Big Data + Analytics = new possibilities to predict sales outcomes

Sales is highly based on human interactions and relationships rendering analysis and automation to be considered impossible.

Now new behavioral analytic techniques are possible given the growth of both data and computing power.  Such analytics have the potential to streamline any unstructured business process by identifying deficiencies and excesses allowing resources to be better allocated and managed.  This is no more true than across the “front office” (as opposed to the “back office”) and creates an opportunity to automate previously manual processes.  If so, are we on the verge of a new industrial revolution powered by analytics applied to social business, specifically front office operations?

If the weatherman said that there’s an 90% chance of showers today, would you carry an umbrella?  Salesmen are often characterized as “rain-makers”.  As such, how certain are you about your  company’s “weather forecast”?  Is there a downpour in your future?  Or a drizzle?   What would it be worth to you to know how your quarter will fare – with 90% accuracy?  Up to 3 months in advance?

Advances in science and technology have given unprecedented precision into nearly all aspects of forecasting.  Meteorologists are able to make accurate predictions of the path and strength of hurricanes to avert disasters and save lives.  Missile and rocket paths can be targeted with pinpoint accuracy.  Even the stock market has been changed by automated algorithmic trading systems.  Businesses are just starting to take advantage of the wealth of data that has been available due to the increasing use of technology in the workplace, and the availability of lower cost cloud-based platforms.  Transactions of all kinds from phone records, emails, shared document repository records, Internet usage, and other records are now stored by the terabyte on on-site and off-site computer servers.  This large volume of unstructured records necessarily precludes manual processing for anything other than the most basic, search-friendly tasks. Yet, this same digital data is a treasure-trove of social behavior, and predictive and institutional knowledge.

As with other forecasting technologies, tapping into this data can help corporations avert disasters and hit their targets with pinpoint accuracy.  A challenge has been how to get all this unstructured data into a digestible format that machine-learning algorithms can use.  Such representations need to be flexible enough to absorb new forms of data, yet robust enough to be accurate.

What’s been missing?  The first is a top-down approach where a model is used and iteratively refined with insights from the second, bottom-up approach.  This second approach uses a proprietary machine representation, pattern recognition, and decision engine that discovers its own models based strictly on the data.  The collaboration allows the method to quickly converge on useful models that provide the greatest predictive abilities.

Sales offers a unique challenge with an equally unique prize.  Sales is a highly human-centric endeavor.  All good salespeople know that their relationship with their customer can seal or break a deal.  The old adage about selling ice to Eskimos is a testament to the very social nature of sales.

Accurately predicting sales opportunities directly affects the entire corporation.  Much of a company’s asset allocation, its budgets and resources, are set based on the predictions from their sales department.  Unfortunately, current predictions from sales are more like fortune-telling.  The reason is simple: humans process this data intuitively; therefore it is difficult to come up with quantitative values.

Until now, that is.  Foretuit brings modern science and technologies using big data and analytics to better predict sales outcomes.  Think of the possibilities when applied to your own business!


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