Time’s writeup of the Obama campaign’s online and data efforts, linked earlier, is fascinating reading.
Constant optimization with A/B testing played a big role in the campaign’s fundraising efforts (emphasis added):
A large portion of the cash raised online came through an intricate, metric-driven e-mail campaign in which dozens of fundraising appeals went out each day. Here again, data collection and analysis were paramount. Many of the e-mails sent to supporters were just tests, with different subject lines, senders and messages. Inside the campaign, there were office pools on which combination would raise the most money, and often the pools got it wrong. Michelle Obama’s e-mails performed best in the spring, and at times, campaign boss Messina performed better than Vice President Joe Biden. In many cases, the top performers raised 10 times as much money for the campaign as the underperformers.
Chicago discovered that people who signed up for the campaign’s Quick Donate program, which allowed repeat giving online or via text message without having to re-enter credit-card information, gave about four times as much as other donors. So the program was expanded and incentivized. By the end of October, Quick Donate had become a big part of the campaign’s messaging to supporters, and first-time donors were offered a free bumper sticker to sign up.
The Obama campaign succeeded online in part because it didn’t know what worked–and admitted it. That’s the hallmark of a good marketer: humility about your skills, a willingness to constantly check your core assumptions.
To succeed as a marketer, you have to take risks and put your ego on the line. As Pixar president Ed Catmull reminds us, “if we aren’t always at least a little scared, we’re not doing our job.”
A/B testing can help you make great leaps in optimizing your online marketing, but it’s not a panacea. It requires a lot of measurement, commitment and patience.
Peep Laja offers three useful warnings:
- Most A/B tests won’t produce huge gains (and that’s okay)
- There’s a lot of waiting (until statistical confidence)
- Trickery doesn’t provide serious lifts, understanding the user does
This is spot on. Most of the tests I have run have failed to achieve any lift, while others were inconclusive statistically even after collecting considerable data. And his final point is critical: focus your testing not on the quick win but on how you can best convince your customers to buy.
If I had to add a fourth point, it’d be this: Run tests only to learn something, not simply for the sake of testing. What question are you trying to answer with your test, and how would the results lead you to do things differently in the future?
The way to boost your site’s Google ranking, Paul Boag says, is to write quality content that your customers want to link to. Don’t waste time with consultants’ SEO voodoo.
“[I]t all comes down to content,” he writes. “If you create great content, people will link to it, and Google will improve your placement. It really is that simple.”
When hiring, finding job candidates with the right technical skills is the easy part. Bryan Goldberg offers advice on how to separate the merely adequate applicants from the all-stars:
[I]f a candidate can’t even tell you why they liked their last job, or what they got out of their college experience, or any of the million other questions that speak to their basic humanness… Then no amount of experience will make them valuable.
Seth Godin says non-profits need to be more innovative, which means they need to be more willing to accept failure:
Go fail. And then fail again. Non-profit failure is too rare, which means that non-profit innovation is too rare as well. Innovators understand that their job is to fail, repeatedly, until they don’t.
This is absolutely right. A non-profit group should do everything it can to better advance its mission. That may mean trying new and better ways to be even more effective. Fear of failure is the surest way to maintain the status quo.
Here is a typical problem: A passenger on the sixth floor wants to descend. The closest car is on the seventh floor, but it already has three riders and has made two stops. Is it the right choice to make that car stop again? That would be the best result for the sixth-floor passenger, but it would make the other people’s rides longer.
For Ms. Christy, these are mathematical problems with no one optimum solution. In the real world, there are so many parameters and combinations that everything changes as soon as the next rider presses a button. In a building with six elevators and 10 people trying to move between floors, there are over 60 million possible combinations—too many, she says, for the elevator’s computer to process in split seconds.
As far as I can tell, small businesses viewed Groupons largely as the former: you give away your product near cost, and gain new customers from Groupon’s huge mailing list.
Anecdotally, Groupon’s salespeople in fact encouraged businesses to give their product away at a loss in order to attract new consumers. By lowering the cost of trying your restaurant or salon, the theory ran, you could win new business that you wouldn’t otherwise have gotten.
The problem is that for consumers, it seems mostly to have been about price discrimination; people used Groupons to buy something that they wouldn’t buy at full price. So while your Groupon deal brought in a huge stampede of new customers, those customers were either too cheap, or too poor to spend a bunch of money at your business. Restaurants, who were supposed to be one of the core businesses for daily deals, complained that Groupon customers were disproportionately poor tippers who took up tables while carefully not spending any more than the face value of the Groupon–no drinks, no dessert. Then they never came back.
The Obama campaign’s crack marketing staff routinely failed to predict which e-mail subject line would work best:
Writers, analysts, and managers routinely bet on which lines would perform best and worst. “We were so bad at predicting what would win that it only reinforced the need to constantly keep testing,” says Showalter. “Every time something really ugly won, it would shock me: giant-size fonts for links, plain-text links vs. pretty ‘Donate’ buttons. Eventually we got to thinking, ‘How could we make things even less attractive?’ That’s how we arrived at the ugly yellow highlighting on the sections we wanted to draw people’s eye to.”
Their success was in their ability to find out what works, not their ability to get it right the first time.
L. Gordon Crovitz on what “big data” has wrought: “Voters need to develop buyer-beware habits. The era of politicians saying the same thing to all voters is over. Campaigns aim to tell voters exactly what each wants to hear: data-driven pandering.”
There’s a powerful force keeping your supporters from giving you money online: friction.
Tim Kachuriak, Dan Gillett, and I will tell you how to identify friction and how to limit its effects on April 8 at the Association of Fundraising Professionals 2013 International Conference in San Diego.
Here’s the event description:
Friction can be described as anything that causes psychological resistance to a given element on a web page. And if you took a good look at your online donation page, you’ll find it is riddled with it. This entertaining workshop will help you to identify the donation-killing friction on your web site and implement strategies to limit it.
How has friction limited your online fundraising?