People are sharing their lives online in an unprecedented way through multiple channels, the hashtag #IncabableOflivingInTheMoment springs to mind.
This live tweeting is useful for marketers because people are inadvertently revealing their needs and desires attune to their potential purchases. A buying signal is a signal from a potential customer that shows intent to buy a product or service.
Spotting these signals could mean the difference between potentially securing the lead, by ushering it through buying process, or just letting it disappear amongst the noisy social media landscape. Even if it doesn’t result in a purchase from the original tweeter, 80 percent of customers do online research before buying in-store, so this could mean other people researching your product or service may vicariously take note of your call to action.
Today we break down the different types of buying signals, and then we invite you to a free webinar on Lead Nurturing in the Social and Mobile Age.
There are many different types of buying signals:
Positive Event Driven (Pre-Buy): This may arise from announcement of a wedding, pregnancy, graduation, or intent to attend to a trade shows or major event.
Negative Event Driven (Pre-Buy): This may arise from a potential theft or loss resulting in a need for a replacement.
Early in the Cycle: These types of signals are based in desire and seeking solution.
Research Phase: This signals are normally people crowd sourcing opinion on a particular product or service this may to fact Check, advice, brainstorming, or requesting recommendations.
Spotting these signals can be tricky and time consuming, but, with the right social media monitoring tool, you can track keywords from across the web and aggregate them into one easy to manage stream ready for you to assign, reply back to or simply monitor. Smart tools like the Twitter AutoReplies – which would send an automated tweet to people who mention keywords that would typically feature in your targeted buying signal — can dramatically reduce the time taken to respond to tweets.