Social networks are playing an ever increasing role in the path to purchase of consumers globally. Dropping in and out of Twitter, Facebook, Sina Weibo and others whilst researching, considering or out and out declaring “I want to buy that” is a common behaviour. Consumers are on the go, on their mobiles and randomly progressing down the path to purchase for one, two or many items they are in the market to buy. Of course they augment this in the moment behaviour with visits to ‘brick and mortar’ shops and looking through web sites on a laptop but the social aspects of ‘micro-moments’ means brands and marketers paying more attention to what they do on social.
Reading through the Forbes article on General Motors’ social media plan you can see one of the world’s largest brands taking social really seriously. (http://www.forbes.com/sites/oracle/2015/08/18/gms-social-media-plan-its-not-about-likes/) They have invested heavily in tools (social listening) and people – lots of people! A social center of expertise to listen out for anything to do with GM :
“They look for opportunities to weigh in on the good and the bad—serve up compelling content, reinforce positive messages, facilitate discussions, and answer questions, as well as address any trending social media messages that put the GM brand in a negative light.”
GM are seeking opportunity to engage with their customers – existing or prospective. To create a conversation and a truly engaged community using the Oracle Social Network Cloud as a solution.
At present all they do is listen to what is being said by them; then they use a vast amount of people to respond in an appropriate way. That is a LOT of listening, a lot of manual intervention and it is paying off. GM is driving media exposure they are measuring worth in the millions of dollars.
Listening is good, recognizing the importance of social data is great; but you need to look for key data that will ultimately really drive your bottom line with sales; not notional $$$ of media exposure. Imagine you could ‘listen’ to every single piece of social data and pick out the key posts exhibiting purchase intent? It can’t be done manually – well I guess it could but would take massive co-ordination and teams!! At Chatterbox we designed a machine learning product called ‘Path 2 Purchase’ with our Chatterbox NLP Framework. Our clever machines have been taught to find, in real time, posts that relate to pre-purchase intent or post purchase info. We separate out pre-purchase intent into interest, consideration, or lead validated intent and can ensure those messages go to a partner solution to be acted on ‘in the moment’.
We know how disruptive our technology is; and can’t wait to be deploying it for brands like GM to take them beyond simply listening and engaging but to enable them to act and drive sales.
For more information on our Path 2 Purchase product please contact Andrew Watson, VP Strategic Alliances email@example.com