Welcome to the SalesPredict blog! SalesPredict is a company that cares about insights. Our predictive analytics solution helps B2B companies uncover new insights in their CRM and marketing automation data–overlooked ...
VentureBeat Singular raises $5M from General Catalyst to simplify mobile marketing VentureBeat Workflow management, analytics, and predictive tools are all located in a single dashboard — hence the name.
The Adobe team, led by John Bates, presented a great five-step PA process. It applies to any solution, of course, not just Adobe’s. My own paraphrase (with an added step 2) is:
Worry – Scope the question: What crazy thing did you notice; what isn’t working; what do you want to improve?Collect & Clean – Build a coherent, normalized, clean profile for each “person” (could be anonymous or known), based on whatever data you have.Explore – Poke into the data set with an open mind and a spirit of adventure; uncover attributes that are related but unexpected (i.e., not “I-knew-that” but “no, really?!”)Group – Find groups of profiles that act alike with respect to key dimensions, perhaps from step (3).These are not predefined segments but groups of profiles/people that emerge from the algorithms; studying these groups (or “clusters”) can point toward unexpected insights.Predict – Finally! Note everything that goes before you leap into the crystal ball. Taking the groups from step (4), try some models to predict their likelihood to do (or not do) X, Y, or Z – whatever it is you care about (like buy, or opt-in).Do Something – Execute the test, offer, campaign, or whatever, against the groups more-likely-to (or less-likely-to, in the case of something bad, like default).
There’s a lot more to say on this topic, of course. (This book by NYU’s Fostor Provost & Tom Fawcett is a great place to start.) In the meantime, I have a prediction of my own (90% confidence): By this time next year, predictive analytics will be as common in leading digital marketing organizations as testing and optimization.
"The recent Kilgray blog post about the "terminology as a service" (TaaS) project reminded me of the considerable unfinished business with the term extraction extraction module introduced three years ago with memoQ 5.0. It's a very useful feature that I apply frequently to my projects, and my prediction years ago that it would not replace SDL's MultiTerm Extract in my workflows was wrong. Overall it proved to be more convenient, and after the shock of discovering that the defective logic of MultiTerm Extract created new German "words" that neither existed nor were in my text sources, I dumped that dodgy tool and stuck to memoQ's extractor. But sometimes its rough edges are irritating, and I wish Kilgray would finally pick up the ball that was ..."
Justin Ward, manager of the data science team at the online streaming service describes the big data environment that enables it to deliver new shows successfully to an increasingly international audience.
Big data drives better decision making, according to The Economist ... TechRepublic Also in the report, 45% who said they are growing faster than their competition also use predictive analytics in their decision making process.
Last week, Salesforce bought sales data intelligence startup RelateIQ for $350 million. But that's just the latest deal in the marketing tech sector, which has seen several billion-dollar acquisitions in the past couple of years.
In addition, Rovio may use and disclose personal data contained in the data file for justifiable purposes (such as direct marketing, distance selling, other direct advertising, opinion polls or marketing research) in accordance ...
“Predictive analytics are a way of making decisions by taking the data of past performance, and using that data to expect future performance.” But the problem is marketing may be tackling this all wrong.
Don’t do these five things, and I predict your predictions will improve:
1. Be self-centered
Predictions usually tell us more about our own preoccupations than they do about the future.
2. Mistake habits for human nature
We assume social mores and the ways we use and abuse our time are not just temporary traps but something much deeper. Yet few things change faster. People don’t smoke on trains. Women vote.
3. Trust our first impressions
As Malcolm Gladwell pointed out in Blink, first impressions say more about us than anyone else. Like habits, frames of reference change. Shoppers who rode the first escalators at Harrod’s in London in 1898 actually fainted.
4. Overestimate the speed of change
Technologies are mired in detail, mistakes are the rule rather than the exception, and a lot of problems (the common cold?) are a lot harder than they look.
5. Overuse the word “revolution”
A good app is not a revolution. In the 1960′s, the well-known UK futurist Gordon Taylor foresaw a “revolution” caused by happy pills and chemical peels. All we can say to that is, welcome to California.
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