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Month: November 2008

Does jargon sell tech products or not?

Those of us in the tech world who shun jargon may forever remain an underclass. We may never rise to the mainstream, where today tech-centric vendors rule. So I’m delighted when I meet another one of our clan who declares proudly his rejection of tech-speak.

Don Farber, vice president of sales and marketing at KnowledgeSync, says that to reach business customers, you have to use words they understand. For many buyers in the mid-market, that means avoiding any jargon at all.

Here’s how he orders a steak: “I ask for ‘pink in the middle.’ When the waiter asks me, ‘Rare?’ I say, ‘I don’t care what you call it, just give me a steak that’s pink in the middle.'”

We have to be careful, though. Some buyers in the mid-market watch for tech words as if it were a secret handshake. One insightful Datadoodle reader read about Farber’s approach last week and posted a reply that began like this:

This is so true. And it cuts both ways. Larger midsize companies have IT teams who are knowledgeable about BI, and if you don’t use all of the most proper complex jargon with them, they think you’re a lightweight solution that doesn’t do what they need or, worse, that you’re a team of idiots who just happened to create what they wanted the first time…

Take that, Strunk and White (Elements of Style).

Play terminology by ear when selling to the mid-market

Those who sell BI software to mid-size companies get to be good at nailing down what shoppers want. These shoppers are smart and hard working. But when they shop for technology, the shopping list may be just a problem, a wish, or a fantasy—known only by a description.

I just spent Monday and Tuesday helping a client sell his BI software at Sage Summit in Denver. I also wandered around to other booths.

Don Farber, VP of sales and marketing at KnowledgeSync, which among its products is automatic alerts, describes a common conversation: “I tell him he may need alerts, and the guy says, ‘No, I don’t need alerts. I need this, this, and this,’ and he describes alerts.’”

When you’re fooling with terminology, you just have to play it by ear.

I’m combing through notes and business cards for a BI This Week story. Farber’s two stories—the other one’s coming soon– are the best I’ve heard.

There’s always a food angle, even in text analytics

Text analytics was one of those things I heard about every so often. Like so many terms in this business, the term comes out of a speaker’s mouth or PR person’s press release only to blow away. There’s no story, no context, nothing to chew on.

Then came a press release at BI This Week with a rare combination: surprise and concreteness. It said text analytics would help with food safety. I’m all for food, but I had no idea what text analytics had to do with it.

I emailed UK-based Linguamatics, publisher of the nifty tool they call I2E. What’s this I hear about food? Product manager Phil Hastings, ready to call it a day in Croatia, called to explain the features to me, barely post-breakfast and not fully verbal. I2E was indeed a powerful little thing, but I still didn’t get the food angle.

It wasn’t until I got William Hayes on the phone that things started making sense. He’s director of library and literature informatics at pharmaceutical research company Biogen Idec. They don’t do food, but close enough.

If you think the Sunday New York Times is enough for one day, consider what the research community has to bear. Hayes says, “If you’ve got 20 million articles to read, where do you start?’

“The research industry works under a tougher knowledge model than terrorist intelligence gathering,” says Hayes. “Our ability to tap that ocean of literature is like dropping a line into the ocean for fish.”

In general, a scientist can read 150 to 200 full text journal articles a year, he explains. A curator can review about 100 abstracts a day “for a few days before you start going nuts.” Text mining is the only way to keep up with the ocean of literature produced each year.

The food industry fries potatoes, but it also has to keep a lookout on research.

TNO information analyst Fred van de Brug told me the acrylamide story: Most people in the food industry missed the first warning. Scientists had published a discovery in 2000 about a possible carcinogen known as acrylamide, which can develop in starch-rich foods like potatoes as they are fried. By the time the warning finally hit the public media in 2002, millions of people became frightened, perhaps unnecessarily. Text mining would have given food processors time to head off a crisis.

I2E is more agile than standard text mining. You can learn to use it in a few hours. Hayes told me, “If you can remember bits of grammar and have some concept of what you’re researching, it’s a piece of cake.”

It’s a story in progress for BI This Week.