Is it possible to get massive amounts of B2B data that's deeply granular and allows for precise targeting?
Bigger Data Doesn’t Mean Better Data
Bigger is better.
Or at least, that’s the idea that persists in numerous industries and even non-business facets of everyday life.
However, when it comes to marketing data, the old adage is misleading at best and a total myth at worst. A few years ago it was all about who can collect the most new email addresses. Today, the question is who can aggregate the most data, but there are more important things to consider than just the size of the database.
THE CORPORATE DATA SHOW - EPISODE 7 - NEIL GLASS
In this episode, Neil Glass, Senior VP at IDG, discusses why the focus on scaling data for digital audiences is overhyped and what you should really be focusing on instead.
“People get hung up on the notion of how many people have purchase intent around a product.” – Neil Glass
When it comes to marketing data, the industry trend leans towards aggregating more and more data, whether it is then used efficiently or not.
A few years ago, the same thing happened with email. The goal was to amass as many new email addresses as possible. Now, everyone has gravitated towards better data and bigger data sets.
The “better” part is definitely a step in the right direction, but is the “bigger” part?
In a recent interview, Neil Glass, Senior VP at IDG, explained while appropriate scaling of marketing data is important, there are two other areas to consider with data collection that are more important than just the size of the database.
Those two areas are data transparency and data usage. Or to put it more simply: where is it coming from and where is it going?
Where is the Data Coming From?
There are massive amounts of data publicly available.
Currently, there are around 7 billion profiles available for buyers, but it’s not clear what that number actually represents because there is a lack of transparency about data origin.
With so much out there, it’s no surprise that there’s a lot of confusion about the sources of the data and how it gets organized. Transparency from data collection partners is the key to cutting through that confusion.
As an example, one metric that people tend to get stuck on is the number of people with purchase intent surrounding a particular product. Let’s say Company A is specifically interested in figuring out how many people out there are looking to purchase a laptop. There are dozens of different data providers that they could go to for this information with the number of available profiles varying from 10,000 to 9 million.
By looking at statistics of laptop purchases in previous months, it’s likely that there will actually be around 2 million purchases in the US over the next month.
That’s a lot higher than the low end of the data profiles, and a lot lower than the high end. Why the wide range? Because there is no common collection method between the different data providers. The collection tactics are often opaque. There’s no sense of how the data was obtained. When working with a data provider, it’s important that they are transparent about how they collect their data so you have the proper context to make use of it.
"It's more important than ever that companies are transparent about how they collect data"
Firms like IDG can give this context and insight into their data pipeline because they own all of it, and they keep their collection methods transparent to help their clients understand what appropriate scale is for data.
That scale is going to vary, but as with the laptop example, the number of legitimately useful profiles will be somewhere in the median rather than at the extreme ends of what is available.
How is the Data Being Used?
“There’s a lot of focus on scale right now for digital audiences: Who can build the biggest database?” – Rick Holmes
It all depends on perspective. Data is useless if it isn’t provided in context.
One way to look at the data is based on market size. For example, IDG estimates that there are 400,000-450,000 IT professionals with decision-making capabilities for their companies. With that number as a jumping off point, IDG’s clients can build better marketing programs because they understand the size of the market.
Also, within that subset of IT professionals, they can use the data to cut down that number based on job title, company, company size, or other specifics. And, through layering on contextual signals, if someone visits a site like PCWorld or MacWorld (two properties of IDG) and they know it is a VP of IT, they can also see that they’ve consumed a certain amount of content on a topic like the cloud.
That’s just one example of how data can be framed to provide actionable information. The important take away is that without context, metrics are just numbers without meaning.
At Every Market Media, we advocate this and are available to consult with you to provide context about your data needs before you begin your marketing efforts. With an over-sized data set or a lack of intent for the data’s usage, you still have the test results for, say, the click through rate of an ad.
But, that’s all you have. Test results without context don’t use data to its full potential!
While the size of a data set is important, a bigger data set isn’t automatically better.
What really matters is: How transparent is the company collecting the data and does that collection provide the context to make solid use of the data? With this information, you can figure out what is the appropriate scale for your marketing database.
This episode is based on an interview with Neil Glass, Senior VP at IDG To hear this episode, and many more like it, you can subscribe to The Corporate Data Show. If you don’t use iTunes, you can listen to every episode here.