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Behavioural targeting will give the best returns when a wide variety of on and off-site factors are pulled into the equation.

The technology can give great results with site content and isn't just something you should be asking your ad network about.

Multivariate testing is now well known among those ‘in the know’ in online marketing and now behavioural targeting technology is being used by more advanced clients, allowing them to generate variants of their pages that are precisely targeted on a user by user basis.

To perform this level of behavioural targeting, it is necessary to harness all data available. This can include off-site factors such as referring keyword or site but the critical difference between behavioural targeting and mere segmentation is that behavioural targeting brings the client’s own CRM data to the party.

This will provide targeting algorithms with information about the visitor, their demographic information and past and present interactions with the site.

The term ‘Behavioural Targeting’ is being watered down by ad networks and others who apply the term to a level of targeting that we would call segmentation; that is, they target adverts dependant on factors such as referring site, browser type or sometimes keyword search term.

You aren’t really targeting on a visitor by visitor basis with segmentation – you’re generating a series of optimised pages that will work well for groups of visitors. In some cases, these groups will still be quite broad.

This approach can still give some good uplifts in click through rates or on-site conversions, however, it is only true behavioural targeting that can truly help tailor offers to an individual.

Full behavioural targeting solutions don’t just optimise the aesthetics and mechanics of a site.

With the wealth of visitor demographic and past interaction data that can be gained from client CRM systems, it is possible to target visitors with the products they’re most likely to purchase, at the time they are most likely to purchase and using creative that you know they will respond well to.

It doesn’t stop there either, once they have something in their basket, behavioural targeting can be used to optimise cross-sell opportunities, providing an opportunity to increase basket value through efficient placement during the browsing stage or within the checkout process.

Sites in the retail and travel sectors find this particularly useful; by monitoring the behaviour of customers the self-learning algorithms can establish what behavioural patterns are likely to precede the booking of a flight or business accommodation, for example, then watch for these same tell-tale signs among other visitors.

Don’t get us wrong; some ad-networks are serving ads based on behavioural targeting that takes in postal/zip code demographics. This is a leap ahead from basic segmentation but true behavioural targeting will deliver far more lucrative returns.

If you are looking to push your on site performance further than the level possible with multivariate testing and segmentation, behavioural targeting is a route worth exploring. But whichever provider you choose, ask a lot of questions; don’t end up paying a behavioural targeting price tag for a service that boils down to segmentation, as we have seen time and time again.

Effective behavioural targeting is a process of continual improvement; the behaviour of visitors will change over time; algorithms that continuously learn then implement their findings for improved optimisation are a must.

This isn’t something where you can perform a study then implement results, it means allowing the algorithms to take over some elements in order that they can do a better job of optimisation.

This takes a leap of faith on the part of larger organisations who may already be confident in the ability of humans to watch for these patterns but believe us, the software algorithms really do have an upper hand here.

We're terming this technology 'Content Intelligence' and will publish a whitepaper shortly on the subject.

Mark Simpson is the MD of Maxymiser Content Intelligence.

Mark Simpson

Published 15 August, 2007 by Mark Simpson

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