The Marketing Strategist:
The End of Suffering: The Promise of Data as a Service
December 12, 2013
Suffering, statistics, and storytelling: these are the “three sexy skills of data geeks,” a phrase that came to prominence in a blog post
of several years ago.
- Suffering is aggregating, parsing, cleaning, organizing, and validating the data.
- Statistics is analyzing it.
- Storytelling pulls analysis and proof points into an insightful elevator pitch.
Buddha might have been thinking of the data journey when he said that all life is suffering. Since the quality of data dissipates constantly, the suffering phase never ends. But there is hope. The rise of a phenomenon called “data as a service”—described by ITSMA Associate Kathy Macchi
, in her lead management workshop at ITSMA’s 20th Annual Marketing Conference, and subsequently in an ITSMA Viewpoint
—suggests that much of the suffering can be outsourced.
And there’s a lot to outsource. Without accurate data, you can’t segment customers or target leads. But data is often dirty and dispersed. The 2013 ITSMA Marketing Technology Survey
found “fragmentation of data” to be tied for second place among 18 challenges. Meanwhile, four in 10 respondents who needed to consolidate and clean their data had trouble finding staff with the right skills.
We’ve all heard about the data deluge. One big deluge, with a single collection point and one set of rules, wouldn’t be a problem. In the real world, data trickles into an organization through hundreds of collectors and ends up in dozens of databases. A new set of rules is required: an integration layer. There’s more software to maintain. A stream of modifications and updates as data needs change. And more complexity to deal with before getting to the payoff—the analysis and insight.
What’s worse, data is a wasting asset. It deteriorates at a rate of two to three percent each month, according to figures from Marketing Sherpa. People constantly change titles, phone numbers, and other identifiers. Left alone, from 25% to 35% of data can go bad each year.
Enter data as a service, also known as customer data platforms. Data comes in continuously. Immediately, before it enters a marketing automation or other internal system, an outside company uses algorithms to de-dupe, clean, and append new data. These companies scrape personal data from many sources. They aggregate social media data by individual. They consolidate it all by customer. They do some analysis. And ultimately, they use the results to guide campaigns and feed marketing automation and other customer-facing systems—customer service, online ads, point of sale—to generate recommendations in close to real time.
There are a number of different companies: names like Gainsight
, Lattice Engines
, and Infer
. Each takes a slightly different approach. But all share a similar pitch: taking the “suffering” piece off your hands. As these companies grow in capabilities and sophistication, the three sexy skills of data geeks may become two.