. Once your page is discovered, search engines determines the authority of the page
Once your page is read, search engines determines what the relevance is for certain searches.

Determining Relevance: On-Page Factors
So how do search engines determine relevance? Well, here’s a rough hierarchy. They look at the title tag of the page first then the H1’s and H2’s, thing that typically indicate importance in HTML. Then they read normal text, and they look at what the URL says. They also look at this page compared to all the pages in their index and see how unique this page is compared to the rest. Search engines prefer unique content. They also look at the last time the page was updated. Frequently updated pages are seen as more reliable to Pinterest. They also look at the # of links on the page. A page with a ton of links is associated with a worse user experience and having less relevance. They also look at where the keywords are on a page. Google breaks up the page into header, footer, sidebars, and content area. Keywords in the content area are weighted higher. They also look at the # of content types. A page with text, video, and images is seen as better than just a page with one of those. They also look at the # of ad blocks on the page. A page with a bunch of ads is seen as less relevant. I know that sounds like a lot to pay attention to, so just keep this short list handy:

  • Title Tags
  • HTML Tags
  • Text
  • URL of the page
  • Uniqueness
  • Freshness
  • Number of Links on the Page
  • Keyword location on the Page
  • Diversity of content types
  • Number of ad blocks on the page
  • Make no mistake about it. This is mostly engineering work. You have to be messing with your site to get it to rank better. Mostly, this means creating pages specifically for keywords you want to target, and optimizing the above for these pages. I have seen so many startups think they can cover SEO by hiring a marketer to manage it. Unless they get engineering help, it will not work.

    Note: this is what you check to answer if your keywords are competitive in Step 2.

    Determining Authority: Off-Page Factors
    So, how do search engines determine authority? Well, the main two things are quantity and quality of external links to the page and domain. Search engines see links as votes, so if another site links to you, that’s a vote that you’re an authority. Now, not all votes are ranked equal. A link from the San Francisco Chronicle will be worth more than a link from my blog. They also look at how other sites link to you. So, the anchor text is very important. If a link says home decor, that will help more than a link that says click here. They also do look at internal links within a site. So, us linking to something from our home page indicates that we think it’s very important, where as a link from our Help page is not as important. Search engines also look at the data they accumulate about a page. So, when a page gets clicked from Google, they look at the bounce rate. When Google shows a page in a search result, they also look at its click through rate. They also look at which parts of the page people link from. A link from the content area of another page is worth more than a footer link. They also look at the diversity of link types. A page that gets links from blogs, news sites, and social media will be better than just a bunch of links from blogs. Too much detail again? Don’t worry; I have you covered with another list:

  • Quantity of external links pointing to page/domain
  • Quality of external links pointing to page/domain
  • Anchor text of links
  • Internal links pointing to the page
  • Metrics from search engines (bounce rate and click through rate)
  • Area on page of internal/external links
  • Diversity of link types
  • If you’re building a good company, this is mostly public relations and business development work. Also, if you’re working on content marketing, the quality of the content alone can drive links, which is why you see every company trying to push their infographics everywhere. Widgets have traditionally been a strong strategy here that may be waning in importance.

    Appendix: Tools at Your Disposal
    Now, search engines give you some tools to help you do this. So, I’ll describe them.

    Google/Bing Webmaster Tools: These destinations give you a host of information on keywords you rank for, crawl rate, errors etc.
    Meta Tags: By default, search engines will use your title tags and meta descriptions to populate how your listings appear on their sites
    Sitemaps: This is a way to send search engines every page you want them to index instead of waiting for them to find a link to it. No guarantee they’ll index all those pages, but they’ll look at them.
    Nofollow Tags: With the explosion of user-generated content and social media, spammers started flooding these sites with links to rank on search engines. Given that it’s very hard to monitor all that content, search engines allow sites to add rel=nofollow to outbound links, saying you can’t vouch for the site you’re linking to. Pinterest uses nofollow to external links as do most other social media sites.
    Canonical Tags: another cool tag. As we said before, Google likes unique content. But Google may figure out how to access the same content from multiple URL’s. If that happens, when Google finds a duplicate version of a page, you can add the rel=canonical tag in the head to indicate that if this page gets a link, use it for this other URL with the same content.
    Hreflang Tags: helps tell Google which version of a page to show users in different languages and countries.
    301 redirects: URL’s change all the time. But if a URL changes, normally that would be considered a new URL that needs to generate its own authority. If you 301 redirect the old URL to the new URL, Google will transfer some of the authority of the old URL to the new URL.
    robots.txt: Search engines obey operatives in your robots.txt file or in meta robots on which pages to crawl or index.
    Rich snippets: This will show different content under your listing, like star ratings and other meta data to help your listing stand out.

    Loyalty Marketing Part II: Making a Program and Keeping It Successful

    Read part 1 of of my series on loyalty marketing.

    In my previous post on loyalty marketing, I talked about the different types of loyalty programs, and how to identify which type of program your company should pursue. Once that happens, do you slap up generic version of a program that tackles your needs and call it a day? Absolutely not. Now that you’ve identified a program type to target, you need to determine a version that your users will respond, that will fit your brand, is profitable over the long term, and is future proof. Let’s tackle user response first.

    Understand Reasons Why
    Your can’t expect your users to change their behavior until you understand why their behavior is the way it is. Let’s say most of your users use your product regularly, but not every time they have the problem you solve. In order to create a successful program, you need to figure out why they don’t use you the times they don’t. The only way to do that is to talk to them. Take random people in the segment you’re trying to change and arrange a phone call. Reward them for it. In 20 minutes, with targeted questions, you can learn all you need to know about the time they’re not using you. A standard question to learn this is “Tell me about the last time you did X and didn’t use us.” Keep doing these calls until you start hearing the same types of responses over and over. In my experience, things settle around four or five reasons. For loyal, but infrequent users, it works very much the same. Talk to users, but this time ask “Why don’t you use X for [new use case]?”

    Understand the People Behind the Reasons, and Pick a Reason
    These phone calls don’t give you any statistical representation around how popular these reasons are for the broader audience that isn’t using you every time. So, now that you have your reasons, you can survey the broader group, asking them, “When you do X and don’t use Y, which reason best describes why?” and make the answer multiple choice with the responses you received over the phone. With a good enough response, you can now stack rank the reasons why people aren’t loyal to you. Some may be product changes you need to make. Some may not be helped. But, more than likely, you can address most of them with an incentive. You can go further down the phone calls + survey rabbit hole until you have full personas of users. Knowing the reasons why users aren’t loyal and what types of users you have can make you say, “I want to target this reason for this persona.” The same philosophy applies to incentivizing use cases. Our survey question is the same question you ask over the phone, except now it’s multiple choice. The goal again is to be able to say “I want to target this use case for this persona.”

    Testing the Program
    Now, you’re ready to build a program. At this point, it’s mostly a creative exercise leveraging psychology. Invent a bunch of a programs that might incentive these users, narrow down the ones that are most likely to incentivize users and be profitable, and test. Email is a great way to test different programs because you don’t have to build much and can book keep manually to get enough data without users knowing it’s not a real thing. It is also not a bad idea to run your users through these program ideas over the phone or in person, but remember that what they say and what they’ll do may be very different. Still, talking to them can prevent some gotchas.

    Once you have a program, you need to test in a live way. Depending on what type of program you build, you may be constricted. For example, Yummy Rummy at GrubHub was considered a sweepstakes, so we could not legally have a control group. A control group is always the best way to test. Sweepstakes laws are at the state level in the U.S., so if you have two states that perform very similarly, that may work. If you don’t, you need to measure pre and post data. Pre and post data is not ideal for a few reasons. The main one is that loyalty programs typically take time to change behavior, and if you turn them off, it will take time for behavior to change in reaction to that as well. You don’t want to be running the program for a over a year, and not be sure if your pre data is still relevant. What typically happens in these scenarios is that programs are pulsed, like the McDonald’s Monopoly game being available for a limited time yearly. There is too much money being spent on a loyalty program typically to not know for sure if it is working or not.

    Long Term Success
    One other dirty little secret about loyalty programs is that they tend to ebb in effectiveness over time. Humans are motivated by variable rewards, and if your program is static, your users may become used to it, and it may not create long-term behavior change. That is why I recommend creating a variable program. At GrubHub, we made Yummy Rummy available every three orders instead of every order, and the reward could be anything from a free drink to free food for a year. Furthermore, if you lost, you got a consolation prize that was something random from the internet. But, I don’t think that is even enough. You should strive to think of your program as constantly evolving to stay interesting to your users. This will make your program stay effective for longer as well as give you the flexibility to tweak elements to make it more interesting to you as the business. I have seen many companies stuck with a program they no longer think is effective, but too afraid to shelve it because of potential user backlash.

    The other advantage of creating a living, evolving program is that, if the original incarnation is effective, you can change it to move users further up your user lifecycle. For example, let’s say you’re trying to incentivize platform use in your original incarnation of your program. You might be very successful at that, and then find an opportunity to take those same users and get them to use the platform more by incentivizing use cases. Now, you can do that by evolving the same program instead of starting from scratch. Or, you might have taken loyal users and gotten them to use you for more use cases. Now, you can adapt that same program to build a moat around them. This all boils down to what a holistic loyalty program should look like in three steps for most internet businesses:
    1) Build loyal users in one use case
    2) Increase frequency by incentivizing use cases
    3) Build moat around those users

    This happens to be how most marketplaces or social networks grow into behemoths. They nail an initial use case, build a loyal user base for that, gradually expand use cases, and then work to keep those users locked into their platform.

    Loyalty Marketing Part I: Strategies and Segments

    There seems to be a lot of confusion about loyalty marketing and how loyalty programs work. To an outside consumer, I guess the confusion is understandable. Most loyalty programs are branded as a value to the customer, a reward for their dedication. Most loyalty programs’ primary goals are not to add more value to consumers (though when they’re done well they do that too); their goal is to create more value for the company. I’ll break down how to think about loyalty if you are a business that is wondering if a loyalty program makes sense for you.

    The first thing to understand is that every business has a loyalty problem; it just might not be the loyalty problem they’re expecting. To make this clearer, I’ll split consumers into four areas. Depending on where most of your company’s consumers fit is where you’ll spend your effort in thinking of a loyalty programs. The first thing to do is split all of your consumers into loyal and non-loyal and frequent and non-frequent. Loyal is defined by doesn’t use a close competitor as well as you for what your product/service does. Frequency is a bit more nuanced. Your product/service should have a target frequency you’re setting. For Pinterest, that might be daily. For GrubHub, that might be once or twice a week. You then can build a 2×2 matrix like the one below.

    Each of these four buckets requires a loyalty program targeting different actions by consumers. Just to be absolutely clear, let’s go through that exercise for each segment.

    Frequent, Loyal
    Action: Keep consumers doing what they’re currently doing

    Frequent, Non-Loyal
    Action: Get consumers to migrate usage of competitors to you

    Infrequent, Loyal
    Action: Get consumers to use product/service more

    Infrequent, Non-Loyal
    Action: Determine if product issue can increase frequency. If not, ignore.

    Now, we should talk about these strategies in a bit more detail. I’ll skip infrequent, non-loyal since it’s a combination of two other strategies, and probably implies a product or market problem.

    Infrequent, Loyal Strategy: Incentivize Use Cases
    In this segment, consumers use your product loyally, but not enough to your liking. This implies that there are not enough use cases for your product in the eyes of the consumer. That could be because these use cases do not exist, or because the consumer doesn’t perceive them to be relevant. If the use cases do not exist in your product/service, you need to build them into your product. Take, for example, Homejoy expanding into all sorts of home services after starting with house cleaning. If the use cases do exist in your product/service, but consumers aren’t using them, you need to invest in awareness or incentivizing a trial of them. For Pinterest, this might be upselling someone who uses the service for recipes to try planning a vacation with the service, or a web Pinner to try the mobile app. For GrubHub, this might be giving a discount for a pizza orderer to order sushi, or a web orderer to try their first mobile order, or a delivery user to try their first pickup order.

    These opportunities might not exist or be worth the effort. When I worked at Apartments.com, we knew people would only look for apartments once a year or less. There was not much we could do influence that. What we could do was stretch our product to be useful for not just the apartment search, but also services you need once you find an apartment e.g. moving. Beyond that, there wasn’t much opportunity we could tackle, meaning we’d probably have to spend money to acquire those same users whenever they looked for an apartment again.

    Frequent, Non-Loyal Strategy: Incentivize Platform Use
    In this segment, consumers are very active, but don’t always use your product/service over a competitor. This is the most common type of loyalty segment because it’s easy to understand the upside. You can typically measure how much activity occurs off your platform. Here, you need to invest in an incentive to move those uses onto your platform. This typically takes the form or rewards points or punch cards.

    Frequent, Loyal Strategy: Build Moat
    In this segment, consumer are very active and don’t use anyone else for your product/service. These are your best customers. So, a loyalty strategy shifts from trying to increase how often someone use the platform to doing all you can to make sure these consumers don’t decrease their use of your platform or are wooed away by a competitor. This is by definition a money losing strategy to decrease risk instead of a money making strategy in the first two segments. Moat strategies can take many different forms and are frequently misunderstood. Some start out looking like the same strategy as frequent, non-loyal. One common one is to increase switching costs. One example of that is Facebook shutting off friend access to competing apps.

    Many other moat building strategies get much more creative. They rely on looking at every possible risk to your consumers doing less of what they’re doing today and trying to address it. One of the most ambitious is Google’s launch of Android. Google makes most of its money from web advertising. They saw consumer attention shifting from an open, web platform they increasingly controlled via their browser Chrome to closed platforms on mobile owned by competitors Microsoft and Apple. So, they acquired and put hundreds of millions of dollars behind their own, open operating system in Android, which they charge no money for, but powers most smartphones all over the world. This is all so they could continue to control how people searched and saw ads in a mobile world.

    So, we can go back to that 2×2 with our strategies now.

    Now that you understand the segments and their corresponding strategies, you need to identify where the opportunity is for your product or service. The easiest way to do that is to run a survey to determine loyalty, and mine your user data for frequency. Then, see where the highest percentage of your users are.

    This post covered how to identify which segment to focus on and the appropriate strategy to pursue. My next post will talk about making that strategy and implementation successful.

    Read part 2 of of my series on loyalty marketing.

    Distribution Real Estate, or an Untalked About Element of Facebook’s Acquisition and Unbundling Strategy

    Many have opined about Facebook’s two major strategies over the last couple of years. The first is their aggressive stance on acquisitions, a 180 from their acquihire only approach pre-IPO. This includes Instagram, WhatsApp, Moves, and the real outlier Oculus. The second and more recent is their unbundling of core functionality from the main Facebook app, as with a standalone Messenger app, a standalone Camera app (now being replaced by Instagram), a standalone ephemeral messaing app (Poke and now soon Slingshot), and a standalone launcher app (the miserable failure Facebook Home). One might think I am against such a strategy due to my previous post criticizing unbundling. What Facebook is attempting is something different though.

    It is rare that companies get to a point where they start to pursue a moat strategy. A moat strategy makes sense when a core business is so profitable that the most sensible course of action is to build things around it to protect it instead of trying to increase value of customers or try to attract more customers. Google is a famous example of this with Adwords. Its core business is so successful that it pursues projects like free mobile operating system Android solely focused on protecting distribution of Adwords as the world shifted to mobile, and free web browser Chrome to protect distribution of Adwords on web as Microsoft tried to bundle browser (Internet Explorer) and search (Bing) together.

    While an entire company ascending so far to the top that its main course of action is building a moat is rare; it is more common on specific distribution channels. Take, for example, search engine marketing and search engine optimization. Once you ascend to the #1 result for an organic search, a normal marketer might stop there and try to optimize other channels. But savvy search engine marketers are just getting started then. A savvy search marketer knows that a #1 result organically does not guarantee that all clicks go to one’s own domain. There are still nine other organic spots and the paid ads, which may still appear above your result. So hardcore search marketers start working on their next trick, owning more than one spot on the search result.

    I pursued this strategy at Homefinder. We would take the #1 ranking for certain keywords like “Fayetteville homes for sale”. Once we achieved this, we would bid highly on Adwords as well to take a second spot on the page. Then, we would work with affiliate marketers to bid below us in Adwords to take the second, third, fourth, etc. spots on the page. If someone clicked on those listings, they would go to a different website (as Google only allows one paid ad per domain). But when someone searched on those domains, they were redirected to Homefinder. By pursuing this strategy, we could own perhaps five or so spots on Google for one search, making the likelihood of someone landing on Homefinder much higher than if we just had the #1 spot and nothing else.

    The travel companies like Expedia are the masters of this, with multiple brands ranking on the top of Google that are all owned by the same conglomerate not very differentiated. Almost all travel purchases start with Google, so the travel companies maximize this distribution channel more than any other category. For example, Expedia has Hotwire, Hotels.com, and Trivago. Priceline has Booking.com, Kayak, and Agoda.

    You might ask what this has to do with what Facebook is doing. Well, on mobile, Google is actually not the only search engine of note. The App Store and Google Play are just as important to optimize for. App store rankings are largely determined by recent download counts, but Google Play is a bit more sophisticated with many engagement metrics. Facebook currently ranks #1 for free apps on Google Play. Did Facebook stop there? No, it unbundled it’s Messenger app completely, which is now the #5 free app. It purchased Instagram, which is the #4 free app. It tried to buy Snapchat, which is the #6 free app. And it purchased WhatsApp, which is the #14 free app. When you already own the top result, you tried to grab as much of the rest of the top real estate as you can.

    If Facebooked buys Pandora in the future, don’t be so shocked. This is not just true on the app search engines though. The home screen of the mobile phone is another limited piece of real estate that is incredibly important. Facebook is likely on the home screen of more mobile users than any other app. But it is still only one app among many one can click on when they pick up their phone. So Facebook is focusing on other app that already have wide home screen distribution. I had Facebook, Instagram, and Moves on my home screen. That means, Facebook had a 3/16 chance every time I opened my phone that they would receive some sort of engagement from me.

    When you’re optimizing channels, I encourage you to think about the real estate you own on each one, and how you can own more. It’s an incredibly effective strategy even if you’re not quite at the moat building stage.