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If yesterday's sales professional depended on a Rolodex and a social network, today's primary sales intelligence tool is predictive analytics.
Companies know that analyzing customer data is core to their competitive advantage, though some are further down the learning curve than others.
"You can't do without it and be competitive today," Scott Robinson, a SharePoint and business intelligence expert, said. "Business intelligence is looking at the data you already have and discovering new questions."
In particular, companies are trying to mine their customer data and apply predictive analytics to identify future patterns of customer behavior and derive insights from the past that might signal their action in the future. Robinson noted that while predictive analytics is being used in many industries, it's been a particularly effective sales intelligence tool.
"You can look at how you're performing internally, you can look at infrastructure, you can look at competition, look at inventory," he said. "BI connects things we know a lot about to things that are unknown: What are things that caused sales to drop off suddenly? Why did a competitor's brand outperform ours, when the products are basically the same?"
Tapping into the crystal ball factor can work, but companies also need to think about some pitfalls with predictive analytics. Robinson noted, for example, that human factors such as bias can interfere with gleaning insight from data derived from a sales intelligence tool and being able to act on it.
"The best practice in applying predictive analytics is to overcome the human impulse to see what we want to see ... to overcome the human impulse to be biased. It's to retune your thinking if the result isn't what you expected."
For more, check out the podcast above.
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