Data As A Service (DaaS)

The role of data insights in marketing is growing. The value of the collected data comes purely from the insights and intelligence distilled from it. Collecting data is treated as a cost. There is evidence from the value added census data that database vendors provide that marketing can make this profitable. Marketing data matters.

A case in point is the American Time Use Survey (ATUS), an on-going household survey of roughly 1,200 Americans per month (1,800 per month in the first year, 2003) that collects time diaries as well as demographic interview information from respondents who had recently been in the Current Population Survey. Funding for the ATUS has been eliminated from the proposed Fiscal Year 2009 budget.

As the Freakonomics blog puts it, ATUS data allow researchers to answer questions that otherwise would be out of reach. For instance, when someone becomes unemployed, what do they do with their time? How much do time do they spend searching for a new job, and how much does that time increase or decrease as their unemployment benefits come closer to running out? Do husbands do any housework? Are black children and white children spending their days doing different activities?

A number of novel uses of the ATUS in economic research, including in the areas of macroeconomics, national income accounting, labor economics, and others illustrate the magnitude of this new survey's possible applications. Marketers use this in their pursuits of data informed communication channel planning. It helps to craft communication and relevant experience based on the activity patterns of different audience groups. Marketers can be better informed of the mindset and busy-ness of their target audience and various times of the day – be it to sell a breakfast cereal or a ready to eat meal.

While supporting the cause to save ATUS, I feel there is a need to make this study more meaningful (and thus more marketable):

1. ATUS records primary activity only. In today’s world, people spend less time in discrete activities. It is important to identify the extent of simultaneity.
2. Simultaneity becomes even more relevant with the youth and the more digitally involved population.
3. Providing data in ready-to-use formats for key user groups may require minimal data processing but could make it a lot more attractive and marketable.

BIG research’s SIMM (Simultaneous Media Survey) is an interesting and useful study that measures simultaneity in media consumption – perhaps the only one of its kind currently looking at media consumption that way. SIMM measures the consumption of 31 different media, which are linked to marketplace consumption. Eight media consumption clusters have been developed from a factor analysis of three unique media consumption characteristics: Experiential Time, Simultaneity and Media Influence.

Old School: High mass media influence (TV, magazines, newspaper) and low in search media (online). Average overall media consumption and simultaneous usage. Active Explorers: High promotion (inserts, coupons, direct) and search media influence. Average media consumption. New Mediacs: Low mass media and promotional media influence. High electronics media consumption. Low print consumption. Simultaneous Readers: Average overall media influence. High network simultaneous usage. High print consumption. Independents: Average search media influence. Low media consumption. Ravenous: High overall media influence. High network, print and electronic consumption. Persuadables: High mass and search media influence. Average promotional media influence. Opportunity Minded: High promotional influence. Average to low media consumption.

ATUS data is at use not only in academic quests but also in commercial applications. A new improved methodology will only make this a profitable proposition, instead of a cost centre. Apart from the data, I can see several marketable products coming out of this study like:

1. Activity Based Consumer Segments
2. Linkages to typical geo-demographic datasets
3. Simultaneity Audience Clusters

If the government bodies can ensure the collection and processing of data with key user groups in mind, it can market the data well and ensure that these projects at least break-even. ATUS is just an example. Many other datasets could be in jeopardy and maybe the business model warrants a change. Even if the objective is a normal profit, this is probably an opportunity for innovation – a public sector innovation in data.

My suggestion is to take a page from the software industry (SaaS), the way it has transformed. Most research organizations build user front ends to data and market the front end at a cheaper level. The raw data is generally priced with a de-marketing attitude. Why Buy the Cow is an interesting read to see how the on demand revolution powers the knowledge economy.

The challenge for the government bodies will be to transform the way raw data is collected and disseminated. Shift from the current model where data is seen as a mere product to think of Data As A Service (DaaS).