Category Archives: data

Obama’s data capture ploy

Over the past week, presumptive Democrat candidate Barack Obama dominated once again the US news cycle. In an otherwise relatively uneventful week, there was intense speculation over the airwaves, online and in print about who was on the Democrat VP shortlist… According to Google Trends, always a good buzz indicator, searches for “VP” doubled over the past week.

More importantly, the press gleefully echoed the campaign’s insistent wish that the supporters should be “the first to know” by registering their email or mobile phone number on the Barackobama.com web site. Everyone anticipated a rapid announcement which will come later than expected… but what if that was the plan all along?

Whether you support or not the Democrat hopeful, you have to admire the carefully orchestrated marketing move around this opportunity.

“First To Know” was an elaborate way to boost the size of the presumptive candidate’s direct marketing database. This may sound a bit innocuous right now but in a potentially close race, every little counts and tactics like this may make all the difference on Election Day. The Barack Obama campaign is earning the permission with the VP announcement to regularly broadcast text alerts to its support base in the fall.

There are a few notable subtleties in the way this was executed.

First the Obama campaign is managing this data capture recruitment drive at a minimal cost since they are not resorting primarily to advertising. I guess that like countless other people, I am contributing to spreading the word through the fact that I am blogging about it. Obama seems to have a strong ability to shape the conversation – both in old and new media.

The capture form includes the zip code of where registrants live, and future text messages could therefore be targeted by state or by district if needs be. This is crucial to adapt messages based on the shape of the local political battlefield, and push different issues in different states. The zip code may potentially allow to refine messaging at an even more local level.

Finally, this operation will allow the Obama campaign to communicate primarily by text message to a younger audience that is notoriously using email much less than instant messaging or mobile devices.

The message “be the first to know” is also a textbook example of proven word of mouth marketing techniques… to target the influencer type, offer exclusive, ahead-of-the-crowd information that they can use as a social currency.

As I write these lines, the announcement of Obama’s VP choice will be made in less than 24 hours (on Saturday August 23rd). It is still too early to tell if Obama’s data capture ploy was successful, and the Obama campaign will probably not disclose how many mobile phone numbers and emails they captured over the past week – if only to keep the McCain campaign guessing.

Let’s just sit back, and watch how often the Democrats leverage this new channel in the coming weeks… the political world is getting addicted to the direct relationship opportunities enabled by digital technologies, and there is no turning back.

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Database Marketing Metrics in a Digital World

I have had a lot of conversations in the last few months about the fact that digital marketing is fundamentally not that different from traditional marketing.

Of course important adjustments are in order when you have to communicate to a consumer who is in control and has less tolerance than ever before for interruption and irrelevant messages. But a lot of things you know about marketing stay the same, and digital only brings more depth and richness to the way. Here is one example from the world of database marketing.

In the early days of database marketing, catalogue marketers were trying to find ways to identify which customers were most likely to buy than others when there was a communication effort. The straightforward way was to segment customers based on how much they had spent to date – and that turned out logically to be a good predictor (or “proxy” for the DM purists).

But relying on the monetary value only proved somewhat limiting: there were lots of customers who were buying even if they were amongst the most valuable ones, and there were many customers identified as very valuable who used to buy a lot but not anymore (you may have heard of them as “lapsed customers”).

It turned out that by looking also at how recently and how frequently customer bought over the last few months, the accuracy was greatly improved. By adding and combining these two additional parameters, database marketers could guess who would buy and who would not – and that could lead to significant savings in printing and postage costs.

And so very empirically the RFM prediction model was born – R for Recency, F for Frequency and M for Monetary value or Money spent. Its efficacy is still as impressive today as it was over the past two decades. Of course, more sophisticated models have appeared over time using statistical techniques such as regression analysis, neural networks or genetic algorithms… RFM has the merit of simplicity and can be applied without advanced statistical know how and resources.

Visit this site if you are interested in reading more about RFM.

So how do you apply a digital lens to RFM? The model stays the same but there is room for additional information. RFM appeared in an era where storage and the number of opportunities for collecting data were limiting factors. RFM focuses therefore on transaction data – but does not necessarily leverage interaction data which can be more easily tracked today.

There is an opportunity to look at two more dimensions: Attention and Engagement. Attention can be for example measured by how frequently a consumer opens your emails or how many of your last 10 emails they opened. Engagement can be indicated by the time a consumer spends on your web site after clicking from an e-mail. In fact the model can be extended outside of e-mail marketing to include online advertising – although it would apply in this case to anonymous prospects rather than identified customers. And in a not so distant future, with new technology that allows delivering targeted TV advertising to specific households, such an approach could expand to other marketing channels.

Moving from RFM to FRAME is a good way to describe how marketers should approach their migration to the digital world – key basic principles stay the same, and additional data open up new opportunities for understanding customers. At the same time, it is very easy to look at too much information or at the wrong information: so when it comes to new marketing models, keeping things simple is paramount.