Product Optimization: Conversion, Engagement, and Happiness
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Product Optimization: Conversion, Engagement, and Happiness
- 1. Product Optimization: Conversion, Engagement, and Happiness Casey Winters Online & Interactive Marketing Director, GrubHub @onecaseman
- 2. Product Optimization in Three Phases • Design/User Experience • Analytics • Psychology
- 3. That’s One Long Ass Funnel Ads or Friend Talking About It Ad Clicks App Store App Download App Open Search Results Restaurant Page Sign-up Payment Order Order Again Create Habit Tell a friend
- 4. The Web Version Ads or Friend Talking About It Ad Click Landing Page Search Results Restaurant Page Sign-up Payment Order Order Again Create Habit Tell a friend
- 5. Conversion Rate Optimization Ads or Friend Talking About It Ad Click Landing Page Search Results Restaurant Page Sign-up Payment Order
- 6. What is Conversion Rate Optimization? • Conversion Rate Optimization is the process of making continual changes to a website/mobile app/landing page with the goal of increasing the amount of visitors who turn into conversions • Every page on a website is an ad for the next page. • If your page did not generate a click to the next page, it failed. • Find the pages that generate the least clicks to the next page and fix them. These can be called bottlenecks.
- 7. Back to the funnel…
- 8. Landing Page Optimization • If your funnel is healthy, you probably should spend most of your time on landing page optimization • A/B testing • Bounce rates • Find the pages that generate the least clicks to the next page and fix them. These can be called bottlenecks.
- 9. Back to the funnel again…
- 10. You found yourself a bottleneck • • • • Exit rate Too many steps? Bounce rates Tools
- 11. The Local Maxima Problem Data Analysis Psychology
- 12. This is where Behavioral Economics comes in. • People are bad at math • People use irrelevant information as a guide to making decisions • People are overconfident • People hate losing something more than they like gaining something
- 13. Prospect Theory 1: People do not think about absolute wealth, but of local gains and losses 2: Whether something is considered a gain or a loss is based on a reference point or anchor 3: People are risk averse with gains and risk seeking with losses 2+3: Risk preference depends on reference point 4: People are more sensitive to losses than gains of the same magnitude, called Loss Aversion
- 14. What does this mean? • It means how you frame a decision affects what decision a person makes • This power can be used for good or for evil • Choice architecture is the technical term for framing problems in a way that makes people more likely to behave in the way you wish them to
- 15. Designing Happiness • Contrast: Anchoring • Adaptation: Local gains and losses • Variable rewards
- 16. Cohort Analysis
- 17. Hook Model
- 18. Stuff You Should Read • • • • • The Goal by Eliyahu Goldratt Thinking, Fast and Slow by Daniel Kahneman Nudge by Richard Thaler and Cass Sunstein Predictably Irrational by Dan Ariely http://www.slideshare.net/nireyal/hookedmodel • http://lsvp.com/2010/07/19/how-toestimate-lifetime-value/
Editor's Notes
- I'm here to discuss in a nutshell how we think about product optimization at GrubHub and at web companies in general. We generally think about product optimization in three areas:design/UX (which hopefully Zeke is covering pretty well for you guys)analytics (measuring what people who arrive at your product actually do)psychology (understanding what they are thinking)Essentially, what you're looking to do is bring the right people into your service (which is marketing), have them understand what the product you are selling is, and have them make the right decision on what to do with that information (even if it's not buy).
- So, how do we break this problem down? Well, we typically think of the process as a very long funnel. If you want to get really broad, you can think of the funnel starting at any touchpoint of a potential user e.g. someone telling a friend, someone seeing an ad on Google or a train, to the landing page of the website, through the interior product pages, all the way to purchase, then back out into repeat purchase and habit formation.
- You can optimize every step along the way here. If not enough people try your product even after their friends rave about it, maybe you need to help them describe it better for you. If an ad isn't driving enough people to your product, change up the copy or the visuals or where you're placing the ad. Most of what I do at GrubHub is just that part actually, but just so we're not here all night, I'll skip to the part where you've actually gotten someone to come to your product. Then you have a funnel like this:
- Now, let's say you've already maximized your CTR on Pandora by testing a bunch of different ads. We tend to measure that part using different tools for different types of ads, and you guys aren't studying to be online marketers, so I'll skip that.
- Once you get them to the app or the site, Zeke would say the real work begins. We call this work conversion rate optimization, which is the process of making continual changes to a website/mobile app/landing page with the goal of increasing the amount of visitors who turn into conversionsThink of it this way:Every page on a website is an ad for the next page.Assuming we got the right people to the site, if your page did not generate a click to the next page, it failed.The goal is to find the pages that generate the least clicks to the next page and fix them. These can be called bottlenecks.
- How do we do that? We go back to our funnel. A healthy funnel is logarithmic. That means you should lose the most people from step 1 to 2, followed by 2 to 3 and so on. If you see a bigger gap between two steps than the step previous, you likely have found your bottleneck and need to test some revisions to that page to improve its conversion rate.
- If you have a healthy funnel, you will spend most of your time on landing page optimization. This can be very much a communication exercise or very much a design exercise. We use tools like Optimizely to A/B test different versions of landing pages and look at bounce rate, which is the amount of people that leave immediately over the total people who come to the page. Now, you're probably asking what is a healthy bounce rate? That depends on the industry, how much and the quality of traffic you think you're sending to the page, etc. A rule of that thumb is that if you're above 50%, you're probably not doing awesome.
- Here, you're measuring exit rate or abandonment. This is the amount of people who left on this page over the total people who reached this page. When you see a large gap, you know you have a bottleneck and need to think about what is causing the issue. Is it bad design? Are we asking for too many things? Are we asking people for things they don't know the answer to? Most funnels have more steps than they need, so simplifying is almost always better. There is a caveat to this though. When you have a business like GrubHub where you ideally use it regularly and not just once, requiring most investment upfront can actually create a more quality repeat user. So, as always, test and do the math on what ultimately benefits your business the most. For example, GrubHub allows diners to place orders with an account, Facebook, or as a guest. Creating an account allows you to re-order quicky, save favorites, etc. The guest account was added to improve conversion rate and make it simper to order. But, we noticed that guests came back less frequently than people who took the extra step to create an account. So, we tried forcing people to create an account to see if our conversion rate would go down, and if it didn't, would these people become more valuable. Conversion rate did not go down, and value of each diner went up. So, now we hide that option.The tools we use to measure this stuff are your standard analytics tools like Google Analytics, KISS Metrics, RJ Metrics, or, my favorite, Mixpanel.
- Once you get in the habit of this, your process becomes measuring exit rates for each important step over time, testing new variations of pages to improve these exit rate, and measuring success of each step over time. Now, this creates a local maxima problem where the more you optimize, the less impact you get over time. So, it's important to test radical redesigns and not just optimizations so find new mountains to climb in your data. The other problem here is just testing on data analysis and not user psychology. Sure, you can make progress this way, but if you want to be really successful, you need to understand how people make decisions based on the choices you give them, and for that, you need primary research (which is time consuming, expensive, and never statistically significant) and you need to understand how people make decisions. Luckily, there is a new field just for this called behavioral economics.
- Traditional economics studies what a rational person does when presented with information and a decision. Behavioral economics studies how actual people make decisions, and they are not always rational. So, what do you study in behavioral economics? You study heuristics/biases, which are the shortcuts people use to make decisions. I can talk for a week about this, but here are of the high level points:People are bad at mathPeople use irrelevant information as a guide to making decisionsPeople are overconfidentPeople hate losing something more than they like gaining something
- The over-arching guide to behavioral economics is called prospect theory. Its inventors were awarded the Nobel Prize in Economics a few years ago. It states:1: People do not think about absolute wealth, but of local gains and losses2: Whether something is considered a gain or a loss is based on a reference point or anchor3: People are risk averse with gains and risk seeking with losses2+3: Risk preference depends on reference point4: People are more sensitive to losses than gains of the same magnitude, called Loss AversionThe receiver of that Nobel Prize recently wrote a book synthesizing all of his learnings called Thinking, Fast and Slow. If your future involves understanding people and how they make decisions, it is a must read.
- What does this means: it means how you frame a decision affects what decision a person makes. This power can be used for good or for evil. Choice architecture is the technical term for framing problems in a way that makes people more likely to behave in the way you wish them to.[Talk landfill image]
- When you factor this knowledge into design of products, you get some really interesting results. One of the interesting things you do is actually define what causes happiness. I'll have to skip the logic for the sake of time, but the answer is that happiness is based on two things: contrast (anchoring) and adaptation (local gains/losses). So, in order to make people happy, they need to look better off than another option, and need to not become used to a situation. Technically, we call this providing variable rewards. Variable rewards are highly addictive, and the most successful products are too.Examples:If you stay a room with a red light for a long time, walk out and see a white wall, what color does it look like? (contrast) Answer: It would be greenIf you stay in a room with a bad smell for a long time, and someone else walks in, how bad do they think it will smelled compared to you? (adaptation)
- Now, if you're a product like GrubHub where you want to drive habit formation and get someone to use your product regularly, the work doesn't stop with getting someone to order just once. You have to get them to come back again and again. We use a technique called cohort analysis to measure this.Cohort analysis groups users by their sign-up date, and then measure how many of that group come back at certain intervals (weeks or months, generally). A good cohort stabilizes over time with a core group of people coming back time and time again.Now, as marketers, we have tools we can use to drive people back to our products. We can use email marketing, push notifications, ads, loyalty programs, discounts, etc. But, what we really want to do is get people to form habits so they come back to our product without us having to do all those things. Here, we need to go back to our behavioral economics to understand how to create habits.
- NirEyal, an entrepreneur out of the Bay Area has come up with a brilliant model of how to create habits called the Hook Model.The hook model starts with an external trigger. Say, you got an email that someone posted a photo of you on Facebook. That trigger needs to generate an action, like visiting Facebook. In order to be effective at doing that, the trigger has to promise a variable reward. Since the human minds adapts to conditions so quickly, good things you receive need to constantly be different, or else they become normal and boring. Right, so once you receive a variable reward, you need to ask the user to do something that feeds to this cycle for other users. That could be you commenting on the photo, liking it, posting another photo, etc. Then other people will be notified about that.Now, Eyal’s theory is that the most popular services transcend the external trigger and create an internal trigger in people’s minds. So, when people are bored, they think about going to Facebook without receiving an email about a photo of them because they’ve been trained to expect some sort of variable reward in their news feed.Caveat: Even though we have these theories and models about human decision making, we can't just rely on them wholesale. Humand are still hard to predict, so research and testing still need to happen even if your designs are informed with behavioral economic wisdom.