In B2B, there are two competing concepts for how a company can maximize access to the demand-driven companies that are actually active in its markets through behavioral data of purchase intent. One is a technology-centric approach, heavily reliant on publicly digital practices available generic data, and characterized by significant opacity regarding quality and compliance.
The other is a model focused on generating
A qualified and controlled audience, to which TechTarget and BrightTALK are committed for the long term. These models have important facebook database implications for the short- and long-term performance of the marketing and sales programs that rely on them. These implications should be considered as you consider using data marketing to evolve the components of your martech and salestech stacks.
The technology-centric model
Based on the fact that new technologies can provide access to multiple sources, data entrepreneurs have developed ever larger and broader additional how to create more attractive budgets data streams to attract marketing and sales clients. They believe (and would have you believe) that digital practices with the right combination of computing power and algorithms, using vast, undifferentiated, publicly available Internet sources, they can reassemble weak and disconnected signals into useful indicators. But is this really the case?
Without direct means to inspect the data
the process, and the effectiveness of the results, it is very difficult to tell. A client does not have the tools to inspect asia phone number exactly – end-to-end – what goes into these data streams, making the results difficult to connect.
Different and poorly understood data
vendors claim to be able to construct useful pictures of actual buyer journeys in action. Leaving aside concerns about privacy or actual legal rights over this data (a regulatory area still under construction. It is a significant problem to believe that unrelated signals can reliably identify actual buying. Processes even when the data sources are decoupled from each other. Given the randomness of this approach—and thus the lack of identifiable links between actual buying team members and digital processes—it may be impossible to piece these signals together to draw anything definitive. Does the increase in search activity on the topic of security, for example, indicate anything meaningful if all companies are displaying it indiscriminately in raw form?
We believe that data buyers should be particularly
careful about this topic. In addition, your teams should be careful not to fall into the correlation versus causation trap. Which is a very common reality of ex post analysis in this field. Correlations digital practices in outcome data are common. But that does not mean that they are the cause of the results. To avoid this kind of trap, you should be able to freely inspect the logic and substance of the data you are buying to be sure that you can trust it. You should be wary of any source for which the link between the data provided and the promised results requires a leap of faith that is not formally verified.
The audience-centric model
In our twenty-plus years of applying our approach. We have demonstrated to thousands of clients that there is a much simpler. More logical and more direct way to exploit demand signals in a market. First, we must focus on satisfying the information needs of buyers. Who are end users and who almost always conduct in-depth research before investing. Our concept is based on the simple principle that. Regardless of the market, most buyers congregate around specific sales or information points that they find useful in making their decisions. This is the opposite of the idea that buyers would randomly distribute themselves. Even in a purchasing context, in unrelated areas of the Internet.
We call these types of gatherings in specific
Spaces on the web our “audiences,” and we invest significant amounts each year to bring them to life decisions. As YouTube has digital practices proven so powerfully in both B2C and B2B, it’s possible to gather valuable audiences (even on the most obscure topics) using relevant, useful content. Tech B2B audiences, with their very specific needs, gather like YouTube’s. They conduct purchasing research where they get useful research support. That’s why the behaviors that are relevant to discovering the tech buyer’s. Journey aren’t distributed everywhere on the web—our model has proven that they occur in limited. Clearly definable spaces.