Meeting the privacy expectations of customers will be essential to successful predictive analytics deployments.Read More
How predictive tools can boost firms’ marketing
When it comes to hunting down new leads and getting a firm's messaging out to customers, ensuring professionals have good access to the right information is one of the best things a business can do to boost its chances of success in this area.
The marketing landscape has changed immensely in the past few years and is now one that operates much more based on insight derived from data than the instincts and feeling of marketers. But with this has come a series of new challenges that firms must overcome.
One of the biggest issues when looking to narrow down leads and make the targeting of campaigns more effective is the sheer scale of the task. It was noted by Tom Petrocelli, research director for enterprise social, mobile, and cloud applications at Neuralytix that this is an issue that has become even trickier in recent years due to new channels such as social media.
In an article for CMS Wire, he said: "There are just too many prospects to reach affordably. It is too expensive to target the world. Social media, which casts as wide a net as possible, yields too many responses or too few good ones."
He noted striking the right balance with marketing is tricky, as aiming campaigns at too few channels restricts who hears the message, while too broad a message will attract people who have no intention to buy.
This is where big data analytics – and particular advanced tools such as predictive analytics – can be hugely useful to a business. Mr Petrocelli explained that applying these tools to customer profiles can help identify and predict customer buying behavior.
Systems do this by gathering data from sources such as CRM solutions, census and other demographic data, sales data, responses to previous marketing campaigns, social media analytics and more. This can then be used to create targeted lists that rank customers by how likely they are to complete a purchase – and can even predict the types of items they will be looking for and how much they are willing to spend.
"Predictive analytics provides ways to drive awareness and demand at lower costs by raising the response rate on a smaller number of prospects," Mr Petrocelli said. "In other words, it allows companies to target fewer potential customers with better results."
Of course, this kind of powerful analytics brings its own issues which will need to be addressed, with questions over customers' privacy high on the list. With tools available that can give highly accurate, detailed insights into a person's personality and buying habits, businesses need to be aware their efforts do not stray too far.
Gartner analyst Frank Buytendijk recently warned of the dangers of "crossing the creepy line", noting that overly-aggressive predictive tools can turn off customers and lead to projects failing.
One infamous example of predictive tools invading customers' privacy was from a couple of years ago, when Target managed to determine that a teenage customer was pregnant even before she had told her father, based on patterns of purchases for items not necessarily directly related to pregnancy, such as supplements.
This caused issues when the firm started sending her personalised mailing for maternity-related products and illustrates how a careful approach needs to be taken to avoid such awkward situations.