Capturing Intention in User Behaviour - Do it Directly

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I had an interesting conversation at OpenCoffee London yesterday around personalisation and recommendations. At they table were several people involved in companies that are in the area of marketing analytics and personalisation and recommendations.

One interesting point raised was that as targeting becomes more and more focused, there is a loss of information that can harm personalisation/recommendation algorithms. There is a point where targeting stops being effective in delivering relevant personalisation and recommendations. I'll return to this later.

Of more note was how capturing attention is difficult, indeed impossible with behavioural tracking. In "Wither Social Networks, Arise Communities" and "Resources vs Answers - Asking a Question of Search" posts I've look at the importance of intent to properly target a user. What came in the conversation yesterday was be direct. Essentially, ask the user what their intent is and stop trying to guess. Allow the user to tell you (the business/software etc.) exactly what their intent is.

The example used was booking flights to Edinburgh. Currently travel sites get you to input the departure, destination and dates. Then give you lots of results which you have to wade through and links to ads for various travel related items in Edinburgh. However, there is no way for the site to tell what links it should show or how to order the results.

If however, the user starts by telling the service "I want flights to Edinburgh for a weekend of fun" suddenly the service has a slew of information that it can use to target the right ads and services and also organise the results. From that simple statement, the system "knows" the following information:

• The flights need to be Friday afternoon/evening and Sunday afternoon/evening
• The purpose is fun so flights need to be cheap/reasonable
• The person will be looking for tourist, entertainment stuff to do

From this new knowledge the system can prioritise flight results and target service suggestions and advertising better to the person's intent. This wouldn't be hard to do. It is a step away from normal form-based UI into NLP but it opens a whole new vista of opportunities.

Liability in the age of targeted ads

Every so often you here about the latest advertising based scam. An ad is located somewhere in magazine or newspaper and this leads the un-suspecting off in a merry dance that sees them loose some or all their life savings.

Generally the service (magazine, newspaper etc) are not held liable for this type of scam. Which is fair enough because the service is not targeting ads at specific people.

But...

What happens when a service is predicated (Blyk) on delivering very target ads to a specific demographic delivers advertising that is the start point of a scam? It could be very easily argued that the scam would not have been successful without the targeting provided by the service. Which of course opens the service to liability.

Liability for scams is something that does need to be considered with highly targeted advertising. Particularly, where the targeting focuses on populations known to be (more) prone to duping by scams.

Tag: Blky, Mobiles, Targeted Advertising