In the summer of 2008, I created a slide deck about consumer predictive behavior for our online news and social network site.
As an internal deck, it is not beautified but it helped channel our thinking. Nevertheless, the deck tells a good story about consumer predictive behaviors and I would like to share it with the community.
There is an ongoing discussion about Social Media ROI (see my previous two posts about Social Media ROI) and an even larger discussion about overall ROI covering both offline and online events.
The idea is that today’s analytical tools only count the last step before a conversion and the actual conversion. This is good but it misses a lot of really important information. What did the consumer do before the last step? What online/offline advertising impressions pushed the consumer to the last step? What online/offline conversations did the consumer join? And so on.
The consumer might have spent time talking to a sales rep in a store, seen an ad in the paper, saw another ad on the TV, browsed the web in the library (unless the consumer logged in, we cannot track him on a public computer) and saw an impression, talked to a friend online, talked to another friend offline, and finally clicked on a banner ad that pushed him over the threshold to be converted into a buyer.
Specifically for large purchases, there is always a chain of events that brings a conversion. The deck tells a good short story.
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Interesting stuff. I helped a prof. of mine do research on what keeps a consumer on a website, what the website does to attract them in the beginning and what helps take them from the research phase to the purchase phase. Very cool stuff actually. The generational differences are a defining point as well as to who actually purchases online vs. brick and mortar and the ways they research products, specs, and consumer reviews.
This is very interesting and there is a lot of research in this area. On the web, there are ways (but they have to be better developed) that a user can be tracked from start to conversion.
The problem is that most users, specially on high-priced items also get input from non-web sources; you talked to your co-worker, you saw an ad on the bus, you heard an ad on the radio, you discussed your finances with your spouse and so on. So, how do you track that?
Currently quite impossible but it is the holy grail of marketing.
With this post and the slide deck, I wanted to make the point that if it could be tracked, it would be a win win for everybody.
Thanks for the comment.
Awesome post, hey I found this story while googling for lyrics. Thanks for sharing I’ll tell my friends about this too.
Thanks. Please do. Let me know if you have additional questions.