Posts Tagged ‘predictive analytics’

The Man Who Feared Analytics

June 9, 2010

A business owner had once been referred to me by a colleague with whom he had already been doing business. For many years, the businessman’s photography business had been sustained through direct mail advertising, and he often received a 5%-7% response rate, an accomplishment that would boggle most direct marketers. But the recent economic downturn combined with photography’s being a discretionary expense, he soon found his direct mail solicitations bringing in a puny 0.8% response rate. The business owner had a great product, a great price, and a great offer, but at that response rate, he was no longer breaking even.

My colleague and I spoke with the businessman about his dilemma. We talked through his business; we looked at his most recent mailer, learned how he obtained his mailing lists, and discussed his promotion schedule. We found that the photographer would buy a list of names, mail them once, and then use a different list, not giving people enough opportunity to develop awareness of his business. We also found that he didn’t have much information about the people he was mailing.

We recommended that analytics could help the photographer maximize his margin by improving both the top and bottom line. Analytics would first help him understand which customers were responding to his mailings. Then he could purchase lists of people with characteristics similar to those past respondents. His response rate would go up, since he would be sending to a list of people most receptive to his photography. He would also be able to mail fewer people, cutting out those with little likelihood of response. He could then use the savings to remail the members of his target segments who hadn’t responded to his earlier mailing, and thus increase their awareness. It all sounded good to the photographer.

And then, he decided he was going to wait to see if things got better!

Why the Fear of Analytics?

The photographer’s decision is a common refrain of marketers. Marketers and business owners who are introduced to analytics are like riders on a roller coaster: thrilled and nervous at the same time. While marketers are excited about the benefits of analytics, they are also concerned about its cost; they’re afraid of change; and they’re intimidated by the perceived complexity of analytics. We’ll tackle each of these fears here.

FEAR #1: Analytics could be expensive.

REALITY: Analytics is an investment that pays for itself.

The cost of analytics can appear staggering, especially in lean times. Some of the most sophisticated analytics techniques can run into tens – if not hundreds – of thousands of dollars for a large corporation. However, for many smaller companies, analytics can run a few thousand dollars, but still a lot of money. But analytics is not an expense; you are getting something great in return: the insights you need to make better informed marketing decisions and identify the areas in your marketing that you can improve or enhance; the ability to target customers and prospects more effectively, resulting in increased sales and reduced costs; and the chance to establish long-term continuous improvement systems.

Had the photographer gone through with the analytics for his upcoming mail, the entire analysis would have cost him somewhere between $1,300 and $1,800. But that fee would have enabled him to identify where his mailings were getting the greatest bang for his buck and he might have made up for it in reduced mailing costs and increased revenues. Once the analytics had saved or made the photographer at least $1,800, it would have paid for itself.

FEAR #2: Analytics means a change in the way we do things.

REALITY: Analytics brings about change gradually and seamlessly.
The photographer had been using direct mail over and over again, because it worked over and over again – until recently. In fact, having lost so much money on his recent direct mails, he’s probably leery of new approaches, so he stays the course out of familiarity. That’s quite common. But this is the nice part about analytics: change can be gradual! Analytics is about testing the waters, so to reduce risk. Perhaps the photographer could have done a test where half of his mailings were executed the traditional way, and half done the way the analytics recommended. Over the course of a short period, the photographer could then decide for himself what approach was working best.

FEAR #3: Analytics is “over my head.”
REALITY: You need only understand a few high level concepts.

Those complicated and busy mathematical formulas, in all their Greek symbol glory, can be intimidating to people who are not mathematicians, statisticians, or economists. In fact, even I get intimidated from those equations. We must remember, however, that these formulas were developed to improve the way we do things! With analytics, all you need to know is what approach was employed, what it does, why it’s important, and how to apply it – all of which are very simple. Analysts like me deal with all the complicated stuff – finding the approach, employing it, debugging it, refining it, and then packaging it in a way that you can apply seamlessly. And if you don’t understand something about the analytical approach employed, by all means, ask! And any good analyst will give you all the guidance you need until you’re able to apply the analytics on your own.

Forgoing Analytics Can Cost Your Business Three Times Over!

Analytics is one of those tools that many marketers know can enhance their businesses, yet decide to hold off on – either for cost, perceived complexity, or just plain fear. This inaction can be very dangerous. Analytics is not just a tool that improves your business decision making; it also helps you diagnose problems, identify opportunities, and make predictions about the future. Failure to do these properly costs you in three ways. First, you market incorrectly, wasting money. Second, you market to the wrong people; they don’t buy, and you lose revenue you could have made marketing to the right people. Third, you fail to recognize opportunities, and you forgo any sales those missed opportunities may have brought. Analytics is an investment that pays for itself, pays dividends down the road, brings about change in an easy and acceptable way, and whose benefits are easy to grasp and financially rewarding.

Charities are Spying on You – But That’s Not Necessarily a Bad Thing!

May 26, 2010

The June 2010 issue of SmartMoney magazine contained an interesting article, “Are Charities Spying On You?,” which discussed the different ways nonprofit organizations are trying to find out information – available from public sources – on current and prospective donors. As one who has worked in the field of data mining and predictive analytics, I found the article interesting in large part because of how well the nonprofit sector has made use of these very techniques in designing their campaigns, solicitations, and programming.

At first glance, it can seem frightening what charities can learn about you. For instance, the article mentions how some charities’ prospect-research departments look at LinkedIn profiles, survey your salary history, and even use satellite images to get information on the home in which you live. And there is a wealth of information out there about us: gives info about the value of our homes and those around it; if you write articles or letters to the editor of your newspaper, online versions can often be found on Google; buy or sell any real estate? That too gets published in the online version of the newspaper; and online bridal and baby shower registries, graduation and wedding announcements, and any other news are fair game. And your shopping history! If you buy online or through a catalog, your name ends up on mailing lists that charities buy. Face it, there’s a lot of information about us that is widely and publicly available.

But is this so terrible? For the most part, I don’t think so. Surely, it’s bad if that information is being used against you. But think of the ways this data mining proves beneficial:


Let’s assume that you and I are both donors to the Republican National Committee. That suggests we’re both politically active and politically conservative. But are we engaged with the RNC in the same way? Most likely not. You might have donated to the RNC because you’re a wealthy individual who values low taxes and opposes a national health care plan; I might have donated because I am a social conservative who wants prayer in public schools, favors school choice, and opposes abortion. By seeking out information on us, the RNC can tailor its communications in a manner that speaks to each of us individually, sending you information about how it’s fighting proposed tax hikes in various states, and sending me information about school choice initiatives. In this way, the RNC maintains its relevance to each of us.

In addition, it’s very likely, in this example, that you’re donating a lot more money to the RNC than I am. Hence, that would likely lead the RNC to offer you special perks, such as free passes for you and a guest to meet various candidates or attend special luncheons or events. For me, I might at best be given an autographed photo of the event – in exchange for a donation of course – or an invite to the same events, but with a donation of a lot of money requested. I might get information about when the next Tea Party rally in my area will be held. Or even a brief newsletter. One can argue that the treatment you’re getting vs. that of what I’m getting is unfair. However, think of it like this: at a casino, people who gamble regularly and heavily are given all sorts of complimentary perks: drinks, food, a host to attend to their needs, and even special reduced rate stays. That’s because these gamblers are making so much money for the casino, that the cost of these “comps” is small in comparison. In addition, the casino wants to make it more fun for these gamblers to lose money, so that they’ll keep on playing. In short, the special treatment you’re getting is something you’re paying for, if indirectly. I’m getting less because I’m giving less; you’re getting more because you’re giving more. And the charity will give you more to keep you giving more!

Reduced Waste

Before direct marketing got so sophisticated, mass marketing was the only tactic. If you had a product to sell, you sent the same solicitation to thousands, if not millions of people and hoped for a 1-2% response rate. Most people simply threw your solicitation in the garbage when it came in the mail. Many recipients didn’t have a need for the item you were selling or the appeal for which you were soliciting, and disregarded your piece. As a result, lots of paper was wasted, and the phrase “junk mail” came into existence. In addition, if you used follow-up methods, such as phone calls after the mailing, that got costly trying to qualify the leads, just because of the labor involved.

Now, with targeted marketing and list rental, sales, and sharing, charities can build predictive models that estimate each current and prospective donor’s likelihood of responding to a promotion. As a result, the charity doesn’t need to send out quite a large mailing; it can mail solely to those with the best chance of responding, reducing the amount of paper, print, and postage involved, not to mention reduced labor costs involved, both in the production of the piece and in the staffing of the outbound call center. In short, the charity’s data mining is helping the environment, reducing overhead, and increasing the top and bottom lines.

Better Programming

By knowing more about you, the charity can know what makes you “tick,” so that it can come up with programs that fit your needs. Even if you’re not a large donor, if you and other donors feel strongly about certain issues, or value certain programs, the charity can develop programs that are suitable to its members at large. And while many larger donors may be granted special privileges, their large donations can help fund the programs of those who donate less. Everybody wins.

Not bad at all

The data mining tactics charities use aren’t bad. People don’t want to be bombarded with solicitations for which they see no value in it for themselves. Data mining makes it very possible to give you an offer that is relevant to your situation, is cost-effective and resource-efficient, and design programs from which you’re likely to benefit. It is important to note, that while major donors get several great perks, charities must not ignore those whose donations are smaller, for two reasons: first, they have the potential to become major donors, and second, because of their smaller donations, it’s very likely their frequency of giving is greater. This can mean a great stream of gifts to the charity over time. Hence, charities should do things that show these donors they’re appreciated – and, quite often, this too is often accomplished by data mining.

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