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Social media is a “double-edged sword,” say researchers who have created a mathematical model that aims to help business forecasters describe future demand by customers.

Mass online forums such as Twitter and Facebook potentially make it much easier for forecasters to rapidly sample the consumer preferences of millions of people, says professor Giovani da Silveira of the ����ɫ��'s . “But consumers are forming their opinions based on an avalanche of information that is being spread and shared all the time through things like social media, so what the market thinks yesterday is no longer the same today,” he says.

This vastly increased complexity has boosted the risk for companies that must commit substantial resources years ahead of time to develop and bring new products to market, says da Silveira. “It’s become way more volatile and complex because consumers are getting all these different influences.”

He helped tackle the problem as part of an international team that included former Haskayne associate professor s, along with professor  of the  in Nancy, France. Their mathematical, or analytical, model was outlined in a  published in the International Journal of Production Economics.

It takes into account three factors influencing customer choices, potentially providing a tool for businesses to assess the risk when making long-term plans based on expected demand involving large numbers of customers. Besides intrinsic preferences (your own choices as a buyer) or market share (the size of the market controlled by a particular company), these factors include inner-circle signals (the influence on you of choices made by your peers, or social network).

Social networks expanded

The importance of such networks — “the friend of a friend of a friend of a friend, to the fourth degree” or more — has been shown in everything from public health studies about obesity to research into how people choose music, says Menezes, who is currently a professor at the in Bordeaux, France.

Social media has enormously expanded such networks’ size and influence, he says. “This way of communicating information is now more important than traditional journalism.”

Traditional ways that businesses have used to test potential sales for a proposed product, such as focus groups involving prototypes, are also becoming less effective, says Menezes. While a growing number of companies are using social media in various ways to try to forecast or influence demand, such methods aren’t sufficient to guide long-term planning, he says.

'Much more uncertain world'

Early in the process, businesses must successfully navigate a series of trade-offs if they are to avoid the expensive mistake of creating too much or too little of a product for the market, he says. “A corporation has to sign the contracts for their suppliers several years ahead of time, and expand or build new facilities, so they need to know how much demand there will be for a new product.”

The analytical model Menezes helped create uses beta-binomial distributions to describe demand. This is a type of mathematical function used in probability theory to describe a high variability of outcomes.

Computer simulations helped test the model, which demonstrates how the range of possible outcomes is being substantially boosted by social media, says Menezes. “You see a much more uncertain world, and I think our paper gives the mathematical foundation about why this is happening — how the social network is playing around with, and really creating volatility in, demand.”