So glad to get more coverage for the team and the personalization work we’ve been doing at eBay.
Proud to see external validation of our CRM and personalization approaches in email: http://marketingland.com/3-brands-email-marketing-right-211020
eBay has come a long way in our CRM and email marketing in the past two years. Personalization is a relatively easy task when you’re dealing with just one region and one vertical and a hundred thousand customers. With 167M active buyers across the globe, eBay’s journey to help each of our buyers find their version of perfect was quite complex.
Like many in our industry, we’ve had to deal with legacy systems, scalability, and engineering resource constraints. And yet, we’ve made email marketing a point of pride — instead of the “check mark” that we started from. Here’s our story.
Here’s the Information Week interview about the CRM and personalization system my team built at eBay.
In life as in work, we’re constantly dealing with uncertainty. As parents, employees, leaders, we look at the future and estimate the odds: what’s the chance that our teenage son will do drugs? What’s the chance that this system’s load will exceed what we designed it for? How likely is this risky investment to result in a huge competitive advantage?
We estimate these chances, and some of us are better than others; we look at the data, ask for advice, look for prior examples. We are hard-wired to estimate the chances – and to over-value potential loss over potential gain, and over-value action over allowing things to proceed on their own. The best of us identify their built-in biases and adjust their decision-making accordingly, but even they can’t avoid the “sacred geometry of chance.“ Continue reading “May the Odds Be Ever in Your Favor”
The most concise, truly beautiful definition of leadership I’ve heard is “having others WANT to follow you.” This definition means two things 1) that you’re actually moving somewhere, not standing still and 2) that others are convinced, not coerced, into going along.
There are so many leadership books out there, some talking about vision, some about audacity, some about authenticity. Advice is often mysterious and convoluted — we hear of “executive maturity” (perfectly ambiguous excuse to keep the outsiders away) and of “situational leadership” (sorry, there are no best practices … every situation is different). Continue reading “If your team isn’t on-track, try this”
You’ve been there. Someone on your team just screwed it up. Your production website went down in the middle of the night, it took hours to bring it back up. It’s 10am the next day, you’re at your daily standup, and the culprit is looking down, ashamed and quiet; the team is noticeably uncomfortable and is expecting you, their leader, to scream and shout about business impact and accountability and how bad this all is.
You’re upset. The outage already cost your group some reputation — you’re seeing tweets and a message from the investor, and you have no idea how something this dumb could have been overlooked.
You can allow your emotions to take over. You can do the screaming, you can shame the perpetrator, who will undoubtedly remember this occasion and probably won’t make a mistake of this kind again. You will scare others at the standup enough for them to be afraid of their own shadow for the next week.
Or you can take a breath.
In digital, you can easily spot two opposing camps — the artists and the quants.
Artists are folks like the New York Times: Pulitzer prize-winning journalists use their intuition and skill — their unique talents — to create one-of-a-kind stories, and the judgment of the Chief Editor is pure gold. Artists create incredible brand value; true loyalty — lifelong fans.
Quants are folks like eHow.com. They use Wall Street-style algorithms to identify long-tail Google queries that have weak competition, and pay amateur writers $5 to create short posts that address those queries. Queries like “how to remove gum from clothing.” Their quant models tell them that stories like this will make $7 on ads in the next year, so they pump out millions of such stories.
Both approaches have problems. If a New York Times writer gets hit by a bus, there’s no replacing them. Their talent dependency is not scalable. eHow stories — millions of them — inspire no loyalty, create no brand value. Let’s face it, it’s crappy content. No wonder Google did everything in its power to kill it. Continue reading “Machine Learning and Digital Marketing: Melding Human and Machine”
You’re staring at the reviews. Looking for a Lite version to try out first. Catching yourself at the thought: “I’ve spent more time thinking about buying this thing than the 99 cents that it’s worth.” Continue reading “Paid Apps Model Revisited”
I had a chance to interact with two companies recently: Homegrown and City of Bellevue Utilities. These two companies helped me crystallize the difference between “value statement on the wall” and “values that are coming through to customers.”
Homegrown’s tagline is “sustainable sandwich shop.” Their About Us page has the word “organic” mentioned 22 times. It says that “stores are designed to be as low-impact as possible… [using] reclaimed, recycled … building materials.” Their napkin dispenser asks you to think about the environment and only take as many napkins as you will use. They have metallic cutlery at every table. Clearly, owners at Homegrown are trying to project an identity that stands for sustainability and environmental awareness.
Yet, when you order a salad “for here,” you get a single-use plastic container with a salad inside.
In life as in business, if you are willing to invest effort into something, you will do better – a lot better – than average. Today’s story is about a real-estate purchase – and how doing your homework makes a 10x price difference for services.
Did you notice that you just paid your agent $1000/hour?
Basic dynamics of a real-estate transaction: when you buy a $500k home, 3% of the purchase price goes to the sellers’ agent; 3%, or $15k, goes to your (buyer’s) agent. What exactly are you paying for? Continue reading “Full Price is for the Lazy, or Stop Financing Their Marketing”
I had the privilege of speaking in front of the Code Fellows class this week; as a part of the talk, I took “scary” interview questions from students and attempted to create framing for answering them. Here are a few:
“What are your greatest weaknesses?”
“Do you have questions for me?”
What to do when you’re stuck or botched a question?
You’re a recent grad from a top engineering school. You come to a hot startup, and in your second week, you volunteer to implement an ambitious new feature. You slave away at it for a week, burning the midnight oil, trying to impress your new colleagues. You’re brilliant: you find an ingenious algo that solves the problem elegantly and with a lot less code than anyone thought was possible. You proudly check the code in, it ships to the site.
You’re proud of your accomplishment. You move on to the next big thing.
Spoiler alert: you screwed up.
Let’s say you have an opening on your technology team: An urgent need for engineer that will expand your application written on top of the Spring Framework in Java. You use Puppet for deployment, and Jenkins for managing your builds. So naturally, you craft a job description that says “must know Spring, Jenkins, and Puppet.”
You look hard for a perfect dev for the job and find one. She’s been writing code in Java for the last 10 years; and Spring was at the core of a big project in the past. She has experience with Puppet. You proceed with the hire — and the new dev flies through the assignment and all is well. Continue reading “Hire for Velocity of Learning”
This article was originally published as a guest post on Geekwire; it is republished here for the readers of this blog.
In early ‘90s, while working on Windows NT, Microsoft popularized an idea to make everyone on the team use early builds of their own software.
Back then, it was quite a painful request — imagine developing an operating system on a box prone to crashes, where your basic tools don’t quite work right. This setup undoubtedly causes loss of productivity and frustration.
And yet, what it gains is something more valuable: an immediate feedback loop, where bugs are found quickly, where there is healthy peer pressure to urgently fix issues that are preventing your colleagues from doing their work. Since the cost of a bug goes up the longer it lives in the codebase, this feedback loop — dubbed “dogfooding” — is a significant net gain.
Today, it’s even easier for most technology companies to dogfood, because most of us aren’t developing operating systems. If your internal build doesn’t work quite right, you can still do basic things – so the downside of dogfooding is minimal. Let’s explore some simple, natural examples:
- Facebook rolls out most features to employees first, and only then to a subset of external customers. Employees, of course, already use Facebook every day and can provide instant feedback.
- Everyone loves LOLCats. Employees of the Cheezburger Network are natural customers, as they consume their own content every day.
At my company, Wetpaint, we build tools for publishers to develop relationships with their readers through social media. We take dogfooding so far that we’ve built an entire media business — a very successful one — to be our own customers, and to test-drive our platform before our clients use it. This has allowed us to evolve our tools at record speeds.
But what if you’re working on a product that isn’t so easy to dogfood? You have to be creative and find a way to incentivize your employees to be users in order to get the information you need. One way to set this up is recurring competitions; here’s what I would do with these businesses, for example:
- Redfin, Zillow, Trulia (real estate): Employees must find the best real estate deal in their area. Give them virtual currency. Have them use your products — and competing products — to make their virtual investment decisions.
- SEOMoz (search engine optimization): Each team member sets up a blog and must use the company’s tools to make it rank the highest a couple weeks later.
- Tableau (data visualization): A leader selects a data set, and everyone is encouraged to find gems in that data set; the fastest, most interesting insight wins.
Give real prizes to the winners. Set up a weekly beer gathering, get the winners to share their strategy. I bet some product ideas will come out of that. Make sure these events are regular, not one-off, to encourage employees to keep thinking competitively and creatively.
Dogfooding programs complement agile and lean development practices very well, because iterating with the rest of your team for a few days before releasing an experiment increases your chance of success. You’ll also get the obvious feedback out of the way early.
Think of it as a modern version of Joel Spolsky’s hallway usability tests: instead of having to interrupt a colleague to review your UI, you’ll overhear “Oooh” and “Ahhh” when your code goes up on dogfood. That’s the perfect time to ask – “Hey, what do you think about this new thing?”
This article was originally published as a guest post on Geekwire; it is republished here for the readers of this blog.
However, in a startup, it’s so difficult to imagine how organizing a hackathon can be anything but harmful: “What do you mean, take a couple work days and drop what we’re doing? We’re in a race with competitors! There are holes in our product – and they’re blocking adoption! We can’t just waste a couple days!”
I know you’re under pressure. That’s the nature of startups.
And yet, allow me to ask you: how many times have you fought an issue for weeks, only to find an elegant solution that takes a day to implement? Have you ever built a feature that nobody ended up using? Have your employees begun talking about the “grind,” the soul-crushing 80-hour-week pace where bugs never end?
If so, hackathons can help with each of these. They let folks take a step back, concentrate on the big picture, and apply their passion – usually where it hurts the most.
Allow me to share a story from Wetpaint. In summer of 2011, we were struggling with our data warehouse system; we’ve had all the symptoms from the list above. This system was so unreliable that our internal customers didn’t trust the data. Engineers were burnt out from every-Saturday-is-a-workday routine. After a couple months of treading water, we realized that we needed to change something structural in our approach.
One key change we introduced was a framework for open-ended innovation. The intent was simple: all participants drop their day-to-day tasks for a couple days, and work on whatever is exciting for them, as long as it has something to do with our overall business. No top-down mandates. Work alone or with others. The only requirement is to show – demo, not PowerPoint! – your results to everyone else at the end.
We called this framework “hack days.”
I was amazed by the results. Initially planned as a morale-boosting exercise, there were somany great ideas that came out of it. One engineer’s 2-day project disposed of the majority of the issues we were having with the data warehouse. It took a completely different approach to the problem, challenging some of the foundational assumptions that no one ever doubted. Another engineer built a mind-blowing prototype of a tool that we ended up building over the next three months, and that tool had a significant impact on our bottom line.
Most importantly, this breath of creative, fresh air gave a sustained boost to everyone’s output, even as we re-entered regularly scheduled sprints. We made these hackathons a recurring activity – every quarter, coinciding with company-wide business reviews. Everyone in the company is invited to the debriefs now – and they walk out energized and motivated by the ingenuity of their peers.
Moreover, folks outside of engineering are adopting this framework, too. Our social marketing team, for example, drops their best-practices playbook for a couple days once a quarter, and encourages each team member to try their craziest, riskiest ideas. We’ve seen great results from it.
Give it a shot in your startup. Hackathons can become a “startup factory” in an established company, too. If you’d like help setting up a hackathon, send me a tweet, I’d be happy to help.
This article was originally posted as a guest post on Geekwire; it is republished here for the readers of this blog.
When you look at productive output from a software development team, there’s one factor that almost always predicts problems. You can have top talent; an outstanding idea; great agile process. And yet, if you don’t treat interruptions as a significant source of danger, the progress will be slow and painful.
We all know and love the feeling of “flow:” You’re in the zone, coding away or deep in thought on a financial model. There’s plenty of research that suggests that we do our best work in this state. We are also happiest at work when we are in the zone often.
But far too often, this state is broken up by a tap on your shoulder or a phone call. There’s a small, innocent question – and it takes you five minutes to answer it. But when you come back to your original task, the inspiration is gone. The “zone” is gone. You need a half hour to just bring back all the variables back into your mind. Or worse, you may not catch the sense of “flow” again that day at all.
That’s the scary thing about interruptions – they typically only take a few minutes to handle, but then bring a trail of a scattered state of mind. What’s worse, it’s easy to embrace this interruption as a good thing – hey, I just solved a problem, unblocked a customer, made someone’s day better. And yet, for an organization, more often than not, this interruption was a net negative.
Technology startups have a key property: if they stagnate – stay with the status quo, spend too much time on sustained engineering – they die. Time is of the essence; competition is fierce, someone else is going to win that customer, build a better product, hire stronger talent. So only the time that you invest into important AND non-urgent things is bringing you closer to your vision. Troubleshooting is a necessary evil. You must make your current customers happy. And yet, if you spend all of your time on it, you’ll never make it.
So I encourage you to take a systematic approach: actually measure interruptions and create goals to reduce them to a reasonable level.
Create a mailbox connected to your issue tracking system. Every time someone has a question or request outside of the current sprint’s priorities, have them send an email to that mailbox – or do it for them. There are, in fact, two mailboxes: one for emergencies (ex. site’s down) and one for regular issues (ex. data in the analytics DB doesn’t add up). At the end of each week, count the chickens.
Categorize each interruption by component. Draw a graph over time. Discuss it with your senior engineers.
You’ll be amazed. I sure was when we did this at Wetpaint. When we started this practice, we noticed that we had an average of 60 interruptions a week for a product development team of 15.
This, coincidentally, was a time when we were seriously struggling as an organization – we had a hard time moving the product forward. We dug into the root causes and noticed that most of these interruptions were triggered by two systems. We invested time in two sprints to systematically address these issues, and the interruption count dropped to 10-15 a week. Not surprisingly, our productive output shot up.
Morale also improved significantly. Folks felt like they are working on features that move the product forward, instead of constant firefighting.
An important factor in our setup: we established a rotation program to triage interruptions –and only placed managers on this pager duty rotation. Some interruptions are 3am emergencies that must be dealt with immediately; when managers have to be the first line of defense, root causes tend to get a systemic resolution surprisingly quickly.
Another positive side effect of being systematic with interruptions is that nothing falls through the cracks anymore. An internal customer would find an issue and send one of the devs an email, or just chat with them in the kitchen about it. Sometimes, requests like this would be lost – or delayed far enough to get the customer concerned. After we set up this rigorous interruption tracking, every client knew where to look up the status of their issue.
The movie Social Network has a magical moment. A loud house party is going on. And yet there’s a guy in the middle of the room with headphones on, coding away. People walk around him, careful not to disrupt – nobody dare interrupt his flow!!
Do you know how many times a week your product development organization is interrupted today? Can reducing that number take your crew to the next level of productivity?
This article was originally posted as a guest post on Geekwire; it is republished here for the readers of this blog.
Facebook and its third-party applications today know a hell of a lot about each us: what content we read (Washington Post Social Reader); what music we listen to (Spotify); what movies we watch (Netflix).
Facebook opened up a green field for the game creators, too: games with friends are just so much more engaging. However, while Zynga and Electronic Arts fight for the attention of the social gamer, the only party that is guaranteed to win is Facebook – they gobble up data from ALL of the apps to compile a multi-dimensional data set that will ultimately allow them to build the best personalization and ad relevance engine on the web.
This strategy of Data Dominance – knowing more about each user than any competitor – is executed through a set of API’s that Facebook calls Custom Open Graph. Each micro-interaction in the vertical universe of a game, a social reader, or a music app is a way for the app to drive traffic; it is also a way for Facebook to learn more about each user. It’s a powerful data mining operation that aligns the interests of all parties involved: the consumer, the app creator, and Facebook.
But how will Facebook use this data advantage? No matter how addictive Facebook is, consumers still spend six out of every seven minutes on other sites. To extend its data dominance to the rest of the web, Facebook should offer analyzed data up as a service to other sites – driving value for third parties and revenue for itself.
In fact, Facebook has already started down this path with its ad products. While Facebook started out by targeting ads on facebook.com using only their own internal data, they recently made the smart move to integrate insights from other publishers’ sites through Facebook Exchange. This was the first step toward an external ad network, and a direct challenge to the eternal enemy, Google, on their AdSense home ground.
With personalization, however, Facebook has been playing it close to the chest: the famous EdgeRank– the ranking algorithm behind the newsfeed that judges what content from your friends will be interesting to you – is so far available to Facebook only. No third party can leverage its great insights. Facebook made a weak attempt to unlock some of its power with the Recommendation Bar plugin; it was a move in the right direction, but the execution sunk it. Instead, Facebook should offer personalization as a cloud data service – and they should charge for it.
Imagine if The New York Times could tell if you’re going to like a particular story – and recommend you a different one if you wouldn’t. Imagine if an online store could know – based on your Facebook profile – which product you are more likely to buy. Both of these businesses would flourish. And Facebook could take a cut of the incremental revenue.
Let’s examine Outbrain, a premium syndication provider. Fundamentally, they are in the relevance business – given a piece of content, they suggest several other pieces of content a reader might like. Facebook could solve this exact problem a lot better – they have more data to base the recommendation on.
Facebook is in a position to unlock incredible new revenue for a whole slew of merchants, if only they allowed partners to tap into the personalization engine directly.
I work at Wetpaint, where we’re building a quantitative platform for audience development. Today, we use Facebook as an efficient content delivery channel to build loyal audiences. We’ve developed ways to run statistical experiments to learn about the audience’s interests, and this analytical approach has driven extraordinary results for us.
And yet we are only scratching the surface of the multiplier effect that is available through the world’s greatest optimization laboratory. Facebook today is mostly a black box; but if Facebook were to open up its personalization engine, publishers and brands would be able to create far deeper and more engaging relationships with readers and customers.
We’re on the cusp of a personalization revolution in publishing. Facebook, with its strong advantage in Data Dominance and its equally strong incentive to make the online experience more personalized (for both users’ and advertisers’ sakes), is uniquely positioned to take us there.
I’ve had a curious experience with Amazon EC2 recently, and it made me think of a the process of adoption of new systems and services. In short: it doesn’t matter how good your product is, if it’s too hard to switch from the old way of doing things to your new-and-revolutionary gizmo. Let me share two stories.
Microsoft Word vs WordPerfect, 1991. Out of the gate, WordPerfect is a giant with almost 50% market share. Microsoft just released a “better mouse trap”; they also know that the competitor’s product has massive adoption, and Word will hit a big wall because of the incompatibility of the two document formats. If a customer buys Word, they can’t open their old WordPerfect documents:
“No matter how good Word is, I have to buy WordPerfect anyway to have access to my old stuff. Damn, I already spent money on one word processor.. Why do I need another?..”
Microsoft does the smart thing: they write adapters for WordPerfect import AND export. Now, if you are an early adopter of the new-and-amazing MS Word, you can still send documents to your dinosaur friends. The barrier has been lifted, the purchasing decision is now to be made only on merit; with this single move, they were able to wipe away most of the network effect advantage of their competitor.
Fast forward to 2012. VMWare and on-premise virtualization providers are under attack by platform-as-a-service vendors, first and foremost, Amazon EC2. Amazon has built a cost-effective, scalable, very advanced mouse trap. It’s not a perfect replacement – but it’s better in many ways. Lots of Amazon’s potential customers today are using various on-premise virtualization solutions. And yet, 6 years after the launch of EC2, there is still no way to take my VMWare Linux box and upload it – seamlessly – into EC2.
No wonder that only under 5% of top 5000 websites by traffic are using Amazon EC2 today.
As I was finishing school, I had a dream – I wanted my job to maximize my influence. I wanted the product of my craft to touch, in a meaningful way, as many people as possible, helping them in small and large ways. It’s mostly pride and desire to maximize the control over your environment: isn’t it awesome when everyone around you knows what you’ve been working on?
“You work on the search engine at Google? Wow, I use that every day!”
“You’re at Boeing developing the new 787? So many people are going to fly on that!”
A beautiful quote from a Microsoft engineer on this subject:
Very few projects at Microsoft have “small” impact. Everywhere you turn, the projects people are working on are likely to be used by thousands or millions of people. You have the opportunity to earn, save, or cost the company millions of dollars through your work. It’s an awesome responsibility, but an awesome chance to create widely influential software.
I’ve found a hole in this logic: it’s missing a key variable. It’s not just about the number of lives you touch. It’s also about the number of people that are working on this same product. The logic is simple: if there are thousands of people working side by side with you, your individual contribution will be lower. You will own and contribute to a smaller part of the puzzle.
Moreover, for technology projects, I’d argue the number of engineers working on the product has an even stronger, quadratic effect on each person’s influence. Ancient, yet so contemporary book Mythical Man Month makes this point well.
Here’s my attempt at quantitatively measuring your work influence number as an engineer in a high-tech company:
Let’s look at some examples:
- Microsoft Office is one of the world’s most used products; yet there are quite a few engineers touching it. Spread-out, shared ecosystem of Office Shared services that own cross-product components and installation, as well as groups that own localization and documentation, makes the denominator in the equation above quite high.
- Facebook is famous for having a restriction on the number of engineers that can work on a given product; I can’t find references to the exact number, but anecdotally, it’s under 10. So let’s say 10. Let’s look at the example of the Timeline: with Facebook’s 900M users, influence of an engineer working on that team is 900M/100 = 900K.
- At Wetpaint, there are 3 engineers working on the wetpaint.com website. Last month, we had 12 million readers. Influence of each engineer = 12M / 9 = 1.3M.
If you’re looking for your job to have influence – right out of the gate – work in a small, isolated team that has full control over its destiny. Startups are by definition structured this way.